Integrating machine learning and the GGE biplot for identification of climate-suitable grasspea genotypes.

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Title: Integrating machine learning and the GGE biplot for identification of climate-suitable grasspea genotypes.
Authors: Barpete S; International Center for Agricultural Research in the Dry Areas (ICARDA)-Food Legumes Research Platform, Sehore, India., Das A; Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Vishwavidyalaya, Mohanpur, West Bengal, India., Parikh M; Department of Genetics and Plant Breeding, Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India., Yumnam S; Department of Genetics and Plant Breeding, Central Agricultural University, Imphal, Manipur, India., Aasim M; Department of Precision Agriculture and Agricultural Robotics, Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, Türkiye., Ali SA; Department of Information Systems and Technologies, Bilkent University, Ankara, Türkiye., Singh A; International Center for Agricultural Research in the Dry Areas (ICARDA), New Delhi, India., Yadav AK; International Center for Agricultural Research in the Dry Areas (ICARDA)-Food Legumes Research Platform, Sehore, India., Devate NB; International Center for Agricultural Research in the Dry Areas (ICARDA)-Food Legumes Research Platform, Sehore, India., Kaul S; International Center for Agricultural Research in the Dry Areas (ICARDA), New Delhi, India., Bhattacharya S; Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Vishwavidyalaya, Mohanpur, West Bengal, India., Roy S; Department of Genetics and Plant Breeding, Bidhan Chandra Krishi Vishwavidyalaya, Mohanpur, West Bengal, India., Gupta S; Division of Crop Sciences, Indian Council of Agricultural Research, Krishi Bhawan, New Delhi, India., Kumar S; International Center for Agricultural Research in the Dry Areas (ICARDA)-Food Legumes Research Platform, Sehore, India.; International Center for Agricultural Research in the Dry Areas (ICARDA), New Delhi, India.
Source: Frontiers in plant science [Front Plant Sci] 2025 Nov 21; Vol. 16, pp. 1647903. Date of Electronic Publication: 2025 Nov 21 (Print Publication: 2025).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101568200 Publication Model: eCollection Cited Medium: Print ISSN: 1664-462X (Print) Linking ISSN: 1664462X NLM ISO Abbreviation: Front Plant Sci Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1664-462X
DOI:10.3389/fpls.2025.1647903