Weather-based models for predicting risk of zonate leaf spot disease in Sorghum

• Published in: Tropical plant pathology 2021-12, Vol.46 (6), p.702-713
• Main Authors: Bhardwaj, Nitish Rattan, Atri, Ashlesha, Rani, Upasana, Banyal, Devinder Kumar, Roy, Ajoy Kumar
• Format: Article
• Language: English
• Subjects: Biomedical and Life Sciences; Climate models; Cultivars; Decision making; Decision support systems; Foliar diseases; Fungicides; Leafspot; Leaves; Life Sciences; Original Article; Plant Pathology; Prediction models; Rainy season; Regression analysis; Regression models; Relative humidity; Risk assessment; Sorghum; Variation; Weather
• ISSN: 1983-2052; 1982-5676; 1983-2052
• DOI: 10.1007/s40858-021-00461-1

Zonate leaf spot (caused by Gloeocercospora sorghi Bain and Edgerton) is the most serious foliar disease in forage sorghum. Disease is currently managed through fungicide applications without any pre-informed decision-making. Prediction models which can help in decision-making regarding fungicide use for zonate leaf spot management are lacking. In this study, we model the relationship between weather conditions and zonate leaf spot to develop a decision support system for disease management. Zonate leaf spot severity on rainy season (last week of June to third week of October) sorghum was recorded during 2010–2020 on susceptible cultivar SL-44 in a monitoring experiment conducted at humid, subtropical location (Ludhiana, India). Window pane analysis resulted in identification of weekly average minimum temperature (Tmin), average temperature (Tav), and afternoon relative humidity (RHa) as potential predictors of zonate leaf spot. Regression models based on Tmin, Tmin + RHa, and Tav + RHa were able to explain 56, 56, and 54% variation in disease severity respectively at the tested location. These three models were also validated for accuracy in hot, semi-humid (at Jhansi on cultivar MP Chari), and sub-humid climatic (at Palampur on cultivar Kanchan) conditions. Model based on Tmin + RHa explained 59% variation in disease severity at Jhansi. At Palampur, models based on Tmin + RHa and Tav + RHa were able to explain 59% variation in disease severity. As the models performed well in different climatic situations, they could be used for risk assessment of zonate leaf spot epidemics in sorghum.