JOURNAL ARTICLE

Machine Learning Enabled Crop Recommendation System for Arid Land

Abstract

The agriculture industry plays a significant role in the economy of many countries, and the population is regarded as an essential profession. To increase agricultural production, crops are recommended based on soil, weather, humidity, rainfall, and other variables which are beneficial to farmers as well as the nation. This paper explores the use of “machine learning” algorithms to recommend crops in for Arid land based on features selected from tropical climate where crops grow effectively. Five “machine learning” models have been validated for recommendation of crops for arid land which resulted in “Random Forest” topping as the best model.

Keywords:
Arid Agriculture Agroforestry Agricultural engineering Land use Population Crop Production (economics) Geography Environmental science Business Agricultural economics Engineering Forestry Economics Ecology

Metrics

2
Cited By
1.15
FWCI (Field Weighted Citation Impact)
4
Refs
0.80
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Soil and Land Suitability Analysis
Physical Sciences →  Environmental Science →  Management, Monitoring, Policy and Law
Smart Agriculture and AI
Life Sciences →  Agricultural and Biological Sciences →  Plant Science
© 2026 ScienceGate Book Chapters — All rights reserved.