Agriculture is the foremost factor which is important for the survival of human beings. Farming contributes to a very big part of GDP; still, several areas exist where improvements are required. One of those is crop recommendation. Crop productivity is boosted as a result of accurate crop prediction. As crop production has already started to suffer from climate change, improving crop output is consequently desirable because agronomists are impotent to select the appropriate crop(s) depending on environmental and soil parameters, and the mechanism of forecasting the selection of the appropriate crops manually has failed. Factors like soil characteristics, soil types, climate characteristics, temperature, rainfall, area, humidity, geographic location etc. affect crop forecast. This chapter focuses mainly on building a recommendation system, i.e., suggesting the kind of the crop by applying various machine learning and deep learning techniques depending upon several parameters. The system would help the farmers for the appropriate decision to be taken regarding the crop type.
Authors: Priyanka Sharma, Pankaj Dadheech, A. V. Senthil Kumar
DOI: https://doi.org/10.4018/978-1-6684-8516-3.ch010
Publish Year: 2023
