agriculture
Article
Meteorological Conditions in a Temperate Climate for
Colletotrichum acutatum, Strawberry Pathogen Distribution
and Susceptibility of Different Cultivars to Anthracnose
Armina Morkeliūnė * , Neringa Rasiukevičiūtė
and Alma Valiuškaitė
Laboratory of Plant Protection, Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry,
Babtai, LT-54333 Kaunas, Lithuania; neringa.rasiukeviciute@lammc.lt (N.R.); alma.valiuskaite@lammc.lt (A.V.)
* Correspondence: armina.morkeliune@lammc.lt
Citation: Morkeliūnė, A.; Rasiukevičiūtė,
N.; Valiuškaitė, A. Meteorological
Conditions in a Temperate Climate
for Colletotrichum acutatum, Strawberry
Pathogen Distribution and Susceptibility
Abstract: Previously, Colletotrichum spp. has been considered a warmer climate pathogen as these
meteorological conditions are most optimal for its development. However, climate change is fostering the spread of plant disease and complicating the ability to predict meteorological conditions
for disease development. This study aims to determine meteorological conditions for anthracnose
development, evaluate the susceptibility of different strawberry cultivars and detect the distribution
of strawberry pathogens in temperate climate conditions. The experiment was carried out in the
Institute of Horticulture Lithuanian Research Centre for Agriculture and Forestry (LAMMC) in
Lithuania during the 2018–2019 strawberry growing season. To evaluate the contamination levels
(fungal and bacterial pathogens) of strawberry plant parts, soil and susceptibility to Colletotrichum
acutatum, samples were collected at four different locations in Lithuania from eleven cultivars. The results revealed that Colletotrichum spp. was not equally prevalent in the soil at all strawberry farms
tested. The evaluation indicated that strawberry leaves and stems were similarly contaminated with
pathogenic fungi. The most frequently isolated fungi from the leaves and stems were Mycosphaerella
spp., Alternaria spp., Fusarium spp., Colletotrichum spp., Phytophthora spp., and Botrytis spp. Our study
confirmed that the response of cultivar susceptibility to C. acutatum was unequal. The most suitable
temperature for C. acutatum development was 25 ◦ C. Monitoring of meteorological conditions, evaluation of inoculum source and appropriate cultivar selection could reduce or avoid yield losses caused
by the C. acutatum.
of Different Cultivars to Anthracnose.
Agriculture 2021, 11, 80. https://
doi.org/10.3390/agriculture11010080
Keywords: Fragaria × ananassa; iMETOS® ; pathogenicity; plant parts; soil; temperature
Received: 10 December 2020
Accepted: 16 January 2021
Published: 19 January 2021
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4.0/).
1. Introduction
Strawberries are one of the most popular dessert berries in the world due to their
pleasant taste and aroma, as well as the fact that they contain many useful bioactive
components [1]. Strawberry is the most important small fruit crop in Lithuania, produced
on 560 hectares. With the growing consumption of fresh fruit and berries, it is becoming
increasingly important not only to expand the range but also to extend the growing season
of berries such as strawberries. As in other parts of the world, the strawberry business
is expanding in Lithuania. Therefore, new varieties are being introduced from warmer
climate zones. Strawberry growing is expanding not only outdoors, but also in greenhouses.
Growing strawberries in greenhouses facilitate the spread of pathogens in tropical and
subtropical climates.
One of the most common strawberry diseases is anthracnose. Strawberry anthracnose
causes yield losses of up to 50% and up to 80% of plant death in nurseries [2]. The Colletotrichum species-genus comprises about 190 species that cause plant disease in various
plant crops worldwide. Complexes of several Colletotrichum species cause strawberry
anthracnose: C. acutatum J. H. Simmonds, brooks and C. gloeosporioides (Penz.) Penz. and
Sacc. [3,4]. Anthracnose infects strawberry roots, crowns, petioles, leaves, runners, buds,
Agriculture 2021, 11, 80. https://doi.org/10.3390/agriculture11010080
https://www.mdpi.com/journal/agriculture
Agriculture 2021, 11, 80
2 of 13
flowers and fruits. The Colletotrichum species complex has several development stages and
infects different plant parts during their vegetation period [5–7]. C. fragariae mainly cause
crown rot and lesions in vegetative tissue, and C. acutatum causes fruit rot [8]. The ability
of these pathogens to attack different plant parts is due to the species complex involved in
strawberry anthracnose [9–11].
Previously, strawberry anthracnose pathogen was considered to be a warmer climate pathogen, where temperatures ranging from 15 to 30 ◦ C and optimal at 25 ◦ C are
needed for disease development. In comparison, the spread of C. fragariae is optimal
between 26.7–32 ◦ C. Temperature is a key factor for anthracnose development and occurrence [12–15]. Colletotrichum spp. mostly causes plant disease in tropical, subtropical
and temperate regions around the world, as these meteorological conditions are most
optimal for pathogen development [16]. Temperature influences the development of Colletotrichum spp. and appressoria formation [17]. Therefore, it is mostly not relevant in
northern countries, except for warmer climate periods during berry harvesting and high
rainfall [12,14,15]. However, C. acutatum causes berry infections at temperatures from
20 ◦ C [13,18] and when there is a period of more than 12 h of leaf wetness [19]. The optimal
temperature for anthracnose development is 12–27 ◦ C and leaf wetness for more than
12 h [17,19]. Lithuania generally has temperate climatic conditions, hence the impact of
Colletotrichum spp. should be minimal. According to our ongoing studies in Lithuania,
the Colletotrichum spp. pathogen is not widespread, but due to climate change and its
extremes, the occurrence of this disease is now more noticeable.
Due to climatic conditions, the battle against plant disease presents new challenges,
and new strategies are required for plant protection. The prediction of meteorological
conditions and the occurrence of plant diseases is a complicated science as it involves
determining the relationship between meteorological conditions and plant disease risk.
At the same time, host development may be influenced by climate change [20]. The growing
demand for new solutions to optimise chemical pesticide usage and disease warning
systems will not only help to monitor disease risk but also to predict disease epidemics.
Meteorological parameters used to predict crop disease occurrence include air temperature,
leaf wetness, precipitation and relative humidity. Disease forecasting models determine
the critical timing of fungicide application when the conditions are most favourable for
disease development. This also avoids unnecessary spraying and applications are made
when the conditions are favourable for disease. Disease forecasting models are based on
the impact of temperature and leaf wetness duration [7,19,21,22]. There are various disease
forecasting models for specific plant diseases. This study summarises the meteorological
conditions for C. acutatum to determine the risk of strawberry anthracnose infection [8].
The anthracnose fruit rot (AFR) model shows that disease control based on an advisory
system could significantly reduce the number of sprayings [23]. Similarly, the StAS webbased forecasting system has the potential to reduce spraying times compared with fixedinterval applications [13,24]. However, all forecasting models are based on counting
the favourable periods for disease development. In Lithuania, IMETOS® meteorological
stations with forecasting models were used for a while [21,22,25,26]. The disease forecasting
models are not only beneficial for the farmer (more precise application) but also for the
environment (fewer pesticides, accurate applications).
The sources of a fungal infection include previous crops, contaminated soil, irrigation
water and farmworkers. Soilborne pathogens can be species-specific, while resistance to
anthracnose differs among strawberry varieties. Soilborne pathogens cause up to 20–30%
yield losses in strawberry crops and can survive in the soil for several years [27–29]. Strawberry disease control generally relies upon several fixed-interval (7–10 days) applications of
fungicides from the time of leaf emergence until harvest, thus requiring significant amounts
of fungicides [7,22,30], which are costly and ideally should be applied when the risk of
infection is high. The growing resistance to pesticide use and their adverse environmental
effects are leading to new, environmentally safer disease control strategies [7,31,32]. The selection of resistant cultivars (cv.) to anthracnose reduces the inoculum levels; additionally,
Agriculture 2021, 11, 80
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meteorological conditions’ monitoring could assist in controlling the spread of C. acutatum.
This study aims to determine the meteorological conditions for anthracnose development,
evaluate the susceptibility of different strawberry cultivars and detect the distribution of
strawberry pathogens in temperate climate conditions.
2. Materials and Methods
2.1. Colletotrichum sp. Isolate
The isolate of Colletotrichum sp. used in this study were collected from the infected
strawberry cultivar ‘Deluxe’ fruit grown in the experimental strawberry field of the Institute of Horticulture, Lithuanian Research Centre for Agriculture and Forestry (LAMMC).
The Colletotrichum sp. mycelium was maintained by sub-culturing on potato-dextrose agar
(PDA) at 25 ◦ C for 7 days. This step repeated twice to purify culture, then single-spore
isolates were extracted. Single spore Colletotrichum sp. isolates were stored on PDA at 4 ◦ C
at the Laboratory of Plant Protection isolate collection. The single spore isolate Nr. Fo5 was
initially identified by its morphological attributes.
Colletotrichum sp. DNA was extracted as described by Rasiukevičiūtė et al. [33].
The DNA was extracted using a genomic DNA purification kit (Thermo Fisher Scientific Baltics, Vilnius, Lithuania). DNA was dissolved in 100 µL of 1 × TE buffer and
visualised in 1.5% agarose gels with Midori Green Direct (Nippon Genetics Europe).
DNA concentration was measured by NanoDrop 1000 spectrometer (Thermo Fisher Scientific, Waltham, MA, USA). C. acutatum isolates were identified using species-specific
primers ITS4 (TCCTCCGCTTATTGATATGC-3) and CaInt2 (GGGGAAGCCTCTCGCGG)
primers [34]. Polymerase chain reaction was performed in a total volume of 25 µL containing 1 µL of DNA, 5 µL 10 × Tag buffer, 0.5 µL 10 mM dNTP Mix, 0.5 µL of each
primer (CaInt2 and ITS4), 1.5 µL 25 mM MgCl2 , 0.2 µL 5 U µL−1 Taq DNA polymerase
(Thermo Fisher Scientific), and 15.8 µL DNase/RNase-free water. The PCR was performed
in UNO96 thermal cycler (VWR International GmbH), for 35 cycles consisting of 1 min at
95 ◦ C, 30 s at 54 ◦ C, and 1 min at 72 ◦ C. Amplification products were separated in 1.5%
agarose gels, stained with Midori Green Direct (Nippon Genetics Europe).
2.2. iMETOS® Meteorological Conditions
This research was conducted at the LAMMC in 2018 and 2019. We evaluated data
from iMETOS® (Pessl Instruments, Weiz, Austria) meteorological stations at four different
locations in Lithuania over four months (May, June, July and August) in 2018 and 2019 to
determine the favourable conditions for C. acutatum spread (Table 1). Farms 1 and 2 were
evaluated in 2019, and Farms 3 and 4 in 2018 and 2019. The studied plant material was
from 2–3 year-old plants.
Table 1. The iMETOS® meteorological station locations in Lithuania and strawberry cultivars.
District
Region
Farm Name
Grown Cultivars
Radviliškis distr.,
GPS 55.892954, 23.870937
North
Farm 1
Florence, Asia, Rumba,
Vibrant, Polka, Malvina
Šiauliai distr.,
GPS 55.740328, 23.519661
North
Farm 2
Flair, Asia, Malvina
Šiauliai distr.,
GPS 55.9712991, 22.9108421
North
Farm 3
Senga Sengana, Rumba,
Polka, Malvina
Kaunas distr.,
GPS 55.084567, 23.806315
Central
Farm 4
Asia, Rumba, Sonata,
Malvina, Elkat, Deluxe
The production of strawberry fruit in Lithuania occurs from mid-April (June-bearing)
until late September (everbearing). iMETOS® meteorological stations are equipped with
various sensors (air and soil temperature, precipitation, leaf wetness, relative humidity).
The C. acutatum infection risk periods were determined according to the meteorological
Agriculture 2021, 11, 80
4 of 13
conditions. Favourable days for disease development were counted if the air temperature
was between 12–27 ◦ C and the leaf wetness period lasted more than 720 min (12 h) [8,35].
2.3. Strawberry Plant Contamination
Asymptomatic strawberry samples were randomly collected in June–July 2018 and
2019 (Table 1). Ten different strawberry cv. were evaluated in a strawberry plant contamination study. The samples of leaves and stems were cut into 1 cm fragments, surfacesterilised for 3 min in 70% ethanol and rinsed five times with sterile distilled water (dH2 O).
Leaves and stems were analysed separately. The plant fragments were placed on potato
dextrose agar (PDA, for fungi) and plate count agar (PCA, for bacteria) and incubated at
25 ◦ C. Contaminant colony units were converted to percentages (%) and identified according to the morphological traits typical of the colonies’ descriptions under a microscope
after 3, 5 and 7 days post-inoculation (DPI). One replication consisted of 50 leaves or stems
per cultivar with four replicates per treatment.
2.4. Soil Contamination
Soil samples were collected randomly in four replicates per cultivar (Table 1). Ten ifferent strawberry cv. were evaluated in the soil contamination study. Soil suspension
dilutions were prepared to evaluate the number of colony-forming units (CFU) of bacteria
and fungi in the soil by the plate count method. The soil (10 g) was diluted with 90 mL
dH2 O to concentrations up to 10−6 . Each sample was replicated twice. The dilutions of
1 mL series were plated onto PDA (for fungi) and PCA (for bacteria) and incubated at
25 ◦ C. The total number of bacteria and fungi was evaluated after 3, 5 and 7 DPI. The total
CFU was converted to a log value (CFU/g−1 ) [36]. All experiments (plant isolations and
soil dilution studies) were conducted twice during the strawberry production season on
14 June 2018 and 18 July 2018, and 20 June 2019 and 25 July 2019. Data from soil experiment
are provided as an average of four sampling dates.
2.5. Effect of Temperature of Growth C. acutatum
Single spore isolate of C. acutatum was maintained by sub-culturing on PDA at
25 ± 2 ◦ C for seven days. Six mm diameter mycelial plugs were cut and placed in the
centre of new Petri dishes containing PDA. The plates were incubated at 5, 10, 15, 20, 22 and
25 ◦ C in darkness. Growth rates were determined by measuring the fungal colony diameter
(cm) at 2, 4 and 7 days post-inoculation (DPI). Four replicates were used in each treatment,
and the experiment was repeated twice.
2.6. Strawberry Cultivars’ Susceptibility to C. acutatum
The susceptibility to C. acutatum was determined on the detached strawberry leaves.
Leaves were obtained from Farm 4 in 2019. The six selected strawberry cvs. were: ‘Malvina’,
‘Asia’, ‘Deluxe’, ‘Sonata’, ‘Elkat’ and ‘Rumba’. Visually healthy strawberry leaves (16 leaves
per replicate, four replicates in one cultivar), composed of three leaflets on a petiole,
and without any visible disease symptoms were sterilised in 70% ethanol solution for
3 min, rinsed five times with sterile distilled water (SDW) and dried for 5 min on sterile
filter paper. The upper surface of the leaf was inoculated with 5 mm mycelial plugs
(mycelial side down) in the centre of each multiple leaves. The experiment was repeated
four times, with four replicates. The Petri plates were incubated at 25 ◦ C in darkness for
15 DPI. The disease severity index of each inoculated leaf was assessed up until 15 DPI
using the following severity scale: (1) 0%—no visible infection; (2) 5%; (3) 10%; (4) 20%;
and (5) 50% or more infected area [37].
2.7. Statistical Analysis
The data were analysed using an analysis of variance ANOVA test with SAS Enterprise
Guide, version 7.1 (SAS Institute Inc., Cary, NC, USA). The standard error in the figures
is marked as an error bar estimated for growth rates of isolates. Duncan’s multiple range
following severity scale: (1) 0%—no visible infection; (2) 5%; (3) 10%; (4) 20%; and (5) 50%
or more infected area [37].
Agriculture 2021, 11, 80
2.7. Statistical Analysis
5 of 13
The data were analysed using an analysis of variance ANOVA test with SAS Enterprise Guide, version 7.1 (SAS Institute Inc., Cary, NC, USA). The standard error in the
figures is marked as an error bar estimated for growth rates of isolates. Duncan’s multiple
test
(p <test
0.05)
to determine
differences
among
Two-wayAnova
Anova
range
(p <was
0.05)used
was used
to determine
differences
amongtreatments.
treatments. Two-way
was
used
to
determine
differences
in
C.
acutatum
mycelium
growth
based
on
two
factors:
was used to determine differences in C. acutatum mycelium growth based on two factors:
day
and
temperature.
day
and
temperature.
3. 3.
Results
Results
®
3.1.3.1.
iMETOS
iMETOS®Meteorological
MeteorologicalStation
Station Conditions
Conditions
AA
comparison
performedfor
forfour
fourfarm
farmlocations
locations
comparisonofofmeteorological
meteorologicalconditions
conditions was
was performed
inin
2018
and
2019
during
May,
June,
July
and
August.
Meteorological
2018
and
2019
during
May,
June,
July
and
August.
Meteorologicalconditions
conditionsfor
forC.C.acutatum
acutainfection
development
are provided
in Figure
1. In 1.
2018
and and
20192019
in Lithuania,
strawberry
tum infection
development
are provided
in Figure
In 2018
in Lithuania,
strawvegetation
seasonsseasons
had quite
climatic
conditions,
a relatively
warm
temperature
berry vegetation
hadsimilar
quite similar
climatic
conditions,
a relatively
warm
temperwith
lowwith
precipitation
and lowand
air humidity.
However,
evaluating
the data the
from
iMETOS
ature
low precipitation
low air humidity.
However,
evaluating
data
from ®
meteorological
stations in 2018
andin2019
for strawberry
iMETOS® meteorological
stations
2018indicated
and 2019different
indicatedconditions
different conditions
for
C. strawberry
acutatum. C. acutatum.
®
Figure
1. The
meteorological
conditions
according
totoiMETOS
((A)Farm
Farm11inin2019;
2019;(B)
(B)Farm
Farm
2 in
Figure
1. The
meteorological
conditions
according
iMETOS®meteorological
meteorological stations
stations ((A)
2 in
2019;2019;
(C) Farm
3
in
2018;
(D)
Farm
3
in
2019;
(E)
Farm
4
in
2018;
(F)
Farm
4
in
2019).
Data
are
presented
as
an
average.
(C) Farm 3 in 2018; (D) Farm 3 in 2019; (E) Farm 4 in 2018; (F) Farm 4 in 2019).
are presented as an average.
The iMETOS® meteorological conditions for strawberry anthracnose of 2018 are
provided in Figure 1. In 2018, the risks of infection in Farm 3 (Figure 1C) lasted for ten days:
one day in May, four days in July and 5 days in August (Table 2). The air temperature,
precipitation and leaf wetness parameters did not create favourable conditions for the
spread of anthracnose for three months in Farm 4 (Figure 1E). Analysis of the iMETOS®
data records showed that conditions for strawberry anthracnose in 2018 were favourable
in August; 5–7 days were suitable for the spread of infection (Farms 4 and 3) (Table 2).
The following factors determined that the risk periods in 2018 for infection: air temperature
between 12.0–25.1 ◦ C and a leaf wetness period lasting more than 720 min.
Agriculture 2021, 11, 80
6 of 13
Table 2. Conditions for strawberry C. acutatum development, according to iMETOS® meteorological station data in 2018.
Farm 3
Infection Conditions
Air temperature
min-max, ◦ C
Leaf wetness
period, min
Total favourable days
Risk days (Days of
the month)
Farm 4
May
June
July
August
May
June
July
August
10.6–21.7
9.4–20.9
11.5–24.8
13.4–25.1
11.5–22.5
11.6–22.0
11.9–25.3
13.2–24.9
0–925
0–430
0–990
0–1180
0–685
0–240
0–330
0–1440
1
0
4
5
0
0
0
2, 3, 13, 30.
11, 12, 14,
25, 26.
7
11, 12, 15,
25, 26,
27, 29.
15
The analysis of iMETOS® meteorological station data showed that, in 2019, favourable
conditions for the spread of C. acutatum infection occurred during strawberry flowering
at the end of May (for 3–4 days) in Farms 1, 2 and 3. (Table 3). The meteorological
station data for 2018 were different compared to 2019. The highest air temperature was
in June, but the amount of precipitation and leaf wetness was low. Therefore, the risk of
infection lasted 2–3 days but did not occur in Farm 4. However, sufficient precipitation,
the temperature and leaf wetness conditions in July created favourable conditions for the
spread of C. acutatum (favourable for 8–11 days). The risk of infection lasted 4–7 days
in August (Table 3). The following factors determined the risk periods for infection:
air temperature between 12–25.8 ◦ C and a leaf wetness period lasting more than 720 min.
Table 3. Conditions for strawberry C. acutatum development, according to iMETOS® meteorological
station data in 2019.
Air
Temperature
Min-Max, ◦ C
Leaf
Wetness
Period, Min
May
June
July
August
May
June
July
August
May
June
July
August
May
June
3.8–20.1
15.1–24.7
12.1–22.9
13.6–21.4
4.3–30.8
15.1–25.8
12.5–23.1
14.2–22.1
4.3–21.6
15.1–25.8
12.5–23.1
14.2–22.1
5.2–22.1
16.4–26.3
0–1375
0–1015
0–1440
0–990
0–1425
0–1000
0–1430
0–995
0–1345
0–1000
0–1430
0–920
0–1055
0–680
4
3
8
6
3
2
8
5
0
2
8
5
3
0
July
12.7–22.8
0–1375
11
August
14–22.1
0–1025
7
Infection
Conditions
Farm 1
Farm 2
Farm 3
Farm 4
Total
Risk Days (Days of
Favourable Days
the Month)
23,27,28,29.
1,14,17.
4,5,7,8,9,10,16,17.
8,9,10,21,22,30.
23,27,28.
1,17.
5,7,8,9,10,16,17,22.
8,9,21,22,30.
1,17.
5,7,8,9,10,11,16,17
9,10,14,15,21.
11,29,31.
3,7,8,9,10,11,16,17,18,
22,27.
2,9,10,11, 21,22,30.
Meteorological data for 2019 showed that the most favourable conditions for the
spread of anthracnose occurred at the end of May and in the first ten days of July. However,
the prevailing temperature was below the optimum. Meteorological data showed that
the favourable conditions for strawberry anthracnose spread varied in different years.
Sufficient precipitation and long periods of leaf wetness provided suitable conditions for
the spread of C. acutatum infection. Therefore, it can be stated that, in a colder climate,
the temperature favourable for the spread of anthracnose is between 15.0–22.0 ◦ C. According to the meteorological data obtained in Farms 1 and 2, the conditions for the spread of
Agriculture 2021, 11, 80
spread of anthracnose occurred at the end of May and in the first ten days of July. However, the prevailing temperature was below the optimum. Meteorological data showed
that the favourable conditions for strawberry anthracnose spread varied in different years.
Sufficient precipitation and long periods of leaf wetness provided suitable conditions for
7 of the
13
the spread of C. acutatum infection. Therefore, it can be stated that, in a colder climate,
temperature favourable for the spread of anthracnose is between 15.0–22.0 °C. According
to the meteorological data obtained in Farms 1 and 2, the conditions for the spread of
strawberry anthracnose differ very slightly in 2019. More favourable conditions for the
strawberry anthracnose differ very slightly in 2019. More favourable conditions for the
spread of C. acutatum infection occurred at the beginning of strawberry vegetation.
spread of C. acutatum infection occurred at the beginning of strawberry vegetation.
3.2.Strawberry
StrawberryContamination
Contamination
3.2.
studyof
ofthe
thecontamination
contaminationofofdifferent
differentparts
partsofofstrawberry
strawberryplants
plantswith
withpathogenic
pathogenic
AAstudy
fungi
showed
that
infestation
of
strawberry
leaves
and
stems
was
similar
(Figure
2). The
fungi showed that infestation of strawberry leaves and stems was similar (Figure 2). The
reresults
from
Farm
1
showed
that
the
highest
contamination
with
pathogenic
fungi
was
sults from Farm 1 showed that the highest contamination with pathogenic fungi was
observed in
in cv.
cv. ‘Malvina’
and
leaves,
respectively),
with
the conobserved
‘Malvina’(75.3%
(75.3%and
and65.8%,
65.8%,stems
stems
and
leaves,
respectively),
with
the
tamination
being
evenly
distributed
on
leaves
and
stems.
The
lowest
contamination
was
contamination being evenly distributed on leaves and stems. The lowest contamination
observed
in cv.
plantplant
parts.parts.
Contamination
of plantofparts
similar
cultivars
was
observed
in‘Vibrant’
cv. ‘Vibrant’
Contamination
plantwas
parts
was in
similar
in
in Farm in
2. Farm
Cv. ‘Rumba’
grown in
Farmin3 Farm
had a3high
in its stems
and leaves
cultivars
2. Cv. ‘Rumba’
grown
had ainfestation
high infestation
in its stems
and
(69% and
respectively).
leaves
(69%47.2%
and 47.2%
respectively).
Figure 2. Fungal contamination of various strawberry cultivars leaves and stems (%). (A) Farm 1 cv. ‘Asia’, ‘Rumba’, ‘Polka’,
‘Malvina’,
‘Florence’; (B)ofFarm
2 cv.strawberry
‘Asia’, ‘Malvina’,
’Flair’;
(C)and
Farm
3 cv.(%).
‘Rumba’,
‘Polka’,
Figure 2. ‘Vibrant’,
Fungal contamination
various
cultivars
leaves
stems
(A) Farm
1 cv.‘Senga
‘Asia’,Sengana’;
‘Rumba’,
(D)
Farm ‘Malvina’,
4 cv. ‘Asia’,‘Vibrant’,
‘Rumba’,‘Florence’;
‘Sonata’, ‘Malvina’,
Results
are presented
means
4). ‘Rumba’, ‘Polka’, ‘Senga
‘Polka’,
(B) Farm ‘Elkat’.
2 cv. ‘Asia’,
‘Malvina’,
’Flair’;as(C)
Farm(n3=cv.
Sengana’; (D) Farm 4 cv. ‘Asia’, ‘Rumba’, ‘Sonata’, ‘Malvina’, ‘Elkat’. Results are presented as means (n = 4).
The results differed between leaves and the stem in different strawberry cv. The contamination
was highest
when
comparing
in the strawberry
same cvs., for
The results
differed
between
leavesthe
andobtained
the stemresults
in different
cv.example,
The con‘Rumba’
andwas
‘Malvina’,
different farms
(Figureresults
2).
tamination
highestgrown
when in
comparing
the obtained
in the same cvs., for examof ‘Malvina’,
strawberrygrown
plant parts
indicated
that(Figure
strawberry
ple, Evaluation
‘Rumba’ and
in different
farms
2). leaves and stems were
similarly
contaminated
with
pathogenic
fungi.
Differences
between
strawberry
cultivars
Evaluation of strawberry plant parts indicated that strawberry leaves
and stems
were
were
observed.
The
highest
contamination
with
pathogenic
fungi
was
observed
in
‘Malvina’
similarly contaminated with pathogenic fungi. Differences between strawberry cultivars
stems and leaves in two strawberry farms. Contamination of ‘Rumba’ plant parts with
pathogenic fungi was lower than ‘Malvina’ in Farms 1 and 4. However, results obtained
in Farm 3 showed contamination of the stems and leaves with pathogenic fungi in cv.
‘Rumba’ was relatively high.
Our data indicate (Table 4) that the isolated fungi were Mycosphaerella spp., Alternaria spp., Fusarium spp., Colletotrichum spp., Mucor spp., Penicillium spp., Phytophthora
spp., Botrytis spp. and that Trichoderma spp. was the most frequently isolated fungus
from the leaf and stem samples of strawberry plants collected from cv. ‘Rumba’, ‘Asia’,
‘Florence’, ‘Malvina’ and ‘Senga Sengana’. The Colletotrichum spp. pathogen was most
Agriculture 2021, 11, 80
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frequently found in cv. ‘Malvina’ compared with other tested cultivars. Identification was
carried out according to the cultural and morphological characteristics.
Table 4. Frequency (%) of isolated fungi from the leaves and stems of strawberry plants, 2018–2019.
Frequency of Isolated Fungi (%)
Isolated
Fungi/Cultivar
No.
%
No.
Rumba
Mycosphaerella spp.
Alternaria spp.
Unknown
Fusarium spp.
Colletotrichum spp.
Mucor spp.
Penicillium spp.
Phytophthora spp.
Botrytis spp.
Trichoderma spp.
Total
0
4
10
46
2
1
15
12
0
2
92
0
4.3
10.9
50
2.2
1.1
16.3
13
0
2.2
100
%
Asia
0
41
27
36
2
5
12
8
2
5
138
No.
%
No.
Florence
0
29.7
19.6
26.1
1.5
3.6
8.7
5.8
1.4
3.6
100
0
7
11
9
3
0
51
4
9
0
94
0
7.4
11.7
9.6
3.2
0
54.3
4.2
9.6
0
100
%
No.
Senga
Sengana
Malvina
21
10
27
40
5
14
10
8
3
13
151
%
13.9
6.6
17.9
26.5
3.3
9.3
6.6
5.3
2
8.6
100
0
22
6
14
1
3
4
1
0
2
53
0
41.5
11.3
26.4
1.9
5.7
7.5
1.9
0
3.8
100
No. = Number of isolated fungi; % = Percentage count of isolated fungi.
3.3. Soil Contamination
Soil samples from leading strawberry farms were collected to determine the prevalence of pathogens in the soil, in which the different strawberries cultivars were grown.
During our research, 571 bacteria and only 99 fungal samples were isolated from the soil.
The species of fungi detected were: Colletotrichum spp., Fusarium spp., Penicillium spp.,
Aspergillus spp., Alternaria spp., Botrytis spp., Mucor spp. and others. The bacteria CFU was
higher than fungi in all strawberry cultivars. The total amount of colony-forming units
detected in the soil is presented in Table 5.
Table 5. The total amount of colony-forming units (CFU g−1 ) in strawberry soil from different farms.
Means followed by the same letter did not differ significantly (p < 0.05).
Total Amount, CFU/g−1
Farm
Farm 1
Farm 2
Farm 3
Farm 4
Cultivar
Bacteria
Fungi
´Florence´
´Asia´
´Rumba´
´Vibrant´
´Flair´
´Malvina´
´Rumba´
´Polka´
´Asia´
´Elkat´
´Malvina´
´Sonata´
´Deluxe´
3.98 ± 0.69 cd
4.14 ± 0.48 d
3.92 ± 1.17 bcd
4.13 ± 1.02 d
3.48 ± 0.27 abc
3.48 ± 0.62 abc
4.05 ± 0.50 d
3.18 ± 0.58 ab
3.18 ± 0.64 ab
4.17 ± 0.87 d
2.87 ± 0.85 a
4.49 ± 0.41 f
4.49 ± 0.65 f
3.60 ± 0.40 bcd
3.44 ± 0.82 bcd
3.24 ± 0.29 ab
3.30 ± 0.63 ab
3.00 ± 0.63 a
3.10 ± 0.64 ab
3.18 ± 0.29 ab
2.70 ± 0.41 a
3.00 ± 0.71 a
3.72 ± 0.91 d
3.60 ± 0.63 bcd
2.70 ± 0.27 a
3.10 ± 0.25 ab
Results are presented as means n = 4 ± SE.
The lowest CFU of bacteria was determined in a soil sample taken from Farm 4
(2.87 × 103 CFU/g−1 ), where various strawberry cv. were grown, but this was particularly low for the ‘Malvina’ cv. However, the CFU of fungal pathogens was one of
the highest (3.60 × 103 CFU/g−1 ). An increase in bacteria CFU was found in ‘Sonata’
(4.49 × 103 CFU/g−1 ) and ‘Deluxe’ (4.49 × 103 CFU/g−1 ) from Farm 4 soil samples. Farm 4
‘Sonata’ and Farm 3 ‘Polka´ had the lowest CFU of fungi (CFU 2.70 × 103 CFU/g−1 ).
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Among all evaluated soil samples from different farms, the highest CFU of fungi were found
in Farm 4 ‘Elkat’ (3.72 × 103 CFU/g−1 ). The soil contamination of bacteria ranged from 3.92
to 4.14 × 103 CFU/g−1, and fungal pathogens ranged from 3.24 to 3.60 × 103 CFU/g−1
among different strawberry cv. in Farm 1. In this study, we found that ‘Rumba’ had
similar contaminations of bacterial and fungal pathogens in different growing locations.
However, in Farm 1, ‘Asia’ had significantly higher contamination of bacterial and fungal
pathogens than those cultivated in Farm 4. The ‘Polka’ in Farm 3 was the least infected
with soil pathogens compared with other cultivars. The lowest CFU of soil pathogens was
detected in Farm 3 compared with Farms 1, 2 and 4. Soil contamination indicates that
there were higher concentrations of pathogens. Colletotrichum spp. was observed in only
three soil samples, that is, one sample from Farm 4 and 2 samples from Farm 1. From our
results, it can be concluded that the anthracnose that causes Colletotrichum spp. was not
equally prevalent in the soil of all strawberry farms. Our data show that bacterial and
fungal pathogens distribution varies in different cultivars and locations. However, as some
cultivars are more susceptible to some pathogens, their distribution was higher.
3.4. Effect of Temperature on Colletotrichum acutatum Growth
Temperature is one of the essential factors influencing Colletotrichum spp. growth.
The isolates of C. acutatum showed significant differences in fungal growth under different
temperature conditions. The highest colony growth rate was observed at 25 ◦ C, and the
lowest at 5 ◦ C. The optimal temperature range was 20–25 ◦ C, and the maximum growth
rate was from 4.41 to 6.01 cm, respectively. Significant differences were observed between
temperatures of 20–25 ◦ C at 7 DPI. C. acutatum mycelium growth differs by only 0.03 cm
at 5 ◦ C after 4 and 7 DPI. The mycelium of C. acutatum was able to grow at 5 and 10 ◦ C,
but growth was slower compared with other temperatures. Furthermore, no visible colonies
were observed at 2 DPI at 5 and 10 ◦ C. Our data revealed that at 10 ◦ C (1.20 cm), C. acutatum
mycelium grew faster compared with 5 ◦ C (0.6 cm) at 4 DPI. The mycelium diameter was
0.81, 1.61 and 2.73 cm after 2, 4 and 7 DPI at 15 ◦ C, respectively. No significant differences
were observed at 2 and 4 DPI. However, the highest growth was observed at 25 ◦ C after 2,
4 and 7 DPI (1.76, 3.35 and 6.01 cm, respectively).
The results of our experiment indicate significant differences in fungal growth under
different temperature conditions. In vitro temperature tests revealed that the optimal
temperature for C. acutatum development was between 20–25 ◦ C. However, the most
suitable temperature for C. acutatum development was 25 ◦ C (Table 6).
Table 6. Effect of temperature on C. acutatum mycelium growth after 2, 4 and 7 DPI. DPI–days
post-inoculation.
C. acutatum Mycelium Growth, cm (Factor A)
Temperatures,
(Factor B)
◦C
5
10
15
20
22
25
Average A (p = 0.054)
2DPI
4DPI
7DPI
Average B
(p = 0.064)
0.00 ± 0.00
0.00 ± 0.00
0.81 ± 0.02
1.25 ± 0.05
1.24 ± 0.11
1.76 ± 0.08
0.84
0.80 ± 0.00
1.20 ± 0.02
1.61 ± 0.03
2.68 ± 0.05
2.90 ± 0.06
3.35 ± 0.05
2.09
0.83 ± 0.02
2.44 ± 0.04
2.73 ± 0.04
4.41 ± 0.11
4.87 ± 0.10
6.01 ± 0.13
3.55 **
0.54 **
1.21
1.71
2.78 **
3.00
3.71 **
2.16
** statistically significant differences at p < 0.05. DPI—Days post-inoculation. Results are presented as means
n = 4 ± SE.
3.5. Susceptibility of Strawberries to C. acutatum
The detached strawberry leaf assay was developed to determine the susceptibility of
strawberry cv. to C. acutatum. The results revealed that C. acutatum isolate from strawberry
was able to cause anthracnose in tested cv. and were pathogenic. Clear C. acutatum necrotic
(black) areas developed around mycelial plugs on inoculated leaves, however, no necrotic
Agriculture 2021, 11, 80
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lesion was observed on control leaves. The ‘Elkat’ and ‘Deluxe’ cv. showed the highest
susceptibility (4.64 and 4.33, respectively). The cultivars ‘Malvina’ and ‘Sonata’ had a lower
disease severity index (3.77 and 2.89, respectively) and were not significantly different.
The ‘Rumba’ (1.50) and ‘Asia’ (1.83) cv. had a significantly lower disease severity index
(Figure 3).
Figure 3. The susceptibility of different strawberry cultivars inoculated by C. acutatum. Means followed by the same letter
did not differ significantly (p < 0.05).
4. Discussion
Climate change is promoting the spread of plant disease, and the spread of the anthracnose pathogen is noticeable. It is becoming complicated to predict meteorological
conditions as well as disease development. The variation between rainfall, temperature
and leaf wetness affects plant diseases [20]. The temperature and relative humidity are
potentially significant factors affecting the development of Colletotrichum species complexes.
We evaluated the meteorological conditions in a temperate climate for C. acutatum development. Our study showed that meteorological conditions have become more favourable
for C. acutatum [7,8,19,21,22,35]. Disease forecasting models help predict disease risks
and reduce fungicide application by 50%. The anthracnose advisory system based on
the AFR model showed that it could significantly reduce the number of sprayings [23,38].
Rasiukevičiūtė et al. [22] evaluated the iMETOS® strawberry Botrytis cinerea forecasting
model. Their results were very promising, as the pesticide applications were reduced based
on the forecasting model. Our results show that meteorological conditions vary in different
areas and years. We found that there were an optimal 12 days in 2018 and 26 days in 2019
for the development and spread of anthracnose in strawberry plants. The anthracnose
infection risk in Farm 3 in 2018 lasted for 10 days in May-August and for seven days
in Farm 4, only in August. Meanwhile, in 2019, in Farms 1 and 4 it lasted 21 days in
May-August, in Farm 2 for 18 days and 15 days in Farm 3.
Meteorological conditions influence the conditions for disease development. However,
there is always a source of infection. The primary source of infection is contaminated soil
and previous crops. Soilborne pathogens reduce strawberry yield by up to 20–30% [27–29].
We conducted a series of experiments to evaluate soil and the contamination of strawberry
plant parts by pathogens. Soil contamination shows that there are higher concentrations of
pathogens. In our research, 571 bacteria and only 99 fungal samples were isolated from the
Agriculture 2021, 11, 80
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soil. The number of bacteria in the soil was higher than that of fungal pathogens. However,
Colletotrichum spp. was not equally prevalent in the soil at all tested farms.
Strawberry plant part evaluation indicated that the contamination of strawberry
leaves and stems was similar. The highest level of contamination by pathogenic fungi was
observed in cv. ‘Malvina’ and ‘Rumba’ stems and leaves. According to the results obtained,
it can be stated that ‘Asia’ leaves and stems were least infected with pathogenic fungi.
Wagner et al. [6] indicated that ‘Florence’ was more susceptible to C. acutatum than other
strawberry cultivars, for instance, ‘Darselect’. The susceptibility of various cv. was unequal.
A source of inoculum is also essential for disease development. The susceptibility
of cv. is important for anthracnose development. Furthermore, the strawberry flower is
more susceptible compared to immature fruit [13]. Jacobs et al. [39] found that there are no
significant differences between Colletotrichum species, but a significant difference among
strawberry genotypes. The cv. ‘Elkat’ and ‘Deluxe’ showed the highest susceptibility;
however, ‘Rumba’ and ‘Asia’ had a lower disease severity index. Casado Diaz et al. [10] and
Wagner et al. [6] observed that ‘Camarosa’ was very susceptible to C. acutatum. We observed
a slight trend between soil and plant parts contamination with pathogenic fungi and
susceptibility to C. acutatum in two strawberry cvs. The highest soil contamination of
fungi was found in cv. ‘Elkat’, also cv. ‘Elkat’ was distinguished as the most susceptible to
C. acutatum among all studied cv. The Colletotrichum spp. pathogen was most frequently
found in cv. ‘Malvina’, soil and plant parts contamination by pathogenic fungi was also
found of the highest levels, furthermore, cv. ‘Malvina’ showed high susceptibility to
C. acutatum.
Temperature plays an essential role in Colletotrichum species complex development,
spore germination and appressorial formation [17]. In the literature, it is considered that
strawberry anthracnose is a warmer climate zone pathogen with an optimal temperature
of 26.7–32 ◦ C for C. fragariae and around 20 ◦ C for C. acutatum [12–15,18]. We evaluated
the influence of temperature on anthracnose mycelium development. Our data confirmed
the results of Feil et al. [5] that C. acutatum mycelium was able to grow at 5 and 10 ◦ C.
He et al. [15] observed that colony growth was fastest in the temperature range of 25–28 ◦ C;
however, we found that the optimal temperature for C. acutatum development was between
20–25 ◦ C.
5. Conclusions
This study confirmed that meteorological conditions play an essential role in pathogen
development. Pathogens’ adaptation to conditions that are not inherent in their growth
and their spread poses increasing management challenges. The soil and the remains of
plant parts are the primary sources of plant diseases.
The results of this study revealed that pathogen distribution in plant parts and soil
varied depending on cultivar. For C. acutatum, a temperature of 20–25 ◦ C is optimal
for pathogen development. The monitoring of meteorological conditions, evaluation of
inoculum source and the selection of less susceptible cultivars could reduce or avoid yield
losses caused by C. acutatum. In future, due to climate change, C. acutatum occurrence and
distribution will be affected.
Author Contributions: Conceptualisation: A.V. and N.R.; methodology: A.V., N.R. and A.M.; software: A.M.; validation: N.R. and A.V.; formal analysis: A.M.; investigation: A.M.; resources: N.R.;
data curation: A.M. and N.R.; writing—original draft preparation: A.M.; writing—review and editing:
N.R., A.V. and A.M.; visualisation: A.M. and N.R.; supervision: A.V. and N.R. All authors have read
and agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Conflicts of Interest: The authors declare no conflict of interest.
Agriculture 2021, 11, 80
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References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
Simpson, D. The economic importance of strawberry crops Chapter 1. In The Genomes of Rosaceous Berries and Their Wild
Relatives; Compendium of Plant Genomes; Hytönen, T., Graham, J., Harrison, R., Eds.; Springer International Publishing: Charm,
Switzerland, 2018; pp. 1–7, ISBN 9783319760209.
Jayawardena, R.S.; Huang, J.K.; Jin, B.C.; Yan, J.Y.; Li, X.H.; Hyde, K.D.; Bahkali, A.H.; Yin, S.L.; Zhang, G.Z. An account of
Colletotrichum species associated with strawberry anthracnose in china based on morphology and molecular data. Mycosphere
2016, 7, 1147–1163. [CrossRef]
Cannon, P.F.; Damm, U.; Johnston, P.R.; Weir, B.S. Colletotrichum—current status and future directions. Stud. Mycol. 2012,
73, 181–213. [CrossRef]
Udayanga, D.; Manamgoda, D.S.; Liu, X.; Chukeatirote, E.; Hyde, K.D. What are the common anthracnose pathogens of tropical
fruits? Fungal Divers. 2013, 61, 165–179. [CrossRef]
Feil, W.S.; Butler, E.E.; Duniway, J.M.; Gubler, W.D. The effects of moisture and temperature on the survival of Colletotrichum
acutatum on strawberry residue in soil. Can. J. Plant Pathol. 2003, 25, 362–370. [CrossRef]
Wagner, A.; Hetman, B. Susceptibility of strawberry cultivars to Colletotrichum acutatum J. H. Simmonds. Acta Sci. Pol. Hortorum Cultus 2013, 15, 209–219.
Zhang, L.; Song, L.; Xu, X.; Zou, X.; Duan, K.; Gao, Q. Characterisation and fungicide sensitivity of Colletotrichum species causing
strawberry anthracnose in Eastern China. Plant Dis. 2019, 104, 1960–1968. [CrossRef]
Peres, N.A.; Timmer, L.W.; Adaskaveg, J.E.; Correll, J.C. Lifestyles of Colletotrichum acutatum. Plant Dis. 2005, 89, 784–796.
[CrossRef]
Horowitz, S.; Yarden, O.; Zveibil, A.; Freeman, S. Development of a robust screening method for pathogenicity of Colletotrichum
spp. on strawberry seedlings enabling forward genetic studies. Plant Dis. 2004, 88, 845–851. [CrossRef]
Casado-Diaz, A.; Encinas-Villarejoa, S.; Santos, B.; Schiliro, E.; Yubero-Serrano, E.M.; Amil-Ruíz, F.; Pocovi, M.I.; Pliego-Alfaro, F.;
Dorado, G.; Rey, M.; et al. Analysis of strawberry genes differentially expressed in response to Colletotrichum infection. Physiol. Plant. 2006, 128, 633–650. [CrossRef]
Zhang, Q.Y.; Zhang, L.Q.; Song, L.L.; Duan, K.; Li, N.; Wang, Y.X.; Gao, Q.H. The different interactions of Colletotrichum
gloeosporioides with two strawberry varieties and the involvement of salicylic acid. Hortic. Res. 2016, 3, 1–10. [CrossRef]
Chandra, A.; Keizerweerd, A.T.; Que, Y.; Grisham, M.P. Loop-mediated isothermal amplification (lamp) based detection of
Colletotrichum falcatum causing red rot in sugarcane. Mol. Biol. Rep. 2015, 42, 1309–1316. [CrossRef] [PubMed]
Forcelini, B.B.; Seijo, T.E.; Amiri, A.; Peres, N.A. Resistance in strawberry isolates of Colletotrichum acutatum from Florida to
quinone-outside inhibitor fungicides. Plant Dis. 2016, 100, 2050–2056. [CrossRef] [PubMed]
Lu, J.; Ehsani, R.; Shi, Y.; Abdulridha, J.; Castro, A.I.; Xu, Y. Field detection of anthracnose crown rot in strawberry using
spectroscopy technology. Comput. Electron. Agric. 2017, 135, 289–299. [CrossRef]
He, L.; Li, X.; Gao, Y.; Li, B.; Mu, W.; Liu, F. Characterisation and fungicide sensitivity of Colletotrichum spp. from different hosts
in Shandong, China. Plant Dis. 2019, 103, 34–43. [CrossRef]
Anciro, A.; Mangandi, J.; Verma, S.; Peres, N.; Whitaker, V.M.; Lee, S. FaRCg1: A quantitative trait locus conferring resistance to
Colletotrichum crown rot caused by Colletotrichum gloeosporioides in octoploid strawberry. Theor. Appl. Genet. 2018, 131, 2167–2177.
[CrossRef]
Wang, Y.; Kerns, J.P. Temperature effects on formation of appressoria and sporulation of Colletotrichum cereale on two turfgrass
species. Plant Pathol. 2017, 13, 123–132.
Pavan, W.; Fraisse, C.W.; Cordova, L.G.; Peres, N.A. Development of the web-based disease forecasting system for strawberries.
Comput. Electron. Agric. 2011, 75, 169–175. [CrossRef]
Pavan, W.; Fraisse, C.W.; Cordova, L.G.; Peres, N.A. The Strawberry Advisory System: A Web-Based Decision Support Tool
for Timing Fungicide Applications in Strawberry. Technical Report. The Agricultural and Biological Engineering Department,
University of Florida, 2009; Bulletin AE450, pp. 1–4. Available online: http://cloud.agroclimate.org/tools/deprecated/sas/
publications/AE45000_SAS%202012.pdf (accessed on 9 June 2020).
Garrett, K.A.; Nita, M.; Wolf, E.D.; Esker, P.D.; Gomez-Montano, L.; Sparks, A.H. Chapter 21—Plant pathogens as indicators of climate
change. In Climate Change, 2nd ed.; Observed Impacts on Planet Earth. P.; Elsevier: Amsterdam, The Netherlands, 2016; pp. 325–338.
Rasiukevičiūtė, N.; Valiuškaitė, A.; Survilienė-Radzevičė, E.; Supronienė, S. Investigation of Botrytis cinerea risk forecasting model
of strawberry in Lithuania. In Proceedings of the Latvian Academy of Sciences, Section B. Natural, Exact and Applied Sciences; Rashal, I.,
Legzdin, a, A., Eds.; Sciendo: Riga, Latvia, 2013; Volume 67, pp. 195–198.
Rasiukevičiūtė, N.; Uselis, N.; Valiuškaitė, A. The use of forecasting model IMETOS® for strawberry grey mould management.
Zemdirb. Agric. 2019, 106, 143–150. [CrossRef]
Cordova, L.G.; Ellis, M.A.; Wilson, L.L.; Madden, L.V.; Peres, N.A. Evaluation of the Florida strawberry advisory system for
control Botrytis and Anthracnose fruit rots in Ohio. Plant Health Prog. 2018, 19, 182–187. [CrossRef]
Swett, C.L.; Butler, B.B.; Peres, N.A.; Koivunen, E.E.; Hellman, E.M.; Beaulieu, J.R. Using model-based fungicide programming to
effectively control Botrytis and Anthracnose fruit rots in Mid-Atlantic strawberry fields and co-manage strawberry sap beetle
(Stelidota geminate). Crop Prot. 2020, 134, 1–10. [CrossRef]
Valiuškaitė, A.; Raudonis, L.; Survilienė, E. Control of grey mould and white leaf spot in strawberry. Zemdirb. Agric. 2008,
95, 221–226.
Agriculture 2021, 11, 80
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
13 of 13
Valiuškaitė, A.; Uselis, N.; Kviklys, D.; Lanauskas, J.; Rasiukevičiūtė, N. The effect of sustainable plant protection and apple tree
management on fruit quality and yield. Zemdirb. Agric. 2017, 104, 353–358. [CrossRef]
Subbarao, K.V.; Kabir, Z.; Martin, F.N.; Koike, S.T. Management of soilborne diseases in strawberry using vegetable rotations.
Plant Dis. 2007, 91, 964–972. [CrossRef] [PubMed]
Feliziani, E.; Romanazzi, G. Postharvest decay of strawberry fruit: Etiology, epidemiology, and disease management. J. Berry Res.
2016, 6, 47–63. [CrossRef]
Dziedzinska, R.; Vasickova, P.; Hrdy, J.; Slany, M.; Babak, V.; Moravkova, M. Foodborne bacterial, viral, and protozoan pathogens
in field and market strawberries and environment of strawberry farms. J. Food Sci. 2018, 83, 3069–3075. [CrossRef] [PubMed]
Carisse, O.; Morissette-Thomas, V.; Van der Heyden, H. Lagged association between powdery mildew leaf severity, airborne
inoculum, weather, and crop losses in strawberry. Phytopathology 2013, 103, 811–821. [CrossRef]
Aguado, A.; Pastrana, A.M.; Santos, B.; Romero, F.; Sánchez, M.C.; Capote, N. The efficiency of natural products for the control of
Colletotrichum acutatum monitored by real-time PCR. Acta Hortic. 2014, 1049, 329–334. [CrossRef]
Mahilrajan, S.; Nandakumar, J.; Kailayalingam, R.; Manoharan, N.A.; Srivijeindran, S. Screening the antifungal activity of essential
oils against decay fungi from palmyrah leaf handicrafts. Biol. Res. 2014, 47, 35. [CrossRef]
Rasiukevičiūtė, N.; Rugienius, R.; Šikšnianienė, J.B. Genetic diversity of Botrytis cinerea from strawberry in Lithuania.
Zemdirb. Agric. 2018, 105, 265–270. [CrossRef]
Xie, L.; Zhang, J.; Wan, Y.; Hu, D. Identification of Colletotrichum spp. isolated from strawberry in Zhejiang Province and Shanghai
City, China. J. Zhejiang Univ. Sci. B 2010, 11, 61–70. [CrossRef]
Gillett, J.M.; Schilder, A.C. Environmental Requirements for Infection of Blueberry Fruit by Colletotrichum Acutatum. Acta Hortic.
2009, 810, 355–360. [CrossRef]
Bahroun, A.; Jouseet, A.; Mhamdi, R.; Mrabet, M.; Mhadhbi, H. Anti-fungal activity of bacterial endophytes associated with
legumes against Fusarium solani: Assessment of fungi soil suppressiveness and plant protection induction. Appl. Soil Ecol. 2018,
124, 131–140. [CrossRef]
Bajpai, S.; Shukla, P.S.; Asiedu, S.; Pruski, K.; Prithiviraj, B. A biostimulant preparation brown seaweed Ascophyllum nodosum
suppresses powdery mildew of strawberry. Plant Pathol. 2019, 35, 406–416.
Cordova, L.G.; Madden, L.V.; Amiri, A.; Schnabel, G.; Peres, N.A. Meta-analysis of a web-based disease forecast system for control
of Anthracnose and Botrytis fruit rots of strawberry in Southeastern United States. Plant Dis. 2017, 101, 1910–1917. [CrossRef]
Jacobs, R.L.; Adhikari, T.B.; Pattison, J.; Yencho, G.C.; Fernandez, G.E.; Louws, F.J. Assessing rate-reducing foliar resistance to
anthracnose crown rot and fruit rot in strawberry. Plant Dis. 2020, 104, 398–407. [CrossRef]