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Non-destructive yield estimation of onion and garlic using UAV-based hyperspectral imaging and hybrid machine learning models.

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Bibliographic Details
Title: Non-destructive yield estimation of onion and garlic using UAV-based hyperspectral imaging and hybrid machine learning models.
Authors: Su Y; Postgraduate Training Base Alliance of Wenzhou Medical University (Zhejiang Cancer Hospital), Hangzhou, Zhejiang, 310022, China., Long J; Forestry Techonology Extension Service Center, Aksu Prefecture, Xinjiang, 843000, China., Chen J; Agricultural Techonology Extension Service Center, Aksu Prefecture, Xinjiang, 843000, China., Zhou R; School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China., Liu Z; School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China. elena00@jnu.ac.kr., Deng H; School of Economics and Management, Xinjiang Institute of Technology, Akesu, 842008, China. 63709341@qq.com., Yuan Y; School of Mental Health, Wenzhou Medical University, Wenzhou, 325035, China. yuanye017@126.com.; School of Economics and Management, Xinjiang Institute of Technology, Akesu, 842008, China. yuanye017@126.com.
Source: BMC plant biology [BMC Plant Biol] 2026 Jun 20; Vol. 26 (1). Date of Electronic Publication: 2026 Jun 20.
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/s12870-026-09289-w