• DEVANSH PRAVIN JAIN
• KETKI R. INGOLE

: The Agro-marketing in Crop Yield Prediction System utilizes advanced technologies and machine learning algorithms to analyze historical data on crop yields, weather, soil quality, and agronomic practices. It provides accurate predictions of future crop yields, accessible through user-friendly web and mobile applications. Customization features enable farmers to tailor predictions to their specific needs, while a feedback mechanism continuously refines the models for improved accuracy. Real-time weather data integration enhances prediction accuracy, and decision support tools offer recommendations for optimal planting times and agronomic practices. Similarly, the Crop Price Recommendation System employs machine learning and real-time data to provide accurate crop price estimations, aiding farmers and stakeholders in making informed decisions for enhanced profitability and sustainability in agriculture.

Introduction of Agro-marketing in Crop Yield Prediction System, Machine learning algorithms, Historical data analysis, Weather data, Decision support tools, Crop Price Recommendation System

"Agro-marketing in crop yield", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.a167-a174, April-2024, Available :http://www.jetir.org/papers/JETIR2404024.pdf

"Agro-marketing in crop yield", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppa167-a174, April-2024, Available at : http://www.jetir.org/papers/JETIR2404024.pdf