ReviewRecent advances in food, nutrition & agriculture2026
Harnessing Artificial Intelligence for Sustainable Agriculture: A Comprehensive Scientometric Review.
Review in Recent advances in food, nutrition & agriculture, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agriculture empowers the economies of most developing countries as it contributes to the GDP and provides employment to half of the population. To augment the functionalities of agriculture, Artificial Intelligence (AI) has emerged as a significant solution. Consequently, substantial research endeavours have been carried out in this direction lately. However, a comprehensive study and scientometric analysis highlighting the potential of AI in agriculture has not been reported in the literature. Therefore, the presented scientometric study depicts the evolution of the pattern of research related to Artificial Intelligence technologies in agricultural practices based on the bibliographic data obtained from Scopus from 2015 to 2024. The data was analyzed and visualized using VOSviewer and Bibliometrix software by examining the publication growth trends, keyword co-occurrence networks, co-authorship networks, co-citation networks, institutional coupling networks, and journal coupling networks. The presented research concluded that India excels in the field, contributing 874 research documents, a substantial portion of the global total of 1,938. As per the link strength, China has secured the top position with 56 links and a total link strength of 1,080, while India follows closely in second place with 56 links and a total link strength of 871. The leading institution funding researchers with the highest number of publications is ICAR, while Science of the Total Environment stands out as the most relevant journal for disseminating their findings. The research topics explored involve using AI for disease detection, addressing nutrient deficiencies, analyzing soil content, and optimizing irrigation schedules. A notable emerging research topic highlights the effectiveness of AI in terms of increasing yield in agriculture. The future of AI in agriculture includes supply chain optimization, task automation, and climate adaptability, boosting food security and sustainability.
Indexed as
Identifiers
40129161What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.