摘要
以76份有代表性的小种红茶为研究对象,采用现行国标方法测定的茶多酚和咖啡碱含量作为近红外预测模型的化学值,对应采集样品的近红外光谱值,分别建立小种红茶茶多酚和咖啡碱含量最佳偏最小二乘法(Partial least squares,PLS)模型。结果表明,所构建的茶多酚含量模型校正集决定系数(Coefficient of determination,R2)为97.59%,校正均方差(Root mean square error of calibration,RMSEC)为0.566%,验证集R2为95.06%,预测均方差(Root mean square error of prediction,RMSEP)为0.855%;咖啡碱含量模型校正集R2为96.98%,RESEC为0.110%,验证集R2为95.67%,RESEP为0.148%。茶多酚和咖啡碱含量定量分析模型效果均较好,可实现对小种红茶茶多酚和咖啡碱含量的快速检测。
A total of 76 representative Souchong samples were studied.Quantitative models of tea polyphenols and caffeine of Souchong were established respectively by partial least squares(PLS).The chemical values of tea polyphenols and caffeine of 76 Souchong samples were measured by Chinese National Standard methods,combined with the near infrared spectrum.The results show that the R2 and RMSEC values of tea polyphenols of calibration set were 97.59%and 0.566%.And the R2 and RMSEP values of validation set were 95.06%and 0.855%.The R2 and RMSEC values of caffeine of calibration set were 96.98%and 0.110%.And the R2 and RMSEP values of validation set were 95.67%and 0.148%.The quantitative models had good prediction results,and could be used for rapid evaluation of the contents of tea polyphenols and caffeine in Souchong.
作者
卢莉
程曦
张渤
沈小霞
刘艳
熊丽
袁潇
李远华
黎星辉
LU Li;CHENG Xi;ZHANG Bo;SHEN Xiaoxia;LIU Yan;XIONG Li;YUAN Xiao;LI Yuanhua;LI Xinghui(College of Tea and Food Sciences,Wuyi University,Wuyishan 354300,China;College of Horticulture,Nanjing Agricultural University,Nanjing 210095,China)
出处
《茶叶科学》
CAS
CSCD
北大核心
2020年第5期689-695,共7页
Journal of Tea Science
基金
福建省自然科学基金(2017J01648)
福建省科技创新平台建设(2018N2004)
国家自然科学基金(31870682)。
关键词
小种红茶
近红外光谱
茶多酚
咖啡碱
模型
Souchong
near infrared spectroscopy(NIRS)
tea polyphenols
caffeine
models