AI DRIVEN BIOTECHNOLOGY FOR CLIMATE RESILIENT AGRICULTURE, HEALTHCARE AND FOOD SYSTEM.
Published In: i-Manager's Journal on Life Sciences (JLS), 2025, v. 4, n. 3. P. 38 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: BAJPAI, DIVYANSH; MISHRA, MANOJ; SINGH, BEER; SIDDIQUI, KHADIM MOIN; SINGH, PRIANSHU; AHMAD, MOHD; GUPTA, PANKAJ; SINGH, SHASHANK; MISHRA, SANJAY 3 of 3
Abstract
Artificial intelligence is emerging as a game-changer for farmers coping with the escalating challenges of climate change, as AI models can predict and mitigate its wide-ranging impacts on agriculture while providing advanced decision-support tools. As environmental issues intensify, artificial intelligence integration is shifting the landscape toward climate-resilient agriculture. To address the complexities of climate unpredictability, this overview discusses how artificial intelligence assists farmers in making adaptive decisions. The advantages of artificial intelligence and climate research working together to identify climate-related risks—such as extreme weather, altered precipitation patterns, and emerging pest threats—are examined, along with its impact on smallholder and rural farmers to enhance overall resilience. A thorough analysis is conducted on the potential benefits and challenges of widespread artificial intelligence adoption across diverse agricultural contexts. Artificial intelligence-powered technologies combining computer vision, deep learning, reinforcement learning, and predictive analytics enable accurate climate forecasting, early disease detection, and efficient resource utilization. Furthermore, reinforcement learning and Internet of Things (IoT) integration support smart irrigation systems and adaptive decision-making under unpredictable climate conditions. This overview provides a comprehensive analysis of artificial intelligence and machine learning applications in precision agriculture, climate-smart farming, and sustainable land management. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:i-Manager's Journal on Life Sciences (JLS). 2025/12, Vol. 4, Issue 3, p38
- Document Type:Article
- Subject Area:Agriculture and Agribusiness
- Publication Date:2025
- ISSN:2583-9500
- DOI:10.26634/jls.4.3.22548
- Accession Number:191340168
- Copyright Statement:Copyright of i-Manager's Journal on Life Sciences (JLS) is the property of i-manager Publications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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