Brassica juncea powdery mildew epidemiology and weatherbased forecasting models for India - a case study
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PflKrankh. 5/04 Brassica juncea powdery mildew epidemiology and weather-based forecasting models 429
Zeitschrift für Pflanzenkrankheiten und Pflanzenschutz
Journal of Plant Diseases and Protection
111 (5), 429–438, 2004, ISSN 0340-8159
© Eugen Ulmer GmbH & Co., Stuttgart
Brassica juncea powdery mildew epidemiology and weather-
based forecasting models for India – a case study
Die Krankheitsentwicklung des Echten Mehltaus (Erysiphe cruciferarum) auf Bras-
sica juncea und wetterbasierende Modelle zur Vorausschätzung seiner epidemiolo-
gischen Entwicklung in Indien – Eine Fallstudie
A. G. Desai1, C. Chattopadhyay2 *, Ranjana Agrawal3, A. Kumar3, R. L. Meena2, P. D. Meena2,
K. C. Sharma2, M. Srinivasa Rao4, Y. G. Prasad4, Y. S. Ramakrishna4
1
Gujarat Agricultural University, S. K. Nagar 385506, Gujarat, India
2
National Research Centre on Rapeseed-Mustard (ICAR), Sewar, Bharatpur 321303, Rajasthan,
India
3
Indian Agricultural Statistics Research Institute (ICAR), New Delhi 110012, India
4
Central Research Institute for Dryland Agriculture (ICAR), Santoshnagar, Saidabad, Hyderabad
500059, India
* corresponding author: Plant Pathology Section, National Research Centre on Rapeseed-Mustard
(ICAR), Sewar, Bharatpur 321303, Rajasthan, India; Phone: +91 5644 260379; Fax: +91 5644
260419; E-mail: chirantan_cha@hotmail.com
Received 7 June 2004; accepted 28 June 2004
Summary
A field experiment was laid out at S. K. Nagar and Bharatpur with Indian mustard (Brassica juncea)
cultivars ‘Varuna’ and Local (‘GM-2’ at S. K. Nagar; ‘PCR-7’ at Bharatpur) sown on 10 dates at weekly
intervals. Each plot was 1.5 m × 5 m size with a spacing of 30 cm × 10 cm. Recommended doses of N
and P fertilizers were applied with no application of K fertilizer; insect-pest protection practices were
undertaken viz., seed treatment with imidachloprid (5 g/kg) and spray 0.25 ml/l oxydematon-methyl
at 15-day intervals. No protection was taken against any disease. First appearance of powdery mildew
disease (Erysiphe cruciferarum) on leaves of mustard occurred during 50–120 days after sowing (d. a. s.),
with higher frequencies in later part of the crop period. Severity of the disease was favoured by > 5 days
of ≥ 9.1 h of sunshine, > 2 days of morning (maximum) relative humidity (r. h.) of < 90 %, afternoon
(minimum) r. h. 24–50 %, minimum temperature > 5 °C and a maximum temperature of 24–30 °C.
Regression analysis showed maximum temperature, minimum (afternoon) r. h. of the week preceding
the date of observation were respectively positively and negatively correlated to disease severity both in
cvs. ‘Varuna’ and ‘GM-2’ within the specified ranges. Models based on weather 1 week preceding date
of observation for prediction of progression of powdery mildew severity at S. K. Nagar and Bharatpur
were devised. Regional and cultivar-specific models could predict the crop age at which powdery
mildew first appears on the crop, the highest mildew severity on the crop and the crop age at peak
mildew severity at least 3 weeks ahead of first appearance of the disease on the crop, thus allowing
growers to undertake timely fungicidal sprays. Models that stood the test of validation are reported.
Key words: Erysiphe cruciferarum; Brassica juncea; crop age; powdery mildew; epidemiology; fore-
casting models; weather430 Desai et al. 5/04 PflKrankh.
Zusammenfassung
Ein Feldexperiment wurde in S. K. Nagar und Bharatpur, Indien, angelegt unter Verwendung der
Brassica-Sorte ’Varuna’ und anderer örtlicher Sorten (c. ‘GM-2’ in S. K. Nagar und c. ’PCR-7’ in
Bharatpur), die in wöchentlichen Abständen an 10 Zeitpunkten gesät wurden. Jedes Feldstück hatte
eine Größe von 1,5 m × 5 m, mit 30 cm × 10 cm Abstand von einander. Empfohlene Mengen an N-
und P-Dünger wurden eingesetzt ohne Verwendung von K-Dünger. Zur Bekämpfung von Schadin-
sekten wurden die Samen mit Imidachloprid vorbehandelt (5 g/kg Samen) und die Pflanzen alle
15 Tage mit 0,25 ml/l Oxydematon-methyl besprüht. Es wurden keine Schutzmaßnahmen gegen
jegliche Art von Pilzkrankheiten angewendet. Der Echte Mehltau (Erysiphe cruciferarum) wurde 50–
120 Tage nach der Aussaat (d. a. s) erstmals auf den Brassica-Blättern beobachtet, wobei eine größere
Häufigkeit zum Ende der pflanzlichen Entwicklung auszumachen war. Die Stärke des Befalls wurde
begünstigt durch ≥ 9,1 h Sonnenschein über einen Zeitraum von ≥ 5 Tagen, > 2 Tage relativer
Luftfeuchte (RLF) von < 90 % am Morgen (Maximum) und 24–50 % am Abend (Minimum), einer
minimalen Temperatur von > 5 °C und einer maximalen Temperatur von 24–30 °C. Regressions-
analysen zeigten, dass bei beiden Sorten ‘Varuna’ und ‘GM-2’ die Daten der maximalen Temperatur
und der abendlichen RLF (Minimum) der Woche, welche dem Beobachtungszeitpunkt vorausging,
innerhalb gegebener Parameter jeweils positiv und negativ zur Befallsstärke korrelierten. Modelle, die
auf den Wetterdaten der Woche vor dem ersten Krankheitsbefall basieren, konnten für die Vorhersage
der Befallsstärke durch den Echten Mehltau in S. K. Nagar und Bharatpur entwickelt werden. Mit
diesen regional- und sortenabhängigen Modellen konnte der Entwicklungsstand der Pflanzen vorher-
gesagt werden, in dem der erste Befall des Echten Mehltaus zu erwarten war, das maximale Befalls-
niveau und das Entwicklungsstadium bei maximaler Befallsausprägung. Diese Vorhersage war zumindest
3 Wochen vor dem ersten Auftreten der Krankheitssymptome möglich, was den Landwirten gestattet,
notwenige Maßnahmen zu ergreifen. Die mit Validationstests bestätigten Modelle werden vorgestellt.
Stichwörter: Erysiphe cruciferarum; Brassica juncea; Entwicklungsstadium; Echter Mehltau; Epide-
miologie; Modell zur Vorhersage; Wetter
1 Introduction
Indian mustard [Brassica juncea (L.) Czern & Coss.] is one of the major oilseed crops cultivated in India
and around the world. Out of 36217 thousand tonnes of rapeseed-mustard seed produced over 23961
thousand ha in the world, India produces 4088 thousand tonnes from 4626 thousand ha (Damodaram
and Hegde 2002). Powdery mildew disease caused by Erysiphe cruciferarum Opiz. ex. L. Junell,
infecting all aboveground parts of the plant has been reported from several parts of the world and is
considered an important constraint in husbandry of Indian mustard in India. Though total destruction
of the crop due to the disease is rare and usually yield losses at harvest are not staggering, they can reach
up to 17 % (Dange et al. 2002) in India while it may be 10–30 % or up to 1200 kg/ha on B. rapa in
France (Penaud 1999). Severity of powdery mildew on Indian mustard differs between seasons and
regions as also between individual cultivars within a region in India. In the absence of stable, desirable
and diverse source of resistance to the mustard powdery mildew, fungicides remain the only effective
means to manage the disease (Singh and Solanki 1974). Despite high consumption of fungicides on
mustard crops in India (IASRI 2002), timing their application has not been optimal. Crops requiring
treatment have been left unsprayed and others sprayed unnecessarily. Knowledge on the epidemiology
of the mildew on mustard is limited. In India, Indian mustard is sown from September to November,
depending on the prevailing temperature and availability of soil moisture for seed germination. Harvest
occurs from February to May. Off-season crops are grown in non-traditional areas from May to
September and this, coupled with harbouring of the fungal pathogen by oilseed and vegetable Brassica
crops, alternative hosts (Capsella bursa-pastoris, Coronopus didymus, Raphanus sativus, Iberis amara),
could be reasons for carryover of the E. cruciferarum from one crop season to another as cleistothecia,
conidia or mycelia (Sharma 1979; Saharan and Kaushik 1981). Thus, air-borne spores of E. cruci-
ferarum form the primary source of inoculum of this polycyclic disease (Kolte 1985). Efficient,
economical and environment friendly control of the mildew may be obtained through knowledge of itsPflKrankh. 5/04 Brassica juncea powdery mildew epidemiology and weather-based forecasting models 431 timing of attack in relation to weather factors, which may enable prediction of its occurrence so as to allow growers to take timely fungicidal sprays for an efficient crop management. Weather is an exceptionally important factor in the severity of powdery mildew of Indian mustard. Preliminary work indicates effects of moderate (17.7–21.5 °C) temperature, low (67–77 %) relative humidity (r. h.) on occurrence of the mildew on Indian mustard (Saharan and Kaushik 1981; Dang et al. 1998). These reports indicate relationships between different weather factors and powdery mildew occurrence through empirical models. However, the available information provides no insight into real-time prediction of the disease on Indian mustard in different parts of India for age of the crop at first appearance of the mildew, expected highest severity of powdery mildew during the crop season and crop age at peak severity of the disease. Accurate forecast of the crop age at first appearance of the disease and the risk of a mildew epidemic would enable farmers to decide on optimum timing of fungicide sprays and to avoid unnecessary pesticide application. Hence, the present study was under- taken to develop forecasts for crop age at time of first appearance of powdery mildew or pinpoint the combination of weather and crop growth stage that triggers initial infection when inoculum is not limiting, for crop age when mildew severity is maximum and for highest severity of the disease on the crop in the season. 2 Materials and methods Selection of centres for the study was based on the importance of powdery mildew as a disease problem in the region. All experiments relied entirely on natural incidence of the disease. Field trials at S. K. Nagar (24° 5’ N; 72° E; 189 m above msl) and Bharatpur (27° 12’ N; 77° 27’ E; 140 m above msl) were laid out in 1999–2000, 2000–2001, 2001–2002, 2002–2003 and 2003–2004 post-rainy (rabi) crop seasons sown on 10 dates at weekly intervals (01, 08, 15, 22, 29 Oct, 05, 12, 19, 26 Nov and 03 Dec) with cv. ‘Varuna’ and an important cultivar in the locality (cv. ‘GM-2’ at S. K. Nagar, cv. ‘PCR-7’ at Bharatpur). Each plot measured 1.5 m × 5 m with a spacing of 30 cm × 10 cm. Recommended doses of N and P fertilizers (NRCRM 1999) were applied with no application of K fertilizer; insect-pest protection practices were undertaken as seed treatment with imidachloprid (7 g/kg) and spray of 0.25 ml/l oxydematon-methyl at 15-day intervals. No protection was taken against any disease. Data for first date of appearance of powdery mildew and gradual progress of the same on the Indian mustard crops was monitored in both the locations. Observations for percent disease severity (PDS) were recorded twice a week (on Tuesday and Friday) until harvest from 10 randomly tagged plants in each plot of the crop on leaves and pods following scale of Conn et al. (1990). Weather data for maximum and minimum temperatures, morning (07:00 h Local Apparent Time or LAT calculated on the basis of longitude of a location as per standard norms of the World Meteorological Organisation or WMO, Ghadekar 2002) and afternoon (14:00 h LAT) r. h., sunshine hours and rainfall were recorded from standard meteorological observatories at both the locations. The meteorological observatories at the locations were 130–140 m from the site of experiments and the data recording instruments were installed as per standard specifications of the WMO (Ghadekar 2002). For each assessment date, PDS of 10 tagged plants from each plot were averaged to give a single value. Different ranges of weather variables of 1 week preceding the assessment date were used as independent variables to identify the boundary and favourable conditions that influenced the depend- ent variables or powdery mildew disease severity on the crops following initial infection, through regression analysis. Correlations of timing (days after sowing or d. a. s.) of first appearance of the mildew on the plants, highest severity of the disease on the crop and crop age (d. a. s.) at peak severity of the mildew with weather variables were studied. Linear prediction models based on the weather parameters as independent variables and crop age at time of first appearance of the disease on the crop (Yx), crop age at highest severity of the disease (Yy) and peak severity of the disease in the season (Yz) at each week starting from week of sowing as dependent variables were fitted by multiple stepwise regression using data of initial 4 years separately. For each weather parameter, a composite weather variable (zi) was developed as the weighted sum of the weather variable in different weeks starting from pre-sowing week up to week of the prediction, weightings being the correlation coefficients between dependent variables under study with the respective weather parameter in different weeks (Ranjana
432 Desai et al. 5/04 PflKrankh.
Agrawal et al. 1986). Similarly, interaction terms (zij) were developed as weighted sums of product
between two weather variables, weightings being correlation coefficients of dependent variable under
study with products of weather variables in respective weeks. The important weather indices were
selected through stepwise regression.
Models were fitted at different points of time, i. e., prediction of highest disease severity or crop age
at peak disease severity or crop age at first appearance of the disease at the time of sowing, 2nd week after
sowing and so on (f = 1, 2, …). The dependent variables were related with weather parameters in
different weeks. The interactions of weather parameters were also found to be significant. Of the
various models developed, the model recommended is of the form:
p p
Y = a0 + Σaizi + Σbijzij + e ... (Equation 1a)
i=1 i≠j
= a0 + a1z1 + a2z2 + .......... + a6z6 + b12z12 + ....... + b56z56 + e ... (Equation 1b)
where
f
zi = Σriwxiw ... (Equation 2a)
w=1
f
zij = Σrijwxiwxjw ... (Equation 2b)
w=1
with Y being the dependent variable, xiw the value of i-th weather parameter in w-th week, riw the value
of correlation coefficient between Y and i-th weather parameter in w-th week, rijw the correlation
coefficient between Y and product of xi and xj in w-th week, p the number of weather variables, f the
week of prediction and e the error term. The fifth (2003–2004) crop season was used to validate the
models for forecasting the targeted parameters at different locations based on the models developed in
each of the initial 4 years for each of the parameters, viz., highest disease severity, crop age at peak
disease severity and crop age at first appearance of the disease. Further, for weekly monitoring of disease
severity after first appearance, models were fitted through stepwise regression using disease severity and
weather of preceding week, age at first appearance of disease and week of sowing. The model is of the
form:
Yi = a + b T + cA + d Yi-1 + f1 x1 + f2 x2 + ... ... (Equation 3)
where Yi is disease severity at i-th week after first appearance of disease (Y0 is disease severity at first
appearance), T is week of sowing, A is age at first appearance of disease and xi are weather variables in
preceding week.
3 Results and discussion
Severity of powdery mildew on Indian mustard was higher in later sown crops (Fig. 1), which matched
earlier findings (Saharan and Kaushik 1981). Initiation of the powdery mildew disease on mustard
occurred during 50–120 d. a. s. with higher frequencies recorded in later part of crop growth. Disease
intensity is reported to increase with plant age (Saharan and Kaushik 1981), which could be the
reason for higher frequencies of disease initiation observed in older plants.
Correlation study of the data from the relevant centres revealed that powdery mildew severity on the
plants was favoured by > 5 days of ≥ 9.1 h of sunshine (R2: 0.9), > 2 days of morning (maximum) r. h.
of < 90 % (R2: 0.7), afternoon (minimum) r. h. 24–50 % (R2: 0.92), minimum temperature > 5 °C (R2:PflKrankh. 5/04 Brassica juncea powdery mildew epidemiology and weather-based forecasting models 433
03/12/2002
26/11/2002
19/11/2002
12/11/2002
05/11/2002
Dates of sowing
29/10/2002
‘GM-2’
22/10/2002
‘Varuna’
15/10/2002
08/10/2002
01/10/2002
0 5 10 15 20 25 30
% powdery mildew severity
Fig. 1. Effect of dates of sowing Indian mustard on powdery mildew severity on two cultivars at S. K. Nagar.
0.87) and a maximum temperature of 24–30 °C (R2: 0.83). This was partially in agreement with earlier
findings (Saharan and Kaushik 1981; Dang et al. 1998) and the minor disagreement regarding
ranges of maximum and minimum temperatures favouring mildew severity (Dang et al. 1998) could
be due to difference in requirements of the geographical isolates as the earlier studies were conducted at
a different location. The earlier report (Crowton and Kennedy 1999) indicating estimated percent-434 Desai et al. 5/04 PflKrankh.
age infection being negatively correlated to the period of exposure to wetness and long periods of
exposure to free water responsible for significant reduction in the ability of conidia to germinate
supported our finding for need of low r. h. to favour the powdery disease severity. The information on
conditions favouring severity of powdery mildew on Indian mustard could be useful while providing
predictions related to the disease (Gilles et al. 2000).
A delayed sowing results in coincidence of the vulnerable growth stage of plants as indicated earlier
with warm (maximum temperature: 24–30 °C; minimum temperature: > 5 °C; > 9.1 h sunshine) and
lower (morning: < 90 %; afternoon: 24–50 %) r. h. conditions. The sustenance of such favourable
conditions decides the longevity of the period of mildew attack and further build-up on the crop, which
consequently affects yield. Thus, the damage caused to a crop by powdery mildew is likely to be related
to sowing date, i. e., late sowing results in higher mildew severity (Fig. 1; Saharan and Kaushik 1981).
Thus, it would be appropriate to sow the crop at the earliest possible time to enable escape or non-
coincidence of the vulnerable disease development stage with favourable weather factors leading to
higher mildew severity on the crop, which affect yield. Thereafter, the later sown crop matures quicker
than the timely sown one due to rising of temperature towards end of crop season, which leads to faster
maturity of the former that result in lower yield. However, it may also be noted that early sown crops
have encountered high disease severity on the crop due to coincidence of favourable weather factors
with vulnerable crop stage (Kolte 1985). Hence, it would also be unwise to consider a thumb rule of
escaping the disease in early sown crop, whereby importance of forecasting needs to be underlined in
this prominent disease of the crop in India.
Crop age at first appearance of the mildew on the crop (Yx), crop age at highest severity of the mildew
(Yy) and peak disease severity (Yz) were related with weather variables in different weeks including pre-
sowing week and the interactions were found significant. The regional and cultivar-specific models
devised using data of initial 4 years thereby could predict the crop age at which powdery mildew first
appears on the crop (Table 1), crop age at highest mildew severity (Table 2), and the peak disease
severity (Table 3). The predictions were possible at least 3 weeks ahead of first appearance of the disease
on the crop, thus allowing growers to undertake timely fungicidal sprays. The disease was never found
to appear before 50 d. a. s. or eighth week after sowing, while the prediction for crop age at first
appearance of mildew was possible for both the locations in the beginning of fifth week. Common
models for the targeted three parameters (Yx, Yy, Yz) with the cultivar of mustard available at both the
Table 1. Models to forecast crop age (Yx) at first appearance of powdery mildew on Indian mustard
Location Cultivar Crop age Model R2
(week) of
prediction
S. K. Nagar ‘Varuna’ 5 Yx = –80.99 + 0.93Zmax-tmp + 2.03Zssh 0.99
S. K. Nagar ‘GM-2’ 3 Yx = 4.11 + 1.67Zmin-tmp 0.98
max-tmp: maximum temperature; min-tmp: minimum temperature; ssh: sunshine hours
Table 2. Models to forecast crop age (Yy) at highest severity of powdery mildew on Indian mustard
Location Cultivar Crop age Model R2
(week) of
prediction
S. K. Nagar ‘Varuna’ 4 Yy = 123.11 + 0.029Zaft-r. h. × ssh + 1.33Zssh 0.92
S. K. Nagar ‘GM-2’ 3 Yy = –124.38 + 0.04Zmin-tmp × aft-r. h. + 0.53Zmorn-r. h. 0.91
Bharatpur ‘Varuna’ 4 Yy = 2.34 + 0.96Zmin-tmp 0.99
Bharatpur ‘PCR-7’ 2 Yy = –10.46 + 4.88Zmin-tmp + 0.11Zmax-tmp × min-tmp 0.98
max-tmp: maximum temperature; min-tmp: minimum temperature; morn: morning; aft: afternoon; r. h.: relative humidity; ssh: sunshine hoursPflKrankh. 5/04 Brassica juncea powdery mildew epidemiology and weather-based forecasting models 435
Table 3. Models to forecast highest severity (Yz) of powdery mildew on Indian mustard
Location Cultivar Crop age Model R2
(week) of
prediction
S. K. Nagar ‘Varuna’ 5 Yz = 12.58 + 0.01Zmax-tmp × ssh 0.96
S. K. Nagar ‘GM-2’ 3 Yz = 4.72 + 0.01Zmin-tmp × ssh + 0.02Zmorn-r. h. 0.98
max-tmp: maximum temperature; min-tmp: minimum temperature; morn-r. h.: morning relative humidity; ssh: sunshine hours
locations, i. e., ‘Varuna’ were attempted. But they had very low R2 values and hence were not
considered for validation. Models for forecast of crop age at first appearance of the disease and its
highest severity in the season at Bharatpur also had low R2 values, hence were not considered for
validation and are not mentioned here. Though Indian mustard is grown across a large part of India
and the powdery mildew disease is also found to be a problem at several of the cropping areas, their
conditions for crop culture vary widely along with the specific conditions that favour the disease at
different places. This could be the reason for the different weather parameters getting entered in models
for the two locations. The application of the first fungicidal spray is critical and differs with seasons and
regions (Sansford et al. 1996). Hence, accurate region and cultivar-specific forecast for the crop age at
first appearance of the disease assumes importance. Thus, based on the predictions of the time of first
appearance of the mildew on the crop and the risk involved on the crop as related to the disease, the
growers could arrange and apply the fungicidal sprays in time and avoid unnecessary ones. The models
were validated in the fifth year, i. e., in 2003–2004 crop season (Table 4). Out of the models developed
in each of the four initial years for forecasting each of the targeted parameters, only those models have
been presented in the Tables 1, 2 and 3, wherein the observed and predicted values matched closely
with low or even no residual values. The models developed for weekly build-up of the disease severity
after first appearance for S. K. Nagar and Bharatpur are presented in Tables 5 and 6, respectively. These
models helped in predicting progression of the disease based on the weather in the preceding week.
Most of the models saw entry of temperature variables with r. h. and sunshine hours also getting
entered, which were indicated as important weather variables to affect powdery mildew even earlier
(Saharan and Kaushik 1981; Rudgard and Wheeler 1985). Further investigation can pinpoint the
importance of the different weather factors favouring powdery mildew attack and progress in order of
their priority. Weather indices based on accumulated weights of different meteorological factors as per
correlation coefficients in different weeks after sowing until the forecast was provided, were taken into
account. Proper monitoring of disease progress could provide accurate forecasts of crop age at first
appearance, crop age at highest severity and highest level of disease severity. We, thereby, do not intend
to undermine the importance of studying the bioecology of the pathogen in relation to weather factors.
Rather, we wish to state that such in-depth studies as done in Australia, Canada and Europe for diseases
of oilseed Brassicas (Gilles et al. 2000; West et al. 2001) could improve the accuracy of the models
presented here as that could provide the grower with an advance warning of the risk of the disease,
which may allow a period of several weeks to make a decision about fungicide applications and the risk
can be updated later based on disease progression models (Gilles et al. 2000). But, in an effort to cater
to the need for providing real-time region and cultivar-specific forecasts against the powdery mildew
menace in India, we have made a beginning by-passing the study of pathogen bioecology, which avoids
the risk of inaccuracy, as it is based on fewer relationships which do not fully describe the dynamics of
the biological processes influencing the disease epidemics (Gilles et al. 2000). The available literature
indicates association of several weather factors with powdery mildew severity (Saharan and Kaushik
1981; Dang et al. 1998; Crowton and Kennedy 1999), but is silent about providing prediction for
forecasting the disease. Hence, as per available literature, this seems to be the first attempt towards
devising prediction models for forecasting of the disease of the important oilseed crop. Using these
models in combination with crop planting dates and standard meteorological data, it would be possible
to provide necessary forecasts for the time being centrally from the National Research Centre on
Rapeseed-Mustard at Bharatpur. While on one hand, the models could be improved with further
detailed study on pathogen inoculum and bioecology, there would be need to provide a simple436 Desai et al. 5/04 PflKrankh.
Table 4. Validation of models for different dependent variables for the cultivars at the two locations
Location/ Dates Crop age (days after Crop age (days after Highest % powdery
Cultivar of sowing) at first sowing) at highest mildew severity (Yz)
sowing appearance of powdery mildew
powdery mildew (Yx) severity (Yy)
Predicted Observed Predicted Observed Predicted Observed
S. K. 29 Oct 89 90 102 101 13 12
Nagar/ 05 Nov 89 90 105 105 15 14
‘Varuna’ 12 Nov 83 83 105 107 20 20
19 Nov 76 76 103 107 25 26
26 Nov 74 74 104 104 27 26
03 Dec 68 70 107 104 31 34
S. K. 29 Oct 89 89 104 104 17 16
Nagar/ 05 Nov 89 90 100 100 18 18
‘GM-2’ 12 Nov 83 83 111 111 23 22
19 Nov 76 76 111 111 30 28
26 Nov 74 74 111 111 31 34
03 Dec 68 70 105 107 33 37
Bharatpur/ 29 Oct NA NA 108 107 NA NA
‘Varuna’ 05 Nov NA NA 104 103 NA NA
12 Nov NA NA 102 102 NA NA
19 Nov NA NA 100 101 NA NA
26 Nov NA NA 100 100 NA NA
03 Dec NA NA 98 99 NA NA
Bharatpur/ 29 Oct NA NA 104 103 NA NA
‘PCR-7’ 05 Nov NA NA 102 102 NA NA
12 Nov NA NA 101 101 NA NA
19 Nov NA NA 101 100 NA NA
26 Nov NA NA 99 99 NA NA
03 Dec NA NA 99 99 NA NA
NA: model not applied for validation
Table 5. Models based on weather one week preceding date of observation for prediction of progression of
powdery mildew severity at S. K. Nagar
Location Cultivar Model R2
S. K. Nagar ‘Varuna’ Powdery mildew severity = 113.03 + 21.67*534 maximum 0.9
temperature – 15.22 minimum temperature + 1.74 maximum
(morning) relative humidity – 4.52* minimum (afternoon) relative
humidity – 60.17*rainfall
S. K. Nagar ‘GM-2’ Powdery mildew severity = 139.455 + 21.242*534 maximum 0.9
temperature – 15.483 minimum temperature + 1.19 morning
(maximum) relative humidity – 4.48* afternoon (minimum) relative
humidity – 57.72* rainfall
computer package to enable any user to get a robust, accurate forecast on the internet. This is expected
to guide growers efficiently for making only need-based timely fungicidal sprays more effective. The
forecasters need to take into consideration the other findings, viz., boundary and favourable conditionsPflKrankh. 5/04 Brassica juncea powdery mildew epidemiology and weather-based forecasting models 437
Table 6. Alternative models to predict progression of the powdery mildew after first appearance at Bharatpur
Cultivar Week after Prediction model R2
first appearance
‘Varuna’ 1 No Variables Entered
2 Y2 = 327.29 + 1.16Y1 + 35.81Xsunshine hours 0.74
3 Y3 = –451.16 + 15.14Xmaximum temperature 0.84
4 Y4 = 1.81 + 1.21Y3 0.86
5 Y5 = –201.14 + 0.98Y4 + 0.96Xmorning (maximum) relative humidity + 0.99
Y5 = 16.36Xsunshine hours
‘PCR-7’ 1 Y1 = –398.55 + 44.67Xsunshine hours 0.59
2 Y2 = –31.56 + 5.66Xminimum temperature 0.81
3 Y3 = 18.27 + 4.69 age of crop 0.85
4 Y4 = 43.32 + 0.99 Y3 –0.80Xmorning (maximum) relative humidity 0.99
5 Y5 = –3.98 + 1.14Y4 0.99
for disease severity on the crop reported here along with the output of region and cultivar-specific
models.
In years of appearance of powdery mildew on crop before the decision week, growers may be advised
about the risk expected. Further, the forecasts need to account for the margin of error in order to
maintain the confidence of resource poor mustard growers of India in the forecast system. More study
in this direction to improve the models with additional data from similar, other new experiments on
pathogen inoculum and bioecology for real-time forecasts of outbreaks of the disease based on climatic
variables is in progress.
Acknowledgements
The facilities provided by the Directors of research units where the investigation was carried out, the
funding received for the investigation from the Indian Council of Agricultural Research under the
World Bank Funded National Agricultural Technology Project and the All Indian Coordinated
Research Project on Rapeseed-Mustard are gratefully acknowledged. Help received from Sh Praveen
Kumar in analysis of data and that from Ms Tonja Wolff (Institut für Botanik, Ernst-Moritz-Arndt
Universität, Greifswald, Germany) in translation of the title, summary and key words of the manu-
script to German language as a requirement for publication in this esteemed journal are thankfully
acknowledged.
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