Madhuri, E V and Rupali, J S and Sharan, S P and Pooja, N S and Sujatha, G S and Singh, D P and Ahmad, K and Kumar, Amrender and Prabha, R (2025) Transforming Pest Management with Artificial Intelligence Technologies: The Future of Crop Protection. Journal of Crop Health, 77. pp. 1-17. ISSN 2948-264X
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Abstract
With increasing global population and limited expansion of cultivated land, it is necessary to identify innovative solutions for enhancement of agricultural productivity and meet growing food demand. Despite significant advancements in crop protection methods, substantial annual crop losses persist particularly due to pests. Artificial Intelligence (AI) has emerged as a transformative tool to reform crop protection strategies. With the support of machine learning and deep learning algorithms, AI enables precise pest detection, risk assessment, monitoring, and forecasting thereby minimizing crop losses and maximizing yields. Further, AI integrates expert system and decision support system with crop management aspects for precise and timely decisions for farmers to enhance the crop productivity. In this review article, attempts are taken to explore the applications, implications, and future prospects of AI in field of pest management, emphasizing its pivotal role in agriculture and thus ensuring food security among evolving challenges.
| Item Type: | Article |
|---|---|
| Divisions: | Global Research Program - Accelerated Crop Improvement |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | Pest management, Artificial intelligence, Risk assessment, IoT, Expert system, Pest forecast, Sensors, Pest detection |
| Subjects: | Others > Plant Protection Others > Pest Management |
| Depositing User: | Mr Nagaraju T |
| Date Deposited: | 07 Jul 2025 09:00 |
| Last Modified: | 07 Jul 2025 09:00 |
| URI: | http://oar.icrisat.org/id/eprint/13210 |
| Official URL: | https://link.springer.com/article/10.1007/s10343-0... |
| Projects: | UNSPECIFIED |
| Funders: | UNSPECIFIED |
| Acknowledgement: | The authors are thankful to Director, ICAR-IARI, New Delhi, and the Head, Division of Entomology, ICAR-IARI, New Delhi for guidance and support during the compilation and drafting of the review article. Authors are thankful to SCOPUS and SCOPUS AI for assistance in compilation of this manuscript. RP is thankful for the support received under the Institute Project “Soil and Crop health monitoring through sensing, modelling, and big data analytics for resource efficient smart agriculture at field to regional scale (CRSCIARISIL20210034319)”. |
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