Intelligent Crop Recommendation System Using Machine Learning Approach

The agricultural sector in India, despite its status as a leading producer globally, grapples with low farm productivity, resulting in diminished incomes for farmers. Addressing this challenge requires a strategic approach centered around increasing productivity, thereby enhancing farmer livelihoods. Crucially, farmers must be equipped with the knowledge of which crops are best suited to their specific plots of land to optimize yield potential. This entails consideration of various factors such as temperature, humidity, soil pH, rainfall patterns, and nutrient composition. However, many farmers lack access to this vital information, leaving them uncertain about which crops to cultivate for maximum yield and profit. Thus, the implementation of crop recommendation systems powered by machine learning algorithms presents a promising solution. By leveraging data on environmental conditions and soil properties, these systems can accurately predict suitable crop choices for individual farms, empowering farmers to make informed decisions and ultimately improve their productivity and income levels.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-29
DOI
https://doi.org/10.22214/ijraset.2025.69677
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Intelligent Crop Recommendation System Using Machine Learning Approach

K DanielRaj
International Journal for Research in Applied Science and Engineering Technology
Smart Agriculture and AI
article

Intelligent Crop Recommendation System Using Machine Learning Approach

K DanielRaj
article en

Abstract

The agricultural sector in India, despite its status as a leading producer globally, grapples with low farm productivity, resulting in diminished incomes for farmers. Addressing this challenge requires a strategic approach centered around increasing productivity, thereby enhancing farmer livelihoods. Crucially, farmers must be equipped with the knowledge of which crops are best suited to their specific plots of land to optimize yield potential. This entails consideration of various factors such as temperature, humidity, soil pH, rainfall patterns, and nutrient composition. However, many farmers lack access to this vital information, leaving them uncertain about which crops to cultivate for maximum yield and profit. Thus, the implementation of crop recommendation systems powered by machine learning algorithms presents a promising solution. By leveraging data on environmental conditions and soil properties, these systems can accurately predict suitable crop choices for individual farms, empowering farmers to make informed decisions and ultimately improve their productivity and income levels.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 94%
Smart Agriculture and AI
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Intelligent Crop Recommendation System Using Machine Learning Approach — K DanielRaj · International Journal for Research in Applied Science and Engineering Technology (2025) | TGRS Research Map | TGRS