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Assesment of pathogenic variabilty in kabuli and desi chick pea genotypes
Assessment of pathogenic variability in kabuli and desi Chickpea genotypes against Chickpea Blight (Ascochyta rabiei2018 •
Chickpea blight is one of the most destructive diseases of chickpea (Cicer arietinum L.) worldwide caused by Ascochyta rabiei (Pass.) Lab. The disease shows more devastating effects particularly in cold and humid ecological conditions. In epidemic condition it results in great damage by spreading at the entire crop in the deserted areas. To alleviate this setback, several interventions are practiced. However, breeding for resistance to the host is the most suitable and environmentally conducive strategy. The present study was conducted with three replications and three treatments (To with no spores, T1 with approximately 8350 spores/ml and T2 with approx. 16700 spores/ml) sprayed to screen the resistant source against chickpea blight in chickpea. Among total six genotypes, three kabuli and three desi genotypes were screened. Disease recorded at international rating scale 1-9. In kabuli genotypes, significant response was observed in treatment T1 and T2. When number of spores/ml increased from T1-T2 then kabuli genotype i.e. K-01248 move on rating scale from resistant to tolerant and K-01250 from tolerant to moderately susceptible. Desi chickpea genotypes showed more resistance against blight than Kabuli ones. The desi resistant and Kabuli tolerant genotypes can be utilized in further breeding program for development of resistant high yield genotypes.
European Journal of Plant Pathology
Effect of growth stages of chickpea on the genetic resistance of Ascochyta blight2010 •
Ascochyta blight (AB, Ascochyta rabiei (Pass.) Lab.) is one of the most important foliar disease of chickpea (Cicer arietinum L.), globally. Chickpea is attacked by AB at any growth stage in cool and humid weather depending on the inoculum availability. However, the disease epidemics are most prominent during the flowering and podding growth stages. The main objective of this study was to determine the effect of growth stages of chickpea on the genetic resistance of AB and use this information in a resistance breeding program. Two susceptible and two moderately resistant chickpea cultivars were spray inoculated at seedling (GS1), post-seedling (GS2), vegetative (GS3), flowering (GS4) and podding (GS5) growth stages with A. rabiei conidial suspension under controlled environment conditions. Irrespective of crop cultivars the incubation period (IP) was shorter in GS1, GS4 and GS5 and was significantly extended in GS2 and GS3. Symptom development was delayed significantly in moderately resistant cultivars. The AB severity 10 days after inoculation ranged between 7 and 9 on susceptible cultivars and 3 and 5 on moderately resistant cultivars. Further the correlation coefficient of disease severity between GS1, GS4 and GS5 was highly significant (r = 0.95) indicating that, evaluation for resistance to AB can be done at GS 1 (seedling stage), and or GS4 (flowering stage) to GS5 (podding stage) growth stages of chickpea. This supports the evaluation for AB resistance using 10-day-old-seedlings in controlled environment at ICRISAT and adult plant field screening at hot-spot locations in Dhaulakuan and Ludhiana in India.
European Journal of Plant Pathology
Development of ascochyta blight (Ascochyta rabiei) in chickpea as affected by host resistance and plant age2007 •
Caderno de Pesquisa …
Chickpea germplasm screening for resistance against Ascochyta blightChickpea (Cicer arietinum L.) an important food legume, ranks third in the world. In Pakistan yield of chickpea is low due to the prevalence of wilt and blight diseases-the two destructive diseases. The control measures available are not feasible and economical, except to exploit host plant resistance mechanism to identify the sources of resistance in existing chickpea germplasm. Fifty four advance chickpea genotypes were screened in blight screening nursery and wilt sick plot. Out of total 54 genotypes 23 were resistant and 16 were moderately resistant to Ascochyta blight disease. Among 23 resistant genotypes; K0058-09, K0062-09, K0066-09, D095-09, K07A005, BK05A015 and BK04A013 had disease rating mean of 3. The results of early wilt showed 19 genotypes as highly resistant and 15 as resistant. The genotypes K0070-09, BKK17106, CH 65/02 and BK04A013 were highly susceptible to wilt during early pathogen infection at seedling stage while the genotypes K0063-09, BKK17106 & BK04A013 were susceptible during late season. Resistance sources identified could be exploited directly and also may be transferred through hybridization to high yielding disease susceptible genotypes.
Journal of Animal and Plant Sciences
Genetic resistance in chickpea against Ascochyta blight: Historical efforts and recent accomplishments2017 •
Chickpea Blight is a devastating disease of chickpea (Cicer areitinum L.) worldwide caused by Ascochyta rabiei (Pass.) Lab. The disease is more disastrous particularly in long cool and humid environmental spells. It results in huge losses by wiping off all the crop in the desert areas whenever hit its epidemics. To manage this disease, different management strategies are practiced. However, breeding resistance to the host is the best and environmentally safe strategy. During 1970s, the loss of host resistance against the pathogen was reported, so extra ordinary efforts were started by the scientists to enhance the host tolerance towards the pathogen. In this way, relatively simple field screening techniques were followed for breeding and identification of new resistant genotypes. The review sums up the efforts regarding host breeding against chickpea blight involving large scale field screening experiments as well as recent marker assisted breeding using the molecular mapping and QTLs against the different strains of pathogen. Moreover, the important aspects covering the related knowledge of the pathogen, its biology, variability, perpetuation, characteristics and factor affecting the disease establishment have also been summarized.
2013 •
were screened for resistance to ascochyta blight disease caused by Ascochyta rabiei, by artificially inoculating the germplasm under glass-house at temperature 20±2 °c and humidity was maintained above 80 % by sprinkling fresh water. Highly significant effect (P<0.01) was observed on chickpea germplasm reaction to three pathotypes of Ascochyta rabiei (Mos02 ‘pathotype III: highly aggressive’, At02 ‘pathotype II: moderate aggressive ’ and Sba02 ‘pathotype I: least aggressive’).Three chickpea germplasm exhibited highly resistant response (Flip 4107, Flip 1025 and Flip 10511), two lines weresusceptible (ILC263 and ILC1929) and anothereight chickpea germplasm (ILC3279, ILC7795, ILC482,ILC483, Flip9393, ILC8068, ICC3996 and INRA199), displayed tolerant reaction. Key words: Aggressiveness Ascochyta rabiei Cicer arietinum Resistance Sensitivity
2015 •
Ascochyta blight is an economically important disease of chickpea caused by the fungus Ascochyta rabiei. The fungus shows considerable variation for pathogenicity in nature. Fifteen chickpea germplasm accessions provided by ICARDA (Aleppo, Syria), their origin from different countries (Table 1), were screened for resistance to Ascochyta blight disease caused by Ascochyta rabiei, by artificially inoculating the germplasm under glasshouse at temperature ranged from 20±2°C and humidity was maintained above 80% by sprinkling fresh water. Highly significant effect (P<0.01) was observed on chickpea germplasm reaction to three pathotypes of Ascochyta rabiei (Mos02 'pathotype III: highly aggressive', At02 'pathotype II: moderate aggressive' and Sba02 'pathotype I: least aggressive'). We found 5 chickpea germplasm exhibited highly resistant response (ILC72, ILC182, ILC187, ILC200 and ILC202), 2 are susceptible (ILC1929 and Flip1025) and other 8 chickpea germplasm (...
2020 •
MENGHITUNG TAKSIRAN PERSALINAN 1. Tafsiran Persalinan Umumnya kehamilan berlangsung selama 37-42 minggu atau rata-rata 280 hari (40 minggu), dihitung dari hari pertama pada menstruasi terakhir. Hari pertama haid terakhir (HPHT) adalah hari pertama siklus menstruasi. Sementara ovulasi terjadi kurang lebih dua minggu setelah masa ini. Jika pada periode ini sperma bertemu sel telur hingga terjadi pembuahan, maka saat itulah kehamilan dimulai. Perhitungan usia kehamilan dalam hitungan minggu umumnya menyertakan dua minggu sejak HPHT tersebut. Maka jika janin Anda berusia empat minggu, maka kehamilan Anda dihitung enam minggu. Untuk mengetahui perkiraan kapan bayi akan lahir, Anda dapat memanfaatkan kalkulator kehamilan dengan menggunakan rumus Naegele dan rumus Parikh a. Rumus Naegele Nama rumus ini berasal dari nama penemunya, Franz Karl Naegele, dokter kandungan di Jerman yang hidup di abad 19. Hari perkiraan lahiran (HPL) dihitung berdasarkan hari pertama haid terakhir (HPHT) Anda. Rumus Naegele adalah sebagai berikut: Rumus pertama digunakan jika HPHT ada di bulan Januari sampai Maret. Misalnya, HPHT Anda adalah 21 Januari 2020, maka perkiraan tanggal persalinan Anda adalah: Tahun: tetap 2020 Bulan: 1+9 = 10 Hari: 21+7= 28 Maka hari perkiraan bayi Anda lahir adalah 28 Oktober 2020. Rumus kedua digunakan jika HPHT ada di bulan April sampai Desember. Jadi, jika hari pertama haid terakhir Anda adalah 1 Mei 2020 maka perkiraan tanggal persalinan Anda adalah: Tahun: 2020+1= 2021 Bulan: 5-3=2 Hari: 1+7= 8 Maka hari perkiraan bayi Anda lahir adalah 8 Februari 2021. b. Rumus Parikh Rumus Naegele di atas punya kelemahan. Rumus ini hanya dapat diterapkan pada wanita dengan siklus menstruasi 28 hari. Bagaimana dengan siklus menstruasi kurang atau lebih dari 28 hari? Jawabannya menggunakan rumus Parikh. Cara penghitungan dilakukan dengan menghitung saat terjadinya ovulasi, yaitu lama siklus menstruasi dikurangi 14 hari. Misalnya, HPHT pada tanggal 1 Januari 2020. Jika siklus menstruasi 28 hari, maka setelah dihitung dengan rumus Naegele, HPL-nya adalah 8 Oktober 2020. Namun jika siklus menstruasi ternyata adalah 35 hari, maka dengan rumus Parikh, tanggal persalinannya menjadi: HPHT + 9 bulan + (35-21) hari = 15 Oktober 2020 MENGHITUNG TAFSIRAN BERAT JANIN 2. Tafsiran berat Janin Menghitung berat janin dari minggu ke minggu kehamilan sangat penting untuk memperkirakan berat lahir janin saat ia dilahirkan. Janin yang memiliki berat lahir sangat kecil (kurang dari 2,5 kg) berpotensi dilahirkan dalam kondisi prematur, sedangkan janin dengan berat lahir terlalu besar (lebih dari 4 kg) berisiko mengalami komplikasi masalah kesehatan tertentu. Ada 2 cara menghitung berat janin, yaitu: a. Rumus McDonald Untuk menghitung taksiran berat janin sesuai usia kehamilan dengan rumus McDonald, memerlukan pita meteran untuk mengukur tinggi dan lingkar rahim. Baik tinggi maupun lingkar rahim dinyatakan dalam centimeter. Tinggi rahim (Symphysiofundal Height atau SFH) diukur dari ujung tulang kemaluan hingga puncak rahim (di bawah dada). Sementara lingkar rahim (Abdominal Girth atau AG) diukur dengan melingkarkan pita meteran sejajar dengan pusar ibu hamil. Setelah mengukur, masukkan angka yang Anda dapatkan ke rumus menghitung taksiran berat janin sesuai usia kehamilan a la McDonald sebagai berikut: TBJ = Symphysiofundal Height (SFH) X Abdominal Girth (AG) Untuk mendapatkan hasil yang akurat, terdapat dua hal yang harus Anda perhatikan ketika mengukur SFH dan AG: • Kandung kemih ibu hamil sebaiknya dalam keadaan kosong ketika diukur, artinya Anda sebaiknya buang air kecil terlebih dahulu sebelum melakukan pengukuran SFH dan AG. • Angka SFH seharusnya sama dengan usia kandungan Anda (dalam hitungan minggu). Jadi SFH Anda akan menunjukkan 23 cm ketika usia kehamilan 23 minggu. • Nilai SFH yang memiliki selisih lebih dari 3 cm menandakan adanya masalah dalam kehamilan, misalnya level air ketuban yang abnormal, bayi dalam posisi horizontal, kehamilan dengan janin kembar, atau adanya fibroid rahim. Meski demikian, kemungkinan terjadinya error dalam perhitungan ini bisa saja terjadi. Jika Anda mengalami hal tersebut, konsultasikan dengan dokter kandungan atau lakukan perhitungan taksiran berat janin sesuai usia kehamilan dengan rumus lainnya. b. Rumus Johnson Menghitung taksiran berat janin sesuai usia kehamilan dengan rumus Johnson hanya memerlukan SFH. Lebih tepatnya, berikut rumus Johnson yang dimaksud: Taksiran berat janin (TBJ) = [SFH (dalam cm) – X] x 155 Huruf X merupakan variabel angka yang sudah ditetapkan dalam rumus ini dan menggambarkan posisi janin di dalam rahim Anda. Untuk mengetahui secara pasti apakah bagian tubuh janin sudah masuk panggul, tentu Anda harus berkonsultasi dengan bidan atau dokter kandungan yang menangani Anda. • X=13 jika bagian tubuh janin (biasanya kepala) belum masuk panggul • X=12 jika bagian tubuh janin sudah berada di pintu panggul • X=11 jika bagian tubuh janin sudah masuk panggul c. Pemeriksaan USG Pemeriksaan USG merupakan suatu metode diagnostik dengan menggunakan gelombang ultrasonik untuk mempelajari morfologi dan fungsi suatu organ berdasarkan gambaran eko dari gelombang uktrasonik dan dipantulkan oleh organ (Prawirohardjo, 2009). Alat ini diperlukan untuk mendeteksi adanya kelainan pada janin, termasuk memantau suatu cara alternatif untuk memantau pertumbuhan berat janin. Dengan demikian diperlukan suatu cara alternatif untuk memantau pertumbuhan berat badan janin dimana fasilitas USG tidak tersedia. Pada prinsipnya pengguna USG baik 2D, 3D bahkan 4D, tidak menimbulkan efek samping pada kehamilan. Pemakaian alat USG baik 2D, 3D dan 4D pada pemakai (user) yang mengerti dan paham akan membawa arah diagnosis ke suatu kelainan janin atau penyakit janin yang lebih jelas, tetapi USG yang dilakukan hanya untuk koleksi perkembangan janin (Morse, 2009).
2018 •
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