Applications and perspectives of Generative Artificial Intelligence in agriculture
Created March 19, 2026
Updated on March 25, 2026
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Language
English
MainTitle
Applications and perspectives of Generative Artificial Intelligence in agriculture
Original ids
10.1016/j.compag.2025.109919; 10261/382763
Type
publication
bestAccessRight
CLOSED
countries
null
Creator/Author
Full name
Federico Pallottino, orcid: 0000-0003-2035-1257 ; Simona Violino, orcid: 0000-0003-1853-7642 ; Simone Figorilli, orcid: 0000-0003-4035-4199 ; Catello Pane, orcid: 0000-0001-8666-2424 ; Jacopo Aguzzi, orcid: 0000-0002-1484-8219 ; Giacomo Colle, orcid: 0000-0002-3166-1755 ; Eugenio Nerio Nemmi, orcid: 0000-0001-6518-7863 ; Alessandro Montaghi, orcid: 0000-0001-8351-0230 ; Damianos Chatzievangelou, orcid: 0000-0001-7512-5105 ; Francesca Antonucci, orcid: ; Lavinia Moscovini, orcid: 0000-0001-9886-3194 ; Alessandro Mei, orcid: 0000-0003-1215-9644 ; Corrado Costa, orcid: 0000-0003-3711-1399 ; Luciano Ortenzi, orcid: 0000-0002-1245-8882
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Description
Artificial Intelligence (AI) applications related to agriculture have recently gained in use and attention. They are indeed valuable tools for interpreting data, improving production chains, and optimizing the use of natural resources. Among AI models, the most recent and promising area is represented by Generative Artificial Intelligence (GAI). After an initial description of its general model architectures, this work aims to review its practical uses and potentials in the following individual sectors: agriculture, precision farming, and animal farming, as well as interdisciplinary applications. The literature search was carried out using the SCOPUS, Google Scholar, and Web of Science databases. GAI holds immense potential for revolutionizing agriculture, offering solutions ranging from precision farming to pest management and supply chain optimization. Though some applications can extend beyond efficiency gains, and hallucinations occurrence i.e. false output information presented as fact, remains an open issue, GAI can be decisive for tasks like improving training datasets, refining models, and facilitating time series analysis. This review extensively describes the vital importance of these tasks for agriculture, precision and animal farming, caused by the rise of new technologies. As a result, by embracing and responsibly implementing GAI applications, it is possible to create a more sustainable and resilient future for agriculture and precision farming. GAI have the capacity to extract specific information from big data systems, offering huge potential to meet a growing global population demand and consequent environmental challenges for the future
Publication Date
2025-03-01
Publisher
Elsevier BV
Subjects
Microsoft Copilot; GAI; ChatGPT; Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation; LLMs; NLP; http://metadata.un.org/sdg/9; GAN
isGreen
false
isInDiamondJournal
false
Publication
Name
Computers and Electronics in Agriculture
Publication
Article
Starting page
109919
issnPrinted
0168-1699
vol
230
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Last Updated
March 25, 2026, 10:38 (UTC)
Created
March 19, 2026, 00:19 (UTC)
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