Review of Crop and Fertilizer Recommendation Systems

Abstract

The agricultural industry is a crucial contributor to a country's economic growth and development. It is more difficult to choose crops, nevertheless, based on the nutrients in the soil. The present paper reviews the recommendation of crops to increase the production of yield, and their sustainability and suggests fertilizers accordingly. Further, it identifies and discusses various aspects of cultivating crops with the help of soil nutrients and finally puts forward suggestions for the variety of technologies and algorithms proposed to solve this problem. The selection of the best crops to grow in a given area while taking into account factors like soil type, climate, and other environmental conditions are crucial components of modern agriculture that are essential in achieving optimal crop yield and soil health. Fertilizer recommendation, on the other hand, involves determining the optimal type, amount, and timing of fertilizers to be applied to the soil to promote plant growth and health. To provide accurate and trustworthy crop and fertilizer recommendations, many methods and technologies, like machine learning and deep learning algorithms, have been created. These approaches help farmers optimize their crop production, reduce costs, and minimize environmental impact by reducing overuse of fertilizers.

Effective crop and fertilizer recommendations require a thorough understanding of the local environment, as well as the principles of soil fertility and crop management. By providing farmers with customized recommendations, we can promote sustainable and profitable agricultural practices while also safeguarding our natural resources.