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Recent advances in artificial intelligence towards the sustainable future of agri-food industry.
- Source :
-
Food chemistry [Food Chem] 2024 Jul 30; Vol. 447, pp. 138945. Date of Electronic Publication: 2024 Mar 05. - Publication Year :
- 2024
-
Abstract
- Artificial intelligence has the potential to alter the agricultural and food processing industries, with significant ramifications for sustainability and global food security. The integration of artificial intelligence in agriculture has witnessed a significant uptick in recent years. Therefore, comprehensive understanding of these techniques is needed to broaden its application in agri-food supply chain. In this review, we explored cutting-edge artificial intelligence methodologies with a focus on machine learning, neural networks, and deep learning. The application of artificial intelligence in agri-food industry and their quality assurance throughout the production process is thoroughly discussed with an emphasis on the current scientific knowledge and future perspective. Artificial intelligence has played a significant role in transforming agri-food systems by enhancing efficiency, sustainability, and productivity. Many food industries are implementing the artificial intelligence in modelling, prediction, control tool, sensory evaluation, quality control, and tackling complicated challenges in food processing. Similarly, artificial intelligence applied in agriculture to improve the entire farming process, such as crop yield optimization, use of herbicides, weeds identification, and harvesting of fruits. In summary, the integration of artificial intelligence in agri-food systems offers the potential to address key challenges in agriculture, enhance sustainability, and contribute to global food security.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1873-7072
- Volume :
- 447
- Database :
- MEDLINE
- Journal :
- Food chemistry
- Publication Type :
- Academic Journal
- Accession number :
- 38461725
- Full Text :
- https://doi.org/10.1016/j.foodchem.2024.138945