高度(三角形)
主成分分析
代谢组学
栽培
线性判别分析
一般化
数学
生物
植物
化学
色谱法
统计
几何学
数学分析
作者
Dan Zou,Xiao-Li Yin,Hui‐Wen Gu,Zhi-Xin Peng,Baomiao Ding,Zhenshun Li,Xian-Chun Hu,Wanjun Long,Haiyan Fu,Yuanbin She
出处
期刊:Food Chemistry
[Elsevier]
日期:2023-10-14
卷期号:436: 137768-137768
被引量:9
标识
DOI:10.1016/j.foodchem.2023.137768
摘要
The accurate identification of tea grade is crucial to the quality control of tea. However, existing methods lack sufficient generalization ability in identifying tea grades due to the effect of temporal and spatial factors. In this study, we analyzed the effect of cultivar and altitude on EnshiYulu (ESYL) tea grades and established a robust model to evaluate their quality. Principal component analysis (PCA) revealed that differences in variety and elevation can mask grade differences. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) was used for grade identification of samples from different altitudes. For ESYL tea samples above and below 800 m altitude, 75 and 35 grade differentiated metabolites were discovered, with 14 common differentiated metabolites. Based on reconstructed OPLS-DA models, the grades of multi-altitude sources ESYL were discriminated with a rate > 85%. These results demonstrate the potential of a grade discrimination model based on common differential metabolites, which exhibits generalization ability.
科研通智能强力驱动
Strongly Powered by AbleSci AI