Multivariate analysis and machine learning prediction of Sorghum cultivar traits under nitrogen regulation.

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Bibliographic Details
Title: Multivariate analysis and machine learning prediction of Sorghum cultivar traits under nitrogen regulation.
Authors: Altaf MT; Department of Field Crops, Faculty of Agriculture, Recep Tayyip Erdoğan University, Pazar, Rize, 53300, Türkiye. muhammadtanveer.altaf@erdogan.edu.tr., Liaqat W; Department of Field Crops, Faculty of Agriculture, Recep Tayyip Erdoğan University, Pazar, Rize, 53300, Türkiye. waqasliaqat0043@gmail.com., Bedir M; Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, 58140, Türkiye., Cömertpay G; Eastern Mediterranean Agricultural Research Institute, Adana, 01370, Türkiye., Ali SA; Department of Information Systems and Technologies, Bilkent University, Ankara, 06800, Türkiye., Aasim M; Faculty of Agricultural Sciences and Technologies, Sivas University of Science and Technology, Sivas, 58140, Türkiye., Nadeem MA; Department of Biotechnology, Faculty of Science, Mersin University, Yenişehir, Mersin, 33343, Türkiye., Baloch FS; Department of Biotechnology, Faculty of Science, Mersin University, Yenişehir, Mersin, 33343, Türkiye.; Institute of Biochemistry, Department of Genetics, Sh. Rashidov Samarkand State University, Samarkand, 140104, Uzbekistan.
Source: BMC plant biology [BMC Plant Biol] 2026 Feb 28; Vol. 26 (1). Date of Electronic Publication: 2026 Feb 28.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 100967807 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2229 (Electronic) Linking ISSN: 14712229 NLM ISO Abbreviation: BMC Plant Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1471-2229
DOI:10.1186/s12870-026-08434-9