Temporal Dynamics of Major Cocoa Diseases in Andhra Pradesh, India: A Two-year Surveillance Study

Abstract

Background: Cocoa production, now expanding in regions like Andhra Pradesh, is heavily affected by fungal and bacterial diseases causing major yield losses, but proper cultural practices like sanitation, pruning, and shade management can effectively reduce disease incidence regardless of the cropping system. Aims: This study aimed to quantify year-to-year and seasonal variation in the incidence of six major cocoa diseases in Andhra Pradesh, assess year-by-season interaction effects, and determine relationships between weather parameters and disease incidence. Study Design: Two-year longitudinal roving survey (2024–2025). Place and Duration of Study: Twelve geo-tagged cocoa farms, Eluru district, Andhra Pradesh, India (16°42′N, 81°06′E); January 2024 to December 2025. Methodology: Monthly disease incidence of stem canker, black pod rot, Lasiodiplodia dieback, charcoal pod rot, cushion gall, and cherelle wilt was recorded from 100 randomly selected trees per farm. Temporal and seasonal variation was analysed using a two-factor completely randomized design (CRD) with year and season as fixed factors; means were separated using Fisher's LSD test (P = .05). Pearson's correlation analysis quantified weather–disease associations. Results: Stem canker declined from 30.67% (2024) to 18.92% (2025; F = 118.67, P < .001) while cushion gall increased from 13.94% to 20.75% (F = 61.79, P < .001). Black pod rot peaked during monsoon (17.68 ± 7.93%) and was strongly correlated with rainfall (r = 0.55, P < .01) and relative humidity (r = 0.63, P < .01). Lasiodiplodia dieback correlated positively with mean temperature (r = 0.62, P < .01). Significant year × season interactions (P < .01 for most diseases) indicated that seasonal dynamics differed between years. Conclusion: Cocoa disease dynamics in Andhra Pradesh are governed by complex temporal, seasonal, and climatic interactions. These findings provide a baseline for developing predictive disease management strategies and climate-adaptive cultivation practices in emerging cocoa-growing regions. Given increasing climatic variability, weather-informed and adaptive management approaches incorporating real-time monitoring and disease forecasting are essential to improve the timing and efficiency of disease control interventions in non-traditional growing regions.