Machine learning driven innovations in agriculture

Agriculture is considered as the mainrnoccupation of the country. It is the major source of income and is the basicrnhuman need. Agriculture has a big role in economy and it is a source ofrnemployment in the developing countries like India. Farmers, the backbone of therncountry put a lot of effort to provide food to the people. A lot of manualrnintervention is needed to handle agriculture issues like crop prediction, yieldrnprediction, fertilizer recommendation, disease detection, and irrigationrnmanagement. These issues mainly depend on the environmental changes such asrnclimatic factors, rainfall, and pesticide usage. Therefore, to make the job ofrnfarmers easy, Machine Learning plays a key role for predicting the requiredrnresources accurately. This paper emphasis on the work of some researchers, whornhave identified the use of various techniques addressing different agriculturalrndomain.

Authors

Publication Details

Journal
International Journal of Communication and Information Technology
Published
2025-01-01
DOI
https://doi.org/10.33545/2707661x.2025.v6.i1b.124
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
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article

Machine learning driven innovations in agriculture

Harsimran Kaur, Sandeep Kaur
International Journal of Communication and Information Technology
Smart Agriculture and AI
article

Machine learning driven innovations in agriculture

Harsimran Kaur, Sandeep Kaur
article en

Abstract

Agriculture is considered as the mainrnoccupation of the country. It is the major source of income and is the basicrnhuman need. Agriculture has a big role in economy and it is a source ofrnemployment in the developing countries like India. Farmers, the backbone of therncountry put a lot of effort to provide food to the people. A lot of manualrnintervention is needed to handle agriculture issues like crop prediction, yieldrnprediction, fertilizer recommendation, disease detection, and irrigationrnmanagement. These issues mainly depend on the environmental changes such asrnclimatic factors, rainfall, and pesticide usage. Therefore, to make the job ofrnfarmers easy, Machine Learning plays a key role for predicting the requiredrnresources accurately. This paper emphasis on the work of some researchers, whornhave identified the use of various techniques addressing different agriculturalrndomain.

International Journal of Communication and Information TechnologyVol. 6(1)
Zero hunger
Openalex Percentile: Top 91%
Smart Agriculture and AI
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