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Department of Agronomy, Ladoke Akintola University of Technology, NIGERIA E-mail: samdelani@yahoo.com Dr. Jamilur Rahman Sher-e-Bangla Agricultural University, BANGLADESH E-mail: jamilsau@yahoo.com Dr. Binoy Sarkar International Lecturer, Lancaster Environment Centre Room No. B535 (LEC1), Lancaster University, Lancaster, UK E-mail: b.sarkar@lancaster.ac.uk Dr. Leonardo Fernandes Fraceto, FRSC Associate Professor Institute of Science and Technology of Sorocaba São Paulo State University – Unesp Sorocaba - São Paulo – BRAZIL E-mail: leonardo.fraceto@unesp.br TECHNICAL EDITORS Dr. Debashis Dutta Project Directorate for Farming Systems Research, Modipuram, Meerut, U.P. INDIA E-mail: debashisdutta74@yahoo.co.in Dr. Anil Bhatt Assistant Professor, Agricultural Economics Division of Agricultural Economics and Statistics, FoA, SKUAST-Jammu, INDIA E-mail: drbhatanil@gmail.com Dr. P. 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Senapathy Department of Rural Development and Agricultural Extension, College of Agriculture Wolaita Sodo University, ETHIOPIA E-mail: mspathy9@gmail.com Dr. Padmanabh Dwivedi Institute of Agricultural Science, Banaras Hindu University, Varanasi, INDIA E-mail: pdwivedi25@rediffmail.com Dr. M.M. Sharma ICRISAT, Patancheru, Andhra Pradesh, INDIA E-mail: murli.sharma@cigiar.org EDITORIAL BOARD Dr. Shyamal K. Ghose Department of Genetics BCKVV, Mohanpur, West Bengal, INDIA E-mail: shyamalghose@hotmail.com Dr. Marcelo Huarte Huarte International Agricultural Consulting Owner 14 de julio 2735(7600), Mar del Plata - ARGENTINA Dr. Ranjan Bhattacharya Indian Agricultural Research Institute New Delhi, INDIA Science & Animal Husbandry, E-mail: ranjan_vpkas@yahoo.com Dr. Soumendra Chakraborty Uttar Banga Krishi Viswavidlaya, Pundibari, West Bengal, INDIA E-mail: soumendra1@gmail.com Dr. Vikas Kumar Department of Agriculture, Vivekananda Global University, Jaipur, Rajasthan, INDIA E-mail: vkskumar49@gmail.com Dr. Dhiman Mukherjee Uttar Banga Krishi Viswavidyalaya West Bengal, INDIA E-mail: dhiman_mukherjee@yahoo.co.in Dr. N. Kumaravadiel Tamil Nadu Agricultural University Coimbatore, INDIA E-mail: kumaravadiveln@yahoo.com Dr. Alireza Haghighi Hasanalideh Central and West Asian Rice Center (CWARC), IRAN E-mail: haghighi.ag@gmail.com MANAGING EDITOR Chanchal Mukherjee editor@ijaeb.com Contents International Journal of Agriculture, Environment and Biotechnology VOL. 15, NO. 2 (SPECIAL ISSUE), JULY 2022 Role of Multispectral Vegetation Indices in Precision Agriculture – A Review 277 Moncy S Akkara, A.R. Pimpale, S.B. Wadatkar and P.B. Rajankar Three-Dimensional Printing in Food Process Engineering: A Prospective and Retrospective Analysis 287 Amrutha, G. and Bhagyashree N Patil A Study on Novel Approach to Sustainable Indian Agriculture - Precision Farming 299 Shwetha U.N. and Nitin S. Gupta Study of Heterosis, Residual Heterosis and Inbreeding Depression in Two Crosses of Tomato 307 Sangamesh Nevani and O. Sridevi A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India 313 B. Srishailam, V. Sailaja and S.V. Prasad Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life of Jasminum sambac Cv. “Mysuru Mallige” 321 Keerthishankar, K., Yathindra, H.A., Mutthuraju, G.P. and Tanveer Ahmed Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes of Okra under Heavy Clay Soil of Southern Rajasthan 329 Hemraj Meena, Kavita, A., Nirmal Kumar Meena, Rajesh Sharma, Ashok Kumar and Rahul Chopra Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature 337 M.N. Dabhi, P.R. Davara, H.P. Gajera, Nirav Joshi and Parth Saparia Physical and Functional Properties of Extruded Snack Products Prepared by Blending of Defatted Peanut Flour with Corn Flour 347 P.R. Davara, Mohit H. Muliya, M.N. Dabhi and V.P. Sangani Effect of Blanching on the Quality of Green Peas During Freezing V.P. Sangani, A.N. Dalsaniya and P.R. Davara 359 Physical Properties of Fresh Turmeric Rhizomes (Var. Salem) 369 Ravina Parmar and Mukesh N. Dabhi Development of Palm Sugar Substituted Yoghurt 379 L. Vijay, N. Karthikeyan, G. Kumaresan and C. Pandiyan Assessment of λ-irradiation Impact on Physiological and Sensory Characteristics of Peanut Kernels (Arachis hypogaea L.) as a Function of Moisture Content 385 D.K. Gojiya, D.M. Vyas and A.M. Joshi Efficiency and Effectiveness of Mutagenic agents (Gamma rays and Ethyl Methane Sulphonate) on Bougainvillea spp. 393 Anita Hosalli, Seetharamu, G.K., Shivapriya, M., Amreen Taj, Gangadhar, B.N., Rajiv Kumar and Anjaneya Reddy Influence of Ozone Treatment on Carbohydrate Content of Wheat (Triticum aestivum) during Bulk Storage 401 Shingala Abhishaben M., M.N. Dabhi, P.J. Rathod and Rathod Ravikumar R. Effects of Process Parameters on Rice Based Extruded Snack Food 407 P.S. Sapariya, V.P. Sangani and P.R. Davara Monitoring and Regulating Climatic Condition of Polyhouse for Successful Off-season Grafting of Citrus Fruits Using Internet of Things Platform 417 Ritu Raj Lamsal, Mamta Bhattarai, Umesh Acharya and Pablo Otero Climate Resilient Practices Adopted in Flood and Drought Prone Areas of Siwan District, Bihar 423 Harsha, B.R., Krishna Bahadur Chhetri, Nandeesha, C.V., Anuradha Ranjan Kumari, Shivam Chaubey, Arun Kumar and Ratnesh Kumar Jha Moisture Dependent Physical Properties of Psyllium Seeds for Different Varieties 427 Nirav U. Joshi and Mukesh N. Dabhi Management of Plutella xylostella on Cauliflower Crop Through Novel Group of Insecticides 437 Abhijith, N., Tirupati Murali Krishna, Kaarumanchi Kiran Kumar and Kayam Devaki Study on Drying Characteristics of Simarouba glauca Leaves 445 S.S. Bhuva and Darshan, M.B. Growth and Yield of Gobhi Sarson as Influenced by Irrigation and Nutrient Management Practices under Conservation Tillage Hemali Bijani, Sanjay K. Sharma and Devanshi Baghla 455 Impact of Heat Units and different Pruning Months on Growth and Flowering of Jasminum grandiflorum 461 Khanchana, K. and M. Jawaharlal Assessing Socio-economic Vulnerability for Development: Evidence from Ahmednagar, Maharashtra 467 P Seenivasan., Ananthan P.S., Neha W. Qureshi and Shivaji Argade Effect of Organic Manures on Germination and Growth of Snake Gourd (Trichosanthes cucumerina L.) 477 Suriya, R. and P. Madhanakumari Comparative Analysis of Performance of Different Fodder Crops Under Pigeonpea Based Intercropping System (1:2) 481 Rajashree, B.M. Dodamani, P.S. Rathod, D.H. Patil, A. Amaregouda and Sahana Effect of Subsurface Draiange on TSS and SAR in Saline Vertisol Under TBP Command Area 485 Sahana, Veeresh, H., Narayana Rao, K., Bhat, S.N., Polisgowdar, B.S. and Rajashree Genetic Variability of Determinate F4 Progenies for Yield Attributes of Indian Bean [Lablab purpureus (L.) Sweet] 489 Pooja C. Bhimani, K.G. Modha and V.B. Darji Feasibility of Vacuum based Cooling System for on Farm Cooling of Milk 495 Gaurav Sharma, Amandeep Sharma, Pranav Kumar Singh, Narender Kumar and Gopika Talwar A Study on Marketing Channels and Marketing Efficiency of Capsicum in Mid-Hills of Himachal Pradesh 503 Parul Barwal, Subhash Sharma, Diksha Bali, Chinglembi Laishram and Parveen Kashyap Evaluation of Biopesticides Against Callosobruchus maculatus Fabricius in Chickpea Under Stored Conditions 509 Amrutha Valli Sindhura Kopparthi and Praveenbhai Harjibhai Godhani Phenotypic Correlation Between Morphological and Yield Related Traits of Rice (Oryza sativa L.) 515 G. Babithraj Goud, D. Saida Naik, R. Abdul Fiyaz, M.M Azam, S. Narender Reddy and B. Balaji Naik Utilization of Bamboo and Wooden Resources for Development of Contemporary Products: An Approach for Climate Change Mitigation and Revenue Generation 521 M.S. Sankanur, T.R. Ahlawat, R.P. Gunaga, A.D. Chaudhary, Archana Mahida and Vrutti Patel Estimation of Genetic Parameters of Willow (Salix spp.) Clones for Leaf Traits Anchal, J.P. Sharma, Tushal, Aman Mahajan and Shikha Thakur 527 Incidence and Dispersion of Plant Parasitic Nematodes in Cauliflower Growing Regions of Tamil Nadu 533 Arun, A., Shanthi, A. and Shandeep, S.G. Assessment of the Impact of Genetically Modified Cotton (Bt Cotton) on Soil Microbial Ecosystem 541 Sivaji Mathivanan Effect of Integrated Weed Management Practices on Flowering, Yield and Economics of African Marigold (Tagetes erecta L.) cv. Arka Bangara-2 551 Mallikarjun Hebbal, Munikrishnappa, P.M., Seetharamu, G.K., Kalyanamurthy, K.N., Rajiv Kumar, Shivanna, M., Rajeshwari, R. and Raghunatha Reddy Impact of Integrated Weed Management Strategies on Growth and Yield of African Marigold (Tagetes erecta L.) cv. Arka Bangara-2 557 Mallikarjun Hebbal, Munikrishnappa, P.M., Kalyanamurthy, K.N., Seetharamu, G.K., Rajiv Kumar, Shivanna, M., Rajeshwari, R. and Somashekhar, S. Phytochemical Analysis, HPTLC Profile, and In-vitro Antioxidant and Antibacterial Activity of Cyperus rotundus L. Rhizome Extracts 567 Radhakrishnan Naveenkumar, R.P. Raman, Saurav Kumar, Anisha, V. and Chandan, G.M. Cryobiotechnological Tool: Cryopreservation of in vitro Grown Shoot tips of Grape (Vitis vinifera L.) cv. Fantasy Seedless 579 Suhasini, S.C., Kulapati Hipparagi, Satish Pattepur, Gollagi, S.G. and Sanjivreddi G. Reddy Online Mode of Education and Constraint in Diploma Agriculture College, ICAR - Krishi Vigyan Kendra Bidar, Karnataka 583 Sunilkumar, N.M., Rakesh Varma, Akshaykumar and Ningadalli Mallikarjun Morphological and Biochemical Markers for Dry Root Rot (Macrophomina phaseolina (Tassi) Goid) Resistance in Brinjal 587 Sherly, J. Impact of Climate Change on Water Requirement and Yield of Tomato Over different Agro-climatic Zones of Tamil Nadu 595 Guhan Velusamy, Geethalakshmi Vellingiri, Bhuvaneswari Kulandhaivelu, Senthilraja Kandasamy and Kowshika Nagarajan Analysis of Resource Use Efficiency and Constraints of Gram Production in Gadchiroli District 601 Asha B. Kayarwar, Rohma Ansari, N.T. Bagde and S.N. Suryawanshi Process Analysis of Production of Fertilizer and Determining Loss due to Failure to Meet the Specification Rohma F. Ansari, Asha B. Kayarwar, S.N. Suryawanshi and N.T. Bagde 607 Morphological Characterization of Roselle (Hibiscus sabdariffa L.) Germplasm for Qualitative Traits 613 N. Hari Satyanarayana, S. Mukherjee, K.K. Sarkar, V. Visalakshmi and S.K. Roy Effect of Moisture Stress on Wheat Crop by IW/CPE Approach on Water Requirement and Water Use Efficiency 619 Rahul Ashok Pachore and Sachin Babaji Deore Induction of Seed Dormancy and its Impact on Seed Quality in Groundnut (Arachis hypogaea L.) 627 Parashivamurthy, R. Siddaraju and Hariah, M.S. Effect of different Moisture Content on the Physical Characteristics of Dill Seeds (Anethum graveolens L.) 633 Vidushi Mehta, R.F. Sutar and Chandani Popalia Development and Characterization of Environment Friendly Starch and Protein Based Packaging Materials for Food Applications 637 Gurpreet Singh, Sivakumar, S., Chawla, R. and Viji, P.C. Artificial Intelligence Based Grading System for Mango Fruit- A Review 641 Kshitiy V. Vibhute, P.P. Patil and A.K. Rupnar Studies on Effect of Organic Manures and Seed Priming on Growth and Seed Yield in Paddy (Oryza sativa L.) 647 Siddaraju, R., Sumalata, B. and Parashivamurthy Pseudomonas Species Potential for Organophosphorus Degradation Priya Borad, Manisha Chaudhari, Khyati Harkhani and Anish Kumar Sharma 653 From Dr. Amitava Rakshit PhD (IIT-KGP) FSES, FTWAS.Nxt (Italy), FBiovision.Nxt (France), FCWSS, FSBSRD Department of Soil Science & Agricultural Chemistry Institute of Agricultural Science, Banaras Hindu University, Varanasi-221005, INDIA E-mail: amitavabhu@gmail.com Voice: 05422-6701604 (O), +91-9450346890 (M), Fax: +91-542-2368465 EDITORIAL Food and agriculture position today at a junction. The three challenges – feeding a mounting population, providing a livelihood for farmers, and shielding the environment – must be tackled together if one need to make sustainable progress in any of them. But making headway on this triple challenge is always a difficult job, as creativities in one sphere can have unintended penalties in another. Nevertheless, advancement has often come with social and ecological costs, including water insufficiency, soil degradation, ecosystem stress, biodiversity damage, declining fish stocks and forest cover, and high intensities of greenhouse gas releases. The productive prospective of our natural assets base has been dented in numerous places round the globe, negotiating the forthcoming luxuriance of the planet. Looking forward, the track to comprehensive prosperity is evidently manifested by the 2030 Agenda for Sustainable Development. Disabling the multifarious challenges that the world faces necessitates transformative action, approving the philosophies of sustainability and attempting the core grounds of poverty and hunger to leave no one behind. This special issue attempted to address themes like sustainable transformation in agriculture and food production system, recent advances in aquaculture for food and nutritional security, innovation in global & regional agricultural education towards youth empowerment, climate change resilient agriculture, post-harvest technology for responsible consumption, global and regional policy transformation in greater detail. Sincerely Amitava Rakshit, PhD Institute of Agricultural Sciences, BHU, Varanasi, India International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 277-285, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.1 Role of Multispectral Vegetation Indices in Precision Agriculture – A Review Moncy S Akkara1*, A.R. Pimpale1, S.B. Wadatkar1 and P.B. Rajankar2 Department of Irrigation and Drainage Engineering, CAET, Dr. PDKV Akola, Maharashtra, India Associate Scientist, MRSAC, Nagpur, Maharashtra, India 1 2 *Corresponding author: moncysakkara@gmail.com (ORCID ID: 0000-0002-8436-3663) Paper No. 986 Received: 01-06-2022 Revised: 26-06-2022 Accepted: 09-07-2022 ABSTRACT Globally, the rising population and exhausting natural resources necessitate the monitoring and management of resources in the best possible way. Precision agriculture deals with the precise supply of agricultural inputs according to the actual crop requirements, thus making the most out of the agricultural practice. The traditional method of field scouting is labor-intensive and time-consuming. The ability to automate the collection, processing and implementation of data increased with new technology viz. GIS, GPS, and remote sensing. Remote sensing can act as a rapid and precise information-gathering technique on spatial variability within the field and temporal variability along long time series. Multispectral vegetation indices were developed to characterize vegetation based on its canopy reflectance. Hence, crop monitoring can be done by using vegetation indices as a surrogate for agronomic parameters. Inferences from crop monitoring based on the vegetation indices can be used for precision agricultural practices and thus achieve better agricultural management. The remote sensing technique with its rapidity and repeatability has got huge potential in analyzing the conditions of soil and vegetation, ultimately leading to applications in sustainable crop and soil management. The paper explores the role of remotely sensed vegetation indices in precision agriculture. HIGHLIGHTS mm Concepts of precision agriculture. mm Basics of Remote Sensing. mm Major Vegetation indices and their application. mm Scope and limitations of using multispectral vegetation indices in precision agriculture. Keywords: Vegetation Indices, Remote Sensing, Precision agriculture, Spatial variability, Crop management With the increasing food demands of the evergrowing world population and deplenishing natural resources, viz. water, the supply, and quality of water became a major concern which is even capable of challenging food security. The situation gains huge gravity in arid and semi-arid regions which were water-sensitive already. Besides, the agriculture sector has now been transformed into a whole new industry which is even regarded as the silver line of the economy. This changed the outlook on agriculture and necessitated the need for adopting cultivation practices that ensures better yield and economic returns. Like any other industry, the commercialization of agriculture arises the need for minimizing the inputs and maximizing the profit through maximizing the crop yield. With new-age technologies, farmers get various options to maximize their profit. Market-oriented cultivation practices by anticipating or delaying cropping, How to cite this article: Akkara, M.S., Pimpale, A.R., Wadatkar, S.B. and Rajankar, P.B. (2022). Role of Multispectral Vegetation Indices in Precision Agriculture – A Review. Int. J. Ag. Env. Biotech., 15(Special Issue): 277-285. Source of Support: None; Conflict of Interest: None Akkara et al. selling carbon credits to industry, and precision agriculture are a few examples. in soil properties and crop productivity owing to their complex arrangement of landscapes and soils. This opens up wide scope for precision agriculture (Tanriverdi 2006). Deplenishing water resources along with increased environmental consciousness also accelerated the shift to precision agriculture. Initiatives by several governmental and non-governmental organizations to increase awareness of achieving a greener safer environment is also notable in stressing the need to lessen chemical fertilizers and pesticides in agriculture. Precision agriculture renders information for better decision making in agricultural management, provides more accurate farm records, reduces input cost via increased application efficiency, improves crop yield, increases profit margin, and reduces pollution, thereby, promoting improved management of agriculture leading to better yield and better economic returns (Arnold et al. 1999). Variability in crop yield is due to the spatial and temporal variability of several factors viz. soil fertility, landscape, climate, etc. Hence, sitespecific management is essential for sustainable agricultural production. The application of remote sensing technology in agriculture helps to identify the spatial variability within a field and temporal variability along a long time series quickly and reliably. The paper reviews the context of using remotely sensed vegetation indices in precision agriculture. Precision Agriculture Concerning irrigation water management, variability within the field can be described by defining zones of difference in total plant available water (TPAW). For higher TPAW gradient over a short distance needs the collection of more soil samples. Though sampling requirements in comparison to a uniform grid can be reduced by using crop yield patterns to determine soil samples, practically, differences in crop yield patterns may not be directly influenced by TPAW variability (Post et al. 1988; Tanriverdi 2006). Precision agriculture involves using the information on site variability to effectively manage the sites. It’s a combination of several tools viz. GPS, GIS, RS, VRT, and sensor-controlled automatization. It facilitates awareness of the site-specific, practical, and profitable management practices among the agricultural input suppliers, growers, and processors (Lowenberg-DeBoer et al. 2002). A major reason for the difficulty in precision agriculture is the time consumed during conventional data collection methods, especially in large field areas. Besides, it cannot be carried out simultaneously. Limitations to precision agricultural practices can be overcome with the combined application of advanced techniques viz. GIS, GPS, and RS. The relationship between climatic factors and crop production can be of first-order level (Huggin and Alderfer 1995). Hence, precision agriculture mainly focuses on management based on spatial variability in a standard to fine climactic conditions. For precision agriculture, sensing systems for different factors viz. soil, crop, disease, and environmental factors are jointly used with a positioning system (Stafford et al. 1997). A large quantity of data can be analyzed at a faster rate and with more accuracy using remote sensing and GIS. Furthermore, it helps in the frequent monitoring of crops. GIS maps can be created using remote sensing and GPS which can be utilized for better resource management. Yield mapping refers to the graphical representation of the quantity of the crop yield on a space and time scale in a map outline using appropriate sensors, GPS hardware, and GIS software. Yield maps help farmers to identify locations within fields where the yield can be improved or inputs can be adjusted to maximize profit along with environmental quality. As the Conventional farming is based on the general assumption that fields are homogenous and hence, treated monotonously. More information on the spatial variability enables site-specific treatment. Thus precision agriculture can effectively reduce the impacts of agricultural inputs such as chemical fertilizers and pesticides on the environment along with increasing crop production. There would be no need for precision agriculture if the fields were uniform due to the high capital cost involved in it. Usually, large agricultural fields are more observed with spatial variability both Print ISSN : 0974-1712 278 Online ISSN : 2230-732X Role of Multispectral Vegetation Indices in Precision Agriculture – A Review recommendations for input and farm profitability depend on crop yield, yield mapping has got a huge role in precision agriculture. Differential Global Positioning System (DGPS) receivers. Also, it updates its working conditions to the users. GPS can be used to precisely study the spatial variability of soil and crop and thus monitor the micro and macro scales of spatial variability in agricultural conditions. Besides, it can generate the architecture of agricultural land viz. field boundaries, field acreage, the disease-affected region, irrigation systems, roads, etc (Sahu et al. 2019). GIS: Often regarded as the brain of precision agriculture, GIS creates a georeferenced map, and data on position and attributes are stored. A high volume of data can be processed within a short period using GIS. Furthermore, GIS acts as a decision management tool combining data with agricultural knowledge and producing spatially variable recommendations on agricultural inputs. Thus, users can efficiently utilize their resources. Remote Sensing Remote Sensing acts as a spatial information source. Remote Sensing is the method to collect information on objects without being in physical contact with them (Diker 1998; Seyhan 2004). Data is collected by measuring the reflected or emitted electromagnetic radiation from the land surface since it is strongly linked to the surface parameters viz. soil moisture content and vegetation. Thus, these parameters can be derived from reflectance measurements. Reflectance is the ratio of the amount of light reflected from the plane to the irradiance to that plane (Suits 1983). Raster GIS characterizes the spatial variability of a field by partitioning the whole area into regular grid cells while vector GIS makes use of points, lines, and polygons. Statistical analysis is used by many researchers to better identify and represent the relationship between agricultural production and spatial factors (Mulla and Schepers 1997). GIS-derived spatial variability maps have got applications in guiding agricultural inputs viz. fertilizer, pesticides, water, etc. by analyzing corresponding factors viz. soil organic carbon content, bulk density, soil profile water retention, etc. Besides, GIS maps can be used to assess environmental health viz. ambient air pollution study (Sahu et al. 2019). Components of a remote sensing system are carrier platform, remote sensors, control, and positioning systems, data transmission system, and data preprocessing system that is included under the three broad classes viz. ground base system, spatial foundation system, and remote sensing data storage system (Yin et al. 2019). Instruments used for collecting data in remote sensing are called remote sensors and it is usually placed on aircraft and satellites (Diker 1998). Remote sensors are broadly classified as imaging and non-imaging. Imaging instruments gives two -dimensional image of features under observation while non-imaging instruments viz. spectroradiometers measure radiation intensity across a wavelength range of very narrow wavebands. Spectroradiometers can finely differentiate characteristics leading to better interpretation of remotely sensed images and selection of spectral bands for prospect remote sensing imaging devices. These instruments can be used to measure reflected and emitted radiation at immensely small intervals of wavelength with high spectral and temporal resolution. It can be utilized to collect ground truth data (Neale 1983). GPS Global Positioning System (GPS) is a satellitebased free navigation system that is developed and maintained by the US. Radio signals from satellites are collected by the receivers which are on the ground and then it is converted to the position data (Bernhardsen 1992). Position data covers all the three dimensions viz. latitude, longitude, and elevation. Hence, GPS helps in obtaining locationspecific values for any parameter. GPS supports GIS by geo-referencing both input data and recommendations. GPS performance has two modes. A single receiver mode collects data on timing which is then converted to position while a differential mode has got two receivers, one stationary and the other on the mobile GPS instrument. Accuracy of positions can be improved up to the range of 1 m using Print ISSN : 0974-1712 279 Online ISSN : 2230-732X Akkara et al. Remote sensing using a satellite platform provides consistent, comparable, and cost-effective data of high spatial resolution even from long time series (Foley et al. 1998). Free access to multispectral and visible data is an added advantage of certain satellite platforms. Satellite remote sensing allows the collection of data on large agricultural fields at frequent intervals. It can be used to monitor agricultural and hydrological conditions of any land surface. The number of bands obtained by remote sensing is increasing as high-resolution spectral instrumentation is used, and the bandwidth is narrowing (Honkavaara et al. 2013). in the tissue and to some extent, affected by leaf structure (Tanriverdi 2006). Reflectance spectra obtained from plants vary with plant variety, growth stage, the moisture content in tissue, and other intrinsic characteristics (Chang et al. 2016). Morphological and chemical traits of the surface of leaves or organs are another determinant factor of spectral reflectance (Zhang and Kovacs 2012). Reflectance measurements can be used for determining chlorophyll content in leaves which can be related to the nitrogen grade of the vegetation (Thomas and Oerther 1972). Spectral reflectance from plants in the thermal infrared region (800014000 nm) can be directly linked to its temperature and hence, can be used for stomata dynamics assessment (Xue and Su 2017). The variances and changes in the green leaves of plants, as well as canopy spectral properties from remotely sensed photos, are used to analyze vegetation information. The major advantage of remote sensing over conventional mapping techniques is that it can derive complex relationships even from an aerial view (Grenzdorffer 1997). Remotely sensed data has got direct and indirect applications. Sensor captured images can be directly used for any purpose or information is derived from the image and then this information is used for any management purpose (Frazier et al. 1997). Remotely sensed data from terrestrial vegetation have got applications in the broader fields of agriculture, biodiversity conservation, environmental monitoring, forestry, urban green infrastructures, etc. Data required in precision agriculture, for sitespecific management can be categorized into three classes. Conditions that are constant throughout the season viz. soil properties are classified as information on seasonally stable conditions and hence, it has to be measured only at the beginning of the season whereas information on seasonally variable conditions is the class of dynamic conditions throughout the season viz. moisture content of the soil, diseases and pest infestation of crop and therefore, it has to be monitored throughout the cropping season. The third class is the information to identify the factors for yield spatial variability and to develop a management strategy, which determines the causes of the variability as it is comprehensive of the first two categories. Remote sensing can be used to acquire all the three categories of information for the successful implementation of precision agriculture (Moran et al. 1997). Remote sensing in precision agriculture C o n ve n t i o n a l m e t h o d s o f t a k i n g g r o u n d measurements of various vegetation parameters viz. leaf area, biomass, etc. are expensive and tiring. Remote sensing methods utilize the spectral reflectance of vegetation and soil to obtain their attributes.. It is based on the fact that any surface reflects, absorbs, or transmits incident light. The length of the growing season was found to be irrelevant since the fresh and green leaves accounted for similar reflectance spectra (Sinclair et al. 1971; Neale 1983). Remote sensing has got applications in terms of both macro and micromanagement in the field of agriculture such as vegetative cover estimation, canopy temperature monitoring, stress identification, water deficit determination, irrigation scheduling along with yield prediction (Mulla 2013). Remote sensing of vegetation is majorly based on the ultraviolet (10 to 380 nm), visible (450-750 nm), and the near and mid-infrared (850-1700 nm) regions of light spectra (Rahim et al. 2016; Cruden et al. 2012). The wavelength spectrum responded differently to leaf characteristics– visible light was absorbed by pigments, the NIR region was affected by internal leaf structure and the wavelength spectrum beyond that was influenced by the concentration of water Print ISSN : 0974-1712 Direct application of remote imagery gained popularity with the advances in technology like GPS and sensors leading to better affordability 280 Online ISSN : 2230-732X Role of Multispectral Vegetation Indices in Precision Agriculture – A Review and availability. The real-time position can be superimposed on the remotely sensed imagery using GPS and any point within the photograph can be accessed. And thus, variability in soil and crop can be analyzed and managed directly from images. Vegetation indices derived from remote sensing are the most effective but simple algorithms to quantitatively and qualitatively analyze vegetation cover along with vigor and its growth dynamics. There is no single mathematical expression for defining every vegetation indices. Since each of them is tailored to suit specific applications and is derived from visible and non-visible spectra, their applicability depends on the platforms and instruments involved (Xue and Su 2017). Indices developed from near and mid-infrared regions can represent various characteristics of plants viz. pigments, water content, sugar content, carbohydrate content, protein content, aromatics, etc. apart from proxy quantification of growth and vigor (Foley et al. 1998). Multispectral vegetation indices derived from the reflectance of the canopy in comparatively broader wavebands can be used to monitor the vegetative growth corresponding to climatic variables (Hatfield and Pinter 1993). Another major direct application of remote sensing in precision agriculture is the extraction of management zones from remote sensing imagery-derived vegetation indices maps using GIS software. When integrated with variable rate sprayer equipment, site-specific requirements are met with the help of real-time sensors, leading to reduced groundwater contamination and improved nutrient use efficiency (Schepers and Francis 1998). The indirect application includes the preparation of a base map with different layers of information using GIS, soil mapping across the field, use of remotely sensed vegetation parameters in crop simulation models, identifying location and factors causing crop stresses viz. diseases, insects, and weeds, improving soil sampling strategies with remotely measured soil and plant parameters. Soil salinity areas can be mapped using remote sensing data (Basso et al. 2004). Ratio Vegetation Index (Jordan 1969) is a simple ratio index with high sensitivity to vegetation and a strong link to plant biomass. Hence, RVI is commonly used for the estimation and monitoring of green biomass, especially when vegetation coverage is very dense. In sparse vegetation conditions, they are susceptible to atmospheric effects leading to poor representation of biomass. Difference Vegetation Index or the Environmental Vegetation Index (Richardson and Weigand 1977) are used to monitor the ecological environment of vegetation and is highly sensitive to soil background changes. Vegetation Indices Vegetation indices are in general, either ratios or linear combinations of spectral reflectance corresponding to different wavelengths obtained from radiometer bands. They can give better correlations with vegetation parameters viz. plant height, green leaf area index, leaf chlorosis fraction, the water content in leaves, vegetation cover percent, and wet and dry biomass, than the individual bands. (Bausch and Neale 1987). Hence, vegetation indices were introduced to monitor and analyze these agronomic parameters. Vegetative growth at any stage can be monitored using the Normalized Difference Vegetation Index (Rouse et al. 1973) and Perpendicular Vegetation Index (Richardson and Wiegand 1977). Besides, PVI can efficiently eliminate soil background effects. Major applications of PVI are LAI calculation, surface vegetation parameter(grass yield, chlorophyll content) inversion along with crop identification and classification (Kaufman and Tanré 1992; Wenlong 2009). Adjustments have to be done to combat sensitivity to soil brightness and reflectivity. Vegetation cover can be estimated from vegetation indices derived from the reflectance of the canopy. This estimated vegetation cover can be used instead of measured vegetation cover (Moran et al. 1994). Thus, crop monitoring can be done which can be used for improved management through precision agriculture. The water deficit of any plant at any growth stage can be estimated from crop monitoring based on reflectance measurements. Thus, water management can be done which is the major part of agricultural crop management. Print ISSN : 0974-1712 The most widely used vegetation index is the NDVI, even used in local and global assessments of vegetation and is highly sensitive to green vegetation. Furthermore, NDVI requires remote sensing 281 Online ISSN : 2230-732X Akkara et al. calibration due to its sensitivity to atmosphere, cloud and cloud overcast, leaf canopy brightness and shadow, soil brightness, and soil color. NDVI is correlated to canopy photosynthesis along with canopy structure and LAI. Many researchers have correlated NDVI with Leaf Area Index (Xue and Su 2017). from regions of interest becomes difficult in such areas due to the variations in soils, weeds, cover crops, and vegetation of interest, especially when a single plant has got different vegetation indices because of spatial variability. Image processing steps viz. filtering and denoising get complicated if the vegetation indices of the study crop are similar to that of other crops. However, a simplistic vegetation index algorithm can give simple but effective tools to quantify the vegetation status on the land surface (Hoffmann et al. 2015; Xue and Su 2017). Several modifications were done on NDVI in an attempt to increase the ability to derive better interpretations. Soil Adjusted Vegetation Index (Huete 1988) and Modified Soil Adjusted Vegetation Index (Qi et al. 1994) minimizing the effect of soil background are examples. Concerning the low noise level, SAVI was suggested as a better vegetation indicator among other basic vegetation indices. In an attempt to optimize the L factor in SAVI, the MSAVI was developed with a variable correction factor, L. This L varies with canopy cover and soil type. A Modified Normalized Vegetation Index (Liu and Huete 1995) integrates both atmospheric and soil adjustment factors. The spectral resolution of remotely sensed data used for the extraction of vegetation indices is yet another challenge to be addressed. Though vegetation indices developed from broader wavebands can identify various stress, they cannot recognize the exact factors causing a specific type of stress. Hence, physiological stresses viz. water and nutrient shortage are better correlated with narrow-band indices like Water Band Index, Normalized Pigment Chlorophyll Ratio Index, Canopy Chlorophyll Content Index, and Photochemical Reflectance Index (Basso et al. 2004). Stress related Vegetation Index (Gardener 1983) and Cubed Ratio Index (Thenkabail et al. 1994) were developed from the Mid-InfraRed Band. Visible Atmospherically Resistant Index (VARIgreen) is another example of vegetation index being in a strong relationship with measured vegetation cover (Gitelson et al. 2001). Spatial resolution and orbit period of satellite platforms are the two major concerns in the precision agriculture applications viz. nutrient and water management. Also, the use of a large number of sensors can make the whole process expensive for long time series. The unavailability of satellite data on cloudy days due to the inability of passive sensors to penetrate through clouds is another concern. Though this issue can be partially rectified by the usage of airborne platforms and Unmanned Aerial Vehicle platforms, it has got its share of drawbacks. The airborne remote sensing method requires air crafts and pilots and hence can be expensive. However, Unmanned Aerial Vehicle platforms have got high temporal and spatial resolution (sub-meter resolution). It makes use of affordable aircraft and camera payloads from visible to thermal infrared and also, 3D LIDAR, and thus, a better alternative platform for assessing plant growth and vigor, irrigation scheduling, evapotranspiration modeling, etc (Xue and Su 2017). Though few researchers found that measured vegetation cover represents the vegetation cover in a better way than the estimated vegetation indices, the practical difficulties involved in a measuring method viz. time required to complete a data set, possible crop damage, usage of instruments for the entire growing season has to be considered. Hence, using vegetation indices over measured vegetation cover has got advantages like lesser time, lesser cost, minimum labor requirements, and large data availability, especially in larger areas (Tanriverdi 2003). Scope and Limitations of Vegetation Indices in Precision Agriculture As vegetation indices are developed from single or limited bands, lack of sensitivity in acquiring data, especially from heterogeneous canopies viz. horticultural tree plantations, might be counted as a shortcoming. Extraction of vegetation indices Print ISSN : 0974-1712 Less developed countries don’t much prefer precision agriculture tools since their smaller agricultural areas and their corresponding cost of agricultural inputs doesn’t signify the use of precision agriculture. The initial cost involved in 282 Online ISSN : 2230-732X Role of Multispectral Vegetation Indices in Precision Agriculture – A Review CONCLUSION using precision agriculture techniques is more in small field areas. Hence, conventional farming techniques are found to be more affordable than precision agriculture techniques in improving the management of agriculture. However, the scattered nature of these agricultural fields necessitates field use planning. Furthermore, precision agriculture offers better results in terms of time, labor, and data availability. It would be better to determine the field size for which precision agriculture is significant considering factors such as water supply and cost of precision agriculture (Tanriverdi 2006). Remote sensing acts as a spatial information source based on the spectral reflectance from vegetation and soil. It has got direct and indirect applications in precision agriculture. The use of vegetation indices to quantify spatial variability within the field and thus manage crops and resources is one such application. Vegetation indices are extracted from the reflectance data obtained from the remotely sensed images. Generally, Vegetation indices are developed from the reflectance measurements from NIR and red bands, combined in various ways. The major advantage of remote sensing in agriculture is its non-destructive nature along with its accuracy and swiftness. Near real-time data obtained from remote sensing helps in actively managing the inputs and thus maximizing yield and economic returns. Vegetation indices derived from remotely sensed data can identify crop stress conditions to a large extent. As each vegetation index was developed to address a different concern, judicious use of vegetation indices is necessary to point out the crop conditions along with underlying factors. High cost in image acquisition, coarse spatial resolution, and insufficient temporal and spectral resolution are the major limiting factors of the use of satellite images in precision agriculture. Major limitations can be overcome by increasing the spatial, spectral, and temporal resolution of remotely sensed data. Free access to high-resolution data is now made available by various agencies like USGS earth explorer while freeware like QGIS is available for the processing of satellite data. As the technology develops, the availability, reliability, resolution, and cost-effectiveness of the remote sensing images are expected to improve further and will lead to better interpretation of vegetation indices on the spatial and temporal variability of crop and soil. The importance of providing accurate and relevant information at a faster pace and low cost is needless to emphasize, for the effective use of remotely sensed vegetation indices in precision agriculture. Thus, just like in every other sector, remote sensing applications become the need of an hour in the agriculture sector. Technological illiteracy among the farmer community might give rise to the hesitation in adopting advanced technology like precision agriculture. Inadequate knowledge and technical expertise in analysis and decision making using a computer at both local and regional levels are probably the major constraints in the success of precision agriculture (Sahu et al. 2019). Requirements for successfully using remotely sensed data in precision agriculture are the high spatial resolution (preferably, not more than 10 m), frequent coverage, timely availability, low cost, and integration with expert systems (Tanriverdi 2003: Sahu et al. 2019). Precision agriculture tools (GIS, GPS, and remote sensing) together can provide a complete data set that is accurate to use in precision agriculture, especially in heterogeneous or large agricultural areas. For the best outcome from precision agriculture, potential limiting factors to crop profitability must be identified and addressed. Poor aeration, Soil water availability, and weed pressure are a few examples of limiting factors. A better understanding of spatial variability in yield and factors responsible for it, both environmental and managemental, will give a finer idea of bestsuited site-specific agricultural operations. With the better correlations evolved between these factors and yield, improved spatially variable recommendations can be obtained (Tanriverdi 2006). Integrating remotely sensed data with crop simulation models has a huge prospect in agriculture applications (Basso et al. 2004). Rapid mapping of insect infestation, treatment logging by variable-rate spray operators, and pattern study of disease spread are a few of the aspects which can be incorporated into precision agriculture with the help of remote sensing (Sahu et al. 2019). Print ISSN : 0974-1712 REFERENCES Arnold, E.J., Rickman, D. and Samuelson, D. 1999. Precis. Agric. pp. 1-2, http://www.ghcc.msfc.nasa.gov/precisionag. 283 Online ISSN : 2230-732X Akkara et al. Basso, B., Cammarano, D. and Vita, P.D. 2004. 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Print ISSN : 0974-1712 285 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 287-297, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.2 Three-Dimensional Printing in Food Process Engineering: A Prospective and Retrospective Analysis Amrutha, G.* and Bhagyashree N Patil Department of Agricultural Process Engineering, Dr. Panjabrao Deshmukh Krishi Vidyapeeth, Akola, Maharashtra, India *Corresponding author: amruthagnirmalyam@gmail.com (ORCID ID: 0000-0002-8767-2840) Paper No. 987 Received: 31-05-2022 Revised: 28-06-2022 Accepted: 07-07-2022 ABSTRACT Three-dimensional printing technology is a novelty which is going to usher the new aeon of localised manufacturing by promising to transfigure food formulation as well as manufacturing process. As compared to the food manufacturing processes based on robotics, three-dimensional food printing combines both the 3D printing and the technique of digital gastronomy to fabricate food products with personalization in shape, texture, color, even nutrition and flavor. This brings up artistic proficiencies to fine dining and extend personalization capabilities to industrial culinary sector. 3D printing is a technology which uses a number of additive manufacturing techniques for food product fabrication. The objective of the study is to analyse various printable materials, printing platforms, and the food printing mechanisms. This study also provides a better insight towards the different advantages and limitations of food product fabrication using 3D food printing. This study is done to analyse and summarise published papers and articles relating to 3D printing, its impact on food process engineering and also to provide an insight to the direction of its future. The printing technique comprising of extrusion based and inkjet printing and binder jetting. From this technology review, it’s clear that the food printing may exert a significant influence on various types of food processing, which allow designers/users to manipulate/customize forms and materials with enhanced and unprecedented capability. HIGHLIGHTS mm Different materials that can be used for 3D food printing were discussed. mm Technologies adopted for printing were reviewed. mm Advantages and limitations of food customization were analysed. Keywords: 3D food printing, printing platforms, multi-materials, extrusion-based printing, sintering technology Food, consisting essentially of protein, carbohydrate, fat and other nutrients used in the body of an organism, being any substance that is eaten, drunk or taken into the body to sustain life. Food products are rapidly evolving, so there is an increasing demand for its manufacturing field to follow up the novel practices and tools to work effectively. About 15-25% of people over 50 years of age endure from swallowing difficulties. Pureed foods not only overcome this difficulty but also provides the necessary nutrition to them, but most of them are unpleasing and unappetizing. Customization has been marked as the driving force to hamper conventional ways to produce and deliver food. There is an expanding market demand for mass customization on colors, textures, shapes, nutrition flavors etc., which covers many of the food products including customized ice creams, cakes, coffees, hamburgers and biscuits. Most of the food structuring techniques are developed for mass production. Personalized foods are How to cite this article: Amrutha, G. and Patil, B.N. (2022). ThreeDimensional Printing in Food Process Engineering: A Prospective and Retrospective Analysis. Int. J. Ag. Env. Biotech., 15(Special Issue): 287297. Source of Support: None; Conflict of Interest: None Amrutha and Patil generally designed by specially trained artisans using methods, which involves assembling of prefabricated parts to meet customer demands. But producing a small number of such pieces are not at all economical (Sun et al. 2015a). So, in order to achieve mass customization economically, an innovative technology to design and fabricate food is necessary. and lifestyle by flawlessly integrating nutrition and enables manufacturing of customized foods (Rodgers 2016). Usually dehydrated raw materials are preferred for 3D printing to evade the deterioration of raw/fresh ingredients (Nachal et al. 2019). The 3D printers have an ability to use dehydrated foods or can dehydrate the foods after printing. This makes 3D printing technology convenient for producing space foods as compared to the traditional processing methods where it requires longer nutritional stability (Terfansky and Thangavelu 2013). By altering or eliminating or decreasing the protein, fibre, vitamin, cellulose and fat contents, and by introducing some functional compounds including carotenoids and anthocyanins to give desired functions, with relative ease, 3D printing technology can produce personalized food for pregnant women and athletes (Dankar et al. 2018). These printed foods with upgraded taste and visual appeal are suitable not only to elderly people and patients with paralysis, Parkinson’s disease and stroke but also for children and teenagers with specific nutritional needs (Portanguen et al. 2019; Hamilton et al. 2018). In fact, 3D printing facilitates fabrication of customized foods, having both health promoting as well as enjoyment factors (Severini and Derossi 2018). Three-dimensional food printing, established since 1980’s, alias additive layer manufacturing, is a novel technology which unites additive manufacturing, numerical control technology, computer technology, material science technology and precision drive technology to produce custom designed 3D food objects in a layer-by-layer fashion without object specific moulding, tooling or human intervention (Yang et al. 2019). Thus, this technique can enhance production efficiency and decrease manufacturing cost for personalized food product fabrication. Also, it has its advantages on food structure personalization, broadening food raw material source, shortening of food supply chain and customized nutrition (Godoi et al. 2016; Chen 2016). This food printing, an automated manufacturing technique, has achieved increased attention for its unique ability to make complex geometric structures, allowing mass production with environment as well as economic benefits, leans on layer-by-layer deposition (Perez et al. 2019). The object designs are made by Computer Aided Design (CAD) software and the food printer is generally connected to a computer system through a USB cable. The products are fabricated on the basis of 3D models and can be structured into any shape in theory. 3D printers are robotics-based machines that can be used fabricate objects through additive manufacturing. In this, printers take only the essential matter in powder or filament, and liquid forms, which the printer then melts or solidifies to obtain the objects final shape, instead of defining shape by eliminating excess raw materials. This process holds great scope for manufacturing as it exceptionally amends all the supply chain dynamics, eliminate the need for economies of scale and also reduces cost, energy consumption, time, and transportation requirements. This study systematically reviews about the 3D printing technology, in detail, applied to food process engineering. The review provides insights about the available printing materials, functional ingredients used in printable food formulas, food printing platforms, printing recipes and various 3D printing technologies. Also, it explores the relative advantages of this technique in maintaining quality of 3D printed foods and features prospects of future research. AVAILABLE PRINTING MATERIALS The available materials for food printing are categorised in to three; natively printable materials, non- printable traditional food materials and alternative ingredients (Sun et al. 2015a). Natively printable materials Natively printable materials are the materials that can be smoothly extruded from a syringe and which shows the ability to maintain their shape after deposition and no further post processing In food processing industry, the 3D printing technique satisfies the need of consumers in accordance with their occupation, age, gender Print ISSN : 0974-1712 288 Online ISSN : 2230-732X Three-Dimensional Printing in Food Process Engineering... et al. (2010) conducted an investigation and found out one particular recipe that can print complex 3D models and maintains their shape even after deep frying. is required after printing. These materials include hummus, cake frosting, hydrogels, chocolate and soft cheese (Dankar et al. 2018). The highlight of such materials is that the food products made by them can be personalized fully for nutritional value, taste and texture. Although, majority of them are not treated as main courses so these are generally reserved for space as well as medical applications. Certain formulations including protein pastes doesn’t retain their shape easily so it requires further processing to improve nutrition absorption and taste (Cohen et al. 2009; Lipton et al. 2010; Sun et al. 2015b). Alternative ingredients These ingredients extracted from fungi, insects, lupine, algae and seaweeds are the emerging sources of fibre and protein. Combination of extrudable icing, soft cheese and insect powders were utilized as printing materials for making tasty pieces and shaping food structures in the ‘Insects Au Gratin’ project (Southerland et al. 2011). Agricultural as well as food processing residues can be used as sources of eco-friendly printing materials, by converting the residues in to enzymes, biologically active metabolites and food flavor compounds. In short, including alternative ingredients to 3D printing would benefit in creating healthier food products (Sun et al. 2018). Non printable traditional materials The foods which are consumed by people on daily basis such as rice, fruits and vegetables, meat etc. are not generally printable in nature. In order to make them capable for extrusion, additives (hydrocolloids) can be added and also it can be utilized by many culinary fields. Using gastronomic tricks, certain semi solid and solid food items have been already altered to become printable but when it comes to the entire list, it’s really difficult to modify and test. Fabricating an element set by using a limited number of ingredients assuring high degree of freedom on flavor and texture is the only potential solution. Concentration of xanthun gum, gelatin and certain other hydrocolloids are fine tuned to obtain a great range of textures (Cohen et al. 2009). A greater number of traditional edibles requires post deposition processing (baking or steaming) after printing, but it finally result to a non-homogenous texture. So, in order to modify cooking recipes for printing as well as post deposition cooking, Lipton 3D FOOD PRINTING TECHNOLOGIES Food pieces are created in a layer-by-layer fashion using food printing, which doesn’t need any high energy source for completely extracting liquid components from food composition. After deposition, the layers need not be fully solidified but the layers should process adequate rigidity and strength to hold up their own and subsequent layer’s weight without remarkable deformation or change in shape. The standard of food items, which are fabricated using food printing technology rely on the process and planning instead of people’s skill. A comparison between 3D food printing technologies is shown in Table 2. (a) (b) Fig. 1: (a) Selective laser sintering (b) Selective hot air sintering Print ISSN : 0974-1712 289 Online ISSN : 2230-732X Amrutha and Patil Table 1: Overview of various food materials successfully printed using extrusion-based 3D-printing Class Material Additive References Protein Turkey meat and scallop Transglutaminase Lipton et al. 2010 Cereal dough snack with yellow mealworm powder Sodium chloride Wang et al. 2017 Severini et al. 2018 Fish surimi gel Lipids Bacon fat Lipton et al. 2010 Chocolate Godoi et al. 2016 Le Tohicet al. 2018 Cheese Carbohydrates Lemon juice gel Potato starch Lipton et al. 2010 Mashed potato Potato starch Derossi et al. 2017 Fruit snack Pectin Yang et al. 2018a Smoothie Fish collagen Severini et al. 2018 Pectin Agar, alginate,glycerol, lecithin Lille et al. 2018 Pea protein Kim et al. 2018 Hydrocolloids Baking cookies Chuanxing et al. 2018 Fruit snack Skim milk powder Selective sintering technology Extrusion based food printing techniques depends on continuous flow of ink in layer-by-layer manner, usually heavily concentrated colloidal inks. Based on the ability of a material to form gel or to achieve paste consistency, the total solids can range from 5-50% concentration. When a pressure gradient ΔP through a length of l is applied, the ink starts flowing through the nozzle. Thus, according to Eq. 1, a radially changing shear stress (τr) is developed, where r denotes the radial position within nozzle (Godoi et al. 2016). At the centre of nozzle wall (r=R), velocity is zero, and at centre (r=0), velocity is maximum (Lewis 2002). The absolute aim of this method is to obtain the output of food extrusion cooking with customized nutrition control and digitalized design. Selective sintering technology is a technique that generally uses a power laser or hot air as a source to selectively bind the particles in powder form layer by layer and finally to a 3D structure. In order to sinter NesQuik powders and sugars, TNO’s food jetting printer used laser and thus built 3D objects (Gray 2010). The material, which is sintered forms the product part while the remaining un-sintered powder provides support to the structure. A low velocity hot air stream is used to melt and sinter a bed of sugar by the CandyFab (2007). The created powder bed is heated to a temperature which is just lower than the melting point of that material so as enable fusion to the preceding layer and to reduce thermal distortion. Both hot air and laser sintering processes enables to rapidly build food items in a short span of time without any further curing. However, their limitation is that they are only appropriate for fat-based materials and sugar, having relatively low melting point, and also as it involves so many variables, machine structure as well as the fabrication processes will be complicated (Sun et al. 2018). τr = …(1) Extrusion based food printers are badly limited by material choices, delamination due to temperature fluctuation and long fabrication time but these printers are of compact size and low maintenance cost (Sun et al. 2018). Table 1 gives an idea of various food materials that can be printed using extrusionbased 3D Printing. Extrusion based 3D Printing The process of forcing solid/semi solid/liquid materials via die opening for fabricating objects with required cross-section is extrusion (Sun et al. 2018). Print ISSN : 0974-1712 r ∆P 2l Melting Extrusion Materials in the form of powder, filament and paste 290 Online ISSN : 2230-732X Three-Dimensional Printing in Food Process Engineering... are generally considered as the suitable materials for melting extrusion. In order ensure printability, it is necessary to control temperature during printing of fat or sugar rich pastes. Chocolate, the most commonly used edible ink because of its melting properties, can be fed to the reservoir of printer either in powder form or in paste like/melted form (Mantilal et al. 2020). Edible filaments are rarely produced and printed. Goyanes et al. (2015) created various filaments, which contains caffeine or paracetamol in a water-soluble polymer appropriate for 3D printing into different pharmaceutical dosage forms. If the filament production is followed by fused deposition modelling (FDM), then the post processing procedures which is generally required for food printing can be avoided. In food processing applications, it’s believed that the food grade filaments will find its usage in the confection of packaging of foods (Godoi et al. 2019). difficulties. This temperature control is utilized for making many economic machines including HFE for fruit printing (Molitch-Hou 2014), hot melt extrusion (HME) for printing chocolate (Choc Edge 2014), room temperature extrusion (RTE) for printing (Alec 2015; Molitch-Hou 2014). Binder Jetting In this technology, every single layer of powder is uniformly distributed across the platform of fabrication, and then a liquid binder sprays to join two consecutive layers (Sachs et al. 1992). In order to stabilize powder material and reduce disturbance occurs due to binder dispensing, a layer of water mist should be sprayed before fabrication. Sugar Lab in 2013 utilized different flavor binders and sugar for fabricating sculptural cakes which are complex in nature for special events and the fabrication utilized 3D System’s color jet printing technique (3D Systems 2013). Binder jetting provides fast fabrication with low material cost, but at the same time, it suffers from high machine cost and rough surface finish (Sun et al. 2015a). Also, in most cases it requires post processing, including curing at increased temperature, for strengthening the bonding. Hydrogel Forming Extrusion (HFE) It is the method of extruding hydrocolloid solutions in to a gel/polymer setting bath with the help of a vibrating nozzle, syringe pipette, jet cutter and similar apparatus. Diameter of these gel droplets should be in the range of 0.2-5 mm and the key to form stable shapes in HFE is controlling solution’s temperature (Sun et al. 2018). Fig. 3: Powder bed binder jetting Inkjet Printing Commercialization of Inkjet printing technology in food printing had done by the company FoodJet (FoodJet 2019). Inkjet printing uses an array of pneumatic membrane nozzle-jets which dispenses a stream of droplets of food ink onto cookies, biscuits, cupcakes, and pizza bases (Kruth et al. 2007). Two types of inkjet printing methods are Fig. 2: HFE This process exclusively depends on the gel forming mechanism and the rheological behaviour of polymer. Serizawa et al. (2014) created an edible gel 3D printer using a dispenser and syringe pump for producing soft foods for those who have swallowing Print ISSN : 0974-1712 291 Online ISSN : 2230-732X Amrutha and Patil Table 2: Comparison of 3D food printing technologies Sintering technology Melting extrusion Binder jetting Inkjet printing Materials Low melting powder Food polymers such as sugar, NesQuik (chocolate) or fat. Powder such as starch, sugars, Low viscosity materials flavors, corn flour and liquid (paste or puree) binder Platform 1. Motorized stage 1. Motorized stage 1. Motorized stage 1. Motorized stage 2. Sintering unit 2. Heating unit 2. Powder bed 2. Inkjet printhead 3. Powder bed 3. Extrusion device 3. Inkjet print-head for binder 3. Thermal control unit jetting Printing resolution Powder size: 100 μm Nozzle dia: 0.5-1.5 mm Nozzle dia ≤ 50 μm Fabricated products Food-grade art objects, Customized chocolates Sugar cube in full color toffee shapes Customized cookies, Benchtop food paste shaping Pros 1. Better printing quality Better printing quality Nozzle dia ≤ 50 μm Powder particle ≥ 100 μm 2. Complex design 1. Cost effective 1. More material choices 2. Fast fabrication 2. Better printing quality 3. Full color potential 4. Complex design Cons 1. Expensive platform Low printing quality 2. High power consumption 1. Slow fabrication 1. Slow fabrication 2. Expensive platform 2. Expensive print-head 3. Expensive platform 3. Limited materials 4. Limited materials Machine Food jetting printer Choc Creator Chefjet Foodjet Company TNO Choc Edge 3D systems De Grood Innovations Sun et al. 2015b; Godoi et al. 2019. there: Continuous Ink-Jet Printing (C-IJP) and Drop-on-Demand Inkjet Printing (DoD-IJP). In the former, ink is dispensed continuously through a piezoelectric crystal vibrating at a constant frequency. The later, DoD-IJP, ink is ejected out from heads under pressure exerted by the valve. In DoD-IJP the printing rates are slower than that of C-IJP systems, but the precision and resolution of produced images are higher. However, DoD-IJP requires the use of an electrically conducting fluid which limits the application in food customization. materials which don’t have enough mechanical strength to hold a 3D structure. Therefore, it is rather used for printing drawings over flat surfaces as surface filling or Image decorations (Pallottino et al. 2016). Grood and Grood (2011) had created DoD-IJP to lay edible liquid onto food surfaces to create appealing images. The FoodJet printer uses pneumatic membrane nozzle jets to dispense edible drops onto a moving object to form an appealing surface (FoodJet 2019). PRINTING QUALITY ASSESSMENT There are generally two important parameters by which the printing quality of a final 3D product is judged. They are shape fidelity and mechanical properties. The criteria for evaluating the printing quality are explained in Table 3. Shape Fidelity He et al. (2019) illustrated that except from printing parameters including printing distance, air pressure and feed rate, lattice area (A) and line distance (D) will also have an impact on gel lattice’s printing quality. The optimum condition for printing can Fig. 4: Inkjet printing In general, inkjet printing deals with low-viscosity Print ISSN : 0974-1712 292 Online ISSN : 2230-732X Three-Dimensional Printing in Food Process Engineering... Table 3: Criteria for printing quality evaluation Printing Quality Score Description 5 The paste should pass through nozzle smoothly. Shape should be supported with excellent precision. Printed and designed size should have a deviation less than 2%. There should not be any distortion of layer-by-layer structure. 4 The paste should pass through nozzle smoothly. Printed and designed size should have a deviation should be in the range of 2-5%. The layer which is distorted is within 5% of the entire layer-by-layer structure. 3 The paste should pass through nozzle. Printed and designed size should have a deviation should be in the range of 5-15%. The layer which is distorted is within 5-15% of the entire layer-by-layer structure. 2 The paste should pass through nozzle but the shape get collapse while printing or the collapse within 30 minutes after printing the complete shape. 1 Because of low viscosity, the printed shape will not be able to support the shape or the paste could not flow through the nozzle because of high viscosity. Liu and Ciftci 2020. also be evaluated by observing the filament material shape extruded from nozzle. The optimum gelation, characterized by an evenly extruded filament in a smooth surface and in three dimensions is illustrated in Fig. 5. It is possible to observe the liquid like behaviour of ink and droplet formation at the end of nozzle at stages of under gelation. A stiff filament with cracks all over its length can be observed when the ink is in over gelation stage. In a lattice structure, Ouyang et al. (2016) exemplified that the printability and circularity level of internal square areas can be correlated. The quality of printing of gel-like inks can be evaluated using Eq. 2 and 3. It has been observed that if Pr=1, ideal gelation is obtained and if Pr<1or Pr>1, it is the stage of under gelation and over gelation respectively. Circularity, C = 2 Pr =  π  ∗  1  = L  4   C  16 A …(2) …(3) Mechanical Properties of a 3D Printed Object Texture analyser helps to measure hardness test of solid food objects and the Texture Profile Analysis (TPA) of semihard materials. The mechanical properties of 3D printed food structures, made of gels or purees or such soft materials can be evaluated using TPA. The important attributes to be generally calculated for gel like systems are adhesiveness, chewiness, springiness, hardness and gumminess (Rosenthal 2010). The mechanical properties of gellan gum, guar gum, xanthan gum, hydroxypropyl methylcellulose, locus bean gum, methylcellulose and gelatin were analysed by Kim et al. (2017) and found that the hardness of samples significantly increases by increasing the concentration. The impact of starch addition in the 3D construct made of lemon juice gels were observed by Yang et al. (2018a, b). The higher starch content results in notable increase of gumminess and hardness as a result of heavily compacted network bore by starch molecules. TPA fails when it comes to hard materials. In those cases, texture analyser can be used for measuring hardness of freeze dried or oven dried protein rich 3D printed structures (Lille et al. 2018). The snap Fig. 5: Schematic demonstration of filament quality. At the left end, 3D lattice is shown emphasising the internal square shape, which can be transformed into the printability parameter at three levels (Pr < 1, Pr = 1 and Pr > 1) (Ouyang et al. 2016) Print ISSN : 0974-1712 4π A L2 293 Online ISSN : 2230-732X Amrutha and Patil quality of printed chocolate objects has been studied by Mantihal et al. (2020) and found the importance of supports on snap force, with the help of texture analyser. fabricated products (Sun et al. 2015c). Using multimaterials and multi-printheads are a new solution to mould food materials under multi scale into fascinating edible structures. MULTI-MATERIAL AND MULTIPRINTHEAD ADVANTAGES AND LIMITATIONS OF FOOD PRODUCT FABRICATION WITH 3D PRINTING There is a need of multi-printheads in the food printing sector for maintaining homogeneity as majority of printers have only one print head for extruding mixture of materials, which makes it difficult to control the distribution of materials within a layer. In this, platform controller activates each print head and thus gives information to individual layers and also controls its feed rate. Researchers had adopted multiple print heads Fab@ homeTM printers and created products including chocolate, muffins, cookie doughs, processed cheese etc. When it comes to multi-material printing, it is applicable only for a limited number of materials. Gray, (2010) solved this limitation by proposing the concept of electrospinning for producing multiple sub-components of food at a large scale. (a) Three-dimensional food printing has widely noticed by food enthusiasts all over the world as it has made so many hitherto impossible things possible. This technology made production of food seamless and fast. The major advantage is that it made possible to design the food so as to meet the concerns of individual related to their requirements and health conditions effectively and also it digitally manage the quality and quantity of food. In addition to this, it helps to reduce the waste output and improves sustainability of environment. This technology becomes eco-friendly and healthy since it converts various ingredients such as leaves from beets or insects, algae-based proteins into tasty food items. It also can utilize animal proteins which are developed in the laboratory or vegetable proteins to make meat substitutes that has high nutritional value and health benefits for intake. In spite of these advantages, this technology faces certain constraints in fabricating 3D foods such as high cost of the printing machine, material suitability for printing, less embodiment of foodsafe printing components, and lack of printing firmware (food based) and software applications (Kewuyemi et al. 2021). The advantages, limitations and suggestions for future work are explained in the following sub-heads. (b) Fig. 6: Multi-material food design and fabrication system (a) Multi-material food designs (b) Actual printed cookies In spite of using multi printheads, it is really difficult to make a single platform for printing food types. Another approach to this is to create a macro material matrix with the help of mixing technique. This matrix enables to sustain homogeneity of material supply within each layer. This mixing technique can be agitated or static and can enable different material composition and making several material supply combinations (Nachal et al. 2019). Static mixing focusses on the force between the feed and force of friction between mixer’s structure and the material. Agitated mixing provides better scope for changing the appearance and composition of Print ISSN : 0974-1712 Available firmware and slicing software In order to communicate the mechanical path of a 3D model, various printers with a firmware (builtin) and slicing software are used and it helps in accurate layer by layer deposition of materials. The mostly used slicing software packages, such as Repetier-Host, Slic3r, Cura, Slimplify3D and Rhinoceros 3D, in order to circulate the planned mechanical route instructions and conditions of processing to 3D food printers are programmed for thermoplastic polymer printing. The elastic nature of printing material can result in certain inconsistencies in printing during deposition or after 294 Online ISSN : 2230-732X Three-Dimensional Printing in Food Process Engineering... Marketing of 3D Printed Foods the printing process. A digital 3D model solid phase (30g/100g), processing a doubles percentage volume fraction from 36% to 69% in wheat alternated with succulent insect printed snack has been reported. It is important to optimize the available slicing software for printing processes or a lasting way of creating slicing application packages for fabricating 3D foods (Guo et al. 2019). This is an attractive technology of food preparation and personalization engineered in pre-defined layers. The adaptability of processing various raw materials and increasing need of food items, fabricated using this technology are the key driving forces to industrial growth to attain an expected global 3D food printing market size of 1015.4 million US dollars in 2027 (Emergen Research 2021). Food Ink, is emerged as the first pop-up restaurant to provide meals made using 3D printers. Barilla, is the first Italian company, which developed the prototype of 3D printer for pasta (Savastano et al. 2018). Its spinout has introduced an E-commerce service, through which customers can order customized printed pasta online. This platform is auspicious for promoting large market share for novel 3D printed foods. Traditional cuisine with prior familiarity plays a crucial role in the sustainability of biomodified printable substrates (Kewuyemi et al. 2021). Furthermore, the printed healthy snacks have been accepted on the basis of their sensory attributes (Krishnaraj et al. 2019). 3D Extrusion Printer Selection and Cost Implication The development of 3D printing applications is limited by the factors such as the prohibitive cost, inflexibility of component-parts and proprietary restrictions (Cohen et al.2009). But, the onset of RepRap open-source 3D printing machines has substantially overcome these challenges. Most of these printers are either uses a cartesian or delta configuration, and the cost is in the range of 1606650 US dollars (Carolo, 2020). Recently, there are dedicated edible desktop printers including Foodbot 3D printers (China), byFlow Focus 3D printer (Netherlands), Natural Machines Foodini (Spain) etc. (Lansard 2021). CONCLUSION AND FUTURE WORK Design of extrusion mechanism 3D food printing has proved its ability on making personalised chocolates or fabricating simple homogenous snacks. Anyhow, these applications are still basic with limited internal structures or monotonous textures. It is important to develop a systematic way to examine the printing materials, platform design, printing technologies and their influences on food fabrication. Meanwhile, the food designing process should be structured to encourage user’s creativity, the fabrication procedure should be quantified to achieve consistency in fabrication results, and a simulation model should be developed to combine design and fabrication with nutrition control. With the evolution of an interactive open web-based user interface, 3D food printers can become part of an ecology system, where networked machines can order new ingredients, prepare favourite food item on demand and even collaborate with doctors to develop/customize healthier diets. Generally, the food printing extrusion mechanisms works on the basis of syringe driven (stepper motor or air pressure) or screw (driver: stepper motor) systems. A syringe’s fusion consisting of a piston, tightly connected with a hose, which supplies compressed air for driving the loaded feed in a barrel(plastic) is depicted in the study of Liu and Cift, (2020). This kind of setup becomes a successful manipulation approach for 3D food printing.Guo et al. (2019) found out that the syringe-based printing system possess simple fluid characteristics with low pressure at the outlet of nozzle and high shear rate but the screw-based systems exhibit complex fluid characteristics with backflows between screw flight and barrel walls and a high shear rate. The existing printing systems can be upgraded from current batch-printing cycles to make remote food grade holding tanks of stainless steel, regulated over a set of conditions such as relative humidity and temperature for suitability of different food systems (Lanaro et al. 2017). Print ISSN : 0974-1712 This study reviews about different food printing technologies, the various available printing materials, advantages and limitations of food product fabrication with 3D printing. From this 295 Online ISSN : 2230-732X Amrutha and Patil technology review, it can be seen that food printing may exert a significant influence on various types of food processing, which allow designers/users to manipulate/customize forms and materials with enhanced and unprecedented capability. This adaptability, applied to domestic catering or cooking service, can improve efficiency to provide high quality, freshly prepared food items to consumers, deliver personalized nutrition and enable users to develop new flavors, textures and shapes to create entirely new eating experiences. An introduction to the principles of 3D food printing. Fundamentals of 3D Food Printing and Applications. Godoi, F.C., Prakash, S. and Bhandari, B.R. 2016. 3D Printing Technologies Applied for Food Design: Status and Prospects. J. of Food Engineering, 174: 44-54. 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J. of Food Science, 81(10): R2309–19. Rosenthal, A.J. 2010. Texture profile analysis - how important are the parameters. Journal of Texture Studies. Yang, F., Zhang, M., Prakash, S. and Liu, Y. 2018b. Physical properties of 3D printed baking dough as affected by different compositions. Innovative Food Science and Emerging Technologies. Sachs, E., Cima, M. and Cornie, J. 1990. Three dimensional printing: rapid tooling and prototypes directly from a CAD model. CIRP Annuals-Manufacturing Technology, 39: 201–204. Print ISSN : 0974-1712 297 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 299-306, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.3 A Study on Novel Approach to Sustainable Indian Agriculture Precision Farming Shwetha U.N.* and Nitin S. Gupta Department of Floriculture and Landscape Architecture, Dr. PDKV, Akola, Maharashtra, India *Corresponding author: shwethaun0@gmail.com (ORCID ID: 0000-0002-3214-5509) Paper No. 988 Received: 23-05-2022 Revised: 28-06-2022 Accepted: 04-07-2022 ABSTRACT Precision farming which is also regarded as site-specific management is reported as emerging approach that recognizes site-specific differences within-field and adjusts management action accordingly. Precision farming utilize the advanced technologies for efficient crop production and to minimize environmental impact caused due to over-usage of inputs. It is necessary to reduce the use of inputs by providing prescribed quantity and to increase the crop yield. Precision farming involves various tools such as Global Positioning System (GPS), Geographic Information System (GIS), Remote Sensing etc. for recording the precise data and making decision according to the stored data. In India, it is high time to adopt precision farming which leads to sustainable agriculture due to depletion of natural resources. It is stated that precision farming has scope for its adoption in small scale farms after considering its advantages and economics. The main purpose of this review is to understand the concept of precision farming and gaining knowledge about its adoption, economics, merits and obstacles. HIGHLIGHTS mm Precision farming should reach all the farmers and its implementation helps to overcome the depletion of natural resources and protection of environment. Keywords: Precision farming, Site-specific management, Environmental impact, Adoption, Economics Million years ago, man started agriculture as a profession and used basic resources like soil, water and air to strengthen his land and increased the agricultural productivity. These natural resources were degraded due to enormous increase in population and rapid industrialization and urbanization (Shanwad et al. 2004). Thus, innovation in agriculture is necessary to meet the demand and also due to use of technology and impacts of green revolution, degradation in environment is evident which should be reversed through sustainable farming. The advancement of technology and irrigation system lead to increase in productivity but at the same time higher use of agriculture inputs are not beneficial in increasing productivity. The management of all resources is essential for sustainability. Its high time to utilize all modern tools by combining the Information Technology and Agriculture Science because of need for maximizing the input use efficiency, poor availability of labors and to improve economic and environmentally sustainable production. Before agriculture mechanization farmers used to monitor and fix the problems in the field mechanically but in recent days farmers are unable to adjust variabilities regarding yield potential, topography, nutrient deficiencies etc. (Robert et al. 2019). This necessitates the role of precision farming which is application of technologies and principles to manage variability linked with all aspects of agricultural production How to cite this article: Shwetha, U.N. and Gupta, N.S. (2022). A Study on Novel Approach to Sustainable Indian Agriculture - Precision Farming. Int. J. Ag. Env. Biotech., 15(Special Issue): 299-306. Source of Support: None; Conflict of Interest: None Shwetha and Gupta for improving both production and environmental quality. outcomes: increased profitability and sustainability, improved product quality, effective and efficient pest management, energy, water and soil conservation and surface and ground water protection. In others words, it is digital agriculture involving very large farm level mapping, comprehensive database creation on required resources generated through space-based inputs and field observation and making a detailed plan of work for maximizing the yield and reducing cost of inputs using decision support system. Precision farming has emerged as current research topic at the end of 20 th century all over the world (Hermann 2001). It is an integrated crop management system that meets the crop need in small areas within field. Precision farming can provide technology for eco-friendly agriculture and is more useful for famers having small land holding in developing countries by supply of minimum inputs and receiving profitable outcome (Hakkim et al. 2016). Precision farming can be achieved by use of appropriate technologies for management and decision making. Adoption of precision farming technologies varies according to geography and technology used. Precision farming is more adopted in developed countries and there is requirement for overall adoption in large scale. However, the developing information technologies along with digitalization of agriculture sector are making adoption possible by increasing the degree of precision, expanding the applications, lowering the cost of inputs and easing the data processing. The profitability and efficiency of technologies will lead to the adoption of precision farming, also there is need for involvement of both public and private sectors in extension process for transferring the technology. The objective of our study is to provide basic information about precision farming and help out the new generation to be aware of this technology. Precision farming based on global positioning system (GPS) is the management of spatial and temporal variability at a sub-field level to improve economic returns and reduce environment impact. It involves both art and science to utilize advanced technologies for increasing crop production and minimize environmental impact. Precision agriculture is often defined by technologies that enable it and referred to as GPS (Global Positioning System) agriculture or variable rate farming or site-specific management (Patil et al. 2013). Generally precision farming is more feasible in large scale production. Variabilities in precision farming includes yield potentials, topography, soil characteristics, nutrient demands, biotic and abiotic stresses, cultivar selections, tillage practices and irrigation scheduling. Precision farming mainly aims to manage and distribute inputs on a site-specific basis rather than applying same amounts of inputs through field. It starts by noting the variations occurring in crop/ soil properties within the field, mapping and later management actions are taken as consequence of continuous investigation of spatial variability within that field (Rains et al. 2009). This recognizes, locates, quantify and records which can be managed by use of specific amounts of inputs at specific locations with the actual crop needs for small areas within a field. By understanding and dealing with natural variability found within a field can increase efficiencies through precision farming and better decision can be made about crop production aspects. Precision Farming Precision farming is generally defined as an information and technology-based farm management system to identify, analyze and manage variability within fields for optimum profitability, sustainability and protection of land resource. The most suitable definition for precision farming in the context of Indian farming scenario could be precise application of agricultural inputs based on soil, weather and crop requirement to maximize sustainable productivity, quality and profitability (Singh, A. K. undated). It is good to have better farm management practices before adopting precision farming because farmers should use information effectively. Both devices and information tend to increase returns to farmers. Maximum economic return can be achieved through precision farming compared to traditional One generic definition is the kind of agriculture that increases the number of decisions per unit area of land per unit time with associated net benefits. Precision farming is a comprehensive approach to farm management and has following goals and Print ISSN : 0974-1712 300 Online ISSN : 2230-732X A Study on Novel Approach to Sustainable Indian Agriculture - Precision Farming agriculture because in precision farming the field is divided into various management zones based on factors like soil pH, yield rates, pest infestation etc. and these zones are managed by application of required inputs using precision farming tools whereas in traditional farming field is treated as a homogenous area with whole field management practices and inputs are supplied uniformly throughout the field (Singh, A. K. undated). Precision farming can be summarized as technology that allows a farmer to follow sitespecific management which is of doing right thing, in the right place, in the right time and in right way (Pierce and Nowak 1999). Precision faming provides a way to automate site-specific management using information technology, thereby making site specific management practical in commercial agriculture. Precision farming gained wide scope in production of major food grain crops like rice, wheat and also in high profit-making horticultural crops. system and better investment in research to provide new solutions to novel problems. Due to limiting availability of natural resources, the adoption of precision farming is necessary. Precision farming potentiality is conceptualized through reduced use of water, fertilizers, herbicides and pesticides besides farm equipment for ecological and environmental benefits. Therefore, the adoption of newly emerged technology is one of the keys in future to increase agriculture productivity. There is a need to convert green revolution to evergreen revolution which can be achieved from precision farming where sitespecific problems can be recognized within fields and management actions are managed accordingly. Basic Steps in Precision Farming The variability in the field can be determined using the technologies, managing them with the use of agronomic practices and finally evaluating the outcomes. The three basic steps are explained in detail (Shanwad et al. 2004). Need for Precision Farming The food production system of our country is majorly profited by Green Revolution in 1960’s by making India self-sufficient. This was achieved due to high input application, increase in fertilization, irrigation, pesticides, higher use of high yielding varieties, increasing cropping intensity and increase in agricultural mechanization. Green revolution has made our country self sufficient but potential productivity of Indian high yielding varieties are lowest compared to world’s crop yield level (Patil and Bhalerao 2013). The green revolution is also correlated with adverse impact on ecology. India’s natural resources are degrading day by day with high input applications and it is reducing the originality of land. Major concern in agricultural growth and development are decline in the total productivity, diminishing and degrading natural resources (Healthy land and quality water both are becoming limited), stagnating farm incomes, lack of eco-regional approach, declining and fragmented land holdings, limited employment opportunities in non-farm sectors and global climate variation. 1. Assessing variation The challenges faced by global food system will likely to increase in future. This can be minimized immediately with the modern technologies and knowledge with sufficient will and investment. But it necessitates more radical changes to food Management of variability is possible if the variability is assessed critically. Managing variability also includes both spatial and temporal variability. For example, the management of potassium and phosphorus is convenient because the temporal Print ISSN : 0974-1712 The first and critical step in precision farming is assessing variation. To manage the variability, one should know about assessing it. Without proper assessment it is difficult to manage the variations. There is variation in elements and operations affecting the crop yield in accordance with space and time. Quantifying and determining variability of elements and operations by knowing the effect of different combinations for spatial and temporal variation is a huge challenge in precision farming. Techniques for assessing both spatial and temporal variation are available but they can proceed simultaneously. Temporal variation is different in different time which need observations at crop growth and development over growing season and this also includes spatial variability. Some variables are produced in space than time, making them more convenient to modern forms of precision management. 2. Managing variability 301 Online ISSN : 2230-732X Shwetha and Gupta 2. Yield monitoring and mapping variation of these nutrients is low. Likewise, management of nitrogen is difficult because the temporal variation is high. According to the assessed condition within field, farmers can implement agronomic practices which should be site-specific and accurate. Site-specific management can be effectively done with the use of various technologies making it easy and economical. 2. Environment Yield monitors are used to record yield data and create yield maps when linked with GPS. Yield monitors include several components like different sensors, data storage device, user interface and task computer (controls integration and interaction of above components). Yield monitors are important because yield data will enable to decide the management practices to be considered and to decide the effect of managed inputs such as fertilizers, seeds, agrochemicals and cultural practices (tillage and irrigation). Yield data of many years should be collected and considered for evaluation because yield data of single year cannot give adequate information as it may get affected by weather parameters along with field factors. 3. Technology 3. Geographic Information System (GIS) 3. Evaluation: Immediately after management it is important to evaluate the condition of field and outcomes. There are three important issues regarding evaluation of precision farming: 1. Economics The analysis of profitability of precision agriculture involves the value that comes from application of data than from the use of the technology. Low usage of agrochemical, higher nutrient use efficiency and increased input efficiency are regarded as benefit to environment. As precision farming involves the application of technologies and agronomic principles for spatial and temporal variability management, transfer of technology to farmers is essential. The technology transfer differs for individual farms because of change in the problems related to each farm. GIS is hardware and software of computers and comprises of procedures that are designed to support the collection, storage, recovery and analysis of attributes and data of location to produce respective maps (Hakkim et al. 2016). It gained importance in agriculture for storing layers of information which include yield data, soil survey maps, rainfall, crops, soil nutrient levels and pests (Singh, A. K. undated). The recorded data can be displayed through visual perspective for interpretation. Other than storage and display of data, GIS can be used to evaluate present and alternative management by combining and manipulating data layers to produce an analysis of management scenarios. After analyzing the information can be used to compare and understand the relationships between the various factors affecting a crop on specific site. Tools in Precision Farming 1. Global Positioning System (GPS) receivers A GPS is a network of satellites and receiving devices that helps the users to record positional information while in motion at any time. This helps farmers by providing the exact position of field information such as soil type, pest occurrences, weed invasion, waterholes, boundaries, obstructions and crop measurements to be mapped (Singh, A. K. undated). This will locate specific spots in field which helps farmers to apply inputs in specific quantity to an individual field based on performance criteria and previous input applications. This system consists of light or sound guiding panel, antenna and receiver. While purchasing GPS, differential correction should be checked so that the signals could match the satellite signals in particular field. Print ISSN : 0974-1712 4. Grid soil sampling and variable rate fertilizer (VRT) application Grid soil sampling increases the intensity of soil sampling and uses the same principles of soil sampling. Soil samples are collected in a systematic grid includes location information that allows the data to be mapped. An application map of nutrient requirement is created through grid soil sampling. For each soil samples the crop nutrient needs are interpreted after analyzing the grid soil samples in laboratory. Variables rate technologies are automatic and applied to numerous farming 302 Online ISSN : 2230-732X A Study on Novel Approach to Sustainable Indian Agriculture - Precision Farming 7. Identifying a precision agriculture service provider operations. Control computer, locator and actuator are three components of variable rate applicator. The fertilizer application map is plotted using the entire set of soil samples. According to the application map that is loaded into a computer mounted on a variable rate fertilizer spreader and a GPS receiver, the amount and kind of fertilizer product is applied to specific-site through product-delivery controller. This enables the land to get specific amounts of fertilizers at proper time (Hakkim et al. 2016). The farmers are advised to consider the availability of custom services when making decisions about adopting site-specific crop management. Agricultural service providers or trained extension workers can offer a variety of precision farming services to farmers (Singh, A. K. undated). Intensive soil sampling, mapping and variable rate applications of fertilizer and lime are most common custom services. These custom services can decrease the cost and increase the efficiency of precision farming by providing capital costs for specialized equipment over more land and by using the skills of precision agriculture activities (Hakkim et al. 2016). 5. Sensor technologies and remote sensing Sensor technologies such as electromagnetic, conductivity, photoelectricity and ultrasound are one of the important tools of precision farming used to measure soil properties and plant fertility/ water status including humidity, vegetation, temperature, texture, structure, physical character, nutrient level, vapor, air etc. Remote sensing technology is useful tool for collecting numerous information simultaneously from a distance without laboratory analysis (Hakkim et al. 2016). These data are used to differentiate crop species, locate biotic and abiotic stress conditions, identify weeds, monitor drought, soil and plant conditions. Near-Infrared images are recorded in electronic cameras that are highly associated with healthy plant tissue. Location, extent and component of crop stress can be determined with the help of remotely-sensed images. A spot treatment plan that optimizes the use of agricultural chemicals is developed and implemented by using these images. Eventhough more information is gathered by remote sensing technology it is difficult to find key management factor because of varying field conditions such as timing and amount of nitrogen fertilizer application, timing and period of mid-season drainage and timing of harvest. 8. Rate controller The devices designed to control the delivery rate of chemical inputs such as fertilizers and pesticides are rate controllers. These rate controllers monitor the speed of the tractor/sprayer traveling across the field, as well as the flow rate and pressure (if liquid) of the material, making delivery adjustments in realtime to apply a target rate. Rate controllers have been available for some time and are frequently used as stand-alone systems. Elements of Precision Farming Mainly there are three elements in precision farming (Robert et al. 2009): 1. Information Basic information or data is foremost needed for further proceedings in precision farming. In modern farming, collection of accurate data at proper timing by farmers is necessary for successful management. This information consists of crop characteristics, response of hybrids, soil properties, fertilizer requirements, weather predictions, weed and pest populations, plant growth responses, harvest yield, post-harvest processing and marketing projections. Farmers must be capable of finding, analysing, and using the available information at each step in the crop system. With the advancement and easy availability of data in recent years makes it possible to get within the requirement period. Data can be extracted from internet which is more accessible and quickly updated. 6. Precision irrigation in pressurized systems GPS based controllers are used for controlling the irrigation machines for commercial use in sprinkler irrigation. Wireless communication and sensor technologies are being developed to monitor soil conditions to achieve higher water application efficiency and utilization by crop (Hakkim et al. 2016). Print ISSN : 0974-1712 303 Online ISSN : 2230-732X Shwetha and Gupta 2. Technology Adoption in Small Scale Agriculture Farmers should know about the adaption of new technologies for their operations. Personal computers can be used to store the data of past years and is accessed whenever required. These personal computers will organize, analyse and manage the data. Computer software including spreadsheets, databases, geographic information system (GIS) and other application software are readily available and easy to use. Global positioning system (GPS) can be used by farmers and agricultural consultants for locating position of field. Geographic information system (GIS) creates a field map by using the data recorded by Global positioning system (GPS) to assess the impact of farm management decisions. The leading issue for agricultural scientist is feasibility of precision farming in small farms. The main point to be noted in precision farming is understanding the variability in the field and characterization of precision farming by variable management. At least two types of variability are observed, one is within-field variability and the other is between-field variability or regional variability (Shibusawa 2000). Each field is considered as unit on a map in case of between-field variability whereas with in- field variability focuses on a single field and cultivated with one plant variety. Considering the kind of variability is essential for precision farming in small farms. Precision farming should mean improved farm management no matter the farms are large or small. Ultimately, it should give higher economic return with a reduced environmental impact. Some low cost and low technology tools may be proved to be useful for small scale farms of developing countries (Mandol and Basu 2009). Sensor technology is used to monitor soil properties, crop stress, growth conditions, yields or postharvest processing are either available or under development and this instant information can be used to control operational inputs. Precision farming uses three general technologies: Crop, soil and positioning sensors – these include both remote and vehicle-mounted, “on-the-go” sensors that detect soil texture, soil moisture levels, crop stress, disease and weed infestations while the tractor travels along the field. Machine controls – these are used to guide field equipment and can vary the rate, mix and locate water, seeds, nutrients, or chemical applications. Computer-based systems – these include GIS maps and databases that use sensor information to prescribe specific machine controls. Possible variable rate applications on a single small farm depends on understanding capacity, knowledge and skills of farmer. As the land size increases, precision farming should coordinate with different types of land use and many farmers having diverse motivations. Precision farming offers the possibility of developing a new kind of industry in view of development in rural area that includes small farms and local companies by fusing agriculture to various kinds of industrial activity. Hence, it is understandable that the size of farm in adoption of precision farming does not matter provided it depends on management strategy. 3. Decision support or management For best management prescriptions of crop production system, combination of traditional management practices and precision farming tools helps farmers. Most of the times it is difficult to understand the decision support system. Building databases based on the relationships between input and potential yields, refining analytical tools and increasing agronomic knowledge at the local level are yet to be accomplished. Agricultural researchers opined that decision support system is the least developed area in precision farming. Diagnostic and database development will eventually replace technologies as the real benefit of precision farming (Robert et al. 2009). Print ISSN : 0974-1712 Economic Studies of Precision Farming The adoption of precision farming involves intensive capital investment and leads to greater expenditures on machinery and equipment as well as for access to information. Precision farming increases the quality of marketed goods. Product quality can be in two forms such as intrinsic and extrinsic quality. Intrinsic quality comprises of color, appearance, protein content, pesticide residue content, sugar content, starch content etc. Extrinsic quality is associated with production practices, origin or related aspects of the production process. Economic results of adoption of variable rate application methods 304 Online ISSN : 2230-732X A Study on Novel Approach to Sustainable Indian Agriculture - Precision Farming ŠŠ Automations using Guidance Systems: Direct economic benefits are achieved using automated unmanned systems (reduced labour costs) and reduced impact on the environment (reduction of machinery pass frequency and reduction of soil compaction) (Thomas and Georgios 2017). depends on the type of crop, field size and type of agriculture. Precision farming profitability is important for implementation of these technologies. The benefits from precision farming are related to optimization of inputs, improvement of management and quality of work, crop yield improvements, minimizing cost through improved process control, reducing content of agrochemicals to the environment, environmental quality and business risk (Robert et al. 2019). None of the technologies adopted does not provide a total solution until and unless it is used extensively for commercial purpose. The coordination between private and public sectors can lead to the economic growth of precision farming by developing and implementing technologies, market development responsibility and customer satisfaction. Economic studies related to profitability are nuclear and noncomparable. Obstacles in Adopting Precision Farming Common obstacles for adoption of precision farming in developing countries like India are as follows (Shanwad et al. 2004): ŠŠ Culture and perceptions of the users. ŠŠ Small farm size. ŠŠ Lack of success stories. ŠŠ Heterogeneity of cropping systems and market imperfections. ŠŠ Landownership, infrastructure and institutional constraints. Merits of Precision Farming ŠŠ Lack of local technical expertise. ŠŠ Knowledge and technical gaps among farmers. ŠŠ Agronomical perspective: Use agronomical practices by looking at specific requirement of crop. ŠŠ Data availability, quality and costs. ŠŠ Technical perspective: Allows efficient time and management. CONCLUSION Precision Farming could be a solution to threats associated to low agricultural productivity and environmental impact. In developing countries, it has not reached every farmer due to lack of transfer of technology and unclear economic framework. Indian farmers with the help of public and private sectors will be able to adopt this technology as well as can deal with the severe problems faced by them such as low outputs, depletion in water levels, increasing cost of inputs only if they are trained about technologies and providing detailed information about precision farming. Precision farming can be adopted in various fields such as agriculture, horticulture and livestock production which will help farmers to increase their economic returns and making India self-sufficient in food production. ŠŠ Economical perspective: Increases crop yield, quality and reduces cost of production by efficient use of farm inputs, labor, water etc. ŠŠ Environmental perspective: Ecofriendly practices in crop. ŠŠ Managing spatial variability for decision making: Precision farming provide complete field related information through direct sampling. ŠŠ Management of environmentally sensitive areas: By calculating the greenhouse gas emissions due to mechanized operations, they can limit emissions to the environment. ŠŠ Precise nutrient applications: Yield maps can be used to alter fertilizer applications that suits current soil characteristics. ŠŠ Precise pesticide application: Specific amounts of pesticides are applied to specific site and it also prevent overlapping during spraying by the use of light bar guidance system. This will reduce the use of inputs and decrease adverse effect on environment. Print ISSN : 0974-1712 REFERENCES Hermann Auernhammer. 2001. Precision farming — the environmental challenge. Comput. and Electron. in Agriculture, 30: 31-43. 305 Online ISSN : 2230-732X Shwetha and Gupta Hakkim Abdul, V. M., Joseph Abhilash, E., Ajay Gokul, A. J. and Mufeedha, K. 2016. Precision Farming: The Future of Indian Agriculture. J. of Appl. Biol. Biotechnol., 4(06): 068-072. Robert Finger, Scott, M. Swinton, Nadja El Benni, and Achim Walter. 2019. Precision Farming at the Nexus of Agricultural Production and the Environment. Annu. Rev. Resour. Econ., 11: 313–35. Mondal, P. and Basu, M. 2009. Adoption of precision agriculture technologies in India and in some developing countries: Scope, present status and strategies. Prog. in Nat. Sci., 19: 659-666. Shanwad, U.K., Patil, V.C. and Honne Gowda, H. 2004. Precision Farming: Dreams and Realities for Indian Agriculture. Map India Conference 2004. Shibusawa, S. 2000. Environmentally friendly agriculture and mechanization trend in Japan: Prospects of precision farming in Japan. Proceedings International Symposium on Farm Mechanization for Environmentally-Friendly Agriculture, Seoul, Korea. The Korean Society for Agricultural Machinery, pp. 53-80. Pierce, F. and Nowak, P. 1999. Aspects of precision agriculture. In D. L. Sparks (ed.), Adv. Agron. pp. 1-86. Patil Shirish, S. and Bhalerao Satish, A. 2013. Precision farming: The most scientific and modern approach to sustainable agriculture. Int. Res. J. of Sci. & Eng., 1(2): 21-30. Singh, A.K. Precision farming. Academia, 6: 166-174. Rains Glen, C. and Thomas Daniel, L. 2009. Precision Farming An Introduction. Thomas Koutsos and Georgios Menexes. 2017. Benefits from the adoption of precision agriculture technologies. A systematic review. Conference Paper. Robert “Bobby” Grisso, Mark Alley, Dan Brann and Steve Donohue. 2009. Precision Farming: A Comprehensive Approach. Virginia Tech., pp. 442-500. Print ISSN : 0974-1712 306 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 307-312, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.4 Study of Heterosis, Residual Heterosis and Inbreeding Depression in Two Crosses of Tomato Sangamesh Nevani* and O. Sridevi Department of Genetics and Plant Breeding, College of Agriculture, University of Agricultural Sciences, Dharwad Karnataka, India *Corresponding author: nevanisangu73@gmail.com (ORCID ID: 0000-0001-6641-233X) Paper No. 989 Received: 25-05-2022 Revised: 30-06-2022 Accepted: 08-07-2022 ABSTRACT Heterosis, which is hybrid vigour that results in an increase in fruit yield with early development and higher quality, is one of the most essential approaches to improve yield and quality attributes. Heterosis is a natural phenomena in which the physical and functional traits of hybrid offspring of genetically heterogeneous individuals improve over time. The goal of this research is to find out how much hybrid vigour and inbreeding depressions, as well as residual heterosis, are present in two tomato crosses (DMT2 LINE-38 and LINE-33-1 LA-1). A population of two crosses was assessed with 14 parameter test of generation mean analysis. The significant and negative heterosis (heterobeltiosis) was depicted for days to first harvest in cross I with negative inbreeding depression, which indicates desirable earliness found in those families. The heterosis, as well as inbreeding depression was observed in the desired direction in cross I and II for fruit yield per plant and for quality viz., pericarp thickness, pH of fruit juice and TSS indicating possibilities to get the desired segregants in a further breeding program. HIGHLIGHTS mm Tomato (Solanum lycopersicum L.) is one of the most important solanaceous vegetable crops all over the world. It was introduced in India by English traders of East India company in 1822 (Kalloo 1988). The tomato originated in a wild form in Ecuador, Peru, and Bolivia of South America (also known as the center of diversity of wild tomato). Globally, it is grown in an area of 5.02 million hectares with the production of 170.75 million tonnes and productivity of 33.99 tonnes per hectare (FAO, 2020). China, India and USA are the major tomato producing countries. In India, it is grown in an area of about 0.88 million hectares with production of 18.74 million tonnes and the average productivity is about 21.24 tonnes per hectare. The important tomato growing states are Andhra Pradesh, Karnataka and Madhya Pradesh. In Karnataka, tomato is grown on an area about 0.06 million hectares with production of about 2.13 million tonnes with the productivity of about 31.54 tonnes per hectare (Anon., 2019). Keywords: Generation mean analysis, Heterosis, Heterobeltiosis, Residual heterosis, Inbreeding depression Tomato is consumed year-round and its importance is mainly derived in two forms: used as a fresh vegetable as well as an important source for the processing industry. At present time, superior quality and adequate quantity of vegetables for commercial agro-processing are not being grown sufficiently. Cultivation of tomatoes began to decline during the last few years, which requires conventional and scientific efforts to increase the production per unit area to compensate for the shortfall in the cultivated area. Many local farmers grow average yielding varieties, which are characteristically low yielding and of poor quality for the traits such as high-water content, poor color and low Brix content against the increasing How to cite this article: Nevani, S. and Sridevi, O. (2022). Study of Heterosis, Residual Heterosis and Inbreeding Depression in Two Crosses of Tomato. Int. J. Ag. Env. Biotech., 15(Special Issue): 307-312. Source of Support: None; Conflict of Interest: None Nevani and Sridevi demand at the local and international levels for superior quality. To overcome these problems, the development of high yielding and superior quality varieties of tomato is imperative in the cultivation to meet the total market demand. Since the 1980s, the emphasis of new cultivar development has been focused on the production of F1 hybrids (Grandillo et al. 1999). Generally, hybrids are preferred over pure line varieties in tomatoes due to their superiority in terms of yield as well as the quality of fruit. Hybrid breeding technology is greatly applied in cross-pollinated crops and is limited in autogamous crops due to the strict genetic makeup of the plant and floral biology. Commercial exploitation of heterosis in self-pollinated crops has been limited owing to technical difficulties involved in hybrid seed production. Tomato is a self-pollinated crop with hermaphrodite flower and can be easily emasculated for crossing technique, therefore it has a suitable mechanism to produce hybrid seed at a commercial scale. However, it adds a higher labour cost to the total production cost. but a great amount of information is still needed for the understanding of the genetics of fruit yield, yield attributing traits, and quality parameters of this crop. The purpose of this study was to estimate the heterosis of yield-related traits as well as inbreeding depression and residual heterosis in the F2 generation. The experimental material is constructed in such a way that the estimation of the heterosis, inbreeding depression, and residual heterosis effect in a respective generation is possible. MATERIALS AND METHODS The experimental material comprises of two crosses, each representing six generations (P 1, P2, F1, F2, B1, and B2) were raised in a compact family block design in field trials. Two crosses were derived from four parents viz., DMT-2, LINE-38, LINE-33-1 and LA-1 with hand emasculation and pollination. Observations for the different traits under study were recorded on randomly selected and tagged plants from each experimental unit and each replication i.e., five plants from each P1, P2, and F1 and 300 hundred plants from each F2 generation and 120 plant for back cross generation was recorded. The mean of F1 hybrids and F2 generation over replication were utilized for the estimation of heterosis, inbreeding depression, and residual heterosis. Heterosis increases yield and quality in many crops and vegetables and it has been intensively used in plant breeding. The identification of superior parental combinations that provide high heterosis for yield and quality is the most important factor in hybrid development. Heterobeltiosis is useful in the identification of promising cross combinations for the improvement of the crop through conventional breeding strategies. It may lead to an increase in yield, reproductive ability, adaptability to general vigour, different biotic and abiotic stresses and also improve fruit quality. Contrarily, inbreeding depression leads to decreased fitness and vigour due to the expression of lethal and sublethal alleles which are generally masked under heterozygosity. It leads to increased homozygosity and fixation of undesirable recessive genes in F2 and successive generations, while in the case of heterosis, favorable dominant genes of one parent are masking the effect of harmful recessive genes of another parent. 1. Estimation of Heterosis. Heterosis expressed as a percent increase or decrease of F1 hybrid over its better parent value (BP) and mid parent heterosis (MH) was computed using the following formulae. 1. Heterosis over better parent (Heterobeltosis) HB (%). The heterosis over better parent was calculated as per the Fonseca and Patterson, (1968). HB ( % ) == BP × 100 Where, F1 = Mean value of F1 hybrid i.e. F1 BP = Mean performance of better parent. 2. Mid parent heterosis MH (%). The heterosis over average of two parents was calculated as per the Meredith and Bridge, (1972). Molecular, genetic, and physiological mechanisms underlying this phenomenon are not well understood yet (Birchler et al. 2010). The demand for tomatoes is increasing day by day but their production and quality is affected by many diseases, stresses and many other factors. A considerable amount of important work has already been done in this crop, Print ISSN : 0974-1712 F1 − BP MP ( % ) == F1 − MP MP × 100 Where, MP = Mean performance of two parents 308 Online ISSN : 2230-732X Study of Heterosis, Residual Heterosis and Inbreeding Depression in Two Crosses of Tomato 3. Estimation of inbreeding depression (ID %). Inbreeding depression was computed by using the following formula, Inbreeding depression (%) = = fruit (4.99 % in Line-33-1 × LA-1), pericarp thickness (0.50 % in Line-33-1 × LA-1), number of locules (0.55 % in DMT-2 × Line-38), total soluble solids (0.80 % for DMT-2 × Line-38 and 0.65 % in Line-33-1 × LA1), pH of fruit juice (0.30 % in DMT-2 × Line-38). F2 − F1 × 100 F2 Similarly significant and positive heterosis over mid parent was observed for plant height (6.37 % in Line-33-1 × LA-1), primary branches per plant (0.25 % in DMT-2 × Line-38), number of clusters per plant (2.47 % in DMT-2 × Line-38), number of fruits per cluster (0.27 % in DMT-2 × Line-38 and 0.42 % in Line-33-1 × LA-1 ), number of fruits per plant (9.72 % in DMT-2 × Line-38 ), average fruit weight (13.26 % in Line-33-1 × LA-1 ), polar length of fruit (5.61 % in Line-33-1 × LA-1 and 2.91 % in DMT-2 × Line-38), equatorial length of fruit (4.59 % in DMT-2 × Line-38 and 3.56 % in Line-33-1 × LA1), pericarp thickness (0.69 % in Line-33-1 × LA-1 and 0.64 % in DMT-2 × Line-38), number of locules per fruit (0.78 % in DMT-2 × Line-38 and 0.42 % in Line-33-1 × LA-1), total soluble solids (1.02 % in DMT-2 × Line-38 and 0.85 % in Line-33-1 × LA-1), pH of fruit juice (0.41 % Line-33-1 × LA-1 and 0.4 % in DMT-2 × Line-38) and yield per plant (0.50 % in DMT-2 × Line-38 and 0.47 % in Line-33-1 × LA1). The positive and significant heterosis over mid parent as well as better parent found undesirable for days 1st harvest in the above mentioned crosses but their magnitude were very less could be neglected. Significant and negative heterosis over better parent observed in days to 1st harvest (-2.19 % in DMT-2 × Line-38), primary branches per plant (0.3 % in Line-33-1 × LA-1). Significant negative mid parent heterosis was not observed for any characters. 4. Estimation of Residual Heterosis (%). The residual heterosis from F2 generation was worked out as per the formula given below: Residual heterosis = F2 − BP BP × 100 RESULTS AND DISCUSSION The results observed for heterosis over mid parent and better parents, residual heterosis as well as inbreeding depression for 14 traits are summarizes in Table 1. The measurement of heterosis over mid parent is of academic importance for studying genetics of heterosis but has limited practical usefulness. On the other hand, the heterosis measured over better parent is of much practical importance. The commercial exploitation of heterosis is considered to be an outstanding application of principles of genetics into the field of plant breeding. Heterosis has been successfully exploited in many crops like tomato, bajra, maize, bitter gourd, sorghum, castor, cotton, bottle gourd and many other vegetable crops. In present study, heterosis over mid as well as better parents, Residual heterosis and inbreeding depression was estimated (Table 1). The heterosis over better parent (heterobeltiosis) for different traits was ranging from -2.19 to 9.26 % and highest heterobeltiosis was recorded in average fruit weight (9.26 % in Line-33-1 × LA-1), mean-while heterosis over mid parent ranges from -1.21 to 13.26 %. The highest heterosis over mid patent recorded in average fruit weight (13.26 % in Line-33-1 × LA-1). Heterosis in desirable direction for various traits in tomato was reported by several research workers such as Shekar et al. (2010), Shankar et al. (2013), Kumar et al. (2018), Madhavi et al. (2018) and Barragan et al. (2019), for total fruit yield per plant; Joshi et al. (2015), Zengin et al. (2015) and Kumar et al. (2018) for plant height, fruit yield, number of fruits plant, fruit length and average fruit weight and for earliness (days to 1st harvest); Kumar et al. (2018). For the character days to 1st harvest the low scoring parent was taken as better parent. The degree of heterosis over better parent as well as mid parent varied from cross to cross for all the 14 characters. Residual heterosis is the amount of heterosis shown by F 2 and subsequent segregating generations. Residual heterobeltiosis and economic heterosis in F2 generations was estimated as the percentage of deviation of generation mean of F2 from better parent Significant and positive heterosis over better parent observed for plant height (9.22 % in DMT-2 × Line38 and 7.22 % in Line-33-1 × LA-1), number of fruits per plant (7.5 % in DMT-2 × Line-38), polar length of Print ISSN : 0974-1712 309 Online ISSN : 2230-732X Print ISSN : 0974-1712 310 8.84** 4.62 ± 2.24 5.20 ± 2.21 -2.19** ± 0.69 0.1 ± 0.69 -41.02** 892.47** -1.49 ± 0.62 -1.47 ± 0.50 DMT-2 × Line-38 Line 33-1 × LA-1 DMT-2 × Line-38 Line 33-1 × LA-1 DMT-2 × Line-38 Line 33-1 × LA-1 * ** -0.3 ± 0.09 1.91 ± 1.13 21.07** 4.42 ± 1.43 1.37 ± 1.16 4.99 ± 0.88 29.01** 7.04** 3.54 ± 0.9 1.99** ± 0.73 DMT-2 × Line-38 Line 33-1 × LA-1 DMT-2 × Line-38 Line 33-1 × LA-1 DMT-2 × Line-38 Line 33-1 × LA-1 ** ** 3.04 ± 1.62 5.61** ± 0.8 Line 33-1 × LA-1 1 ± 0.94 ** 13.82** 3.56** ± 1.04 4.59** ± 1.49 2.91** ± 1.03 DMT-2 × Line-38 Equatorial length of fruit (mm) Polar length of fruit (mm) * * 7.29** 0.52**± 0.09 0.34 ± 0.06 ** 6.41** 16.8** 0.50 ± 0.12 ** 0.23** ± 0.07 0.69** ± 0.11 0.64** ± 0.08 0.14 ± 0.17 1.06 ± 0.19 ** 38.64** 7.15** 0.12 ± 0.25 0.55* ± 0.22 0.42* ± 0.2 0.78** ± 0.21 Number of locules 1.46 ± 0.87 4.02 ± 0.92 ** 36.32** 11.64** 0.37 ± 1.12 0.92 ± 1.18 1.8 ± 1.02 2.47* ± 1 Number of clusters Thickness (mm) Pericarp -0.02 ± 0.05 0.29 ± 0.1 ** -4.82** 6.87** ** 7.72 ± 2.46 ** 0.15 ± -0.12 -0.1 ± 0.06 0.25* ± 0.11 Primary branches per plant 9.22** ± 2.39 6.37** ± 2.28 Crosses ** * 0.54 ± 0.1 Line 33-1 × LA-1 2.71 ± 2.41 -1.21 ± 0.67 DMT-2 × Line-38 , Significant at 5 and 1 % levels, respectively Inbreeding depression Residual Heterosis Better Parent heterosis Mid parent heterosis Inbreeding depression Residual Heterosis Better Parent heterosis Mid parent heterosis Plant height (cm) Days to 1st harvest Crosses 0.64** ± 0.09 0.89 ± 0.06 ** 6.16** 4.37** 0.65 ± 0.13 ** 0.80** ± 0.08 0.85** ± 0.10 1.02** ± 0.07 TSS (0 brix) 0.05 ± 0.12 0.04 ± 0.09 18.04** 10.36** 0.15 ± 0.15 0.22 ± 0.12 0.42** ± 0.13 0.27** ± 0.1 Number of fruits per clusters 0.09 ± 0.08 0.3 ± 0.11 * 33.78** 13.40** 0.13 ± 0.09 0.30** ± 0.10 0.41**± 0.09 0.4** ± 0.08 pH of fruit juice 2.27 ± 2.41 8.14 ± 5.06 ** 9.98** 2.95 2.88 ± 3.18 7.5* ± -2.97 2.42 ± 2.7 9.72** ± 2.45 Number of fruits per plant 0.36** ± 0.11 0.43** ± 0.11 6.24** 4.23** 0.24 ± 0.15 0.31 ± 0.16 0.47** ± 0.12 0.50** ± 0.13 Yield per plant (kg) 2.5 ± 5.3 1.45 ± 2.92 5.66 19.19** 9.26 ± 5.49 3.1 ± 3.23 13.26*± 5.18 5.31 ± 2.82 Average fruit weight (g) Table 1: Estimates of heterosis over mid parent (MP), heterobeltiosis (BP), reidual heterosis (RH) and inbreeding depression (ID) for 14 characters in two crosses of tomato Nevani and Sridevi Online ISSN : 2230-732X Study of Heterosis, Residual Heterosis and Inbreeding Depression in Two Crosses of Tomato and standard check value respectively Residual heterosis was found positive and significant for most of the traits except number of fruits per plant of cross I and average fruit weight of cross II with the range of -41.02-892.47. Similar findings were observed by Damor et al. (2021) and Kumar and Singh (2016). harvesting, plant height, number of fruits per plant, number of fruits per cluster, average fruit weight, polar and equatorial length, number of locules, TSS, pH of fruit juice, and yield per plant showed the highest and significant heterosis in the desired direction; however, residual heterosis was observed for the majority of the characters. In most of the crosses, heterobeltiosis/heterosis over midparent was substantial for main traits, showing the importance of hybrids for commercial crop genetic gain exploitation. The presence of overdominant gene activity is represented by estimations of substantial inbreeding depression with significant heterosis. The F 2 generation’s estimates of low inbreeding depression show a decrease in mean. Low inbreeding depression, on the other hand, lets the breeder to produce pure lines by using long selfing cycles. More emphasis on hybrid breeding can be made to improve self-pollinated crops by adding more male sterility and apomictic genes. In the present study, either low or moderate amount of inbreeding depression (ID) in desirable direction was found in most of the traits. The inbreeding depression in two crosses was within the range of -1.49 % to 8.14 %. The character which manifested low heterosis in F1 also showed low inbreeding depression in F 2. The significant and negative heterosis found in days to 1st harvest (-1.49 % in DMT-2 × Line-38 and -1.47 % in Line-33-1 × LA1) indicating that F1’s matured earlier than their respective F2’s. It is desirable to have highly significant and positive heterosis over better parent with low inbreeding depression for traits like fruit yield and its component characters such as plant height, number of clusters per plant (Line-33-1 × LA-1), number of fruits per cluster (DMT-2 × Line-38 and Line-33-1 × LA-1), number of fruits per plant (Line33-1 × LA-1), average fruit weight (DMT-2 × Line-38 and Line-33-1 × LA-1), equatorial length of fruit (Line-33-1 × LA-1), number of locules (Line-33-1 × LA-1). The magnitude of inbreeding depression in the present investigation varied from cross to cross indicating influence of genetic constitution of cross. Similar results were found by Singh et al. (1996) and Kumar and Singh (2016) reported considerable inbreeding depression in the F 2 generation for plant height, days to 1st harvest, fruit length and width and fruit yield per plant; Dagade et al. (2015) observed significant inbreeding depression for number of fruits per plant, fruit yield per plant and total soluble solids; Avidokos et al. (2021) found high degree of inbreeding depression for pericarp thickness and number of locules per fruit. ACKNOWLEDGMENTS The authors wish to express immense thanks to UGC NF-PWD, Govt. of India, for providing Fellowship for conducting the experiment. REFERENCES Anonymous, 2019, National Horticulture Board Database 2019, NHB, Gurgaon, pp. 177-185. Avidokos, I.D., Tagiakas, R., Tsouvaltzis, P., Mylonas, I., Xynias, I.N. and Mavromatis, A.G. 2021. Comparative evaluation of tomato hybrids and inbred lines for fruit quality traits. Agron., 11: 609. Barragan, O.G., Benitez, A.L., Herrera, S.A.R., Maas, J.N.E., Ramos, D.M.H. and Rico, J.S.G.J.A. 2019. Studies on combining ability in tomato (Solanum lycopersicum L.). Agron. Res., 17(1): 77–85. Birchler, J.A., Yao, H., Chudalayandi, S., Vaiman, D. and Veitia, R.A. 2010. Heterosis. The Plant Cell, 22(7): 2105-2112. Dagade, S.B., Barad, A.V., Dhaduk, L.K. and Hariprasanna, K. 2015. Estimates of hybrid vigour and inbreeding depression for fruit nutritional characters in tomato, Int. J. Environ. Sci. Technol. (Tehran)., 4(1): 114 – 124. Damor, H., Patil, K., Pusarla, S., Shiwani and Pandya, P. 2021. Heterosis, Residual Heterosis and Inbreeding Depression Study in Tomato [Solanum lycopersicum (L.)]. Biological Forum – An Int. J., 13(4): 565-570 CONCLUSION Plant breeding has achieved tremendous success in the development of hybrid cultivars, particularly in self-pollinated crop plants. For fruit yield, earliness, and quality attributes, the examination of available tomato germplasm demonstrated a considerable heterotic influence. Days to first Print ISSN : 0974-1712 FAO, 2020. World Food and Agriculture - Statistical Yearbook 2020. Grandillo, S., Zamir, D. and Tanksley, S.D. 1999. Genetic improvement of processing tomatoes: A 20 years perspective. Euphytica, 110: 85–97. 311 Online ISSN : 2230-732X Nevani and Sridevi Kalloo, G. 1988. Breeding for quality and processing attributes in vegetable breeding. Vol. 3, CRC press. INC Boca Raton. Florida, pp. 62. Shankar, A., Reddy, R.V.S.K., Sujatha, M. and Pratap, M. 2014. Development of superior F1 hybrids for commercial exploitation in tomato, (Solanum lycopersicum L.). Int. J. Farm Sci., 4(2): 58-69. Kumar, C. and Singh, S.P. 2016. Heterosis and inbreeding depression to identify superior F1 hybrids in tomato (Solanum lycopersicum L.) for the yield and its contributing traits. J. Appl. Nat. Sci., 8(1): 290 – 296. Shekhar, L., Prakash, B.G., Salimath, P.M., Hiremath, C.P., Sridevi, O. and Patil, A.A. 2010. Implication of heterosis and combining ability among productive single cross hybrids in tomato (Solanum lycopersicum L.). Ele. J. Plant Breed., 1(4): 706-711. Kumar, C. and Singh, S.P. 2016. Heterosis and inbreeding depression to identify superior F1 hybrids in tomato (Solanum lycopersicum (L.)) for the yield and its contributing traits. J. of Appl. and Natu. Sci., 8(1): 290 – 296. Singh, A., Singh, P.K., Dixit, J., Gautam, J.P.S. and Singh, D.N. 1996. Heterosis and inbreeding in tomato. J. Res., 8(1): 89-90. Kumar, K., Sharma, D., Singh, J., Sharma, T.K., Kurrey, V.K. and Minz, R.R. 2018. Combining ability analysis for yield and quality traits in tomato (Solanum lycopersicum L.). J. Pharmacogn Phytochem., 7(6): 1002-1005. Zengin, S., Kabas, A., Oguz, A., Eren, A. and Polat, E. 2015. Determining of general combining ability for yield, quality and some other traits of tomato (Solanum lycopersicum L.) inbred lines. Akdeniz üniversitesi ziraat fakültesi dergisİ., 28(1): 1-4. Madhavi, Y., Reddy, R.V.S.K. and Reddy, C.S. 2018. Combining ability studies for growth and quality characters in tomato (Solanum lycopersicum L.), Int. J. Curr. Microbiol. App. Sci., 7(10): 2287-2291. Print ISSN : 0974-1712 312 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 313-320, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.5 A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India B. Srishailam*, V. Sailaja and S.V. Prasad Department of Agricultural Extension Education, S.V. Agricultural College, Tirupati, Acharya N.G. Ranga Agricultural University, Andhra Pradesh, India *Corresponding author: sribathini15@gmail.com (ORCID ID: 0000-0001-9475-1873) Paper No. 990 Received: 26-05-2022 Revised: 29-06-2022 Accepted: 09-07-2022 ABSTRACT Natural Farming is a chemical-free alias traditional farming method. It is considered as agroecology based diversified farming system which integrates crops, trees and livestock with functional biodiversity. In India, Natural farming is promoted as Bharatiya Prakritik Krishi Paddhati Programme (BPKP) under centrally sponsored scheme- Paramparagat Krishi Vikas Yojana (PKVY). Government of Andhra Pradesh expanded zero budget natural farming in 2015. Andhra Pradesh’s Department of Agriculture appointed Rythu Sadhikara Samstha (RySS) to oversee the Climate Resilient Zero Budget Natural Farming program. RySS, a state-run research institute, was established to train farmers and promote farmer-to-farmer learning. The state launched ZBNF as a pilot program with over 700 villages and approximately 40,650 farmers in 2016 (RySS 2019). As of March 2020, approximately 623,300 farmers were enrolled in Andhra Pradesh’s ZBNF program and the total amount of land cultivated under ZBNF was almost three percent of total net sown area in the state (181,600 hectares). By 2027, Andhra Pradesh plans to expand ZBNF to all 6 million farmers and 8 million hectares. The ZBNF program is funded by the national and state government through Paramparagat Krishi Vikash Yojana and Rashtriya Krishi Vikash Yojana programs, as well as other partners, including the Azim Premji Philanthropic Initiative, the International Fund for Agricultural Development, and the Bill & Melinda Gates Foundation. The cost to RySS to transition one farmer to ZBNF is approximately 25,550 INR (348 USD), where 73 percent of the cost is dedicated to capacity building. Recent agricultural graduates are also stationed in a village for two years as Natural Farming Fellows where they lease land and practice ZBNF to demonstrate its viability to nearby farmers. Natural Farming Fellows adapt ZBNF’s core elements to local conditions and help to attract youth to the program. Women’s self-help groups are instrumental in scaling up ZBNF. As of 2019, more than 161,000 women’s self-help groups were mobilizingfarmers to adopt ZBNF, preparing farming plans, marketing ZBNF locally, and monitoring farmers’ progress. RySS relies on women’s self-help groups to identify landless farmers to participate in kitchen gardens etc. HIGHLIGHTS mm To know the present status of natural farming in the state and as well as different stakeholders engaged in the practice of natural farming promotion in the state. Benefits as well as constraints faced by the natural farming farmers and what are the condition to be set up to increase the area of natural farming in the state. Keywords: Chemical free farming, Debt free farmers, Natural farming fellows, Women SHGs, BPKP-PKVY How to cite this article: Srishailam, B., Sailaja, V. and Prasad, S.V. (2022). A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India. Int. J. Ag. Env. Biotech., 15(Special Issue): 313-320. Source of Support: None; Conflict of Interest: None Srishailam et al. Government of Andhra Pradesh expanded zero budget natural farming in 2015. Andhra Pradesh’s Department of Agriculture appointed Rythu Sadhikara Samstha (RySS) to oversee the “Climate Resilient Zero Budget Natural Farming” program. RySS, a state-run research institute, was established to train farmers and promote farmer-to-farmer learning. The state launched ZBNF as a pilot program with over 700 villages and approximately 40,650 farmers in 2016 (RySS 2019). As of March 2020, approximately 623,300 farmers were enrolled in Andhra Pradesh’s ZBNF program (almost 10.5 percent of all farmers in Andhra Pradesh), and the total amount of land cultivated under ZBNF was almost three percent of total net sown area in the state (181,600 hectares) (Khurana and Kumar 2020). By 2027, Andhra Pradesh plans to expand ZBNF to all 6 million farmers and 8 million hectares (RySS 2019). The ZBNF program is funded by the national and state government through Paramparagat Krishi Vikash Yojana and Rashtriya Krishi Vikash Yojana programs, as well as other partners, including the Azim Premji Philanthropic Initiative, the International Fund for Agricultural Development, and the Bill & Melinda Gates Foundation (Mishra 2018; RySS 2019). The cost to RySS to transition one farmer to ZBNF is approximately 25,550 INR (348 USD), where 73 percent of the cost is dedicated to capacity building (RySS 2019). Farmers do not receive a subsidy from the government to adopt ZBNF (Gupta and Jain 2020). ZBNF’s rapid expansion in the state can be attributed to the program’s extensive network of fellows to recruit and train farmers, along with its strategic linkage with women’s self-help groups. In each village where the program is active, 50 Community Resource Persons (CRPs), who have previously been identified as “champion farmers” for their success with ZBNF, train other farmers in their community, provide marketing support, and collect data for RySS (RySS 2019). scaling up ZBNF. Millions of women in self-help groups across Andhra Pradesh collectively invest their own savings, loans, and government grants into their communities (Deshmukh-Ranadive 2004). As of 2019, more than 161,000 women’s self-help groups were mobilizingfarmers to adopt ZBNF, preparing farming plans, marketing ZBNF locally, and monitoring farmers’ progress (RySS 2019). RySS relies on women’s self-help groups to identify landless farmers to participate in kitchen gardens or lease land (Gupta and Jain 2020). Women’s selfhelp groups are also a source of financial capital for farmers during their transition to ZBNF (Gupta and Jain 2020). ZBNF is promoted as a solution to the farmer debt crisis and environmental degradation in Andhra Pradesh and throughout other states in India as well. Himachal Pradesh is promoting ZBNF under the state-sponsored scheme, “Prakritik Kheti Khushal Kisan” (Department of Agriculture Himachal Pradesh). ZBNF is also practiced in Karnataka, Kerala, Haryana, and Gujarat (Khurana and Kumar 2020), and continues to attract international attention as a burgeoning agroecological movement. Pillars of ZBNF Concerning soil fertility, soil microbes play an important role, they involve in a nutrient cycle like C & N cycle which are required for plant growth (Lazarovits 1997). 1. Jivamrita/Jeevamrutha Microorganisms play an important role in the conversion of unavailable forms of nutrients to available form in the plant root zone. The microbes present in jeevamrutha helps non-available form to dissolved form when it is inoculated into the soil. It also helps as antagonism to (biological control) pathogens (Glick & Bashan, 1997). PGPR, cyanobacteria, and Solubilizing Bacteria (PSB), mycorrhizal fungi, Nitrogen-fixing bacteria are some important microbes present in the product (Chen et al. 1995). it requires 20 kg cow dung, 5-10 l urine, 2 kg dicot flour are well mixed and this add-in irrigation tank at regular intervals of 15 days until the soil is enriched or spray 2001 of jeevamruth twice in a month. It provides nutrients, microbial population, and helps to prevent fungal and bacterial plant diseases. It requires only 1st three Recent agricultural graduates are also stationed in a village for two years as Natural Farming Fellows where they lease land and practice ZBNF to demonstrate its viability to nearby farmers. Natural Farming Fellows adapt ZBNF’s core elements to local conditions and help to attract youth to the program (Gupta and Jain 2020). Women’s self-help groups are instrumental in Print ISSN : 0974-1712 314 Online ISSN : 2230-732X A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India years cycle after that system that self-sustaining. According to Mr. Palekar, only one cow is needed for 30 acres of land that should be a local desi cow not imported Jersey or Holstein because of imported cow dung and urine contains more pathogens and desi cow dung contains 300 to 500 crores of effective beneficial microbes. By their root nodules fixes atmospheric N into the soil which helps N supply to crops. From these residues retention on the surface of soil increases the microbial degradation process and liberation of N from nitrification. It also supplies organic matter to the soil which contains many micro and macronutrients. Improves seed germination without soil plowing, reduce soil temperature in extreme condition, and increase soil temperature during winter. It conserves soil moisture by reducing evaporation loss of water from the soil layer and retains water for a longer time. 4. Whapasa –aeration The main concern here is conserving water and the precise application of water-based on crop water requirement. Application of water in alternative furrows because of all roots of plants not absorb efficiently, younger horizontal and vertical roots absorb more amount of water than older one and nutrients by older roots. In soil, out of soil mineral and organic matter, there is an equal proportion of water and air present. If a higher amount of water application leads to hold air space in the soil and plant suffers oxygen deficiency it may lead to cause death of plants except water-loving plants like rice. The soil aeration also an important parameter to plant growth so application interval should be longer. Pest management in ZBNF Crops are damaged by pests and diseases about most of the yield loss by weeds followed by pests and diseases. Controlling of this loss is also a big challenge in natural farming. Plant extractions are used to make a compound that kills or controls the pest population in the crop field. Some of plant protections are made by using a mixture of butter milk, cow milk, pepper powder, neem seed and green chilli (Palekar 2016). Some research papers found some naturally extracted chemical-free compounds are explained below. They are— 2. Bijamrita It is composed of 20 l water, 5 kg cow dung, 5l urine 50 g lime, and a hand full of soil are thoroughly and store in a tank. It is used as a seed treatment, contains naturally occurring beneficial microorganisms. Research studies showed that inoculating with bijamrith to protect the crop from harmful soil-borne pathogens and young seedlings roots from fungus and soil-borne and seed-borne diseases also help to produce IAA and GA3 (Sreenivasa et al. 2010). 1. Agriastra 3. Acchadana/Mulching It consists of local cow urine (10l), tobacco leaves (1 kg), green chili (500 g), local garlic (500 g), and neem leaves pulp crushed in cow urine (5l) store it in a cool place. Take 2l per 100l of water and spray Mulching is of three types followed, they are straw mulch, soil mulch, and live mulch. The growth of cover crops like legumes helps to reduce the weed population and increases water infiltration capacity. Print ISSN : 0974-1712 315 Online ISSN : 2230-732X Srishailam et al. on crops. It effectively controls the pests like Leaf Roller, Stem Borer, Fruit borer, Pod borer. marginal farmers (owning or renting less than 2.5 acres), approximately 20 percent were small farmers (2.5 to 5 acres), and the remaining percentage were large farmers (more than 5 acres) (Gupta et al. 2020). In Karnataka, approximately 72 percent of ZBNF farmers surveyed owned less than 10 hectares (Khadse et al. 2018). On average, ZBNF farmers received more education than non-ZBNF farmers. Forty-two percent of non-ZBNF farmers surveyed in Gupta et al. (2020) did not receive any formal schooling, compared to only 20 percent of ZBNF farmers (Gupta et al. 2020). Based on a survey of 60 farmers in Andhra Pradesh, one study concluded that education has a positive, statistically significant impact on farmers’ perception of ZBNF (Sarada and Kumar 2018). A small proportion of women relative to men adopt ZBNF, although more than 161,000 women’s self-help groups form the foundation of the program (RySS 2019). Gupta et al. (2020) found that 4 and 7 percent of conventional and ZBNF farmers surveyed, respectively, were women. Women in Andhra Pradesh typically participated in the ZBNF program by selling inputs, marketing to other farmers in the community, and monitoring farming plans (RySS 2019; Tripathi et al. 2018). Studies did not observe significant differences between ZBNF and non-ZBNF farmers by caste. Scheduled Caste and Scheduled Tribe farmers represent the smallest share of ZBNF farmers, followed by the general or Other Backward Class (Gupta et al. 2020; RySS 2019). 2. Brahmastra It is 2nd way to control the pest population in natural farming, it can be made by collecting different plant leaves like neem leaves, custard apple leaves, lantern camellia leaves, guava leaves, pomegranate leaves, papaya leaves, and white datura leaves are crushed and boiled with urine finally make filtration. After filtration, the extractant can store for longer use. It is most effective against all of the sucking pests, pod borer, fruit borer, etc. 3. Neemastra By using 5 l of local cow urine, 5 kg cow dung, 5 kg neem leaves 5 kg of neem pulp mixed well, and keep to airtight for 24 hours for fermentation. After the fermentation process is ready to use. Mainly controls sucking pests & Mealy Bug. ZBNF ADOPTION Partial adoption: Some farmers reduce the risks associated with adopting ZBNF by experimenting with only a subset of ZBNF practices, most commonly jeevamrutham and beejamrutham (Gupta et al. 2020). This incremental adoption of ZBNF practices is referred to as a vertical transition (Gupta et al. 2020) and also as stacking (especially when there are two or more practices implemented at the same time). Some farmers also choose to adopt ZBNF on only a portion of their land. RySS expects that a farmer will typically adopt ZBNF on a quarter of their landholding in the first year, half of their landholding in the second year, and complete adoption during the third year—a process described as a horizontal transition (Gupta et al. 2020; RySS 2019). As a result, the land area under ZBNF adoption is lower than the total amount of land associated with farmers in the ZBNF program. Reasons for adoption: Farmers primarily chose to adopt ZBNF to reduce the cost of cultivation (Bishnoi and Bhati 2017; Biswas 2020; Khadse et al. 2018; Khurana and Kumar 2020; Mier y Terán Giménez Cacho et al. 2019; Münster 2017). Since ZBNF does not require chemical inputs, overall input costs decrease dramatically, thereby reducing the need for credit to purchase chemical inputs. One farmer stated that costs were so low that he was no longer concerned with achieving a certain yield to return a profit (Bishnoi and Bhati 2017). Khurana and Kumar (2020) conducted focus groups with 142 farmers across five districts and found that 100 percent of farmers surveyed felt their costs decreased under ZBNF (Khurana and Kumar 2020). In a concurrent survey of 40 farmers, 90 percent of farmers believed costs decreased under ZBNF, and 10 percent felt that costs remained the same as in conventional farming (Khurana and Kumar 2020). In the Prakasam district Farmer characteristics: Farm size and education are the most predictive farmer characteristics for ZBNF adoption. Most ZBNF farmers have small to medium sized landholdings (Gupta et al. 2020; Khadse et al. 2018). The Council on Energy, Environment, and Water (CEEW) surveyed 581 farmers (254 ZBNF, 327 non-ZBNF) in six districts in Andhra Pradesh. More than 70 percent of ZBNF farmers surveyed were Print ISSN : 0974-1712 316 Online ISSN : 2230-732X A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India of Andhra Pradesh, farmers held diverging views on the cost impacts of ZBNF (Sarada and Kumar 2018). Forty-five percent of farmers surveyed in Prakasam believed that ZBNF did not reduce costs relative to conventional farming, and 42 percent believed ZBNF did reduce costs. The remaining 13 percent were undecided (Sarada and Kumar 2018). The results in Prakasam were likely different from the aforementioned studies due to changes in labor costs. In Karnataka, farmers primarily adopted ZBNF due to health benefits (presumably from reduced exposure to chemicals), followed by food self-sufficiency, environmental reasons, and reduced costs and debt (Khadse et al. 2018). Other motivations for adopting ZBNF in Karnataka included economic independence from corporations and spiritual reasons (Khadse et al. 2018). Case Study A College Lecturer turns into a Profitable Natural Farming Farmer- A successful case of Reddy Mahalakshmanudu at Vadlamuru Village, Agiripally Mandal, Krishna District, and Andhra Pradesh State. Name: Mr. Reddy Mahalakshmanudu Village: Vadlamanu Mandal: Agiripally District: Krishna Contact No: 9640727329 Education: M.Ed Mr Reddy Mahalakshmanudu, a college lecturur who turned in a progressive Natural farming farmer. Barriers to adoption: Research has shown that barriers to ZBNF adoption include time and labor constraints, access to cows, land access, and tenant farmer arrangements (Bhattacharya 2017; Galab et al. 2019a; Khurana and Kumar 2020). Small farmers noted that ZBNF input preparation is time and labor intensive (Galab et al. 2019a; Gupta et al. 2020; Khurana and Kumar 2020; Reddy et al. 2019). Gupta et al. (2020) concluded beejamrutham required the most labor out of all ZBNF inputs due to manual seed coating and hand-mixing of ingredients (Gupta et al. 2020). The Centre for Study of Science, Technology, and Policy (CSTEP) surveyed 120 farmers and reported that each acre of paddy under ZBNF required 60 hours of work from men, 800 hours from women, and 10 hours of bullock labor, compared to 110 hours of work from men, 530 hours from women, and 40 hours of bullock labor per non-ZBNF acre (CSTEP 2020). Studies found that large farmers were less likely to adopt ZBNF due to labor and time constraints, as the increased costs to hire labor affected their profitability (Das 2020; Gupta et al. 2020; Khurana and Kumar 2020). One author claimed ZBNF was not profitable for farmers owning more than five acres (Das 2020). Although ZBNF’s farmer-tofarmer network helps to fill knowledge gaps on implementation, knowledge about how to prepare and use bio-pesticides (e.g., neemastra, agniastra, brahmastra) is still a constraint to adoption (Galab et al. 2019a; Sarada and Kumar 2018). Print ISSN : 0974-1712 Training & Motivation His father and other villagers were basically farmers practicing conventional method of farming. His family they observed wiping out of their mango orchard due to indiscrimiate use of chemical and low income from orchard and even from other crops. In mango, they were facing the problem of stem and leaf falling, no fruit bearing and uneven ripening along with reduced production. He highlighted that the soil condition was deteriorating, as the soil turned harder and soil organisms were disapperaing. Mr Reddy Mahalakshmudu is well educated person and knew the value of soil and had respect towards agriculture made him to meet his friend Srinivas Rao, who was working has a Community Resource Person (CRP) under Rythu Sadhikara Samstha (RySS) in his village. Discusing with his friend he decided to practice natural farming in 2016. The training programme of Sri Subhash Pallekhar motivated his towards natural farming and there he learned all the preparation methods of natural farming inputs like Jeevamrutham, Beejamrutham, Neemastra, Gana Jeevamrutham etc. Adoption of natural farming practices and achievements Initially he started natural farming in his 4 acres of land, 317 Online ISSN : 2230-732X Srishailam et al. he incured losses in his early stage but he continued because natural farming had a positive effect on his family health. After 3 years, his field started earning well and then he brought extra 5 acres of land as lease to continue natural farming along with his 4 acres of land. He prepare his input himself and expressed it as nor difficult neither labour intenstive. He prepares beejamritham, ghanajivamritham, jeevamritham, Gokrupa amrutham, mulching, growth regulators (fish amino acid, egg amino acid, botanical extract, sapthdanya kashayam, etc,.), and kashayams for pest management. Low cost input substition, like he uses overriped mangoes (which has no market value) instead of jaggery in jeevamritham, use of waste plaste bottle with lure (saves moneys from Rs 10-15 and use of bananas to ripe Managoes evenly). Better use of by products, used in selling and also in preparation of natural farming inputs in his field. His farm serves as a model farm for not only the farmers of his village but also the farmers of nearby villages and officials too. a amount of money to his income. He is awarded as best farmer from Krishna district by Rythu Nastham Foundation, 2018. Mr Reddy Mahalakshmanudu success story is an inspiration to other, who would like to earn good profits in Agriculture and respect in society. He stated that by providing good market facilities for the natural produce and recognising natural farming farmers will leads to adopt natural farming by all farmers of the state. Challenges to adopt ZBNF Natural farming is eco-friendly sustainable to the environment maintains good health of soil, plant as well as human beings by increasing beneficial microbial population, chemical-free nutrients supply to plants and toxic-free food supplies to consumers (man and animals). But still, farmers are not going to adapt this technology due to some lacunas so the govt, researchers, scientist and extension workers should think about major challenges to success this zero budget natural farming technology in a large area, and according to authors view some of the major challenges are listed below. Table 1: Comparison between Natural and Conventional Farming by Mr. Reddy Mahalakshmanudu Parameters Natural Farming Conventional Farming Crop Mango Paddy Mango Paddy Cost of 51,000 cultivation (in `) 25,000 74,000 23,000 Production (Quintals) 30 20 15 18 Gross returns (in `) 2,40,000 93,500 70,000 28,000 Net returns (in `) 1,99,000 68,500 24,000 5,000 B:C ratio 0.95 1.2 4.71 3.74 1. The labor requirement is increased compared to conventional farming. 2. The demand for animal manure is high. On a national scale, the number of cattle in India could not support this level of manure application. 3. With the demand and consumption pattern constantly changing when it comes to highvalue products. 4. Better technology and high investment are required on farmland. Well developed heavy machinery, implements are not used in natural farming due to it creates soil compaction even there is no use of tractors in it. Benefits He expressed that by practicing natural farming in his farm, he got profits and notable increase in production of crops by 10 per cent then conventional farmers. Enhanced quality of vegetables and improved the shelf life of mango and taste of rice has improved double fold. He is an innovative farmer, as he tries practicing new thing in his farm for better yield and incocme, for example; he tried grafting in a mango tree with 17 varities of mangoes. He sells his mangos and other vegetables to the local officials and school teachers and other public representatives, this has gained good recognition. There no issue regarding marketing, as he does direct marketing of his produce without middlemen to the consumers of cities and towns like Visakapatnam, Vijaywada, Hyderabad, Benguluru etc (Whatsapp group with his consumers to promote and sell his produce). He rears his indigenious cows naturally, sells their milk at good price and this adds Print ISSN : 0974-1712 5. Weakened agricultural market infrastructurethere is no value of natural products in large scale areas even the price also similar to chemically produced products. 6. N o s c i e n t i f i c va l i d a t i o n - m i c r o b i a l composition, efficiency, and impact of jivamrith, bijamrith, bramhastra, dashaparni kashaya not yet tested and there is no scientific data on it. 318 Online ISSN : 2230-732X A Critical Study on the Present Status and Scope of Natural Farming in the State of Andhra Pradesh, India 7. Hybrid varieties, not permitted-continuously increasing global population food is scarce to all populations. Even by using chemicals, we are not reaching our food production target, without hybrids, it is impossible to reach the target. 6. Scheme for cattle and other live stock farmers far the purpose of it maintaince and marketing of live stock produce. 7. Ensure the availability of natural farming inputs in all villages under Rythu Barosa Kendras it will be help full for initial period farmers to get good yields 8. Promotion of ZBNF on a large scale without scientific validation and under the political influence- no scientific data on crop yield. 8. More training and demonstration respect to crop specific will be given to natural farming farmers and also teach the techniques of preparation of natural farming inputs. 9. Pest management is difficult- different cropspecific weeds, diseases, insects are damaging to crop drastically, by using natural products its control is not satisfactory to farmer’s level. 9. Increase the availabilty of Non Pesticides Management shops in all villages and aslo give some financial assistance for the managers of NPMs 10. Quality planting material and other proven techniques like GMO’s are not considered in ZBNF. 10. Need to create special marketing channel far the natural farming inputs that will fletch to get more profits to the natural farming farmers. It will also motivate other farmers also to take up natural farming. 11. Criticizes other agroecological and organic farming techniques. 12. Non-availability of indigenous cow, it contains Millions of beneficial microbes and pathogen-free dung. CONCLUSION 13. As ZBNF adapted in India by Mr. Subash Palekar is not adopted in his own state Maharashtra. Zero budget farming is environmentally friendly. Savings on the cost of seeds, fertilizers, and plant protection chemicals have been substantial. Because of continuous retention of crop residues replenishment the soil fertility, it helps to maintain the soil health. Other thing is that management of pest and diseases is a key component in zero budget natural farming crop production systems. Successfully control pests in ZBNF, it is essential to understand the interactions of different components in a specific ecosystem. The new system of farming has free debt trap of farmers and it has instilled in them a renewed sense of confidence to make farming an economically viable venture. The challenges and opportunities are two parameters that show the systems lacunas to researchers, scientists, and extension workers and benefits to adopters, and policy intervention is necessary to make the success. Suitable Suggestions for Improving Natural Farming in Andhra Pradesh State 1. Essential to recognise the natural farming farmers and thay need special programmes for there welfare and stability. 2. Creating Brand value to the natural farming produce and also location specific brand identity will be needed like geographical Indication in natural farming for the produce. 3. Marketing will be major issue to the natural farming farmers it need to be resolved most priority basis and special price for the natural farming produce willbe ensured. 4. Hand holding support from the government side will need to the natural farming farmers in initial periods. 5. The state department of agriculture and others related institutes of agriculture like SAUs and KVKs, ATMA, DAATTC, will focus more on natural farming involvement will be needed. Print ISSN : 0974-1712 319 Online ISSN : 2230-732X Srishailam et al. REFERENCES Ahmed, K. 2018. Taking agroecology to scale: the Zero Budget Natural Farming peasant movement in Karnataka, India, The J. Peasant Stud., 45(1). https://indianexpress.com/article/cities/ahmedabad/ pm-modi-natural-farming-farmers-burning-cropresidue-7675909/) https://indianexpress.com/article/opinion/columns/roadmapfor-india-natural-farming-ambitions-nirmala-fmbudget-7788054/ https://spnfhp.nic.in/SPNF/en-IN/spnf.aspx https://www.niti.gov.in/natural-farming-niti-initiative. Khurana, A. and Kumar, R. 2022. Evidence (2004-20) on holistic benefits of organic and natural farming in India, Centre for Science and Environment, New Delhi. Khurana, A. and Kumar, V. 2020. State of organic and natural farming: Challenges and possibilities, Centre for Science and Environment, New Delhi Rajesh K Rana and Singh, R. 2018. Restoring human and environmental health through creative natural farming practices, Agri-Innovators: The Torch Bearers of Brighter Agriculture, ICAR-ATARI, Zone-I, Ludhiana, India, pp. 19-24. The Economic Survey. 2019. https://www.indiabudget.gov.in/ economicsurvey/2019-20. Source: Answer to a question in Lok Sabha Print ISSN : 0974-1712 320 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 321-328, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.6 Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life of Jasminum sambac Cv. “Mysuru Mallige” Keerthishankar, K.1*, Yathindra, H.A.1, Mutthuraju, G.P.2 and Tanveer Ahmed3 Department of Floriculture and Landscape Architecture, College of Horticulture, Bengaluru, India Department of Entomology, College of Horticulture, Mysuru, India 3 Department of Agriculture Economics, College of Horticulture, Mysuru, India 1 2 *Corresponding author: keerthishankar55@gmail.com (ORCID ID: 0000-0002-6280-7585) Paper No. 991 Received: 22-05-2022 Revised: 24-06-2022 Accepted: 01-07-2022 ABSTRACT Experiment was carried out in the Department of Floriculture and Landscape Architecture, College of Horticulture Mysuru during 2019-2021 to find out the effect of chemical preservatives and biodegradable nano silver film on post-harvest life of Jasminum sambac cv. Mysuru Mallige. The experiment was laid out in Factorial Completely randomized Design (FCRD) with 15 treatment and two replications. The periodical observations recorded every 12 hrs from 0 hrs to 36 hrs. were physiological loss of weight, freshness index and shelf-life. Results of this experiment envisaged that flowers which are treated with 5 per cent boric acid and packed in 60 micron biodegradable nano silver film recorded less physiological loss of weight with maximum fragrance index and shelf-life of the flower. HIGHLIGHTS mm Jasmine (Jasminum spp.) is one of the most fragrant flowers belongs to the family Oleaceae and flowers have a great economic value in India and mainly used as loose flower for making garland and oil extraction. Among the commercial species of jasmine, Jasminum sambac Ait. commonly known as Arabian jasmine, Tuscan jasmine, Mogra and Bela. There have several cultivars like Motia, Double Mogra, Single Mogra, Gundu Mallige, Bela, Khoya, Madanbana, Ramabana and Mysuru Mallige. Among these cultivars, Mysuru Mallige (Mysuru Jasmine) being associated with the city of Mysuru, patronized by the wodeyar of the kingdom of Mysuru because of its flower fragrance. The Mysuru Jasmine has got Geographical Indication status (GI under Registration of Protection Act 1999) under agriculture commodity (69th G.I. Product of India) by Govt. of India during 2007-08 for its unique fragrance and flowering characters and commonly cultivated in Mysore and Mandya regions of Karnataka. Keywords: Jasmine, Preservatives, Nano silver film, Shelf-life Mysuru Mallige flowers are highly perishable in nature and got good demand in local market as well as outside market like Kerala, Tamilnadu, Mumbai etc. One of the major problems faced by grower are lack of suitable packaging technology for export. The flowers are very delicate and show signs of wilting with abrupt loss of fragrance within 24 -36 hours after harvest. Under normal condition, jasmine flowers do not retain for more than a day and show a sign of browning or rotting of petals on the second day of harvest with an abrupt loss in fragrance. Krishnamoorthy (1990) reported that packaging is a fundamental tool for post-harvest management How to cite this article: Keerthishankar, K., Yathindra, H.A., Mutthuraju, G.P. and Ahmed, T. (2022). Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life of Jasminum sambac Cv. “Mysuru Mallige”. Int. J. Ag. Env. Biotech., 15(Special Issue): 321-328. Source of Support: None; Conflict of Interest: None Keerthishankar et al. of highly perishable commodities and adequate packaging protects the produce from physical, physiological and pathological deterioration during transport and marketing, enhancing their shelf-life by retaining their attractiveness. So, standardization of post-harvest techniques to extend shelf-life of Mysuru Mallige flowers will helpful to famers to exploit distant market. Keeping this in mind, a study was under taken to enhance the post-harvest life of Mysuru Mallige. packing and at 12th, 24th, and 36th hr after harvesting of flowers and expressed as percentage. Freshness score were recorded based on scale, the score was expressed on 1 to 10 (Isac, 2015) and average was calculated. Shelf-life of the flower was measured as time taken to wilt 50% of flowers. The resulted data were statistically analyzed using the method of Panase and Sukhatme (1967). RESULTS AND DISCUSSION The result obtaining with respect to Physiological loss in weight, Freshness index and Shelf life of Mysuru Mallige flowers are presented in the table 2, 3 and 4 respectively. MATERIALS AND METHODS The experiment was carried out in the Department of Floriculture and Landscape Architecture, College of Horticulture Mysuru during 2019-2021 to find out the effect of chemical preservatives and biodegradable nano silver film on post-harvest life of Jasminum sambac cv. Mysuru Mallige. The experiment was laid out in Factorial Completely randomized Design (FCRD) with two replications and two factors: Different preservatives at different concentration and different thickness of biodegradable nano silver film. The first factor comprised of five treatments viz., T1: Boric acid at 4 per cent, T2: Boric acid at 5 per cent, T3: Silver nitrate at 0.2 per cent, T4: Silver nitrate at 0.3 per cent and T5: Water spray (Control) and second factor contains 3 treatments viz., B1: 40-micron Nano silver film, B2: 60-micron Nano silver film and B3: 70-micron Nano silver film. 500g of uniform size, freshly harvested flowers buds are used for each treatment and observation like physiological loses of weight (PLW), freshness score and shelf-life were recorded during storage of flowers at 24 hours of intervals. Physiological loss in weight of the flowers (%) The data on physiological loss in weight of the flower (%) as influenced by different preservatives and biodegradable packaging materials and their interaction effects are presented in Table 2. Chemical preservatives (T) Among different chemical preservatives, the minimum physiological loss in weight of the flowers (1.02 per cent, 1.87 per cent and 2.52 per cent) was recorded in 5 per cent boric acid (T2) and maximum physiological loss in weight of the flowers (4.50 per cent, 6.31 per cent and 7.26 per cent) was recorded in T5 i.e., water spray at 12, 24 and 36 hours after imposing the treatments respectively during 2019-20. Similarly, during 2020-21, the minimum physiological loss in weight of the flowers (0.94 per cent, 1.83 per cent and 2.45 per cent) was recorded in T2 i.e., spray of 5 per cent boric acid and maximum physiological loss in weight of the flowers (4.45 per cent, 6.26 per cent and 7.24 per cent) was recorded in water spray (T5, control) at 12, 24 and 36 hours after imposing the treatment respectively. Pooled data revealed that, spray of 5 per cent boric acid (T2) recorded minimum physiological loss in weight (0.98 ± 0.06 per cent, 1.85 ± 0.03 per cent and 2.49 ± 0.05 per cent) and maximum physiological loss in weight of the flower (4.47 ± 0.04 per cent, 6.29 ± 0.04 per cent and 7.25 ± 0.01 per cent) was recorded in T5 i.e., water spray at 12, 24 and 36 hours after imposing the treatment respectively. Table 1: Freshness score details Freshness index Score Original colour/ fresh flower 1 Partial fading of original colour 2 Complete fading of original colour 3 1 to 10% brown 4 11 to 15% brown 5 16 to 30% brown 6 30 to 50% brown 7 51 to 75% brown 8 76 to 90% brown 9 All brown 10 Biodegradable packaging material (B) Physiological loses of weight was calculated by subtracting fresh weight of flowers at the time of Print ISSN : 0974-1712 Among the different thickness of biodegradable 322 Online ISSN : 2230-732X Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life... Table 2: Effect of different preservatives and biodegradable packaging material on physiological loss in weight (%) Treatments 2019-20 12 hrs. 24 hrs. 36 hrs. T1 T2 T3 T4 T5 S. Em. ± C.D@5% 1.29 1.02 3.22 2.87 4.50 0.05 0.13 2.09 1.87 4.50 4.23 6.31 0.04 0.12 2.99 2.52 5.58 4.85 7.26 0.04 0.12 B1 B2 B3 S. Em. ± C.D@5% 2.84 2.34 2.57 0.04 0.10 4.13 3.45 3.82 0.03 0.09 5.01 4.29 4.62 0.03 0.09 T1B1 T1B2 T1B3 T2B1 T2B2 T2B3 T3B1 T3B2 T3B3 T4B1 T4B2 T4B3 T5B1 T5B2 T5B3 S. Em. ± C.D@5% 1.36 1.21 1.31 1.39 0.75 0.93 3.38 3.06 3.21 3.16 2.53 2.92 4.91 4.14 4.46 0.08 0.23 2.28 1.92 2.08 2.11 1.65 1.83 4.81 4.03 4.65 4.55 3.95 4.20 6.90 5.72 6.32 0.07 0.20 3.24 2.80 2.94 2.92 2.23 2.42 5.90 5.21 5.64 5.27 4.35 4.92 7.72 6.86 7.20 0.07 0.20 2020-21 24 hrs. 36 hrs. 12 hrs. Preservatives (T) 1.27 2.07 2.94 1.28 ± 0.01 0.94 1.83 2.45 0.98 ± 0.06 3.16 4.46 5.55 3.19 ± 0.04 2.76 4.17 4.78 2.81 ± 0.08 4.45 6.26 7.24 4.47 ± 0.04 0.05 0.04 0.04 — 0.13 0.12 0.13 — Biodegradable packaging material (B) 2.73 4.11 4.96 2.79 ± 0.08 2.30 3.43 4.24 2.32 ± 0.02 2.51 3.74 4.57 2.54 ± 0.04 0.04 0.03 0.03 — 0.10 0.09 0.10 — Interactions 1.35 2.23 3.17 1.36 ± 0.01 1.21 1.93 2.77 1.21 ± 0.00 1.26 2.04 2.90 1.29 ± 0.03 1.27 2.07 2.87 1.33 ± 0.09 0.68 1.62 2.17 0.72 ± 0.05 0.87 1.80 2.32 0.90 ± 0.04 3.27 4.80 5.87 3.33 ± 0.08 3.03 4.03 5.17 3.05 ± 0.02 3.17 4.55 5.60 3.19 ± 0.03 2.97 4.50 5.22 3.07 ± 0.14 2.50 3.88 4.28 2.51 ± 0.02 2.80 4.13 4.83 2.86 ± 0.08 4.80 6.95 7.68 4.85 ± 0.08 4.10 5.67 6.83 4.12 ± 0.03 4.44 6.17 7.20 4.45 ± 0.01 0.08 0.07 0.08 — 0.23 0.21 0.22 — 12 hrs. Pooled Mean 24 hrs. 36 hrs. 2.08 ± 0.02 1.85 ± 0.03 4.48 ± 0.02 4.20 ± 0.04 6.29 ± 0.04 — — 2.97 ± 0.03 2.49 ± 0.05 5.57 ± 0.03 4.81 ± 0.05 7.25 ± 0.01 — — 4.12 ± 0.01 3.44 ± 0.02 3.78 ± 0.06 — — 4.99 ± 0.03 4.27 ± 0.03 4.60 ± 0.04 — — 2.26 ± 0.04 1.93 ± 0.01 2.06 ± 0.02 2.09 ± 0.03 1.63 ± 0.02 1.82 ± 0.02 4.80 ± 0.00 4.03 ± 0.00 4.60 ± 0.07 4.53 ± 0.04 3.92 ± 0.05 4.17 ± 0.05 6.93 ± 0.04 5.69 ± 0.04 6.24 ± 0.11 — — 3.20 ± 0.05 2.78 ± 0.02 2.92 ± 0.03 2.90 ± 0.03 2.20 ± 0.05 2.37 ± 0.07 5.88 ± 0.02 5.19 ± 0.03 5.62 ± 0.03 5.24 ± 0.04 4.32 ± 0.05 4.88 ± 0.06 7.70 ± 0.02 6.85 ± 0.02 7.20 ± 0.00 — — T1: Boric acid at 4 per cent; T2: Boric acid at 5 per cent; T3: Silver nitrate at 0.2 per cent; T4: Silver nitrate at 0.3 per cent; T5: Water spray; B1: 40-micron Nano silver film; B2: 60-micron Nano silver film; B3: 70-micron Nano silver film. packaging material, flowers which are packed in 60 micron nano silver film (B2) recorded minimum physiological loss in weight (2.34 per cent, 3.45 per cent and 4.29 per cent) and maximum physiological loss in weight (2.84 per cent, 4.13 per cent and 5.01 per cent) of the flower was recorded in 40 micron nano silver film (B1) at 12, 24 and 36 hours after imposing the treatment respectively during 2019-20. Similarly, during 2020-21, the flowers which were packed in 60 micron nano silver film (B2) recorded minimum physiological loss in weight (2.30 per cent, 3.43 per cent and 4.24 per cent). Maximum physiological loss in weight (2.73 per cent, 4.11 per cent and 4.96 per cent) was recorded in B1 i.e., Print ISSN : 0974-1712 40 micron nano silver film at 12, 24 and 36 hours after imposing the treatment respectively. Pooled data revealed that, minimum physiological loss in weight of the flower (2.32 ± 0.02 per cent, 3.44 ± 0.02 per cent and 4.27 ± 0.03 per cent) was recorded in B2 (60 micron biodegradable nano silver film) whereas maximum physiological loss in weight of the flower (2.79 ± 0.08, 4.12 ± 0.01, and 4.99+ 0.03 per cent) was recorded in 40-micron biodegradable nano silver film (B1). Interaction (T × B) Interaction effect was significant on physiological loss in weight (%) at 12, 24 and 36 hours after 323 Online ISSN : 2230-732X Keerthishankar et al. imposing the treatment in both the season i.e., 201920 and 2020-21. different chemical preservatives and biodegradable packaging material and their interaction effects during 2019-20 and 2020-21 are presented in Table 3. The interaction results showed that, T2B2 (spray of 5 per cent boric acid and packed in 60 micron biodegradable nano silver film) recorded minimum physiological loss in weight of the flower (0.75 per cent, 1.65 per cent and 2.23 per cent) followed by T2B3 i.e., 0.93 per cent, 1.83 per cent and 2.42 per cent. Maximum physiological loss in weight (4.91 per cent, 6.90 per cent and 7.72 per cent) was recorded in T5B1 interaction (water spray and flowers are packed in 40 micron biodegradable nano silver film) at 12, 24 and 36 hours after imposing the treatment respectively during 2019-20. During 202021, flowers which are treated with 5 per cent boric acid and packed in 60 micron biodegradable nano silver film (T2B2) recorded minimum physiological loss in weight (0.68 per cent, 1.62 per cent and 2.17 per cent) followed by T2B3 (0.87 per cent, 1.80 per cent and 2.32 per cent). Interaction of T5B1 (water spray and storage in 40 micron biodegradable nano silver film) recorded maximum physiological loss in weight of the flower (4.80 per cent, 6.95 per cent and 7.68 per cent) at 12, 24 and 36 hours after imposing the treatment respectively. Pooled mean revealed that, T2B2 (Spray of 5 per cent boric acid and packed in 60 micron biodegradable nano silver film) interaction recorded minimum physiological loss in weight (0.72 ± 0.05 per cent, 1.63 ± 0.02 per cent and 2.20 ± 0.05 per cent) and maximum physiological loss in weight (4.85 ±0.08 per cent, 6.93 ± 0.04 per cent and 7.70 ± 0.02 per cent) was recorded in T5B1 interaction (water spray and flowers are packed at 40 micron biodegradable nano silver film). Chemical preservatives (T) The treatment consisting of boric acid spray at 5 per cent (T2) recorded maximum freshness index score of 9.52, 8.33 and 4.78. Whereas minimum freshness index (8.00, 5.60 and 2.09) was recorded in T5 (Water spray) at 12, 24 and 36 hours after imposing the treatment respectively during 2019-20. Among the different spray of chemical preservatives, the maximum freshness index score (9.56, 8.37 and 4.82) was recorded in spray of 5 per cent boric acid (T2) and minimum freshness score (8.03, 5.54 and 2.04) was recorded in T5 i.e., water spray at 12, 24 and 36 hours after imposing the treatment respectively during 2020-21. Pooled data revealed that, spray of 5 per cent boric acid (T2) recorded maximum freshness index score (9.54 ± 0.03, 8.35 ± 0.03 and 4.80 ± 0.03) and minimum freshness score (8.02 ± 0.02, 5.57 ± 0.04 and 2.07 ± 0.04) was recorded in T5 i.e., water spray at 12, 24 and 36 hours after imposing the treatment respectively. Biodegradable packaging material (B) Flowers packed in 60 micron biodegradable nano silver film (B2) recorded maximum freshness index score (9.01, 7.40 and 3.95), whereas 40 micron biodegradable nano silver film (B 1 ) recorded minimum freshness index (8.74, 6.55 and 2.85) at 12, 24 and 36 hours after imposing the treatment respectively during 2019-20. Among the different thickness of biodegradable packaging material, flowers which are packed in 60 micron nano silver film (B2) recorded maximum freshness index score of 9.03, 7.40 and 3.96. Minimum freshness index score (8.75, 6.56 and 2.86) was recorded in 40 micron nano silver film (B1) at 12, 24 and 36 hours after imposing the treatment respectively during 2020-21. Pooled data revealed that, B2 i.e., flowers packed in 60 micron biodegradable nano silver film recorded maximum freshness index score (9.02 ± 0.01, 7.40 ± 0.00 and 3.96 ± 0.01) and minimum freshness index score (8.75 ± 0.01, 6.56 ± 0.01 and 2.86 ± 0.01) was recorded in 40 micron nano silver film (B1) at 12, 24 and 36 hours after imposing the treatment respectively. Boric acid is an anti-senescence agent, increases water balance in flower, delay the ethylene production, minimizes the physiological loss of weight and phenol accumulation. Similar results were also obtained by Jawaharlal et al. (2012) and Mukhopadhyay et al. (1980) in jasmine. Nano silver film has most effective bactericidal property against a wide range of pathogenic microorganism, including bacteria, yeasts, fungi and viruses (Marttinez et al. 2012) Thus, it also increases shelf-life of flower without altering physical characteristics (Emamifar et al. 2010). Freshness Index (10 point scale) The data on freshness index as influenced by Print ISSN : 0974-1712 324 Online ISSN : 2230-732X Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life... Table 3: Effect of different preservatives and biodegradable packaging material on freshness index (10 point scale) 12 hrs. 2019-20 24 hrs. 36 hrs. T1 T2 T3 T4 T5 S. Em. ± C.D@5% 9.32 9.52 8.58 9.02 8.00 0.03 0.09 7.62 8.33 6.23 7.11 5.60 0.07 0.19 4.06 4.78 2.63 3.43 2.09 0.05 0.15 B1 B2 B3 S. Em. ± C.D@5% 8.74 9.01 8.91 0.02 0.07 6.55 7.40 6.99 0.05 0.15 2.85 3.95 3.39 0.04 0.12 T1B1 T1B2 T1B3 T2B1 T2B2 T2B3 T3B1 T3B2 T3B3 T4B1 T4B2 T4B3 T5B1 T5B2 T5B3 S. Em. ± C.D@5% 9.27 9.40 9.30 9.33 9.67 9.57 8.53 8.63 8.57 8.80 9.20 9.07 7.77 8.17 8.07 0.05 0.15 7.30 7.90 7.67 7.90 8.70 8.40 5.83 6.83 6.03 6.40 7.60 7.33 5.30 5.97 5.53 0.12 0.34 3.50 4.60 4.07 4.53 5.00 4.80 2.10 3.30 2.50 2.63 4.27 3.40 1.50 2.60 2.17 0.09 0.27 Treatments 2020-21 24 hrs. 36 hrs. 12 hrs. Preservatives (P) 9.32 7.66 4.10 9.32 ± 0.00 9.56 8.37 4.82 9.54 ± 0.03 8.58 6.20 2.58 8.58 ± 0.00 9.02 7.16 3.47 9.02 ± 0.00 8.03 5.54 2.04 8.02 ± 0.02 0.03 0.07 0.05 — 0.08 0.20 0.14 — Biodegradable packaging material (B) 8.75 6.56 2.86 8.75 ± 0.01 9.03 7.40 3.96 9.02 ± 0.01 8.93 6.99 3.40 8.92 ± 0.01 0.02 0.05 0.04 — 0.06 0.15 0.11 — Interactions 9.27 7.33 3.55 9.27 ± 0.00 9.40 7.93 4.65 9.40 ± 0.00 9.30 7.70 4.10 9.30 ± 0.00 9.37 7.95 4.57 9.35 ± 0.03 9.70 8.73 5.05 9.69 ± 0.02 9.60 8.43 4.85 9.59 ± 0.02 8.53 5.80 2.05 8.53 ± 0.00 8.63 6.80 3.25 8.63 ± 0.00 8.57 6.00 2.45 8.57 ± 0.00 8.80 6.45 2.67 8.80 ± 0.00 9.20 7.65 4.30 9.20 ± 0.00 9.07 7.37 3.45 9.07 ± 0.00 7.80 5.25 1.45 7.79 ± 0.02 8.20 5.90 2.55 8.19 ± 0.02 8.10 5.47 2.13 8.09 ± 0.02 0.05 0.12 0.08 — 0.14 0.34 0.24 — 12 hrs. Pooled mean 24 hrs. 36 hrs. 7.64 ± 0.03 8.35 ± 0.03 6.22 ± 0.02 7.14 ± 0.04 5.57 ± 0.04 — — 4.08 ± 0.03 4.80 ± 0.03 2.61 ± 0.04 3.45 ± 0.03 2.07 ± 0.04 — — 6.56 ± 0.01 7.40 ± 0.00 6.99 ± 0.00 — — 2.86 ± 0.01 3.96 ± 0.01 3.40 ± 0.01 — — 7.32 ± 0.02 7.92 ± 0.02 7.69 ± 0.02 7.93 ± 0.04 8.72 ± 0.02 8.42 ± 0.02 5.82 ± 0.02 6.82 ± 0.02 6.02 ± 0.02 6.43 ± 0.04 7.63 ± 0.04 7.35 ± 0.03 5.28 ± 0.04 5.94 ± 0.05 5.50 ± 0.04 — — 3.53 ± 0.04 4.63 ± 0.04 4.09 ± 0.02 4.55 ± 0.03 5.03 ± 0.04 4.83 ± 0.04 2.08 ± 0.04 3.28 ± 0.04 2.48 ± 0.04 2.65 ± 0.03 4.29 ± 0.02 3.43 ± 0.04 1.48 ± 0.04 2.58 ± 0.04 2.15 ± 0.03 — — T1: Boric acid at 4 per cent; T2: Boric acid at 5 per cent; T3: Silver nitrate at 0.2 per cent; T4: Silver nitrate at 0.3 per cent; T5: Water spray; B1: 40-micron Nano silver film; B2: 60-micron Nano silver film; B3: 70-micron Nano silver film. Interaction (T × B) acid and packed in 60 micron biodegradable nano silver film (T2B2) recorded maximum freshness index score of 9.70, 8.73 and 5.05 followed by T2B3 (Spray of 5 per cent boric acid and packed in 70 micron biodegradable nano silver film) (9.60, 8.43 and 4.85). Interaction of T5B1 (water spray and flowers are packed in 40 micron biodegradable nano silver film) recorded minimum freshness index score of 7.80, 5.25 and 1.45 at 12, 24 and 36 hours after imposing the treatment respectively. Pooled mean revealed that, T2B2 (spray of 5% boric acid and packed in 60 micron biodegradable nano silver film) interaction recorded maximum freshness index score (9.69 ± 0.02, 8.72 ± 0.02 and 4.83 ± 0.04 and minimum freshness index score (7.79 ± 0.02, 5.28 ± 0.04 and The interaction results noted that, T2B2 (Spray of 5 per cent boric acid and packed in 60 micron biodegradable nano silver film) interaction recorded maximum freshness index score (9.67, 8.70 and 5.00) followed by the treatment includes spray of 5 per cent boric acid and packed in 70 micron biodegradable nano silver film (T2B3) i.e., 9.57, 8.40 and 4.80. Minimum freshness index of 7.77, 5.30 and 1.50 was recorded in T5B1 interaction (Water spray + flowers are packed in 40 micron biodegradable nano silver film) at 12, 24 and 36 hours after imposing the treatment respectively during 2019-20. During 202021, flowers which are treated with spray of 5% boric Print ISSN : 0974-1712 325 Online ISSN : 2230-732X Keerthishankar et al. 1.48 ± 0.04) was recorded in flowers are sprayed with water and packed in 40 micron biodegradable nano silver film (T5B1) interaction at 12, 24 and 36 hours after imposing the treatment respectively. life (38.27 hrs) was recorded in 40 micron nano silver film (B1) during 2019-20. During 2020-21, the flowers which are packed in 60 micron nano silver film (B2) recorded maximum shelf-life of the flower (40.20 hrs) whereas minimum shelf-life of the flower (38.31 hrs) was recorded in B1 i.e., 40 micron nano silver film. Pooled mean data indicated that, maximum shelf-life of the flower (40.14 ± 0.08 hrs) was recorded in B2 (60 micron biodegradable nano silver film) whereas minimum shelf-life of the flower (38.29 ± 0.03 hrs) was recorded in 40 micron biodegradable nano silver film (B1). Boric acid proved effective by registering higher levels of moisture, relative water content, lowest rates of PLW. This, in turn reduces solute leakage from flowers, indicating increased membrane integrity of flowers. All these factors proved effective in retaining freshness index of flowers (Jawaharlal et al., 2012 in jasmine). Similar results were also obtained by Maruthamuthuchandran et al., (2018) and Mukhopadhyay et al., (1980) in jasmine. Flowers packed in 60 micron nano silver film are capable of modifying the atmosphere in the packs and thus allowing the flowers to be stored for long hours without affecting the freshness (Tavakoli et al. 2017). These results are in close agreement with the findings of Madaiah and Reddy (1994) and Mukhopadhyay et al., (1980) in jasmine. Table 4: Effect of different preservatives and biodegradable packaging material on shelf-life (hrs) Treatments 2019-20 T1 T2 T3 T4 T5 S. Em. ± C.D@5% Shelf-life (hrs) The data on shelf-life (hrs) of the flowers as influenced by different spray chemical preservatives and biodegradable packaging material and their interaction are presented in Table 4. B1 B2 B3 S. Em. ± C.D@5% Chemical preservatives (T) Among the different spray of chemical preservatives, the maximum shelf-life of the flower (43.05 hrs) was recorded in T2 (Spray of 5 per cent boric acid) and minimum shelf-life of the flower (33.59 hrs) was recorded in T5 i.e., flowers were treated with only water spray during 2019-20. During 2020-21, the maximum shelf-life of the flower (43.14 hrs) was recorded in treatment where flowers were treated with 5 per cent boric acid and minimum shelf-life (34.07 hrs) was recorded in water spray (T5- control). Pooled data revealed that, spray of 5 per cent boric acid (T2) recorded maximum shelf-life (43.09 ± 0.06 hrs) and minimum shelf-life (34.04 ± 0.06 hrs) was recorded in T5 i.e., water spray. T1B1 T1B2 T1B3 T2B1 T2B2 T2B3 T3B1 T3B2 T3B3 T4B1 T4B2 T4B3 T5B1 T5B2 T5B3 S. Em. ± C.D@5% Biodegradable packaging material (B) Among the different thickness of biodegradable packaging material, flowers which are packed in 60 micron nano silver film (B2) was recorded maximum shelf-life (40.08 hrs) and minimum shelfPrint ISSN : 0974-1712 2020-21 Mean Preservatives 42.35 42.04 42.20 ± 0.07 43.05 43.14 43.09 ± 0.06 37.37 37.33 37.35 ± 0.02 39.55 40.08 40.02 ± 0.09 33.59 34.07 34.04 ± 0.06 0.14 0.15 0.40 0.44 Biodegradable packaging material 38.27 38.31 38.29 ± 0.03 40.08 40.20 40.14 ± 0.08 39.11 39.16 39.14 ± 0.04 0.11 0.12 — 0.31 0.34 — Interactions 41.25 41.42 41.33 ± 0.12 42.50 42.58 42.54 ± 0.06 42.10 42.13 42.12 ± 0.02 41.50 41.58 41.54 ± 0.06 44.15 44.28 44.22 ± 0.09 43.50 43.55 43.53 ± 0.04 36.45 36.20 36.33 ± 0.04 37.40 37.48 37.44 ± 0.18 37.05 37.12 37.08 ± 0.06 39.00 39.13 39.07 ± 0.05 40.20 40.40 40.30 ± 0.09 39.45 39.50 39.48 ± 0.14 33.15 33.23 33.19 ± 0.06 34.18 34.27 34.23 ± 0.06 33.45 33.52 33.48 ± 0.05 0.24 0.26 — 0.70 0.76 — T1: Boric acid at 4 per cent; T2: Boric acid at 5 per cent; T3: Silver nitrate at 0.2 per cent; T4: Silver nitrate at 0.3 per cent; T5: Water spray; B1: 40-micron Nano silver film; B2: 60-micron Nano silver film; B3: 70-micron Nano silver film. 326 Online ISSN : 2230-732X Influence of Preservatives and Biodegradable Nano Silver Film on Post-harvest Life... Shelf-life (hr's) 45.00 40.00 35.00 30.00 25.00 20.00 15.00 10.00 5.00 0.00 T1B1 T1B2 T1B3 T2B1 T2B2 T2B3 T3B1 T3B2 T3B3 T4B1 T4B2 T4B3 T5B1 T5B2 T5B3 Fig. 1: Effect of different preservatives and biodegradable packaging material on shelf-life (hrs) Interaction (T × B) optimum humidity and proper balance of CO2 and O2 concentration which interns slows down the process of respiration and evapotranspiration and ultimately reduced the PLW and enhances shelf-life of flower. Nano silver film has potential to minimizes the microbial load (Marttinez et al. 2012). Thus, it also increases shelf-life of flower without altering physical characteristics (Emamifar et al., 2010). Boric acid also improves water balance, threeto-six-fold increase in activity of peroxidase and catalase, maximum accumulation of carbohydrates and retaining freshness index and shelf-life of flower by delaying wilting (Jawaharlal et al., 2012). The potential of boric acid in prolonging postharvest life of flowers has also been reported by Mukhopadhyay et al., 1980 and Karuppaiah et al., 2006 in jasmine. Interaction effect was significantly influenced on shelf-life of the flowers in both the season i.e., 201920 and 2020-21. The interaction results shows that, T2B2 (spray of 5 per cent boric acid and packed in 60 micron biodegradable nano silver film) interaction recorded maximum shelf-life of the flower (44.15 hrs) followed by T2B3 i.e., (43.50 hrs) and minimum shelf-life of the flower (33.15 hrs) was recorded in T5B1 interaction (water spray + flowers are packed in 40 micron biodegradable nano silver film) during 2019-20. During 2020-21, the flowers which are treated with 5 per cent boric acid and packed in 60 micron biodegradable nano silver film (T2B2) recorded maximum shelf-life (44.28 hrs) followed by T2B3 (43.55 hrs). Interaction of T5B1 (water spray + flowers are packed in 40 micron biodegradable nano silver film) was recorded with minimum shelflife of the flower (33.23 hrs). Pooled mean shows that, flowers sprayed with 5 per cent boric acid and stored in 60 micron biodegradable nano silver film (T2B2) recorded with highest shelf-life (44.22 ± 0.09 hrs) and lowest shelf-life of the flower (33.19 ± 0.06 hrs) was recorded in T5B1 interaction (water spray and flowers are packed at 40 micron biodegradable nano silver film). REFERENCES Emamifar, A., Kadivar, M., Shahedi, M. and SoleimanianZad, S. 2010. Evaluation of nanocomposite packaging containing Ag and ZnO on shelf-life of fresh orange juice. Innov. Food Sci. Emerg. Technol., 11: 742-748. Isac, X.A. 2015. Blossoming and fragrance testing of jasmine (Jasminum sambac ait.) for fresh flower utility and essential oil extraction, Ph.D. Thesis, Tamil nadu Agric. Uni., Coimbatore. Jawaharlal, M., Thamaraiselvi, S.P. and Ganga, M., 2012, Packaging technology for export of jasmine (Jasminum sambac Ait.) flowers. J. Hortl. Sci., 7(2): 180-189. Boric acid act as anti-oxidant, improving water balance, delayed ethylene production during storage of flowers (Karuppaiah et al. 2006 in jasmine). Similar results were also obtained by Yathindra et al. (2018) in jasmine. Maintenance of Print ISSN : 0974-1712 Karuppaiah, P., Ramesh K.S. and Rajkumar, M. 2006, Effect of different packages on the post-harvest behavior and shelf-life of jasmine (Jasminum sambac). Int. J. Agric. Sci. 2(1): 447-449. 327 Online ISSN : 2230-732X Keerthishankar et al. Krishnamoorthy, S. 1990, Packaging of horticultural crops. Packaging India, pp. 17-20. Mukhopadhyay, T.P., Bose, T.K., Maiti, R.G., Misra, S.K. and Biswas, J. 1980. Effect of chemicals on the post-harvest life of jasmine flowers. National Seminar on Production Technology of commercial Flower Crops, Tamil Nadu Agric. Univ., Coimbatore, pp. 47–50. Madaiah, D. and Reddy, T.V. 1994. Influence of polyethene packaging on the post-harvest life of tuberose cv. Single florets. Karnataka J. Agric. Sci., 7(2): 154-157. Panse, V.S. and Sukhatamane, P.V. 1967. Statistical methods for agricultural workers, ICAR, New Delhi, pp. 152-155. Marttinez-A.A., Lagaron, J.M. and Ocio M.J. 2012, Development and characterization of silver based antimicrobial ethylene- vinyl alcohol copolymer (EVOH) films for food-packaging application. J. Agric. Food Chem., 60: 5350-5359. Tavakoli, H., Rastegar, H., Taherian, M., Samadi, M. and Rostami, H. 2017. The effect of nano-silver packaging in increasing the shelf-life of nuts: An in vitro model. Ital. J. Food. Saf., 6(4): 6874-6885. Maruthamuthuchandran, R., Jawaharla, M., Natarajan, N. and Easwarn, E. 2018. Effect of hexanol and boric acid on shelf-life of jasmine (Jasminum sambac Ait.) cv. Gundi malli. Int. J. Chem. Stud., 6(5): 3069-3071. Yathindra, H.A., Keerthishankar, K., Rajesh. A.M., Harshavardhan, M., Mutthuraju, G.P. and Mangala, K.P. 2018. Packaging technology for extending shelf-life of jasmine (Jasminum sambac cv. Mysuru Mallige) flowers. J. Pharmacognosy and Phytochemi., Sp3: 257-259. Mukhopadhyay, T.P., Bose, T.K., Maiti, R.G., Misra, S.K. and Biswas, J. 1980. Effect of chemicals on the post-harvest life of jasmine flowers. National Seminar on Production Technology of commercial Flower Crops, Tamil Nadu Agric. Univ., Coimbatore, pp. 47–50. Print ISSN : 0974-1712 328 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 329-336, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.7 Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes of Okra under Heavy Clay Soil of Southern Rajasthan Hemraj Meena1, Kavita, A.1, Nirmal Kumar Meena2*, Rajesh Sharma3, Ashok Kumar3 and Rahul Chopra4 Department of Vegetable Science, College of Horticulture and Forestry, Jhalawar, Rajasthan, India Department of Fruit Science, College of Horticulture and Forestry, Jhalawar, Rajasthan, India 3 Department of Basic Science, College of Horticulture and Forestry, Jhalawar, Rajasthan, India 4 Department of Natural Resource Management, College of Horticulture and Forestry, Jhalawar, Rajasthan, India 1 2 *Corresponding author: nirmalchf@gmail.com (ORCID ID: 0000-0003-1528-2664) Paper No. 992 Received: 23-05-2022 Revised: 27-06-2022 Accepted: 02-07-2022 ABSTRACT The present experiment was conducted to find out the effects of organic manures and different dose of inorganic fertilizers on yield and quality of okra cv. Varsha Upkar. The experiment consisted of 21 treatment combinations with four organic manures (control, 15 t FYM. ha-1, 5 t vermicompost. ha-1, 5 t poultry manure. ha-1) and three fertility levels (control, 75% RDF and 100% RDF) in Factorial Randomized Block Design (FRBD) with three replications. The results showed that the application of poultry manure 5t/ha significantly found superior which took minimum days to first flower appearance (38.90), days to 50 percent flowering (44.70), maximum number of fruits per plant, fruit weight (18.28g), yield parameters (385.99 g/plant), chlorophyll content and crude protein. Further, 100% RDF and combined application (100% RDF + poultry manure 5 t/ha) were also exhibited better results of flowering, yield and biochemical parameters. HIGHLIGHTS mm Poultry manure is a good source of organic manure for okra plant growth and yield. mm Application of poultry manure significantly enhanced the number of flowers and fruits per plant. mm Poultry manure found suitable in enhancing the yield of okra. mm Biochemical traits of okra fruits such as chlorophyll and protein also influenced by the application of poultry manure. Keywords: Okra, poultry manure, inorganic, chlorophyll, crude protein Vegetables are the protective food and consumed worldwide due to their numerous health benefits. Okra (Abelmoscus esculentus L.) is an important vegetable, belongs to the family Malvaceae and grown in tropical and subtropical tracts globally as well as in India (Akanbi 2002). This is cultivated for its edible green seed pod. Okra is a good source of vitamins, calcium, potassium, and other minerals. It has been reported that okra contains good amount of potassium, sodium, calcium, iron zinc and other elements (Adekia et al. 2019). Due to its high iodine content, consumption of okra is good for the control of goiter. In India, okra is cultivated over an area of 5.11 lakh ha area with production of 62.1 lakh MT (NHB, 2018-19). In Rajasthan, it is grown extensively How to cite this article: Meena, H., Kavita, A., Meena, N.K., Sharma, R., Kumar, A. and Chopra, R. (2022). Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes of Okra under Heavy Clay Soil of Southern Rajasthan. Int. J. Ag. Env. Biotech., 15(Special Issue): 329-336. Source of Support: None; Conflict of Interest: None Meena et al. in the district of Sirohi, Bundi, Jodhpur, Sikar, Jhalawar, Nagaur, Bharatpur and Jhunjhunu and covers around 5.71 thousand hectares area with annual production of 49.68 thousand metric tonnes. Horticulture & Forestry, Jhalrapatan city, Jhalawar during kharif season, 2019-20. The present experiment was conducted on okra crop cv. Varsha Uphar. Treatments Details Despite of popularity among stakeholders, okra produces fewer yields under soil condition of Southern Rajasthan. Being highly black cotton and heavy soil, the productivity of okra is very less. The soil of southern humid parts of Rajasthan contains high soil pH (8.0 to 9.5) and low organic matter content. Soil organic matter is a crucial factor in soil for sustainable crop production (Agboola 1990). Improper use of chemical fertilizers declined the soil fertility and leached out the nutrients from the soil. Besides, continuous use of inorganic fertilizers also changed the physical and chemical status of soil thus resulting in reducing fertility level and poor crop production. Use of organic manures, poultry manures, vermicompost and farm yard manure enriches organic matter content subsequently enhances yield and quality attributes in various vegetables (Sameera et al. 1995). Poultry manure is an excellent organic fertilizer, is concentrated source of nitrogen and other essential nutrients. It has direct effect on plant growth. It is well documented that it is an excellent source of fertilizer and increased nutrient uptake (Abusaleha 1992). In addition to that, organic manures also positively improve the health of soil as well as ecosystem. The use of chemical fertilizers in an integrated manner with organic manures could enhance the yield and productivity of crops with minimum disturbance of soil. In the climate changing scenario, the judicious use of chemical fertilizers with organic manures is need of the hour for sustainable crop production (Chowdhury et al. 2014). Among the nutrient N, P and K are the essential nutrients which are needed for growth, flowering and fruiting (Solangi et al. 2005). However, these studies are insufficient to validate the existing findings under humid zone of Southern Rajasthan. This study was investigated to find out the impact of various organic manures and fertility level on Okra yield and biochemical attributes under heavy clay soil. The treatments manures viz. FYM, Poultry manures and vermicompost were applied in the soil before sowing of seeds. The inorganic manures N:P:K in the various levels viz. control, 75% RDF and 100% RDF were applied through urea, di-ammonium phosphate (DAP) and murate of potash (MOP) respectively. The recommended dose of NPK for okra crop was 60:32:30 kg ha-1, respectively. For each fertilizer treatment combination, the NPK dose were calculated and applied timely. Full dose of phosphorus and potassium and half dose of nitrogen are applied as basal dose just before sowing and rest half dose of nitrogen was applied in two splits i.e. 30 and 45 days after sowing. The details of treatments combinations are given underneath:Treatment Treatment Combination Notation 1 O0 Control I2 100% RDF O2 FYM 15 tons/ha O4 Vermicompost 5 tons/ha O6 Poultry manure 5 tons/ha I1O2 75% NPK + FYM 15 tons/ha I1O4 75% NPK + Vermicompost 5 tons/ha I1O6 75% NPK + Poultry manure 5 tons/ha I2O2 100% NPK + FYM 15 tons/ha I2O4 100% NPK + Vermicompost 5 tons/ha I2O6 100% NPK + Poultry manure 5 tons/ha 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 MATERIALS AND METHODS I1 75% RDF O1 FYM 7.5 tons/ha O3 Vermicompost 2.5 tons/ha O5 Poultry manure 2.5 tons/ha I1 O1 75% NPK + FYM 7.5 tons/ha I1O3 75% NPK + Vermicompost 2.5 tons/ha I1O5 75% NPK + Poultry manure 2.5 tons/ha I2O1 100% NPK + FYM 7.5 tons/ha I2O3 100% NPK + Vermicompost 2.5 tons/ha I2O5 100% NPK + Poultry manure 2.5 tons/ha The number of days taken for plants to first flowering in each plot and replication was recorded and expressed in days. The number of days taken for 50 per cent of flowering in each plot was Location The present experiment was conducted at farm of Department of Vegetable Science, College of Print ISSN : 0974-1712 Sl. No. 330 Online ISSN : 2230-732X Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes... recorded and expressed in days. The number of fruit of five tagged plants was counted and the average was worked out. Fruit weight was calculated by weighing with electronic weighing machine. The estimated yield per plant was calculated by multiplying fruit weight with total number in a individual plant. The days taken for 50 per cent flowering exhibited highly significant variation over control with application of organic and inorganic manures. The application of organic manures significantly affected the days taken to 50 percent flowering over control. Minimum days taken for 50 per cent flowering was recorded in O6 (44.70) and it was found statistically at par with treatment O5 (46.06), O3 (46.64), O4 (46.81), and O2 (47.04), whereas maximum days taken for 50 per cent flowering was recorded in control with 50.69. Further, the application of inorganic fertilizer exhibited significant result over control. Minimum days were taken for 50 per cent flowering was recorded in I 2 (100% RDF) with 45.13 and maximum in control with 49.24. The combination of organic and inorganic fertilizers also exhibited significant variation over control. The treatment O6I2 (100% RDF + PM@ 5 ton) showed minimum days to 50% flowering over control i.e., 39.97 and 57.00, respectively. Days to first flower appearance is also an important trait which determines its flowering and earliness. Addition of poultry manure makes reproductive booster nutrients and helps them to restore thus the early flowering and 50% flowering was observed in the treatment. Our research findings are in agreement with previous studies by (El-shakweer et al. 1998; Sanwal et al. 2007). Chlorophyll and Crude Protein Content Chlorophyll content in leaves was measured as per method suggested by Sadasivam and Manickam (1997) and expressed in mg/100g. The amount of protein in okra fruit was calculated in per cent. The formula used for calculating the protein is as under: Protein % = Nitrogen% × 6.25 This is based on the assumption that plant protein contains 16 per cent nitrogen. Estimation of nitrogen was done by colorimetric method as suggested by Snell and Snell (1949) using the Spectronic-20 (Model SL-177). Statistical Analysis The experimental data are to be recorded during the course of investigation for various characters under study with appropriate statistical analysis (Panse & Sukhatme 1985) along with suitable interpretation. Fruit Yield and Quality Parameters The result presented reflects that fruit weight showed significant variation (Table 2). The application of organic manures increased significantly the fruit weight over control. Maximum fruit weight was recorded in O6 (18.28), and it was found statistically at par with O4 i.e., 18.02 whereas minimum fruit weight was found in control (13.79). Similarly, the application of inorganic manures also increased the fruit weight significantly over control. Maximum fruit weight was recorded in I2 (100% RDF) with 20.11 g and minimum in control with 12.44 g. The interaction effect of organic and inorganic manures also showed significant effect on fruit weight over control. Maximum fruit weight 21.61 g was recorded in treatment O4I2 (100% RDF + VC 5 ton) over control with 9.14 g. A perusal of data regarding to fruit yield per plant presented and revealed that fruit yield per plant was significantly affected by the application of different organic RESULTS AND DISCUSSION Days Taken to Flower Appearance The data recorded for days to first flower appearance was influenced by application of organic and inorganic manures over control, which showed significant variation over control (Table 1). Minimum days to first flower (38.90) were recorded in treatment O6, whereas maximum was recorded in control (44.53). Similarly, the application of inorganic manures with treatment I2 (100% RDF) took minimum days to first flower appearance with 40.70 over control with 43.29. Further, the application of organic manures with inorganic manures minimized the number of days to first flower appearance over control. Minimum days to first flower appearance was recorded in treatment O 6I 2 (100% RDF + PM@ 5 ton) with 34.87 and maximum in control (47). Print ISSN : 0974-1712 331 Online ISSN : 2230-732X Meena et al. manures and fertility levels. The application of organic manures significantly increased the fruit yield per plant over control. Maximum fruit yield per plant was recorded in O6 (385.99), and it was found statistically at par with O4 (381.57) and O5 (361.90), whereas minimum fruit yield per plant was found in control (277.06). Further, inorganic manures also played an important role in increasing the fruit yield per plant. Maximum fruit yield per plant was recorded in I2 (100% RDF) i.e., 430.99g and minimum in control i.e., 243.75g. Results with respect to interactive effect of organic and inorganic showed that maximum fruit yield per plant (462.33g) was recorded in treatment O6I2 (100% RDF + PM 5 ton) and it was found statistically at par with treatment O4I2, O2I2, O5I2 and O3I2 while minimum was recorded in control (173.34 g). The result of present study has with respect to estimated fruit yield has been presented which reflects that fruit yield q/ha showed significant variation. The increased yield and yield attributes with poultry manure might be because of rapid availability and utilization of nitrogen for various internal plant processes for carbohydrates production. Later on these carbohydrates undergo hydrolysis and get converted in to reproductive sugars which ultimately helped in increasing yield. Singh and Srivastava (1970) reported that high carbohydrates content due to application of poultry manure might be attributed to balanced C:N ratio and increased activity of plant metabolisms. These results are in accordance with the findings of Naidu et al. (2002) and Islam et al. (2012). The increased balanced C: N ratio might have increased the synthesis of carbohydrates with ultimate improvement in yield and yield attributes Chander et al. (2005), Kondappa et al. (2009), Sharma et al. (2009) and Yadav and Yadav (2010). The application of 100 per cent RDF resulted in the highest and significantly more values of yield and yield attributes. These findings are similar of those Garhwal et al. (2007), Vennila and Jayanthi (2008a), Sharma et al. (2009) in okra crop. The reason for enhancement in yield attributes could again be ascribed to the role which might have been played by the nutrients supplied to the plants. The quality yield depends on several management factors such as fertilizers and nutrient management, water, light, etc. but the role of fertilizers and nutrients is crucial and important in determining the fruit quality as well as yield. It is relevant to mention Print ISSN : 0974-1712 here that adequate supply of nitrogen to plants not only promotes the manufacture of food but also its subsequent partitioning in skin. Similarly, phosphorus play a unique role in laying down the floral primordial. Potassium facilitates translocation of photosynthates towards various organs of plant body (Marschner 1995). The application of NPK favoured the metabolic and auxin activities in plant and ultimately resulted in increased fruit size, number of fruits per plant and yield per plant (Garhwal et al. 2007). Biochemical Parameters A critical examination of the data pertaining to chlorophyll content in leaves has been presented in table. Chlorophyll content in leaves was significantly affected by application of different organic manures. The treatment O6 (PM 5 ton) was recorded significantly higher chlorophyll content (0.82 mg g-1) in leaves and it was found statistically at par with treatment O4 (0.79), whereas lower chlorophyll found in control (0.66 mg/100 g). Further, application of inorganic manures also showed significant effect over control on chlorophyll content in leaves. The treatment I2 (100% RDF) resulted in significantly higher chlorophyll content (0.92 mg g -1) in leaves and lower in control I0 with (0.60 mg g-1). However, the interactive effect of organic and inorganic manures also recorded significant effect on chlorophyll content in leaves over control. Maximum chlorophyll (1.05 mg g-1) was found in O6I2 (100% RDF + PM 5 ton) and minimum in control O6I0 (0.52 mg g-1) respectively but O4I2 was found statistically at par with O6I2. Leaf chlorophyll content is major parameter which imparts greenness to the leaf as well as also acts as reservoir of pigment for pod development. Plant chlorophyll is directly correlated with nutrient assimilation and better photosynthesis process. The organic manures enhance the vegetative flushes, which favors more photosynthesis along with some important micro and macro nutrient such as iron and Mg. The interactions of these minerals is a complex phenomenon but directly indirectly involved in photosynthetic processes (Senjobi et al. 2010). It is evident from data in Table that crude protein exhibited significant variation over control with application of organic and inorganic manures. 332 Online ISSN : 2230-732X Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes... Table 1: Effect of organic manure and inorganic fertilizer level on days to first flower appearance of okra cv. Varsha Uphar Treatments I0 (Control) I1 (75% RDF) I2 (100% RDF) Mean I O I×O O0 (Control) 47.00 44.00 42.60 44.53 SE m ± 0.43 0.66 1.15 O1 FYM 7.5 Tons/ha 45.60 42.47 42.83 43.63 O2 FYM O3 VC 15 Tons/ha 40.67 44.27 42.10 42.34 2.5 Tons/ha 42.97 41.50 40.83 41.77 O4 VC 5 Tons/ha 44.47 41.47 41.37 42.43 O5 PM 2.5 Tons/ha 41.87 41.73 40.33 41.31 C.D. (p=0.05) 1.25 1.91 3.30 O6 PM 5 Tons/ha 40.47 41.37 34.87 38.90 Mean 43.29 42.40 40.70 42.13 Data represents the mean value of Factor I (organic manure) and Factor-II (Inorganic RDF) and their interactions. (FYM-Farm Yard Manure; VC-Vermicompost; PM-Poultry Manure). Table 2: Effect of organic manure and inorganic fertilizer level on days to 50 per cent flowering of okra cv. Varsha Uphar Treatments I0 (Control) I1 (75% RDF) I2 (100% RDF) Mean I O I×O O0 (Control) 57.00 48.10 46.97 50.69 SEm ± 0.54 0.83 1.43 O1 FYM 7.5 Tons/ha 51.17 48.20 46.70 48.69 O2 FYM 15 Tons/ha 46.30 49.47 45.37 47.04 O3 VC 2.5 Tons/ha 47.80 45.87 46.27 46.64 O4 VC 5 Tons/ha 49.77 45.73 44.93 46.81 O5 PM O6 PM 2.5 Tons/ha 46.87 45.57 45.73 46.06 C.D. (p=0.05) 1.55 2.37 4.10 5 Tons/ha 45.77 48.37 39.97 44.70 Mean 49.24 47.33 45.13 47.23 Data represents the mean value of Factor I (organic manure) and Factor-II (Inorganic RDF) and their interactions. (FYM-Farm Yard Manure; VC-Vermicompost; PM-Poultry Manure. Table 3: Effect of organic manure and inorganic fertilizer level on fruits weight (g) of okra cv. Varsha Uphar Treatments O0 O1 FYM 7.5 Tons/ha 11.64 14.71 19.73 15.36 O2 FYM 15 Tons/ha 14.58 17.38 20.30 17.42 O3 VC 2.5 Tons/ha 11.67 20.37 19.64 17.23 O4 VC 5 Tons/ha 12.66 19.79 21.61 18.02 O5 PM I0 (Control) I1 (75% RDF) I2 (100% RDF) Mean (Control) 9.14 12.65 19.59 13.79 SEm ± 2.5 Tons/ha 12.76 19.63 19.53 17.31 C.D. (p=0.05) I 0.15 0.43 O 0.23 0.66 I×O 0.40 1.15 O6 PM 5 Tons/ha 14.60 19.86 20.38 18.28 Mean 12.44 17.77 20.11 16.77 Data represents the mean value of Factor I (organic manure) and Factor-II (Inorganic RDF) and their interactions. (FYM-Farm Yard Manure; VC-Vermicompost; PM-Poultry Manure. Maximum crude protein was recorded in O6 (2.21), whereas minimum crude protein was found in control (1.68). Further, maximum crude protein was recorded in 100% RDF with 2.46. Results with respect to interactive effect of organic and inorganic showed that maximum crude protein (2.74) was recorded in treatment 100% RDF + PM 5 ton and it was found statistically at par with treatment 100% Print ISSN : 0974-1712 RDF + VC 5 ton, 100% RDF + FYM 15 ton, 100% RDF + PM 2.5 ton. The protein content is composed of several amino acids which are influenced with field management, nutrients, and environmental factors. The composition of protein also helps in judging the quality produce and this is one of the important index for quality trait among biochemical parameters. The soil application of organic manures 333 Online ISSN : 2230-732X Meena et al. Table 4: Effect of organic manure and inorganic fertilizer level on fruits yield per plant (g) of okra cv. Varsha Uphar Treatments I0 (Control) I1 (75% RDF) I2 (100% RDF) Mean I O I×O O0 (Control) 173.34 250.72 407.11 277.06 SEm ± 6.44 9.85 17.06 O1 FYM 7.5 Tons/ha 225.05 296.92 412.87 311.61 O2 FYM 15 Tons/ha 250.83 353.87 431.01 345.24 O3 VC 2.5 Tons/ha 227.17 404.46 421.25 350.96 O4 VC 5 Tons/ha 285.02 403.85 455.85 381.57 O5 PM 2.5 Tons/ha 253.36 405.82 426.52 361.90 C.D. (p=0.05) 18.43 28.15 48.77 O6 PM 5 Tons/ha 291.46 404.19 462.33 385.99 Mean 243.75 359.97 430.99 344.90 Data represents the mean value of Factor I (organic manure) and Factor-II (Inorganic RDF) and their interactions. (FYM-Farm Yard Manure; VC-Vermicompost; PM-Poultry Manure. Table 5: Effect of organic manure and inorganic fertilizer level on chlorophyll content in leaves (mg/100g) of okra cv. Varsha Uphar Treatments I0 (Control) I1 (75% RDF) I2 (100% RDF) Mean I O I×O O0 (Control) 0.52 0.64 0.82 0.66 SEm ± 0.008 0.01 0.02 O1 FYM 7.5 Tons/ha 0.54 0.69 0.85 0.69 O2 FYM 15 Tons/ha 0.59 0.71 0.94 0.75 O3 VC 2.5 Tons/ha 0.57 0.77 0.88 0.74 O4 VC 5 Tons/ha 0.65 0.73 1.00 0.79 O5 PM 2.5 Tons/ha 0.61 0.79 0.91 0.77 C.D. (p=0.05) 0.021 0.03 0.05 O6 PM 5 Tons/ha 0.67 0.75 1.05 0.82 Mean 0.60 0.73 0.92 0.75 Data represents the mean value of Factor I (organic manure) and Factor-II (Inorganic RDF) and their interactions. (FYM-Farm Yard Manure; VC-Vermicompost; PM-Poultry Manure. Table 6: Effect of organic manure and inorganic fertilizer level on crude protein content (%) of okra cv. Varsha Uphar O0 O1 FYM O2 FYM O3 VC O4 VC O5 PM O6 PM I0 (Control) I2 (100% RDF) Treatments (Control) 7.5 Tons/ha 15 Tons/ha 2.5 Tons/ha 5 Tons/ha 2.5 Tons/ha 5 Tons/ha Mean 1.33 1.34 1.36 1.45 1.54 1.63 1.65 1.47 I1 (75% RDF) 1.71 1.75 1.78 1.82 1.87 1.93 2.25 1.87 1.99 2.12 2.71 2.34 2.72 2.61 2.74 2.46 Mean 1.68 1.74 1.95 1.87 2.05 2.06 2.21 1.94 SEm ± C.D. (p=0.05) I 0.01 0.05 O 0.02 0.08 I×O 0.05 0.14 enhances root microbial activity and nutrient assimilation along with cation exchange capacity. The mineralogy of soil alters the plant physiology and its catabolic and anabolic reactions. Certain enzymes helps I synthesis of amino acids due to higher assimilate and a strong source sink relationship. The highest value of crude protein in okra pod in our study, might be due to positive Print ISSN : 0974-1712 impact of poultry manure in soil as well as in plants which favours the more synthesis of amino acids thus increased protein content. Soremi et al. (2017) reported that poultry manure change the soil fertility status that resulted in whole biochemical composition of soil as well plants. This also releases organic acids and increase organic content into the soil which retain the loss of various nutrients. 334 Online ISSN : 2230-732X Organic Manure and Fertility Level Affects the Flowering, Yield and Quality Attributes... Our results are in agreement of previous studies by Trupiano et al. (2017) and Imasuen and Aisien (2015). The significant influence of NPK fertilization on N, P, K and protein content in fruits appeared to be due to improved nutrient both in the root zone and the plants system because nutrient in the plant directly related to its availability in the feeding zone and the growth of the plant. The protein content in fruits is infact a manifestation of nitrogen content. The increase in nitrogen content in fruits resulted in higher protein content in fruits. These results are in close conformity with findings of Yadav (2001), Maheswari and Haripriya (2007) and Premshekhar and Rajashree (2009). The higher content in fruits seems to be higher functional activity of roots for longer duration under the treatment. The increase in N, P and K content in fruit due to adequate fertilization have also been observed by Nanthakumar and Veeragavathatham (2003) and Selvi et al. (2004). The accumulation of higher protein content in the fruits might be correlated with the increased activity of nitrate reductase which helped in synthesis of certain amino acids and proteins. These results are also corroborated by the findings of Yadav et al. (2006) and Garhwal et al. (2007) in okra crop. Integrated nitrogen management in okra (Abelmoschus esculentus (L.) Moench) hybrids. Haryana J. Horti. Sci., 36(1&2): 129-130. Imasuen, A.A. and Aisien, M.S.O. 2015. Helminth parasites of Silurana tropicalis from the Okomu National Park, Edo State, Nigeria. Nigerian J. 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Effect of integrated nutriet management on yield and quality attributes of brinjal (Solanum melongena L.) cv. Palur-1. South Indian Horti., 49(special): 195-198. CONCLUSION Premsekhar, M. and Rajashree, V. 2009. Influence of organic manures on growth, yield and quality of okra. American – Eurasian J. Sustainable Agric., 3(1): 6-8. In conclusion it was observed that the treatment O6 5 t poultry manure/ha most suited to okra crop cv. Varsha Uphar which enhanced the flowering parameters and yield. The combination of poultry manure and 100% RDF and solely 100% RDF found best for overall yield and quality under hard clay soil. However, further investigation need to elucidate the mechanism and mineralogy under such soil conditions. Sameera, D.L., Shankaraiah, V. and Srihari, D. 2005. Effect of packaging and storage on organic manures grown okra (Abelmoschus esculentus L. Moench). J. Res. ANGRAU, 33(4): 30- 35. Selvi, D., Thiageshwari, S., Santhy, P. and Kannan, B.R. 2004. Fruit yield and nutrient uptake by brinjal due to integrated nutrient management in an inceptisol. J. Maharashtra Agric. Univ., 29(2): 220-223. Senjobi, B.A., Peluola, C.O. Senjobi, C.T., Lawal, I. O., Ande, O.T. and Salami, B.T. 2010. Performance of Cochorus olitorius as influenced by soil type and organic manure amendments in Yewa North Local Government Area, Ogun State. African J. Biotechnol., 9(33): 5309-5312 REFERENCES Chander, G., Naveen, D. and Sharma, R.P. 2005. Effect of vermicompost, farm yard manure and chemical fertilizers on yield, nutrient uptake and soil fertility in Okra (Abelmoschus esculentus) onion (Allium cepa) Sequence in wet Temperate Zone of Himachal Pradesh. J. Indian Soc. Soil Sci., 57(3): 357-361. Sharma, R.P., Datt, N. and Chander, G. 2009. Effect of vermicompost, FYM and chemical fertilizers on yield, nutrient uptake and soil fertility in okra [Abelmoschus esculentus (L.) Moench] – onion (Allium cepa) sequence in wet temperate zone of Himachal Pradesh. J. Indian Society of Soil Sci., 57(3): 357-361. El- Shakweer, M.H.A., El-Sayed, E.A. and Ewees, M.S.A. 1998. Soil and plant analysis as a guide for interpretation of the improvement deficiency of organic conditioners added to different soil in Egypt. Communication Soil Sci. Plant Anal., 29: 206-208. Singh, K. and Srivastava, O.P. 1970. Effect of organic manure on soil fertility as showed by nutrition availability and yield response in potato. Proc. Int. Sympt. Soil Fert. Eval., New Delhi, 1: 815-820. Garhwal, O.P., Fageria, M.S. and Mukherjee, S. 2007. Print ISSN : 0974-1712 335 Online ISSN : 2230-732X Meena et al. Singh, V. and Pandey, M. 2006. Effect of integrated nutrient management on yield of and nutrient uptake by onion and on soil fertility. J. Indian Soc. Soil Sci., 54(3): 365-367. Yadav, O.S. 2001. Effect of nitrogen sources and bio-fertilizers on growth, yield and quality of cow pea (Vigna unguiculata (L.) Walp). M.Sc. (Ag.) Thesis, Rajasthan Agricultural University, Bikaner. Trupiano, D., Cocozza, C., Baronti, S., Amendola, C., Vaccari, F.P., Lustrato, G. and Scippa, G.S. 2017. The effects of biochar and its combination with compost on lettuce (Lactuca sativa L.) growth, soil properties, and soil microbial activity and abundance. Int. J. Agron. Yadav, P., Singh, P. and Yadav, R.L. 2006. Effect of organic manures and nitrogen levels on growth, yield and quality of okra. Indian J. Hortic., 63(2): 215-217. Vennila, C. and Jayanthi, C. 2008. Effect of integrated nutrient management on yield and quality of okra. Res. Crops., 9(1): 73-75. Print ISSN : 0974-1712 336 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 337-345, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.8 Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature M.N. Dabhi1*, P.R. Davara1, H.P. Gajera2, Nirav Joshi1 and Parth Saparia1 AICRP on Post-Harvest Engineering and Technology, Processing and Food Engineering Department, College of Agricultural Engineering and Technology, Gujarat, India 2 Department of Biotechnology, Junagadh Agricultural University, Junagadh, Gujarat, India 1 *Corresponding author: mndabhi@jau.in (ORCID ID: 0000-0002-0062-5970) Paper No. 993 Received: 21-05-2022 Revised: 23-06-2022 Accepted: 06-07-2022 ABSTRACT The turmeric used as a ground powder. Turmeric grinding is carried out in grinding mill. During grinding operation the temperature inside the grinding mill increases. The bioactive compounds along with their biological activity and stability depends on the grinding temperature. High temperature during grinding reduced the bioactive compounds along with their biological activity and stability. Four grinding methods and two feed temperature were chosen on the hypothesised mechanisms of reduction in temperature during the grinding. The effects of grinding temperature and feed temperature on the phenolic content, flavonoid content, antioxidant activity and curcumin content of turmeric ground powder were studied. Antioxidant activity, flavonoid content, curcumin content and phenolic content increased with decrease in grinding temperature. The temperature inside the grinding chamber at the end of grinding of 3 kg sample of turmeric reached to 43 °C for traditional grinding, and this was reduced to 18.33 ⁰C for coolant circulation with low temperature feed. This reduction in grinding temperature resulted in the highest phenol content (3.13%), flavonoid content (1.43%), and antioxidant activity (59.31%) for coolant circulation with low feed temperature. Chilled water circulation with low temperature feed resulted the highest curcumin content (2.48%). This bioactive compound were significantly differed with grinding method as well as feed temperature. HIGHLIGHTS mm The article focuses on the effect of both moisture content and variety on the physical properties of psyllium seeds mm The moisture content and variety both had a significant effect on the physical properties of psyllium seeds mm The size, thousand seed weight, angle of repose, coefficient of static friction and terminal velocity were increased while bulk density, true density and porosity were decreased as the moisture content was increased Keywords: Turmeric powder, low temperature grinding, curcumin, flavonoid, phenolic, antioxidant activity The origin of genus Curcuma from the Zingiberaceae family lies in the Indo-Malayan Region spreading in the tropics of Asia to Africa and Australia (Pusglove 1968). Turmeric powder, generally used as a spice, food preservative, colouring agent, is obtained by grinding turmeric rhizome of Curcuma longa L. Turmeric compounds possess anti-inflammatory, anti-HIV, antibacterial, antioxidant, anti-diabetes, and anti-carcinogenic activities (Park Chang Yang, Kyo-Yeon Lee, Khalid Gul, M. Shafiur Rahman, How to cite this article: Dabhi, M.N., Davara, P.R., Gajera, H.P., Joshi, N. and Saparia, P. (2022). Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature. Int. J. Ag. Env. Biotech., 15(Special Issue): 337-345. Source of Support: None; Conflict of Interest: None Dabhi et al. Ah-Na Kim, Jiyeon Chun, Hyun-Jin Kim & SungGil Choi 2019). The important active compounds of turmeric are curcumin which may be in the form of dihydrocurcumin, demethoxycurcumin, and bisdemethoxycurcumin which are important for most of the turmeric’s beneficial effects (Prathapan, Lukhman, Arumughan, Sundaresan, & Raghu 2009). Curcumin has property of antiinflammatory activity. Curcumin is an effective inhibitor for reactive oxygen-generating enzymes like lipoxygenase/cyclooxygenase, xanthine dehydrogenase/oxidase, and inducible nitric oxide synthase (Lin, Pan & Lin-Shiau 2000). Metabolism activity of Curcumin reduces it through an NADPH dependent curcumin reductase consequential in a dihydrocurcumin. Dihydrocurcumin again reduces through an NADPH-dependent dihydrocurcumin reductase bring about in a tetrahydrocurcumin (THC) (Aggarwal, Deb, and Prasad, 2015, Khopde, Priyadarsini, Guha, Satav, Venkatesan, P., & Rao 2000). 1963), depending on the oil and moisture content, consequently, it loses a substantial portion of its volatile oil. The fat in spices poses extra problems and is an important consideration in grinding. By circulating water or air around the mill, temperature reduction can possible, but it is not that effective. Though cryogenic grinding is very costly. Low temperature grinding techniques can also be easily available for small mills than cryogenic grinding. It was also found that the colour and other properties of the low temperature grind material were not changed, and the flavour and nutrients of the medicines were not lost. From the statements above, there seems enough justification for low temperature grinding of turmeric to obtain a high quality product. Theoretically, though low temperature grinding of turmeric is better than ambient grinding, the available literature is scanty to support the above justification. Hence, in the present study, efforts were made to develop low temperature grinding technique for turmeric. Ancillary metabolites of plant metabolism, phenolic compounds can chelate metallic ions, scavenge free radicals during oxidative stress, and increase antimicrobial activities (Pereira et al. 2009). Bioactive compounds frequently store in the plant in lesser quantities and sometimes in specific cells (Finley 2005). In the middle of them certainly are recognized as phenolic, flavonoids, and essential oils, which have a wide range of biological activities such as antioxidant, anti-inflammatory, anti-aging, antibacterial, anti-tumor, and other functions (Karimi, Jaafar, & Ahmad, 2013; Oskoueian, Abdullah, Hendra & Karimi, 2011). MATERIALS AND METHODS Grinding methods Dried turmeric rhizome of Salem variety was purchased from local market. Turmeric powder was prepared by different grinding methods viz. L0 = Ambient grinding, L1 = Grinding with ambient temperature water circulation through jacket, L2= Grinding with chilled water circulation and L3= Grinding with coolant circulation. The temperature inside the grinding chamber at the end of grinding were noted. The powder were collected. Ground powder of turmeric rhizome obtained by various treatments through low temperature grinding mill was packed carefully, stored to room temperature at dark, dry and hygienic place and opened at the time of analysis only. Self-sealing zip lock transparent plastic bags were used for packing after cooling the powder to room temperature. Care was taken not to allow air inside. Additional wrapping of ordinary transparent plastic cover was also followed. Consumer demand for healthier products having less synthetic additives is motivating for research to discover substitute sources of natural antioxidants. Natural antioxidants like phenolic and flavonoid compounds are available in plants and they are appealing a great deal of responsiveness due to amassed confirmation suggesting that they may inhibit chronic conditions, such as cancer, atherosclerosis, and neurological diseases (Marinova, D., Ribarova, F. & Atanassova, M. 2005). Biochemical parameters of turmeric powder obtained through different treatments were determined by using standard protocols. All the samples with triplicates were analysed at a time for determination of a particular parameter. In the traditional grinding of spices, frictional heat is generated in the grinder. The grinding process increases the product temperature to a high level in the range of 42-95°C (Pruthi and Mishra Print ISSN : 0974-1712 338 Online ISSN : 2230-732X Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature Preparation of low temperature feed Total flavonoid content Pre-weighted turmeric rhizome were packed in self-sealing zip lock transparent plastic bags. Additionally, packing was wrapped by an ordinary transparent plastic cover. Packed rhizomes were kept in freezer at -10° ± 2° overnight, the day before grinding. Besides that, feed was withdrawn from the freezer at the time of grinding only and once withdrawn, placed at feed hopper immediately. Each packet of the rhizome involved half the amount of decided sample size, which allowed one half of the sample to be in the freezer instead of the feed hopper while grinding. Care was taken to feed the other half well before completion of the first half size of sample in the feed hopper. Aluminium chloride colorimetric method was used to determine total flavonoid content of turmeric powder, as given by Chang et al. (2002). Quercetin was used for preparation of calibration curve. Different diluted quercetin standard solutions (10, 25, 50 and 100 µg/ml) were prepared in 80% ethanol. The sample was also extracted in ethanol. From each tube, 0.5 ml aliquot was pipetted out in separate test tubes. Then 1.5 ml of 95% ethanol followed by 0.1 ml of 10% aluminium chloride and 0.1 ml of 1 M potassium acetate was added to each tube. Total volume in each tube was made up to 5 ml by adding 2.8 ml distilled water. For preparation of blank solution, aluminium chloride solution was substituted by the same amount of distilled water. After incubation at room temperature for 30 minutes, absorbance was measured at 415 nm by UV-Visible spectrophotometer (Thermo Scientific, GENESYS 50). The quantity of flavonoid was then expressed in mg equivalent of quercetin by using the following equation. Total phenol content The phenol content of the turmeric powder was estimated as per the method given by Malick and Singh (1980). 0.1 g of turmeric powder (weighed to the nearest 0.0001 g) was extracted in 10 ml of 80% ethanol. Centrifugation was done and, the supernatant was collected. Then 0.1 ml of aliquot was pipetted out into a test tube and was evaporated to dryness. After drying, the residue was dissolved in 1 ml of distilled water. Then 0.2, 0.4, 0.6, 0.8, and 1 ml of working standard into a series of test tubes was pipetted out and the total volume of each was made up to 1 ml using distilled water. 1 ml of distilled water in a test tube was set for a blank solution. 0.5 ml of Folin-Ciocalteau reagent was then added to each tube including blank. After three minutes, 2 ml of 20% Na2CO3 solution was added to each. The solution was mixed thoroughly and was placed in a boiling water bath for exactly one minute. After cooling to room temperature, colour was read at 650 nm using a UV-Visible spectrophotometer (Thermo Scientific, GENESYS 50). At last, the percentage of total phenol was calculated by preparing a standard curve of catechol. The following formula was used. Total flavonoid (%) = V = Volume of sample extract (ml) W = Weight of sample extracted (mg) Antioxidant activity The aluminium chloride colorimetric method was used to determine the total flavonoid content of turmeric powder, as given by Chang et al. (2002). Quercetin was used for the preparation of the calibration curve. Different diluted quercetin standard solutions (10, 25, 50, and 100 µg/ml) were prepared in 80% ethanol. The sample was also extracted in ethanol. From each tube, 0.5 ml aliquot was pipetted out in separate test tubes. Then 1.5 ml of 95% ethanol followed by 0.1 ml of 10% aluminium chloride and 0.1 ml of 1 M potassium acetate was added to each tube. The total volume in each tube was made up to 5 ml by adding 2.8 ml distilled water. For the preparation of the blank solution, aluminium chloride solution was substituted with the same amount of distilled water. After incubation at room temperature for 30 …(1) Where, GF = Graph factor OD = Optical density Print ISSN : 0974-1712 …(2) Where, C = Concentration of sample extrapolated from calibration curve (mg/ml) Total phenol (%) = GF × OD × Total volume (ml) × 10 –6 Sample aliquot (ml) × Sample Weight (g) C ×V × 100 W 339 Online ISSN : 2230-732X Dabhi et al. minutes, absorbance was measured at 415 nm by a UV-Visible spectrophotometer (Thermo Scientific, GENESYS 50). The quantity of flavonoid was then expressed in mg equivalent of quercetin by using the following equation: temperature inside the grinding chamber will rise. It is necessary to reduce the grinding temperature. In this different treatment, grinding method affects significantly on the value of temperature inside the grinding chamber at the end of grinding. The highest temperature (41.17°) was found for the grinding treatment L 0. Significantly, the lowest temperature (19.17°) was found for the grinding treatment L3. The effect of feed temperature (p<0.05) on the same parameter was also found significant (Table 1). The significant highest value found was 35.75° for ambient temperature feed (T 0). The value in case of low temperature feed (T1) was significantly lowest, i.e. 34.08°. In addition to that, the interaction effect of grinding method and feed temperature (L*T) on the value of temperature inside the grinding chamber at the end of grinding was found non-significant. DPPH scavenging effect (%) = A control – A test × 100 A control …(3) Curcumin content The curcumin content of the turmeric powder was estimated as per the method given by Geethanjali et al. (2016). 1 g of the turmeric powder was accurately weighed and transferred into 500 ml round bottle flask. 75 ml acetone was added up to the mark. It was refluxed for 1.5 hour, after which it was filtered and made up to 200 ml with acetone. From this further 1ml was taken and made up to 100ml adding acetone in a standard flask. The UV spectral reading for this solution was recorded under 420 nm using UV-Visible spectrophotometer (Thermo Scientific, GENESYS 50). A UV spectrum for standard curcumin was recorded. The obtained absorption value of turmeric powder samples was compared with the standard value of curcumin. The percentage curcumin in samples was calculated using the formula: Curcumin (%) = Ds × As × 100 100 × Ws × 1650 Table 1: Effect of grinding method temperature inside grinding chamber at the end of grinding Grinding method (L) …(4) Ambient temperature grinding (L0) 41.17 Chilled water circulation (L2) 22.50 Ambient temperature water circulation (L1) 35.17 Coolant circulation (L3) 19.17 S. Em± 0.4787 C. D. at 5% 1.4352 Feed temperature (T) where, Ds - sample dilution volume (i.e., 200*100 = 20000 ml); Ws - sample weight (g); As - absorbance of the sample; 1650 - standard value calculated by experts. Ambient temperature feed (T0) 35.75 Low temp. feed (T1) 34.08 S. Em± 0.3333 C. D. at 5% 0.9994 Interaction (L*T) STATISTICAL ANALYSIS The observed data were subjected to analysis of variance (ANOVA) using Factorial Completely Randomized Design at 5% level of significance (p<0.05). S. Em± 0.6667 C. D. at 5% NS C. V% 3.307 Number of replications, n=3 The mean values (n=3) for this parameter for all the treatments are graphically presented in the following figure (Fig. 1(a)). It varied from 43.00° for treatment combination L 0 T 0 to 18.33° for treatment combination L3T0. This shows the effect of circulation of liquid around the grinding chamber and temperature of feed material. RESULTS AND DISCUSSION Temperature inside the grinding chamber at the end of grinding Turmeric is used as ground powder. During grinding operation, heat will be generated and hence Print ISSN : 0974-1712 Temperature inside grinding chamber at the end (°) Effect 340 Online ISSN : 2230-732X 10 0 30 0.50 [VALUE] 8.06 [VALUE] 8.38 [VALUE] [VALUE] 8.38 8.40 8.40 8.40 [VALUE] [VALUE] 8.38 8.40 [VALUE] 8.38 [VALUE] 8.06 20 1 [VALUE] 1.43 [VALUE] [VALUE] [VALUE] [VALUE]1.39 1.43 1.43 1.39 [VALUE] 1.43 0.00 0.00 1.00 Ambient Ambient Ambient Ambient Chilled Chilled CoolantCoolant grinding circulation 0.00 grinding temp. temp. water water circulation water circulation water circulation Ambient Ambient Chilled Coolant 0.50 circulation grinding circulation temp. water circulation water circulation (d)circulation total flavonoid content 0.00 Ambient temp. feed feed Ambient temp.Low feedtemp. Low temp. feed Chilled water (d) total flavonoid content circulation circulation Coolant circulation 2.44 Ambient 2.35 Ambient (d) total flavonoid grinding temp. content water (d) total flavonoid content 2.44 3 2.23 (c) total phenol content 2 Low temp. feed 2.48 2.35 59.31 55.11 [VALUE] 55.11 [VALUE] 53.47 [VALUE] 53.47 [VALUE] 40 30 20 temp. water water (c) total phenol content circulation circulation 3 Coolant circulation Cucumin content (%) 40 50 (c) total phenol content Ambient Chilled (c) total phenol content 49.16 [VALUE] 50 [VALUE] Antioxidant activity (DPPH scavenging %) Ambient grinding 60 60 49.16 [VALUE] Ambient temp.temp. feed feed Low temp. feed feed Ambient Low temp. 0 [VALUE][VALUE] 1.15 1.15 [VALUE] [VALUE] 1.15 [VALUE] [VALUE] 1.15 1.25 1.25 [VALUE] [VALUE] [VALUE] 1.25 [VALUE] 1.25 1.39 1.39 3.13 circulation 1.00 0.50 0.50 1.50 2.48 2.41 water Ambient temp. feed 2.33 2.41 temp. water circulation circulation (c) total phenol content Antioxidant activity (DPPH scavenging %) 3.13 [VALUE] 2.49 2.49 3.01 2.49 [VALUE] 2.00 [VALUE][VALUE] [VALUE] [VALUE] 2.00 2.00 [VALUE] grinding 1.50 1.00 1.00 2.00 2.33 2.22 1 AmbientAmbient AmbientChilled ChilledCoolant Coolant Ambient grinding temp. circulation grinding temp. waterwater waterwater circulation circulation circulation Ambient circulation Ambient Chilled Coolant circulation Ambient temp. feed Low temp. feed (b) moisture content 2.00 1.50 1.50 2.37 2.23 0 Total flavonoid content QE/g content of extract) Total(mg flavonoid (mg QE/g of extract) 0 59.31 [VALUE] 2 0 Low temp. feed Ambient temp. feed Lowfeed temp. feed Ambient temp. feed Low temp. 2.00 2.00 (b) moisture content Cucumin content (%) 1 [VALUE] 1 1 [VALUE] 2 2.00 2 Ambient temp. feed 2 flavonoid (mgofQE/g of extract) Total Total flavonoid contentcontent (mg QE/g extract) (b) moisture content 3.13 3.13 [VALUE] 3.01 [VALUE][VALUE] 3.01 3.01 [VALUE] 2.49 [VALUE] [VALUE][VALUE] Total phenol Total phenol contentcontent (mg/g) (mg/g) Total phenol content (mg/g) Total phenol content (mg/g) 3 3 [VALUE] (b) moisture content content (b) moisture circulation Ambient Ambient temp.temp. feed feed Low Low temp.temp. feed feed Ambient temp. feed Low temp. feed (a) temperature inside the grinding chamber 4 3 3 8.06 water circulation circulation water circulation (a) temperature inside the grinding chamber 4 7.66 [VALUE] 8.06 [VALUE] Ambient Chilled Coolant temp. water circulation water Ambient circulation Chilled Ambient Coolant circulationtemp. grinding water circulation Ambient Chilled Coolant temp. water circulation water circulation Ambient Ambient Chilled Coolant circulation grinding water (a) temperature inside thetemp. grinding chamber (a) temperature inside the grinding chamber circulation (a) temperature inside the grinding chamber 4 4 7.66 [VALUE] 7.66 [VALUE] 1 Ambient 0grinding Ambient grinding 0 7.66 [VALUE] [VALUE] [VALUE] 9 8 Ambient temp. feed Low temp.Low feed temp. feed Ambient temp. feed 7 6 5 94 83 72 61 50 Ambient Ambient ChilledChilled CoolantCoolant 4 Ambient Ambient grinding temp. temp. water water circulation grinding circulation 3 water water circulation circulation 2 circulation circulation 2.37 2.22 0 Moisture content (%w.b.) Moisture content (%w.b.) Moisture content (%w.b.) Moisture content (%w.b.) 18.33 21.67 [VALUE] 18.33 [VALUE] 18.33 3 2 1 0 0 Ambient Ambient Chilled Coolant Ambient Ambient Chilled Coolant grinding circulation grindingtemp.temp. waterwater circulation waterwater circulation circulation circulation circulation 10 10 18.33 0 [VALUE] 20 [VALUE] 30 30 10 10 20 21.67 [VALUE] 33.67 [VALUE] [VALUE] [VALUE] 33.67 33.67 [VALUE] [VALUE] 40 40 20 20 39.33 50 50 30 30 9 8 7 6 5 49 8 3 7 2 6 15 04 Low feed Lowtemp. temp. feed 21.67 21.67 33.67 [VALUE] 39.33 [VALUE] [VALUE] Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature Ambient temp.feed feed 40 Ambient temp. [VALUE] Temp. inside grinding chamber at end (℃) 40 39.33 [VALUE] 50 39.33[VALUE] inside grinding at end (℃) Temp. insideTemp. grinding chamber at endchamber (℃) Temp. inside grinding chamber at end (℃) 50 Ambient temp. feed Low temp. feed Ambient temp. feed Low temp. feed Ambient temp. feed Low temp. feed Ambient temp. feed Low temp. feed 2 (d) total flavonoid content 1 0 Ambient 0 grinding 10 Ambient Ambient Chilled Coolant temp. water circulation water circulation Ambient Ambient Chilled Coolant circulation 0 grinding grinding temp. water water (e) Antioxidant activitycirculation Ambient Chilled Coolant temp. water water circulation circulation circulation Ambient Ambient Chilled Coolant grinding circulation circulation temp. water water circulation circulation circulation (f) Curcumin content Fig. 1: Effect of various treatments on (a) temperature inside the grinding chamber and (b) Moisture content, (c) Total phenol (e) Antioxidant activity (f) Curcumin content content, (d) Total flavonoid content, (e) Antioxidant activity (f) Curcumin content in turmeric powder (e) Antioxidant activity Print ISSN : 0974-1712 Number of replications, n = 3 341 (f) Curcumin content Online ISSN : 2230-732X Dabhi et al. The fall in temperature in grinding chamber becomes substantial with the change in grinding method compared to the change in feed temperature keeping the grinding method same, especially when jumping to chilled water and coolant circulation methods from ambient temperature water circulation. Possibly, resting of considerable amount of time in the feed hopper increased the temperature of low temperature feed, which in turn diminished its effect to some extent. This may be due to continuous absorption of heat generated during grinding operation. Additionally, lowering the temperature of liquid and circulating around the grinding chamber results in appreciable falling of final temperature inside the grinding chamber. That was caused by absorption of more amount of heat generated during grinding operation due to increase in the value of difference in temperature between grinding chamber and circulating liquid around. decrease the loss of moisture in surrounding by evaporation. However, a decrease in the value of moisture content was observed in ground powder compared to the moisture content of turmeric rhizome (8.59%) for all the treatments. That might be due to the loss of moisture at higher temperatures generated during the grinding operation. Total phenol content A significant difference (p<0.05) was observed in the phenol content of turmeric powder for different grinding methods (Table 2). The lowest value (1.91 mg/g) was found for the treatment L0 while the treatment L3 was found to have the highest value of total phenol (3.08%) in powder. Additionally, the effect of feed temperature on the value of total phenol was also found significant (p<0.05). The value found in the case of low temperature feed (2.66 mg/g) was higher than that of ambient temperature feed (2.46 mg/g). Instead of that, the interaction effect of grinding method and feed temperature (L*T) on the value of total phenol content of ground powder was found non-significant at the same level of significance. Moisture content The grinding method affects significantly the value of moisture content of ground product at a 5% level of significance. The lowest value (7.33%) was found for the grinding treatment L0 while the grinding treatment L3 exhibited higher percentages of moisture (8.31%). The effect of feed temperature on the value of moisture content was also found significant (p<0.05). The values found were 7.70% and 8.13% for ambient temperature and low temperature feed, respectively. In addition to individual effects, the interaction effect of the grinding method and feed temperature (L*T) on the same parameter was found non-significant. Graphically presentation of the mean values (n=3) of total phenol of ground powder for all the treatments is given in Fig. 1(c). The figure shows that the value of total phenol of ground powder increases when moving from treatments involving no circulation to coolant circulation treatments. Values ranged from a minimum of 1.83% for the control treatment (L0T0) to a maximum of 3.13% in treatment combination (L3T1). Turmeric having a higher content of phenolic compounds has been intensively studied (Braga, Leal, Carvalho, & Meireles, 2003; Prathapan, Lukhman, Arumughan, Sundaresan, & Raghu, 2009). During grinding, different temperatures create different thermal gradients that induce varying stresses, resulting in the liberation of phenolic. Therefore, different phenolic compounds are available at different temperatures. An increase in total phenol of ground powder with moving from left to right in the graph might be due to the fall in the value of temperature inside the grinding chamber at the end of the grinding operation. As higher temperature causes degradation of phenolic compounds, it decreases total phenol content in ground powder. The mean values (n=3) of moisture content of ground powder for all the treatments are graphically presented in the following figure (Fig. 1(b)). The figure reveals that the value of moisture content of ground powder increases when moving from left to right, i.e. treatments involving ambient grinding to ambient, chilled water, and coolant circulation treatments. Values varied from a minimum of 7.00% for ambient grinding with ambient water circulation and low temperature feed (L1T1) to a maximum of 8.40% for the treatment combination L3T1. An increase in moisture content of ground powder might be attributed to the condensation of moisture with low temperature inside the grinding chamber. Further, lower temperature of ground powder might Print ISSN : 0974-1712 342 Online ISSN : 2230-732X Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature Table 2: Effect of grinding method and feed temperature on bioactive compounds of turmeric powder Anti-Oxidant Flavonoids content Activity (mgQE/g) (%) Curcumin content (%) 1.91 1.12 48.15 2.30 Ambient temperature water circulation (L1) 7.76 2.41 1.24 52.69 2.27 8.26 2.84 1.36 55.00 2.44 Coolant circulation (L3) Effect Phenol M. C. (%w.b.) content (mg/g) Without liquid circulation (L0) 7.33 Chilled water circulation (L2) Grinding method (L) 8.31 3.08 1.42 57.92 2.39 S. Em± 0.0766 0.0685 0.0167 0.7269 0.0435 C. D. at 5% 0.2296 0.2053 0.05 2.1792 0.1304 Feed temperature (T) Ambient temperature feed (T0) 7.70 2.46 1.27 52.62 2.30 8.13 2.66 1.31 54.62 2.40 S. Em± 0.0541 0.0484 0.0118 0.5140 0.0307 C. D. at 5% 0.1623 0.1452 0.0354 1.5409 0.0922 Low temp. feed (T1) Interaction (L*T) S. Em± 0.1083 0.0969 0.0236 1.0279 0.0615 C. D. at 5% NS NS NS NS NS C. V% 2.3694 6.5555 3.1779 3.3317 4.5302 Number of replications, n=3. Total flavonoid content (L 0T 0) to maximum of 1.43 mg QE/g extract in coolant circulation with low temperature feed (L3T1). Grinding method affects significantly (p<0.05) on the value of total flavonoid content of ground product (Table 2). The lowest value (1.12 mg QE/g extract) was found for the grinding method without liquid circulation (L0) while the highest (1.42 mg QE/g extract) for the method involving coolant circulation around the grinding chamber (L3). The effect of feed temperature on the value of total flavonoid was also found statistically significant (p<0.05). The values found in case of ambient feed and low temperature feed were 1.27 and 1.31 mg QE/g extract, respectively. Besides that, the interaction effect of grinding method and feed temperature (L*T) on total flavonoid content of ground powder was found non-significant at the same level of significance. Increase in total flavonoid of ground powder with moving from ambient grinding with ambient temperature feed to coolant circulation grinding with low temperature feed might be due to the decrease in the elevation of temperature inside the grinding chamber at the end of grinding operation. As flavonoids are the largest group of phenolic compounds (naturally occurring) (Sulaiman and Balachandran, 2012), higher temperature engenders degradation of flavonoids and it decreases total flavonoid content in ground powder. Antioxidant activity Table 2 shows that grinding method affects significantly on the value of antioxidant activity of ground (p<0.05). The lowest value (48.15 %) was found for the treatment L0, while the highest (57.92 %) for the treatment L3. The effect of feed temperature on the value of the same parameter was also found statistically significant (p<0.05). The value found in case of low temperature feed (54.26%) was significantly higher with that of ambient temperature feed (52.62%). Conversely, the interaction effect of grinding method and feed The mean values of total flavonoid of ground powder for all the treatments are graphically shown in the following figure (Fig. 1(d)). Figure indicates that the value of total flavonoid of ground powder increases when moving from treatments involving ambient grinding to ambient water, chilled water and coolant circulation treatments. Values ranged from minimum of 1.09 mg QE/g extract for ambient grinding with ambient temperature feed treatment Print ISSN : 0974-1712 343 Online ISSN : 2230-732X Dabhi et al. temperature (L*T) on the value of antioxidant activity was found non-significant. flavonoid content are significantly, curcumin may be available in the form of dihyrocurcumin or tetrahydrocurcumin, hence its content have not been observed significant effect. The mean values of antioxidant activity of ground powder for all the treatments are graphically demonstrated in the Fig. 1(e). It shows that the value of antioxidant activity of ground powder increases when moving from treatments involving no circulation to ambient, chilled water and coolant circulation treatments. Values ranged from minimum of 47.14 % DPPH scavenging for control treatment (L0T0) to maximum of 59.31 % DPPH scavenging in treatment combination L3T1. The mean values (n=3) of curcumin content of ground powder for all the treatments are graphically demonstrated in the Fig. 1(f). It shows that the values ranged from minimum of 2.22 % for treatment L1T0 to maximum of 2.48 % for treatment combination L3T1. It has been reported that curcumin in turmeric exhibit antioxidant activity by preventing lipid peroxidation in various cells including erythrocytes, liposomes and macrophages. In addition, the presence of phenolic groups in the structure of curcumin explains its ability to react with reactive oxygen species and reactive nitrogen species (Trujillo et al. 2013). Lowering of grinding temperature increases the antioxidant power and hence antioxidant activity in relation to the concentration of the secondary metabolites (Tuba & Gulcin, 2008). The same reason of increase in grinding chamber temperature can be concluded for decrease in DPPH scavenging per cent when moving from right to left in the graph. As phenolics are the largest group of phytochemicals which account for most of the antioxidant activity in plants (Sulaiman and Balachandran, 2012), degradation of phenolic compounds at higher temperature also caused decrease in antioxidant activity percentages in ground turmeric powder. The pattern of increase in antioxidant of ground powder is the same as total flavonoid content of ground powder. Tanvir et al. (2017) reported that presence of antioxidant flavonoids inhibit or interrupt the substrates’ oxidation even at low concentrations, and hence it prevents oxidation by the pro-oxidants. Phenolics and flavonoids are nonenzymatic antioxidants that inactivate pro-oxidants due to reaction. Oxidative stress plays a major role in the pathogenesis of various diseases such as haemorrhage and shock, myocardial ischaemia, neuronal cell injury, hypoxia and cancer. CONCLUSION In summary, the results of this study demonstrated that grinding temperature affects the moisture content, antioxidant activity, phenol content, and curcumin content in turmeric powder. The ideal grinding method is grinding with coolant circulation resulting in significantly the highest moisture content, phenol content, flavonoid content, and antioxidant activity which was superior to ambient grinding for the better bioactive compounds in turmeric powder. The ambient grinding of turmeric at high temperatures led to the significant reduction of antioxidant activity, phenol content, and flavonoid content. These changes were abridged through with circulating the coolant in the jacket of the grinding chamber and hence by reducing the grinding temperature at the end of grinding. The findings of this study will be helpful for the reduction of the grinding temperature without the cryogenic principle. The results will also help retain curcumin, phenolic, flavonoids, and antioxidant activity during turmeric grinding. Curcumin content Curcumins are sensitive to high processing temperatures and are thus degraded during intense and/or prolonged thermal treatment (Prathapan et al. 2009). It was observed that grinding method affects non-significantly (p<0.05) on the value of curcumin content of ground product. The lowest value (2.23%) was found for the treatment (L0) while the highest (2.24 %) for the method involving treatment L2. As the anti-oxidant activity, phenol content and Print ISSN : 0974-1712 ACKNOWLEDGEMENTS This study was carried out under the Research Project of ICAR-AICRP on Post-Harvest Engineering and Technology, Junagadh Centre. 344 Online ISSN : 2230-732X Bioactive Compounds of Turmeric Powder Affected by Grinding Method and Feed Temperature REFERENCES Mallick, C.P. and Singh, M.B. 1980. Plant enzymology and Histoenzymology. Kalyani publishers, New Delhi. Aggarwal, B.B., Deb, L. and Prasad, S. 2015. Curcumin differs from tetrahydrocurcumin for molecular targets, signaling pathways and cellular responses. Molecules, 20(1): 185-205. Marinova, D., Ribarova, F. and Atanassova, M. 2005. Total phenolics and total flavonoids in Bulgarian fruits and vegetables. J. Univ. Chem. Technol. Metallurgy, 40: 255–260. Braga, M.E., Leal, P.F., Carvalho, J.E. and Meireles, M.A. 2003. Comparison of yield, composition, and antioxidant activity of turmeric (Curcuma longa L.) extracts obtained using various techniques. J. Agric. Food Chem., 51(22): 6604-11. Oskoueian, E., Abdullah, N., Hendra, R. and Karimi, E. 2011. Bioactive compounds, antioxidant, xanthine oxidase inhibitory, tyrosinase inhibitory and anti-inflammatory activities of selected agro-industrial by-products. Int. J. Mol. Sci., 12: 8610–8625. Chang, C., Yang, M. and Wen, H. 2002. Estimation of total flavonoid content in propolis by two complementary colorimetric methods. J. Food Drug Anal., 10: 178–182. Park Chang Yang, Lee Kyo-Yeon, Gul Khalid, Shafiur Rahman M., Kim Ah-Na, Chun Jiyeon, Kim Hyun-Jin, and Choi Sung-Gil. 2019. Phenolics and antioxidant activity of aqueous turmeric extracts as affected by heating temperature and time. LWT-Food Sci. Technol., 105: 149-155. Finley, J.W. 2005. Bioactive compounds and designer plant foods: The need for clear guidelines to evaluate potential benefits to human health. Chron. Horticult., 45: 6–11. Pereira, D.M., Valentao, P., Pereira, J.A. and Andrade, P.B. 2009. Phenolics: from chemistry to biology. Molecules, 14(6): 2202–2211. Geethanjali, A., Lalitha, P. and Jannathul, F.M. 2016. Analysis of Curcumin Content of Turmeric Samples from Various States of India. Int. J. Pharm. Chem. Res., 2(1): 55-62. Prathapan, A., Lukhman, M., Arumughan, C., Sundaresan, A. and Raghu, K.G. 2009. Effect of heat treatment on curcuminoid, colour value and total polyphenols of fresh turmeric rhizome. Int. J. Food Sci. Technol., 44(7): 1438–1444. Hendra, R., Ahmad, S., Sukari, A., Shukor, M.Y. and Oskoueian, E. 2011. Flavonoid analyses and antimicrobial activity of various parts of Phaleria macrocarpa (Scheff.) boerl Fruit. Int. J. Mol. Sci., 12: 3422–3431. Pruthi, J.S. and Mishra, B.D. 1963. Physical, chemical and microbial changes in curry powdes during drying, milling and mixing operations. Spice Bulletin, 3(8): 9-13. Karimi, E., Jaafar, H.Z.E. and Ahmad, S. 2013. Antifungal, anti-inflammatory and cytotoxicity activities of three varieties of Labisiapumilabenth: From microwave obtained extracts. BMC Complement Altern Med., 13: 1–10. Pusglove, J.W. 1968. Tropical Crops: Dicotyledons 1, Dicotyledons 2; Longmans: London, UK. Khopde, S.M., Priyadarsini, K.I., Guha, S.N., Satav, J.G., Venkatesan, P. and Rao, M.N.A. 2000. Inhibition of radiationinduced lipid peroxidation by tetrahydrocurcumin: Possible mechanisms by pulse radiolysis. Biosci. Biotechnol. Biochem., 64: 503–509. Trujillo, J., Chirino, Y.I., Molina-Jijon, E., AndericaRomero, A.C., Tapia, E. and Pedraza-Chaverri, J. 2013. Renoprotective effect of the antioxidant curcumin: recent findings. Redox Biol., 17(1): 448-56. Tuba, A.K. and Gülçin, İ. 2008. Antioxidant and radical scavenging properties of curcumin. Chem. Biol. Interact, 174(1): 27–37. Lin, J.K., Pan, M.H. and Lin-Shiau, S.Y. 2000. Recent studies on the biofunctions and biotransformations of curcumin. BioFactors, 13(1–4): 153–158. Print ISSN : 0974-1712 345 Online ISSN : 2230-732X International Journal of Agriculture, Environment and Biotechnology Citation: IJAEB: 15(Special Issue): 347-358, August 2022 A E A B ASSOCIATION FOR AGRICULTURE ENVIRONMENT AND BIOTECHNOLOGY DOI: 10.30954/0974-1712.03.2022.9 Physical and Functional Properties of Extruded Snack Products Prepared by Blending of Defatted Peanut Flour with Corn Flour P.R. Davara*, Mohit H. Muliya, M.N. Dabhi and V.P. Sangani Department of Processing and Food Engineering, College of Agricultural Engineering and Technology, Junagadh Agricultural University, Junagadh, Gujarat, India *Corresponding author: pareshdavara@yahoo.com (ORCID ID: 0000-0002-2209-3186) Paper No. 994 Received: 23-05-2022 Revised: 27-06-2022 Accepted: 06-07-2022 ABSTRACT Extruded snack products were prepared by blending of corn flour and defatted peanut flour using twin screw extruder. The flours were mixed and added with water put for conditioning prior to the extrusion cooking. The combined effects of feed moisture content, defatted peanut flour content, die head temperature and screw speed on the important physical (expansion ratio) and functional (water absorption index, water holding capacity and water solubility index) properties of extrudates were studied. The Response Surface Methodology (RSM) was used in designing the experiment. Since, the defatted peanut flour is poor in starch content, the flour content restricted the gelatinization and limited the expansion of the product. Defatted peanut flour was found to be suitable for the preparation of extruded snacks with the appropriate blending corn flour as a base material. The optimum treatment condition was found as 13% feed moisture content, 26% defatted peanut flour, 135 °C die head temperature and 250 rpm screw speed for the production of extruded product by blending of defatted peanut flour with corn flour. HIGHLIGHTS mm Utilization of defatted peanut flour in extrusion cooking. mm Physical and Functional properties of extrudates. mm Optimization of extrusion cooking conditions. Keywords: Extruded product, Defatted peanut flour, Extrusion cooking, Functional properties Extrusion cooking has been used increasingly in the production of food and food ingredients such as breakfast cereals, baby foods, flat breads, snacks, meat and cheese analogues and modified starches, etc. (Ding et al. 2004). Extrusion has gained popularity due to its versatility, cost of processing and high production rate. A very wide variety of products are possible by changing the ingredients, the operating conditions of the extruder and the shape of the dies. Extrusion has lower processing costs and higher productivity than other cooking or forming processes (Fellows, 2000). Due to lower moisture content, the shelf life of extruded products are enhanced significantly. Further, this products are nutritionally rich and are microbiologically safe (Pathak and Kochhar 2018). The combination of high temperature and high shear in extrusion cooking can be used as an effective cooking method to transform raw ingredients into ready-to-eat snack products. The acceptability and nutritional quality of the final product is not only determined by feed ingredient, but also manipulation of extrusion parameters including How to cite this article: Davara, P.R., Muliya, M.H., Dabhi, M.N. and Sangani, V.P. (2022). Physical and Functional Properties of Extruded Snack Products Prepared by Blending of Defatted Peanut Flour with Corn Flour. Int. J. Ag. Env. Biotech., 15(Special Issue): 347-358. Source of Support: None; Conflict of Interest: None Davara et al. feed moisture, screw speed, screw configuration, and temperature. Feed moisture has been found to be the main parameter in governing the texture of extrudates because it substantially influences the rheological properties of the molten starch. Moisture acts as a plasticizer, which reduces the viscosity and mechanical energy dissipation during extrusion. The effect of screw speed on the quality of extrudate is complex and highly dependent on temperature. A higher screw speed results in greater mechanical energy, or frictional heat, which leads to an increase in product temperature. The combination of shear and temperature can lead to a change in rheological properties of the melt and therefore affect the texture of extrudate (Choton et al. 2020). defatted peanut flour was purchased from Nutrinity Foundation, Junagadh. It was available in the vacuum packed bag in the fine powder form. Proximate composition of raw materials The biochemical characteristics viz. moisture content, carbohydrate, protein, fat and ash content, of the corn flour and defatted peanut flour were determined as per the standard procedures. Moisture content was determined by oven drying method according to AOAC (2005). Carbohydrate content of the prepared flour was determined by Phenol Sulphuric acid method for total carbohydrate (Nielsen 2010). Protein content of raw flour as well as extruded product was determined by Microkjeldahl method AOAC (1965). Fat content of the composite flour in the sample was determined by Soxhlet extraction method described by AOAC (1965). All analysis are expressed as the mean (±SD) of triplicate analysis. Ash content of the flour was determined using muffle furnace as described by AOAC (2005). Successful production of ready-to-eat snack products requires close control of many extrusion parameters including feed moisture, feed rate, barrel temperature, screw speed and barrel temperature. These process variables determine the transformation of raw materials during processing, which then influence the rheological properties of plasticizer melt in the extruder. Understanding the relationships between the ingredients is quite necessary to achieve desired product quality targets and to develop new products (Forsido and Ramaswamy 2011). Experimental design The Response Surface Methodology (RSM) is an empirical statistical modelling technique employed for multiple regression analysis using quantitative data obtained from properly designed experiments to solve multivariable equations simultaneously. It was used for designing of the experiment (Myers, 1976; Khuri and Cornell, 1987; Montgomery, 2001). A four-factor five-level Central Composite Rotatable Design (CCRD) with quadratic model was employed to study the combined effect independent variables on different response variables. The levels as selected for the independent parameters along with their coded and actual values are presented in Table 1 and the treatment combination are given in the Table 2. At present human are becoming more and more health conscious thus incorporating of ingredients in snack products becoming necessary. Hence, the focus of this research was to enhance the nutritional and functional properties of extrudates for the development of snack product. To achieve that, specific blends of defatted peanut flour and corn flour subjected to twin-screw extrusion process under identical set of processing parameters with the objective of testing the feasibility of defatted peanut flour in the production of extruded product. MATERIALS AND METHODS The second order polynomial coefficients were calculated by using the software package Design Expert version 10 (STAT-EASE Inc., Minneapolis, MN, USA) to estimate the responses of the dependent variable. Raw materials The corn grains required for the research work was obtained from the local market of Junagadh city. The corn grains were cleaned manually to remove all impurities and then coarse grinded using stone mill. The flour was then sieved to obtain uniform particle size flour. The flour was then packed in polyethylene bag and stored in refrigerator. The Print ISSN : 0974-1712 Extruded product preparation Extrusion trials were performed using a co-rotating twin-screw extruder (Basic Technology Pvt. Ltd., 348 Online ISSN : 2230-732X Physical and Functional Properties of Extruded Snack Products Prepared by Blending... Table 1: Independent parameters and their coded and actual values employed for the preparation of extruded product Sl. No. Parameters Code 1 2 3 4 Feed moisture content (% w.b.) Peanut flour (%) Die head temperature (°C) Screw speed (rpm) (X1) (X2) (X3) (X4) -2 10 10 90 100 -1 13 20 105 150 Coded levels 0 +1 16 19 30 40 120 135 200 250 +2 22 50 150 300 Table 2: Matrix of experimental central composite rotatable design for preparation of extruded products Coded variables Treatment No. T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 T21 T22 T23 T24 T25 T26 T27 T28 T29 T30 X1 X2 X3 X4 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -1 1 -2 2 0 0 0 0 0 0 0 0 0 0 0 0 -1 -1 1 1 -1 -1 1 1 -1 -1 1 1 -1 -1 1 1 0 0 -2 2 0 0 0 0 0 0 0 0 0 0 -1 -1 -1 -1 1 1 1 1 -1 -1 -1 -1 1 1 1 1 0 0 0 0 -2 2 0 0 0 0 0 0 0 0 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 -2 2 0 0 0 0 0 0 Uncoded variables DPF FMC (X1) % (w.b.) (X2) (%) 13 20 19 20 13 40 19 40 13 20 19 20 13 40 19 40 13 20 19 20 13 40 19 40 13 20 19 20 13 40 19 40 10 30 22 30 16 10 16 50 16 30 16 30 16 30 16 30 16 30 16 30 16 30 16 30 16 30 16 30 DHT Screw speed (X3) (°C) 105 105 105 105 135 135 135 135 105 105 105 105 135 135 135 135 120 120 120 120 90 150 120 120 120 120 120 120 120 120 (X4) (rpm) 150 150 150 150 150 150 150 150 250 250 250 250 250 250 250 250 200 200 200 200 200 200 100 300 200 200 200 200 200 200 FMC, feed moisture content, DPF, defatted peanut flour, DHT, die head temperature. Kolkata, India). Prior to use the extruder, it was kept in the running condition without feeding the material. It is necessary for removal material residue deposited in the barrel assembly. After cleaning of barrel, the heating system of twin screw extruder was kept in the on condition for a duration till the required temperatures were attained at different sections. The round hole die of 3 mm diameter Print ISSN : 0974-1712 was used for preparing the extruded product. 300 gram of composite flour prepared by blending of corn flour and defatted peanut flour was fed and extrusion was carried out with different processing variables. The cutter speed was adjusted appropriately. The extruded product was collected in a tray and dried using laboratory tray drier at 60 °C temperature for 1 hour to reduce moisture 349 Online ISSN : 2230-732X Davara et al. Effect of feed moisture content, defatted peanut flour, die head temperature and screw speed on response variables content up to 2-3% (w.b.) from product. Then product was packed in zipped lock plastic bags and put under storage at room temperature for future analysis. The treatment-wise data regarding various physical and functional characteristics of extruded products prepared by blending of DPF and corn flour is presented in the Table 4. Physical, functional and mechanical properties The ratio of diameter of extruded and the diameter of die was used to express the expansion of extruded (Fan et al. 1996). The Water Solubility Index (WSI) and Water Absorption Index (WAI) were measured using a technique developed for cereals (Ding et al. 2006). The Water Holding Capacity (WHC) was calculated using the formula given by Deshpande and Poshadri (2011). Expansion ratio The effect of feed moisture content, defatted peanut flour, die head temperature and screw speed on expansion ratio of extrudates is presented in the Table 4. while the response surface plots are shown in the Fig.1. ER increased with an increase in the DPF and FMC up to its minimum level i.e. 10% and 10% (w.b.), respectively. Similarly, another probability for increased in expansion ratio with increase the FMC up to its maximum level i.e. 22 % (w.b.) and DPF up to its minimum level i.e. 10%. Further, the ER increased with an increase the DHT up to its maximum level i.e. 150 °C and FMC is up to 10% (w.b.). The ER also increased with an increase the screw speed up to its maximum level i.e. 300 rpm and FMC up to its minimum level i.e. 10% (w.b.). It can also be observed that the ER increased with an increase in the DPF up to its minimum level i.e. 10% and DHT up to its maximum level i.e. 150 °C. The interaction of DPF and screw speed showed that the ER increased with increase the screw speed up to its maximum level i.e. 300 rpm and DPF up to its minimum level i.e. 10 %. DHT and screw speed at its maximum level i.e. 150 °C and 300 rpm, gave the highest ER of 2.30 mm/mm. Banerjee et al. (2003) also studied expansion ratio decreased with increase in moisture content. Ding et al. (2004) also studied higher barrel temperature increased the extrudate expansion. Liu et al. (2000) observed screw speed had no significant effect on expansion ratio. Suknark et al. (1997) studied as amylase content of starch increased, the expansion ratio increased. STATISTICAL ANALYSIS The statistical analysis of the experimental data was carried out to observe the effect of selected process parameters on the various responses. The obtained data were subjected to analyse for graphical representation, analysis of variaance (ANOVA) and multiple regrassion using the software Design Expert version 10 (Anderson and Whitcomb, 2005). The three-dimensional (3D) response surface plot were generated by keeping one variable constant at the centre point and varying the other two variables within the experimental range. The effect and regression coefficients of individual linear, interaction terms and quadratic terms were determined from the ANOVA table. The significance of all the terms in the polynomil equation was judges statistically by computing the F-value at a probability (p) value of 0.001, 0.01 and 0.05. RESULTS AND DISCUSSION Proximate composition of raw materials The biochemical characteristics of the corn flour and defatted peanut flour selected for the study are presented in the Table 3. Table 3: Biochemical characteristics of corn flour and defatted peanut flour. Sl. No. 1 2 3 4 5 Characteristic Moisture content % (w.b.) Carbohydrate (%) Protein (%) Fat (%) Ash (%) Print ISSN : 0974-1712 Corn flour 8.62±0.23 72.35±2.73 9.55±0.39 5.71±0.27 1.64±0.04 350 Defatted peanut flour 5.64±0.09 23.59±0.57 61.98±0.77 3.96±0.19 4.76±0.17 Online ISSN : 2230-732X Physical and Functional Properties of Extruded Snack Products Prepared by Blending... Table 4: Physical and functional characteristics of extruded product prepared by blending of defatted peanut flour and corn flour Treatment No. T1 T2 T3 T4 T5 T6 T7 T8 T9 T10 T11 T12 T13 T14 T15 T16 T17 T18 T19 T20 T21 T22 T23 T24 T25 T26 T27 T28 T29 T30 Control FMC (X1) % (w.b.) 13 19 13 19 13 19 13 19 13 19 13 19 13 19 13 19 10 22 16 16 16 16 16 16 16 16 16 16 16 16 13 Independent variable DPF DHT Screw speed (X2) (%) 20 20 40 40 20 20 40 40 20 20 40 40 20 20 40 40 30 30 10 50 30 30 30 30 30 30 30 30 30 30 — (X4) (rpm) 150 150 150 150 150 150 150 150 250 250 250 250 250 250 250 250 200 200 200 200 200 200 100 300 200 200 200 200 200 200 250 (X3) (°C) 105 105 105 105 135 135 135 135 105 105 105 105 135 135 135 135 120 120 120 120 90 150 120 120 120 120 120 120 120 120 135 ER (mm/mm) 2.59 2.54 1.79 1.69 2.98 2.61 1.80 1.80 2.80 2.58 1.76 1.71 3.05 2.67 1.89 1.87 2.10 2.54 3.25 1.65 1.53 2.35 2.04 1.81 1.69 2.12 2.00 2.04 1.93 1.95 2.82 Responses WSI WAI WHC (%) 10.55 4.46 11.23 7.48 18.02 13.85 16.50 12.13 8.60 5.88 12.11 8.65 18.85 14.52 14.00 11.66 13.27 10.44 5.38 8.17 9.34 18.37 7.46 11.25 7.97 7.10 13.07 10.11 9.07 9.76 4.78 (%) 401.21 388.56 357.41 375.10 482.32 475.65 402.57 389.53 412.32 417.21 389.65 377.68 498.56 465.23 378.65 407.21 399.65 372.32 428.70 373.73 372.12 501.23 456.36 445.10 406.65 431.27 413.93 412.11 436.05 426.56 435.93 (g/g) 5.25 5.23 4.26 4.62 5.79 5.61 4.22 4.34 5.46 6.58 4.42 4.09 6.11 5.73 4.83 5.05 3.14 4.52 5.80 3.98 4.83 5.24 6.21 5.21 4.66 3.87 4.43 4.48 4.47 4.39 5.22 ER, expansion ratio, WSI, water solubility index, WAI, water absorption index, WHC, water holding capacity. Water Solubility Index (WSI) DHT up to its maximum level i.e. 150 °C and DPF up to its minimum level i.e. 10%. At this interaction WSI was expected to be increased up to 23.31%. WSI was reported to be maximum (10.84%) for the interaction of DPF (30%) and screw speed (300 rpm). For the interaction of DHT and screw speed, the WSI was increased (21%) with an increase in DHT and screw speed up to its maximum level i.e. 150 °C and 300 rpm, respectively. Kadan et al. (2003) also reported WSI increased with an increase in extrusion temperature. Ding et al. (2004) also evaluated increasing feed moisture content results lower WSI. Fig. 2 represents the effect of feed moisture content, defatted peanut flour level, die head temperature and screw speed on water solubility Index. The highest WSI (15.74%) was observed for the interaction of DPF at 30% and FMC at 10%. WSI was observed to be increased up to 23.01% with an increase the DHT up to its maximum level i.e. 150 °C and FMC up to its minimum level i.e. 10 % (w.b.). The interaction effect of FMC and screw speed showed that the WSI increased up to 17.18% with an increase in the FMC and screw speed up to its minimum level i.e. 10% (w.b.) and 100 rpm, respectively. WSI increased with an increased in the Print ISSN : 0974-1712 351 Online ISSN : 2230-732X Davara et al. Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 1.53 1.53 X1 = A: Feed M.C. X2 = C: Die head temp. Actual Factors C: Die head temp. = 120 D: Screw speed = 200 Actual Factors B: Defatted peanut flour = 30 D: Screw speed = 200 Expansion ratio 5 4 3 2 1 5 4 Expansion ratio X1 = A: Feed M.C. X2 = B: Defatted peanut flour 3 2 1 10 10 10 12 20 12 14 150 14 16 30 16 18 40 B: Defatted peanut flour (%) 20 138 126 18 A: Feed M.C. (%wb) A: Feed M.C. (%wb) 114 20 102 22 50 22 90 C: Die head temp. (°C) Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 1.53 1.53 X1 = B: Defatted peanut flour X2 = C: Die head temp. X1 = A: Feed M.C. X2 = D: Screw speed Actual Factors B: Defatted peanut flour = 30 C: Die head temp. = 120 Actual Factors A: Feed M.C. = 16 D: Screw speed = 200 5 4 Expansion ratio 4 Expansion ratio 5 3 2 1 300 3 2 1 150 260 10 12 10 220 14 126 20 180 16 138 D: Screw speed (rpm) 18 140 20 A: Feed M.C. (%wb) 22 114 30 C: Die head temp. (°C) 102 40 100 B: Defatted peanut flour (%) Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 50 90 Design-Expert® Software Factor Coding: Actual Expansion ratio 3.25 1.53 1.53 X1 = B: Defatted peanut flour X2 = D: Screw speed X1 = C: Die head temp. X2 = D: Screw speed Actual Factors A: Feed M.C. = 16 C: Die head temp. = 120 Actual Factors A: Feed M.C. = 16 B: Defatted peanut flour = 30 5 5 4 Expansion ratio Expansion ratio 4 3 2 1 300 260 10 B: Defatted peanut flour (%) 300 260 220 114 180 D: Screw speed (rpm) 126 D: Screw speed (rpm) 140 40 1 102 180 30 2 90 220 20 3 C: Die head temp. (°C) 50 100 140 138 150 100 Fig. 1: Effect of feed moisture content, defatted peanut flour, die head temperature and screw speed on expansion ratio Print ISSN : 0974-1712 352 Online ISSN : 2230-732X Physical and Functional Properties of Extruded Snack Products Prepared by Blending... Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 4.46 4.46 X1 = A: Feed M.C. X2 = B: Defatted peanut flour Actual Factors B: Defatted peanut flour = 30 D: Screw speed = 200 25 20 15 10 5 0 10 10 12 30 Water Solubility Index (WSI) Water Solubility Index (WSI) Actual Factors C: Die head temp. = 120 D: Screw speed = 200 X1 = A: Feed M.C. X2 = C: Die head temp. 30 25 20 15 10 5 0 150 10 14 20 138 12 16 40 20 50 114 18 18 B: Defatted peanut flour (%) 126 14 16 30 A: Feed M.C. (%wb) 102 20 A: Feed M.C. (%wb) 22 C: Die head temp. (°C) 90 22 Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 4.46 4.46 X1 = B: Defatted peanut flour X2 = C: Die head temp. X1 = A: Feed M.C. X2 = D: Screw speed 30 30 Actual Factors A: Feed M.C. = 16 D: Screw speed = 200 25 Water Solubility Index (WSI) Water Solubility Index (WSI) Actual Factors B: Defatted peanut flour = 30 C: Die head temp. = 120 20 15 10 5 0 300 10 260 12 25 20 15 10 5 0 150 10 138 20 220 14 16 140 20 A: Feed M.C. (%wb) 22 126 30 180 18 D: Screw speed (rpm) 114 40 102 B: Defatted peanut flour (%) 100 Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 50 C: Die head temp. (°C) 90 Design-Expert® Software Factor Coding: Actual Water Solubility Index (WSI) 18.8486 4.46 4.46 X1 = B: Defatted peanut flour X2 = D: Screw speed 30 Actual Factors A: Feed M.C. = 16 B: Defatted peanut flour = 30 25 20 15 10 5 0 300 10 Water Solubility Index (WSI) 30 Water Solubility Index (WSI) Actual Factors A: Feed M.C. = 16 C: Die head temp. = 120 X1 = C: Die head temp. X2 = D: Screw speed 260 20 25 20 15 10 5 0 150 100 138 220 30 140 126 180 40 B: Defatted peanut flour (%) 140 50 180 114 D: Screw speed (rpm) 220 C: Die head temp. (°C) 102 260 90 100 D: Screw speed (rpm) 300 Fig. 2: Effect of feed moisture content, defatted peanut flour, die head temperature and screw speed on water solubility index Table 5: Constraints, criteria and output for numerical optimization of extruded snack food Variables Constraint Goal Importance Optimum value Feed moisture content % (w.b.) In the range 3 13 Defatted peanut flour (%) Maximum 3 26 Die head temperature (°C) In the range 3 135 Screw speed (rpm) In the range 3 250 Responses Constraint Goal Importance Predicted value Experimental Deviation (%) value Expansion ratio (mm/mm) Maximum 3 2.51 2.26 9.96 Water solubility index (%) Maximum 3 16.47 16.51 -0.243 Water absorption index (g/g) Maximum 3 5.24 4.27 18.51 Water holding capacity (%) Maximum 3 467.38 473.44 -1.30 Print ISSN : 0974-1712 353 Online ISSN : 2230-732X Davara et al. Water Absorption Index (WAI) was observed up to 10% and 150°C, respectively which yielded the WHC of 566.22%. The interaction of DPF at 10% and screw speed at 300 rpm yielded the highest WHC of 479.86%. Similarly, the WHC was found to be increased up to 526.84% for the interaction of DHT at 150°C and screw speed at 100 rpm. For all the above conditions further rise the independent variables decreased the response variables. Banerjee et al. (2003) also reported the rise in the WHC with an increase in the moisture content as well as temperature. The effect of feed moisture content, defatted peanut flour, die head temperature and screw speed on WAI is graphically presented in the Fig. 3. From the graphs it could be observed that the WAI was increased up to 6.24 g/g with an increase in the DPF level up to its minimum level i.e. 10% and FMC up to 18% (w.b.). The interaction of DHT (150°C) and FMC (15.80%) gave the maximum WAI of 5.38 g/g. The WAI was increased up to 6.04 g/g with an increase in the screw speed up to its maximum level i.e. 300 rpm and FMC up to 19% (w.b.). The DPF with its minimum level of 10% and DHT with its maximum level of 150°C increased the WAI up to 7.09 g/g. The interaction of DPF and screw speed showed that WAI was increased with increase the DPF up to its minimum level i.e. 10% and screw speed up to its maximum level i.e. 300 rpm. At this interaction of DPF and screw speed, the WAI increased the up to 7.97 g/g and 7.29 g/g, respectively. The interaction of DHT (150°C) and screw speed (300 rpm) gave the highest WAI of