弗洛斯
绿原酸
偏最小二乘回归
化学
色谱法
近红外光谱
定性分析
食品科学
计算机科学
生物
机器学习
生物化学
社会学
神经科学
定性研究
芦丁
抗氧化剂
社会科学
作者
Jintao Xue,Yang Quanwei,LI Chun-yan,Liu Xiaolong,Bingxuan Niu
出处
期刊:Food Chemistry
[Elsevier]
日期:2021-04-01
卷期号:342: 128386-128386
被引量:24
标识
DOI:10.1016/j.foodchem.2020.128386
摘要
Lonicerae Japonicae Flos (LJF) has historically been widely utilized as a tea and health food. To better understand and evaluate its quality evaluate its quality, a near-infrared spectroscopy (NIRS) method was developed for the rapid and simultaneous analysis of the 3 main active components (chlorogenic acid, isochlorogenic acid A and isochlorogenic acid C). The NIRS model was built using 2 different strategies: partial least squares (PLS) as a linear regression method and artificial neural networks (ANN) as a nonlinear regression method. Furthermore, the NIRS method was applied to analyze the 4 main quality factors, which included 5 processing methods (shade drying, sun drying, vacuum drying, freeze drying and hot-air drying), 2 kinds of harvest time (flower bud stage and florescence stage), 2 species and 8 geographical origins. Collectively, NIRS is a promising method for the quality analysis of LJF.
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