ABSTRACT
Risk is a pivotal facet of the agricultural industry. The inherent uncertainties linked to weather conditions, crop yields, market fluctuations, governmental policies, global economic trends, and various other factors can lead to significant variations in farm profitability. [1] Effective risk management involves selecting from various strategies aimed at mitigating the financial repercussions arising from such uncertainties. With the abundance of data available and the integration of machine learning, along with user-friendly interfaces easily accessible to farmers, innovative solutions for risk management in agriculture can be developed.
