吴瑞梅,岳鹏翔,赵杰文,黄星奕,陈全胜.特征变量筛选在近红外光谱测定绿茶汤中茶多酚的应用[J].农业机械学报,2011,42(12):154-157,163.
Wu Ruimei,Yue Pengxiang,Zhao Jiewen,Huang Xingyi,Chen Quansheng.Application of Characteristic Variables Selection in Determination of Polyphenols Content in Green Tea Infusion by Near Infrared Spectroscopy[J].Transactions of the Chinese Society for Agricultural Machinery,2011,42(12):154-157,163.
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特征变量筛选在近红外光谱测定绿茶汤中茶多酚的应用   [下载全文]
Application of Characteristic Variables Selection in Determination of Polyphenols Content in Green Tea Infusion by Near Infrared Spectroscopy   [Download Pdf][in English]
  
DOI:10.3969/j.issn.1000-1298.[year].[issue].[sequence]
中文关键词:  茶多酚  近红外光谱  联合区间偏最小二乘法  遗传算法
基金项目:国家自然科学基金资助项目(30971685)、江苏省自然科学基金资助项目(BK2009216)、福建漳州市蓝火计划资助项目(Z2010016)和江苏大学博士创新计划资助项目(CX10B_020X)
作者单位
吴瑞梅 江苏大学,江西农业大学 
岳鹏翔 大闽食品(漳州)有限公司 
赵杰文 江苏大学 
黄星奕 江苏大学 
陈全胜 江苏大学 
中文摘要:利用化学计量学方法从绿茶汤近红外光谱中提取茶多酚光谱信息,建立茶多酚近红外光谱定量分析模型。光谱采集使用5mm光程的石英比色皿,利用联合区间偏最小二乘法(siPLS)筛选特征光谱区间,然后在筛选的光谱区间内进一步利用遗传算法(GA)优选特征变量。结果表明,siPLS筛选的特征光谱区间避开了水的强吸收峰影响,利用GA在筛选的特征光谱区间内优选出166个特征变量建立PLS模型,模型预测集均方根误差为0.685%,相对标准差为5.26%,相对分析误差为3.22,所建模型能达到精度要求,可用于实际检测。
Wu Ruimei  Yue Pengxiang  Zhao Jiewen  Huang Xingyi  Chen Quansheng
Jiangsu University,Jiangxi Agricultural University;Damin (Zhangzhou)
Food Co., Ltd.;Jiangsu University;Jiangsu University;Jiangsu University
Key Words:Polyphenols, Near infrared spectroscopy, Synergy interval PLS, Genetic algorithm
Abstract:The feasibility to extract the polyphenols spectra information from near infrared spectroscopy of green tea infusion using chemometrics methods was attempted. A cylindrical quartz glass tube with an optical path of 5mm was used. First, synergy interval PLS (siPLS) was implemented to select efficient spectral regions from SNV preprocessed spectra. Then, optimal variables were selected using genetic algorithm (GA) from these selected spectral regions by siPLS. This study showed that the selected characteristic spectral intervals were not within the range of the strong absorbance for water. When 166 variables selected by GA and eight PLS factors were included, the optimal model (siPLS-GA) was achieved with PRMSEP=0.685%, PRSD=5.26% and PRPD=3.22 in the prediction set. The results showed that the performance of siPLS-GA model could be employed to measure polyphenols content in green tea infusion by near infrared spectroscopy in practice.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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