| Abstrakt: |
Crop production needs to double by the year 2050 to meet the food requirements of the growing global population. Proper management of fertilization and timely disease control are essential in this endeavor. Machine learning technologies are poised to address these challenges by evaluating various elements, including geographical location, soil acidity, and the presence of essential nutrients such as nitrogen, phosphorus, and potassium. The paper proposes an agro-informatic system that helps farmers in crop prediction, fertilizer recommendation, and disease prediction. The proposed system incorporates critical inputs from farmers, ML algorithms such as RF and thrid-party apps. [ABSTRACT FROM AUTHOR] |
