红外, 2015, 36 (12): 41, 网络出版: 2016-01-25
基于近红外光谱的西湖龙井茶产地的精细判别
Precise Discrimination of Xihu Longjing Tea from Different Producing Regions Based on Near-infrared Spectra
西湖龙井 近红外光谱 光谱预处理 主成分分析 判别分析 Xihu longjing tea near-infrared spectroscopy spectral pretreatment principal component analysis discriminant analysis
摘要
不同产区的西湖龙井茶的品质具有差异。采用近红外光谱技术和光谱预处理、主成分分析和判别模型等数学方法鉴别了分别产自龙井村、梅家坞村和葛衙庄三个地区的西湖龙井茶。结果表明,二阶导数光谱预处理方法对去除近红外光谱中的噪音最有效,贝叶斯判别分析是这三个地区产的西湖龙井茶的最佳判别模型。在模型中输入5个主成分数后,最佳的原始判别率和交叉验证判别率分别为100%和82.35%。在交叉验证判别中,产自葛衙庄、龙井村和梅家坞的茶叶的判别正确率分别为80%、83.33%和83.33%。因此,该模型可以用于龙井村、梅家坞村和葛衙庄三个地区产的西湖龙井茶的鉴别,为西湖龙井茶产区的判别提供理论依据。
Abstract
Xihu longjing tea from different producing regions has different quality. Near-infrared spectroscopy, spectral pretreatment, principal component analysis and discriminant model are used to discriminate Xihu longjing tea from Longjingvillage, Meijiawu village and Geya village. The results show that the second derivative pretreatment method is most effective for the removal of the noise in near infrared spectra and the Bayes discriminant analysis is the best discriminant model for thetea from the above three regions. Setting the components as 5 in the Bayes model, the best original discriminant rate and the cross-validation discriminant rate are 100% and 82.35% respectively. In the cross-validation, the discriminant accuracies of the tea from Longjing village, Meijiawu village and Geya village are 80%, 83.33% and 83.33% respectively. Therefore, the model can be used to discriminate Xihu longjing tea from Longjing village, Meijiawu village and Geya village and can provide the theoretical basis for the producing region discrimination of Xihu longjing tea.
张龙, 潘家荣, 朱诚. 基于近红外光谱的西湖龙井茶产地的精细判别[J]. 红外, 2015, 36(12): 41. ZHANG Long, PAN Jia-rong, ZHU Cheng. Precise Discrimination of Xihu Longjing Tea from Different Producing Regions Based on Near-infrared Spectra[J]. INFRARED, 2015, 36(12): 41.