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Artificial intelligence for crop yield prediction: a bibliometric analysis


Affiliations
1 The Graduate School, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India; ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
2 Division of Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
3 Division of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
4 Division of Computer Application, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India

The synergy between artificial intelligence (AI) and agricultural sciences has garnered substantial attention, especially in the realm of crop yield prediction. The present bibliometric analysis examines the worldwide research trends about the application of AI in predicting crop yields. The global literature on crop yield prediction using AI published between 1997 and 2022 is searched in the Scopus database. Five hundred and forty research articles were used to compile the analysis; they were located in the Scopus database and processed through the VOSviewer. Our research reveals a significant surge in scholarly publications, particularly focusing on countries including China, the United States, India and Canada. These research endeavours aim to apply AI methodologies for forecasting agricultural produce yields in tandem with developments in remote sensing technologies that facilitate more accurate yield predictions. These insights offer a valuable reference for researchers and illuminate potential directions for future investigations in the domain of AI-based crop yield prediction

Keywords

: Artificial intelligence, bibliometric analysis, crop yield prediction, deep learning, machine learning, remote sensing, VOSviewer.
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  • Artificial intelligence for crop yield prediction: a bibliometric analysis

Abstract Views: 126  | 

Authors

M. Lokeshwari
The Graduate School, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India; ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
Girish Kumar Jha
Division of Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India
K. V. Praveen
Division of Agricultural Economics, ICAR-Indian Agricultural Research Institute, New Delhi 110 012, India
Anshu Bharadwaj
Division of Computer Application, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012, India

Abstract


The synergy between artificial intelligence (AI) and agricultural sciences has garnered substantial attention, especially in the realm of crop yield prediction. The present bibliometric analysis examines the worldwide research trends about the application of AI in predicting crop yields. The global literature on crop yield prediction using AI published between 1997 and 2022 is searched in the Scopus database. Five hundred and forty research articles were used to compile the analysis; they were located in the Scopus database and processed through the VOSviewer. Our research reveals a significant surge in scholarly publications, particularly focusing on countries including China, the United States, India and Canada. These research endeavours aim to apply AI methodologies for forecasting agricultural produce yields in tandem with developments in remote sensing technologies that facilitate more accurate yield predictions. These insights offer a valuable reference for researchers and illuminate potential directions for future investigations in the domain of AI-based crop yield prediction

Keywords


: Artificial intelligence, bibliometric analysis, crop yield prediction, deep learning, machine learning, remote sensing, VOSviewer.



DOI: https://doi.org/10.18520/cs%2Fv126%2Fi10%2F1245-1253