摘要
绿茶中的茶多酚与氨基酸含量之比(即酚氨比)是评价绿茶滋味品质的量化指标。本文提出利用近红外光谱技术快速分析绿茶汤的酚氨比,并对光谱的特征变量进行筛选以提高模型的精度和稳定性。试验采用联合区间偏最小二乘法(siPLS)结合连续投影算法(SPA)筛选特征变量,建立酚氨比的估测模型,并与PLS、iPLS和siPLS方法建立的模型性能相比较。结果表明,应用siPLS结合SPA优选7个特征变量,主成分因子数为4时,所建模型性能最好,模型预测集相关系数(R p)为0.906,预测均方根误差(RMSEP)为0.258。对预测集30个样本的预测值与参考值进行t检验时,预测值与参考值无显著差异,说明模型准确可靠,可实现绿茶滋味品质的近红外光谱快速估测。
The ratio of tea polyphenols to free amino acids content is a quantitative index to evaluate the taste quality of green tea. In this paper, near infrared spectroscopy was used to rapidly predict the ratio of tea polyphenols to amino acids in tea infusion. Synergy interval PLS （siPLS） combined with successive projections algorithm （SPA） was implemented to select feature variables and a siPLS-SPA model was developed. And the performance of siPLS-SPA was compared with that of other models （eg. PLS, iPLS and siPLS）. The result showed that siPLS-SPA model was superior to others, and the optimal siPLS-SPA model was achieved with Rp = 0. 906 and RMSEP = 0. 258 in the prediction set when only 7 variables were selected and 4 PLS factors were included. T-test was done on 30 samples in prediction set, and the result indicated that there was no significant difference between the reference values and the prediction values. The result showed that siPLS-SPA model was accurate and reliable, and could be used to achieve the quick estimation of green tea taste quality.
出处
《核农学报》
CAS
CSCD
北大核心
2013年第10期1495-1500,共6页
Journal of Nuclear Agricultural Sciences
基金
江西省科技计划项目(20112BBF60019)
江西省教育厅科学基金项目(GJJ11081)
关键词
近红外光谱
绿茶滋味品质
酚氨比
联合区间偏最小二乘法
连续投影算法
Near infrared spectroscopy
Taste quality of green tea
Ratio of polyphenols to amino acids
Synergyinterval PLS
Successive projections algorithm
