Artificial intelligence in agriculture

Artificial Intelligence (AI) is revolutionizing agriculture by enhancing efficiency, productivity, and sustainability across various farming practices. AI-driven technologies, including machine learning, computer vision, and robotics, enable precision farming, allowing for real-time monitoring of crops, soil, and environmental conditions. AI algorithms are used to optimize irrigation, fertilization, and pesticide application, significantly reducing resource waste and improving crop yield. Additionally, AI-powered drones and sensors facilitate early detection of plant diseases and pests, while predictive models assist in forecasting weather patterns and market trends, aiding in strategic decision-making. Despite the promising advancements, challenges such as data availability, high costs, and the need for farmer training remain critical to the widespread adoption of AI in agriculture. This paper examines the potential of AI to transform farming practices and discusses the hurdles that need to be addressed for its broader implementation.

Authors

Publication Details

Journal
International Journal of Agriculture Extension and Social Development
Published
2024-10-01
DOI
https://doi.org/10.33545/26180723.2024.v7.i10g.1256
Citations
3
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
1.47
Controls
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article

Artificial intelligence in agriculture

Anita Choudhary, Kirti Shekhawat
3 citations
International Journal of Agriculture Extension and Social Development
Impact of AI and Big Data on Business and Society
1.47
article

Artificial intelligence in agriculture

Anita Choudhary, Kirti Shekhawat
article en
3 citations

Abstract

Artificial Intelligence (AI) is revolutionizing agriculture by enhancing efficiency, productivity, and sustainability across various farming practices. AI-driven technologies, including machine learning, computer vision, and robotics, enable precision farming, allowing for real-time monitoring of crops, soil, and environmental conditions. AI algorithms are used to optimize irrigation, fertilization, and pesticide application, significantly reducing resource waste and improving crop yield. Additionally, AI-powered drones and sensors facilitate early detection of plant diseases and pests, while predictive models assist in forecasting weather patterns and market trends, aiding in strategic decision-making. Despite the promising advancements, challenges such as data availability, high costs, and the need for farmer training remain critical to the widespread adoption of AI in agriculture. This paper examines the potential of AI to transform farming practices and discusses the hurdles that need to be addressed for its broader implementation.

International Journal of Agriculture Extension and Social DevelopmentVol. 7(10)
Openalex Percentile: Top 16%
Impact of AI and Big Data on Business and Society
1.47
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