Corynespora cassiicola, cotton, weather parameters, correlation and regression.

Cotton known as "White Gold" in world and it is a one of the most commercially important natural textile fiber crops with significant contributor of oilseeds. It is one of the most ancient and important cash crops next only to food grains and is the principle raw material for a flourishing textile industry. Cotton, although under pressure from synthetic fibers has made resurgence worldwide and remains as the most improved crop species producing lint plus oil and meal from seed (Nosberger et al., 2001). Biotic stress on cotton caused by pests and diseases contribute to 10-30% of annual yield loss worldwide (Hagan et al., 2015; Bowen et al., 2018). Cotton crop is affected by fungal, bacterial and viral diseases. In India, foliar diseases (fungal, bacterial, viral and boll rot) have been estimated to cause yield losses up to 20 to 30 per cent (Mayee and Mukewar 2007). In case of  foliar diseases of cotton crop is affected by throughout the season. Among the fungal diseases, alternaria leaf spot/blight, grey mildew and rust cause economic losses under congenial conditions (Monga et al., 2013). 

A fungal foliar diseases, corynespora target spot caused by Corynespora cassiicola has been increasing its prevalence and severity in cotton growing areas of south central United States and Central India (Butler et al., 2016 ; Salunkhe et al., 2019). Recently, Corynespora cassiicola (Berk & M.A. Curtis) C. T. Wei the cause of target spot, an emerging disease on cotton in India. Earlier, Corynespora cassiicola was minor in cotton and first reported by (Parakhia et al., 1989) in Gujarat. 

Meteorological parameters are the critical components of disease development. Corynespora target spot is occured frequently and in severely in regions with  prevailing moderate temperature of 25-30 C, high relative humidity (>90%) with intermittent rainfall were essential for disease establishment. Considering the importance of the target spot in cotton an attempt was made to know the influence of weather factors on disease development.

A field experiment was conducted during Kharif-2023 at Cotton Research Station, JAU, Junagadh and Oilseeds Research Scheme, JAU, Manavadar using G. Cot.-38 variety with bulk plot an area of 226 m2. Fifty plants in the middle rows at random was tagged. All other agronomical practices was followed as per the scientific recommendations. The crop under the experiment was kept free from any fungicidal sprays throughout the crop season. The data on corynespora target spot was weekly examined from true leaf stage to end of December on leaves using 0-4 grade scale (Sheo Raj, 1988). The per cent disease intensity (PDI) was calculated by using the following formula (Wheeler, 1969). 

Meteorological data such as rainfall, rainy day, maximum temperature and minimum temperature, relative humidity at morning and evening hours, sunshine hour and evaporation was collected from the Meteorological Weather Station, JAU, Junagadh and Manavadar. Correlation and regression analysis was conducted to determine the influence of weather conditions on the severity of corynespora target spot disease in cotton. The weather parameters were correlated to weekly disease intensity by calculating the Karl Person’s correlation coefficient (r). Correlation  coefficient  values  were  tested  individually  for  their  significance  at  5 per cent and 1 per cent probability level using following formula

where,

t = Test of significance

r = Correlation coefficient

n = Number of observations

Disease development under natural conditions was found to be influenced by environmental factors. The data from crop season revealed that sowing on the 27th standard meteorological week (SMW) during Kharif 2023. Observations were recorded from 35th and 32nd SMW in weekly interval at Junagadh and Manavadar, respectively. The first appearance of target spot was noticed at Junagadh and Manavadar 63 and 42 days after sowing, respectively which progressed thereafter (Table 1). The development of the disease was initially slow but it reached to the maximum (70.5%) during the 39th SMW of 2023. The previous week had maximum temperature (30.4°C), minimum temperature (25.5°C), morning relatively humidity (94%), evening relatively humidity (77%), sunsine (2.5 hrs),  evaporation rate (2.5 mm), rainfall (55.70 mm) and four rainy days (Table 2). In case of Manavadar, disease was reached maximum (22.5%) 38th SMW and the previous week had maximum temperature (32.4°C), minimum temperature (23.5°C), morning relatively humidity (91%), evening relatively humidity (77%), sunsine (3 hrs),  evaporation rate (3.1 mm), rainfall (100.7 mm) and five rainy days (Table 3).

Correlation studies. The data from the table revealed that the Junagadh centre, there was non-significant positive correlation of morning humidity (r=0.46), evening humidity (r=0.44), rainy day (r=0.46) and rain fall (r=0.36) and significantly positive correlation with minimum temperature (0.61*). There was significant negative correlation evaporation (r=-0.58*) and non-significant negative correlation with maximum temperature (r=-0.02) and sunsine hour (r=-0.51) and the data from the table revealed that the Manavadar centre, significantly positive correlation were found minimum temperature(r=0.54*). Non-significant positive correlation was recorded in morning humidity (r=0.44), evening humidity (r=0.34). Non-significantly negative correlation was observed in maximum temperature (r=0.03), rainfall (r=-0.15), sunsine hour (r=-0.02), evaporation (r=-0.15) and rainy days (r=-0.13) (Table 1).  

Regression studies. Multiple linear regression statistics of corynespora target spot (PDI) with weather variables during Kharif-2023 at Junagadh location, multiple linear regression equation was fitted to the data and the equation arrived for the weather parameters were Y= 56.66 - 0.17 Tmax + 2.09 Tmin - 1.43 RH I + 0.80 RH II - 0.03 RF - 1.36 RD + 4.00 SSH - 7.51 Evap. R2=0.9699. (Table 4)  Equation showed that when there was increase in one unit of minimum temperature, evening relatively humidity and sunsine hour, the per cent disease intensity increased by 2.09, 0.80 and 4.00 units, respectively. While when there was increased in one unit of maximum temperature, evening relatively humidity, rainfall, evaporation and rainy days, the per cent disease intensity decreased by 0.17, 1.43, 0.03,7.51 and 7.51 units respectively. The R2 values indicated the combination of eight weather factors accounted for variation in disease development. R2 value close to 1 proved the goodness and feasibility of model. The stepwise regression was used for identify the best subset of weather variables that play crucial role in development of disease. Using these variables, the regression models were developed to foretell the relationship between disease severity and weather variables. Stepwise regression equation obtained Y= -41.22 + 3.56 Tmin   R2=0.4670 (Table 5).

Multiple linear regression statistics of corynespora target spot (PDI) with weather variables during Kharif-2023 at manavadar location, multiple linear regression equation was fitted to the data and the equation arrived for the weather parameters were Y= - 146.04 + 1.70 Tmax - 1.20 Tmin + 0.14 RH I + 1.22 RH II + 0.007 RF - 1.31 RD + 4.08 SSH + 6.56 Evap. R2=0.9015 (Table 4). Equation showed that when there was increased one unit maximum temperature, morning relatively humidity, evening relatively humidity, rainfall, sunsine hour and evaporation, the per cent disease intensity increased by 1.70, 0.14, 1.22, 0.007, 4.08 and 6.56, respectively. While when increased in one unit of minimum temperature and rainy days, the per cent disease intensity decreased by 1.20 and 1.31 units respectively. The stepwise regression was used for identify the best subset of weather variables that play crucial role in development of disease. Using these variables, the regression models were developed to foretell the relationship between disease severity and weather variables. Stepwise regression equation obtained Y= -107.52 + 1.07 RH II + 4.95 SSH + 7.56 Evap.   R2=0.8590 (Table 5).

The present investigation are in more or less similar with the finding of  Roshan (2020); Acosta et al. (2020);  Yamuna et al. (2021); Bandi (2022) on corynespora target spot of cotton, where influence of weather parameter on disease incidence was  74 to 96.99 per cent. 

Table 1: Correlation between per cent disease intensity of corynespora target spot and weather factors.

* Significant at (P=0.05) level (R value 0.514) at Junagadh, n=15

* Significant at (P=0.05) level (R value 0.497) at Manavadar, n=16

Table 2: Weather data of Junagadh centre with disease intensity.

Table 3: Weather data Manavadar centre with disease intensity.

Table 4: Multiple linear regression of weather parameters with corynespora target spot disease intensity of cotton.

Table 5:  Stepwise multiple regression of weather parameters with corynespora target spot disease intensity of cotton.

* Significant at (p=0.05) level

X1 = Maximum temperature (C°);   X2 = Minimum temperature (C°); X3 = Morning relative humidity (%) ; X4 = Evening relative humidity (%) ; X5 = Rainfall (mm) ; X6 = Rainy days ; X7 = Sunsine (hrs) ; X8 = Evaporation (mm) ; R2 = Coefficient of determination

The effect of weather parameters on disease development was studied two location Kharif 2023. Prevailing moderate temperature of 25-30°C, high relative humidity (>90%) with intermittent rainfall were essential for disease establishment observed in two location. Disease initiation was observed in 35 and 32 standard meteorological week which required weather parameters for disease development at Junagadh and Manavadar, respectively.

Plant diseases are more common and severe in humid area with warm temperature. During pathological investigations, the interaction between pathogen populations with host population was studied under the influence of environmental factors. The knowledge of weather conditions predisposing for development and spread of the disease is important and it will helpful to farmers to take up timely management practices and data will used to develop predication model

Dharmesh K. Davara, Iteshkumar B. Kapadiya and Amit M. Polara (2024). Role of Weather Parameters on Development of Target Spot of Cotton caused by Corynespora cassiicola. Biological Forum – An International Journal, 16(8): 211-214.