Automated machine learning based prediction of monounsaturated and polyunsaturated fatty acids in Brassica napus L. using field-level agronomic data

Purpose: Rapeseed (Brassica napus L.) oil quality depends on monounsaturated (MUFA) and polyunsaturated (PUFA) fractions, but routine GC-FID profiling is slow and costly. This study develops fast, field-data–driven models to predict five individual unsaturated fatty acids (palmitoleic, oleic, eicose...

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Principais autores:	Amir Hossein Shirani Rad, Saba Shiranirad
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	Elsevier 2026-05-01
סדרה:	Industrial Crops and Products
נושאים:	Automated machine learning (AutoML) TPOT Brassica napus L. Monounsaturated fatty acids Polyunsaturated fatty acids SHAP
גישה מקוונת:	http://www.sciencedirect.com/science/article/pii/S0926669026006965
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