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Research Article Open access CC BY 4.0

Influence of Weather Parameters on Sugarcane Wilt (Fusarium sacchari) Disease under Field Conditions

Piyush Kumar, Md. Minnatullah, Shiva Pujan Singh, C.S. Choudhary, Sudhir Paswan, Aman Tutlani, Sahil Kumar, Babburi Sai Maheswari

International Journal of Environment and Climate Change · pp. 439–445 · Published 15 Sep 2025

10.9734/ijecc/2025/v15i95028

Abstract

Sugarcane wilt disease, caused by Fusarium sacchari, is a major constraint in sugarcane production in India, with its incidence strongly influenced by weather parameters. The study was carried out during the 2023–24 cropping season at the Kalyanpur Sugarcane Farm, Sugarcane Research Institute, RPCAU, Pusa, Samastipur, Bihar, with the objective of assessing the influence of climatic factors on disease progression under field conditions. Meteorological data, including maximum and minimum temperatures, relative humidity, rainfall and sunshine hours, were collected from Agro Meteorological Advisory Services, RPCAU, Pusa. Disease incidence was recorded fortnightly and statistical analyses, including correlation and multiple linear regression (MLR), were employed to assess the impact of weather factors. Results indicated that disease incidence varied from 0.60% to 26.60% during the study period, with peak incidence (26.60%) recorded in the second fortnight of July 2023. This period was characterized by high relative humidity (84.40% morning, 62.60% evening), elevated minimum temperatures (25.90°C), maximum temperature (40.2°C) and substantial rainfall (82.60 mm). Correlation analysis revealed that minimum temperature (r = 0.720) and relative humidity at 14:00 hours (r = 0.560) were significantly associated with disease incidence. The MLR model explained 87.8% (R² = 0.878) of disease variability, highlighting the crucial role of these factors in incidence of the disease. The results suggest that environmental conditions during the rainy season significantly favour F. sacchari infection. Therefore, timely disease monitoring and predictive modelling based on weather trends can enhance disease management strategies in sugarcane cultivation.

Sugarcane wilt weather parameters disease incidence correlation analysis multiple linear regression

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