摘要
通过对当年新茶及其在室温条件下陈化处理1年后的陈茶进行HPLC分析,分别获得了其色谱峰,利用其峰面积数据(变量X)结合通过对新茶和陈茶分别人为定义的一个新数值(变量Y),用偏最小二乘法(partial least squares,PLS)建立了预测模型,通过量化的模型计算得到的预测值与新茶和陈茶的临界值的比较实现了新茶和陈茶的精确鉴别,对2006年生产的120个定标样和38个外部未知茶叶样品的鉴别准确率分别达到了100%和97.37%,同时对2007年生产的14个新茶样本的判别准确率也达到了92.8%。
Chromatograms area data of tea samples ( new tea and old tea stored in the room temperature for a year) were obtained by HPLC. PLS was used to establish the quantitative prediction model with area data (variance X) and defined numeral (variance Y). The results calculated by the PLS model were used to identify new tea and old tea through comparison with the critical numeral. The result showed that the accuracy rate of identification was 100% in 120 known samples set and 97.37% in 38 unknown samples produced in 2006, and 92.8% in 14 new tea samples was achieved which was produced in 2007 .
出处
《江西农业学报》
CAS
2008年第7期58-61,共4页
Acta Agriculturae Jiangxi
基金
国家科技基础条件平台项目(2005DKA1002)
浙江省自然科学基金项目(Y305096)