Machine Learning-Based Crop Recommendation System for Sustainable Agriculture

1. Abstract Agriculture is the backbone of the Indian economy, employing a significant portion of the population and contributing substantially to the country’s GDP. Despite its importance, Indian agriculture faces many challenges, including unpredictable weather patterns, soil degradation, and inefficient crop selection, which often lead to suboptimal yields and financial losses for farmers. Selecting the right crop to cultivate based on soil health, climatic conditions, and regional factors is a critical decision that impacts productivity and sustainability. However, many farmers, especially in rural and resource-constrained areas, lack access to scientific guidance and rely on traditional practices or trial-and-error methods.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-23
DOI
https://doi.org/10.55041/ijsrem48570
Primary Topic
Smart Agriculture and AI
Type
article
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article

Machine Learning-Based Crop Recommendation System for Sustainable Agriculture

P. Ravi
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Smart Agriculture and AI
article

Machine Learning-Based Crop Recommendation System for Sustainable Agriculture

P. Ravi
article en

Abstract

1. Abstract Agriculture is the backbone of the Indian economy, employing a significant portion of the population and contributing substantially to the country’s GDP. Despite its importance, Indian agriculture faces many challenges, including unpredictable weather patterns, soil degradation, and inefficient crop selection, which often lead to suboptimal yields and financial losses for farmers. Selecting the right crop to cultivate based on soil health, climatic conditions, and regional factors is a critical decision that impacts productivity and sustainability. However, many farmers, especially in rural and resource-constrained areas, lack access to scientific guidance and rely on traditional practices or trial-and-error methods.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 92%
Smart Agriculture and AI
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