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Volume 13
Issue 5
10.3390/agronomy13051397
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Review

Artificial Intelligence: Implications for the Agri-Food Sector

by
Akriti Taneja
1,
Gayathri Nair
1,
Manisha Joshi
1,
Somesh Sharma
1,*,
Surabhi Sharma
2,
Anet Rezek Jambrak
3,
Elena Roselló-Soto
4,*,
Francisco J. Barba
4,
Juan M. Castagnini
4,
Noppol Leksawasdi
5 and
Yuthana Phimolsiripol
5,*
1
School of Bioengineering and Food Technology, Shoolini University, Solan 173229, Himachal Pradesh, India
2
School of Agricultural Science and Technology, RIMT, Fatehgarh Sahib 147301, Punjab, India
3
Faculty of Food Technology and Biotechnology, University of Zagreb, 10000 Zagreb, Croatia
4
Department of Preventive Medicine and Public Health, Food Science, Toxicology and Forensic Medicine, Faculty of Pharmacy, Universitat de València, Avda. Vicent Andrés Estellés s/n, 46100 Burjassot, Spain
5
Faculty of Agro-Industry, Chiang Mai University, Chiang Mai 50100, Thailand
*
Authors to whom correspondence should be addressed.
Agronomy 2023, 13(5), 1397; https://doi.org/10.3390/agronomy13051397
Submission received: 8 April 2023 / Revised: 14 May 2023 / Accepted: 15 May 2023 / Published: 18 May 2023
(This article belongs to the Section Precision and Digital Agriculture)
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Abstract

Artificial intelligence (AI) involves the development of algorithms and computational models that enable machines to process and analyze large amounts of data, identify patterns and relationships, and make predictions or decisions based on that analysis. AI has become increasingly pervasive across a wide range of industries and sectors, with healthcare, finance, transportation, manufacturing, retail, education, and agriculture are a few examples to mention. As AI technology continues to advance, it is expected to have an even greater impact on industries in the future. For instance, AI is being increasingly used in the agri-food sector to improve productivity, efficiency, and sustainability. It has the potential to revolutionize the agri-food sector in several ways, including but not limited to precision agriculture, crop monitoring, predictive analytics, supply chain optimization, food processing, quality control, personalized nutrition, and food safety. This review emphasizes how recent developments in AI technology have transformed the agri-food sector by improving efficiency, reducing waste, and enhancing food safety and quality, providing particular examples. Furthermore, the challenges, limitations, and future prospects of AI in the field of food and agriculture are summarized.
Keywords: machine learning; smart farming; internet of things; sustainable management; food quality; food safety machine learning; smart farming; internet of things; sustainable management; food quality; food safety

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MDPI and ACS Style

Taneja, A.; Nair, G.; Joshi, M.; Sharma, S.; Sharma, S.; Jambrak, A.R.; Roselló-Soto, E.; Barba, F.J.; Castagnini, J.M.; Leksawasdi, N.; et al. Artificial Intelligence: Implications for the Agri-Food Sector. Agronomy 2023, 13, 1397. https://doi.org/10.3390/agronomy13051397

AMA Style

Taneja A, Nair G, Joshi M, Sharma S, Sharma S, Jambrak AR, Roselló-Soto E, Barba FJ, Castagnini JM, Leksawasdi N, et al. Artificial Intelligence: Implications for the Agri-Food Sector. Agronomy. 2023; 13(5):1397. https://doi.org/10.3390/agronomy13051397

Chicago/Turabian Style

Taneja, Akriti, Gayathri Nair, Manisha Joshi, Somesh Sharma, Surabhi Sharma, Anet Rezek Jambrak, Elena Roselló-Soto, Francisco J. Barba, Juan M. Castagnini, Noppol Leksawasdi, and et al. 2023. "Artificial Intelligence: Implications for the Agri-Food Sector" Agronomy 13, no. 5: 1397. https://doi.org/10.3390/agronomy13051397

APA Style

Taneja, A., Nair, G., Joshi, M., Sharma, S., Sharma, S., Jambrak, A. R., Roselló-Soto, E., Barba, F. J., Castagnini, J. M., Leksawasdi, N., & Phimolsiripol, Y. (2023). Artificial Intelligence: Implications for the Agri-Food Sector. Agronomy, 13(5), 1397. https://doi.org/10.3390/agronomy13051397

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