Optimizing potato yield predictions in Uttar Pradesh, India: a comparative analysis of machine learning models.

ABSTRACT: Potato as a staple food, plays a crucial role in ensuring a sustainable food supply and mitigating poverty and malnutrition in various regions across the globe. India, specifically holding the second position in global potato production, plays a significant role in the global potato market. The accurate prediction of potato yield is crucial for addressing global food security and sustainable farming practices. Looking into these facts, this study focused on seven districts in Uttar Pradesh, India, viz, Agra, Aligarh, Etawah, Farrukhabad, Firozabad, Hathras and Kannauj. This research aims to compare the performance of five machine learning models-Elastic Net (ELNET), Random Forest, Artificial Neural Network (ANN), Extreme Gradient Boosting (XGBoost) and Support Vector Regression (SVR) to id

SUBMITTER: Alsaber A 

PROVIDER: S-EPMC12289936 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature