Fatty Acid Profile-Based Chemometrics to Differentiate Metabolic Variations in Sorghum
Fatty Acid Profile-Based Chemometrics to Differentiate Metabolic Variations in Sorghum
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基于脂肪酸谱的化学计量学区分高粱的代谢变化
DOI:
10.1021/acsfoodscitech.1c00320
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发表时间:
2021
期刊:
影响因子:
--
通讯作者:
McDonald, Armando G.
中科院分区:
文献类型:
--
作者:
Mengistie, Endalkachew;Alayat, Abdulbaset M.;Sotoudehnia, Farid;Bokros, Norbert;DeBolt, Seth;McDonald, Armando G.
The extractive content and fatty acid profiles of Della andREDforGREEN(RG) sweet Sorghum varieties grown in two different seasons have been evaluated. The stalk internodes and nodes were quantitatively extracted with CH2Cl2. The extracts were converted to their fatty acid methyl ester (FAME) derivatives and analyzed by gas chromatography-mass spectrometry (GCMS). The main fatty acids detected were azelaic (C9:0), lauric (C12:0), myristic (C14:0), palmitic (C16:0), palmitoleic (C16:1), stearic (C18:0), oleic (C18:1), linoleic (C18:2), and eicosanoic acids (C20:1). Fatty acids were considered as chemical descriptors of varieties to evaluate metabolic variations, where principal component analysis (PCA) and linear discriminant analysis (LDA) multivariate analysis methods were applied. LDA allowed discrimination between Della and RG varieties with higher prediction accuracy, suggesting metabolic variations between them. The high predictive power suggests the use of a fatty acid composition as a fingerprint to reveal metabolic variations.
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作者:
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期刊:
影响因子:
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作者:
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