• Dr. Navnath B. Waghchaure

The state of Maharashtra, particularly the Nashik district, stands as a prominent hub for grape production in India. Despite favourable agro-climatic conditions, grape cultivation in this region faces persistent challenges due to the variability of expert advice, environmental fluctuations, and the lack of standardized cultivation protocols. This research proposes a novel artificial intelligence (AI)-based model designed to formulate dynamic, context-sensitive Standard Operating Procedures (SOPs) for grape farming. The model synthesizes a diverse set of expert recommendations, environmental parameters (such as temperature, rainfall, and soil moisture), and historical yield data to generate optimized cultivation guidelines tailored to specific field conditions. By collecting structured input from grape farmers and viticultural experts across Nashik, the study constructs a training dataset that reflects real-world farming decisions and their outcomes. A supervised machine learning framework is employed to identify high-impact advice patterns and translate them into adaptive SOPs that evolve with environmental and seasonal changes. The resulting AI-powered system not only enhances consistency and productivity in grape cultivation but also empowers farmers with data-driven decision-making tools. The dynamic nature of the SOPs ensures relevance amid climate variability, supporting sustainable viticulture practices in the region. This research contributes to the modernization of Indian agriculture by bridging traditional agronomic wisdom with emerging AI technologies. The proposed model holds significant potential for scalability across crops and regions, offering a transformative approach to precision farming. The findings underscore the importance of integrating expert knowledge, farmer experience, and intelligent systems to foster a resilient and efficient agricultural ecosystem.

artificial intelligence, standard operating procedure, grape cultivation, precision agriculture, Nashik district, machine learning, sustainable viticulture, data-driven farming

""AI-Driven Framework for Developing Dynamic Standard Operating Procedures for Grape Cultivation: A Case Study of Nashik District, Maharashtra"", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.700-708, May-2025, Available :http://www.jetir.org/papers/JETIRGV06100.pdf

""AI-Driven Framework for Developing Dynamic Standard Operating Procedures for Grape Cultivation: A Case Study of Nashik District, Maharashtra"", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. pp700-708, May-2025, Available at : http://www.jetir.org/papers/JETIRGV06100.pdf