Predicting Alternaria blight severity in radish: A comprehensive analysis of meteorological influence and time series modelling

Abstract Alternaria leaf blight (ALB), caused by Alternaria brassicicola , poses a significant threat to radish cultivation, particularly in the agroclimatic conditions of Jammu and Kashmir, India. This study investigates the epidemiology of ALB during 2019/2020 and 2020/2021 growing seasons, focusing on the impact of meteorological factors on disease progression. Disease severity was monitored across various radish‐growing regions, revealing considerable spatial and temporal variability. The analysis identified maximum temperature (Tmax) as the most critical factor influencing percent disease index (PDI), with a strong positive correlation observed in both seasons, particularly in 2020/2021. Conversely, maximum relative humidity (Max RH) showed a negative correlation with PDI, suggesting complex interactions between temperature and humidity in disease dynamics. Principal component analysis further highlighted the distinct weather patterns between the two seasons, highlighting the role of environmental variability in disease progression. The study employed an advanced time series model, seasonal autoregressive integrated moving average (SARIMA), to forecast disease progression based on historical PDI data and corresponding weather parameters. The SARIMA model, by incorporating seasonal components, was found to be the best fit for predicting disease outbreaks. The findings of this study highlight the importance of integrating meteorological data into disease forecasting models to provide early warnings and guide timely interventions. By enhancing the understanding of ALB epidemiology, this research offers valuable insights for the development of sustainable disease management strategies in radish cultivation, reducing reliance on chemical fungicides and mitigating yield losses.