Seasonal Evaluation of Agrometeorological Advisory Services and Farmer Response in Sugarcane Cultivation under GKMS
Ramanand Patel *
Regional Research Station, Agwanpur, Saharasa, (BAU, Sabour), 852201, Bihar, India.
Amrendra Yadav
Krishi Vigyan Kendra, Kannauj (CSAUA&T, Kanpur), 209725, Uttar Pradesh, India.
Vikas Kumar
ICAR- Indian Agricultural Statistics Research Institute, 110012, New Delhi, India.
*Author to whom correspondence should be addressed.
Abstract
Agrometeorological Advisory Services (AAS) blend weather cues with local insights, to give farmers more trustable, weather-driven agronomy suggestions that back climate resilient farming in a practical way. In this study, we look at how well the advisory services work in different seasons, especially those sent through the Gramin Krishi Mausam Sewa (GKMS) and the District Agromet Unit, demonstration program, focusing on sugarcane cultivation during 2022 in Bulandshahr district. For the analysis, data was taken from 1,392 farmers spread over four separate seasons. These were grouped using Standard Meteorological Weeks (SMWs) i.e. pre-monsoon, monsoon, post-monsoon and winter. What we observed was that the adoption of agromet advisories stayed fairly high throughout the year, about 81.03% up to 87.93%. The top value showed up in the post-monsoon season, when farm activities are usually less chaotic, and field operations can go more smoothly. On the satisfaction side, farmers also reported high levels. The satisfaction scores reached their best in winter and pre-monsoon, while the monsoon period showed lower satisfaction. The main reason mentioned was operational pressure and also the limited access to advisories during that time, which makes timely follow-up kind of harder. The study also points out a clear positive association between advisory relevance and farmer satisfaction, meaning when the guidance feels more location-appropriate and arrives on time, the overall experience improves noticeably. Yet, there was a negative impact on advisory effectiveness when there were delays in communication and slow response time. The ANOVA results indicated significant seasonal variation in farmers’ adoption behavior, confirming that weather conditions strongly influence the utilization of advisory services. Overall, the study demonstrates that agrometeorological advisories play a crucial role in improving decision-making in sugarcane farming by providing timely and relevant seasonal guidance. However, challenges during the monsoon period limit their full effectiveness. The study highlights the need to strengthen real-time communication systems and improve farmer preparedness to maximize the benefits of agrometeorological services.
Keywords: Agrometeorological advisory services, sugarcane, seasonal analysis, farmer adoption, weather-based advisory