Crop Yield Prediction Using Machine Learning

Abstract

Crop yield prediction is an application that helps farmers to improve crop yield. As selection of every crop is very important in agricultural planning, it mainly depends on market price, climate and production rate. The proposed project predicts the crop yield quantity, based on the following factors Temperature, Humidity, Moisture level of soil and area of field. The rate of yield predicted by our proposed project is displayed as an output to the user that aids the farmer to harvest the crop.

Crop Yield Prediction for Cereals using Machine Learning

“…Awan, A. M., & Sap, M. N. M. [20] developed an intelligent system for crop yield prediction, employing kernel methods and considering parameters like plantation, latitude, temperature, and rainfall precipitation. Their experiment with weighted k-means kernel method with spatial constraints showed promise in analyzing oil palm fields, although limitations may arise in its generalizability to other crops and regions.Anakha Venugopal, Aparna S, Jinsu Mani, and Rima Mathew's [20] study elucidates machine learning's utility in agricultural decision-making via crop yield prediction, though challenges like historical data reliance and parameter precision persist. Despite these obstacles, classifiers like Random Forest exhibit promising accuracy, offering farmers informed crop selection.…”

Computational Model for Pepper Yield Prediction Using Support Vector Regression

“…Data-driven agriculture, with the help of robotic solutions incorporating artificial intelligent techniques, sets the grounds for the sustainable agriculture of the future [2][3][4][5]. This paper reviews the current status of advanced farm management systems by revisiting each crucial step and studied various soil, climatic properties which affects the yield of pepper.…”