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近红外光谱结合化学计量学技术快速测定面条中马铃薯全粉的含量
引用本文:吕都,董楠,陈中爱,王辉,李俊,刘嘉. 近红外光谱结合化学计量学技术快速测定面条中马铃薯全粉的含量[J]. 现代食品科技, 2019, 35(4): 230-236
作者姓名:吕都  董楠  陈中爱  王辉  李俊  刘嘉
作者单位:贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006;贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006;贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006;贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006;贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006;贵州省农业科学院生物技术研究所,贵州省农业科学院食品加工研究所,贵州贵阳550006
基金项目:国家重点研发计划(2016YFNC010104);贵州省科技计划项目(黔科合基础[2017]1179);贵州省科技计划课题(黔科合重大专项字[2014]6016);贵州省农业科学院课题(黔农科院科技创新[2017]07号)
摘    要:马铃薯干物质的主要成分为淀粉,将其与面粉混合后采用传统工艺制作成的马铃薯面条,使用化学检测方法很难测定马铃薯面条中马铃薯全粉的含量和面粉的含量。本研究旨在建立一种快速检测面条中马铃薯全粉含量的方法,为市场监督部门提供技术支撑。以不同马铃薯全粉含量的面条样品236份为实验材料,采集样品近红外漫反射光谱,结合化学计量学软件建立并优化预测模型。结果表明:近红外光谱图范围为9403.6~5446.2 cm-1时,采用最小-最大归一化预处理光谱,建立的预测模型稳定性强预测精度高,预测模型的外部验证决定系数(R2val)为0.9775、预测均方根误差(RMSEP)为1.28%,斜率为0.95,模型的相对分析误差(relative prediction deviation,RPD)为4.74。采用近红外漫反射光谱技术可以快速预测面条中马铃薯全粉的含量,可以为市场监督部门提供技术支持。

关 键 词:近红外  马铃薯  面条  含量
收稿时间:2018-12-03

Rapid Determination of Potato Powder Composition of Noodles by NIR Spectroscopy and Stoichiometry
LYU Du,DONG Nan,CHEN Zhong-ai,WANG Hui,LI Jun and LIU Jia. Rapid Determination of Potato Powder Composition of Noodles by NIR Spectroscopy and Stoichiometry[J]. Modern Food Science & Technology, 2019, 35(4): 230-236
Authors:LYU Du  DONG Nan  CHEN Zhong-ai  WANG Hui  LI Jun  LIU Jia
Affiliation:(Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China),(Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China),(Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China),(Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China),(Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China) and (Biotechnology Institute of Guizhou Province, Food Processing Institute of Guizhou Province, Guiyang 550006, China)
Abstract:It was difficult to determined the content of whole potato powder and flour in potato noodles by chemical method. The objective of the study was to establish prediction model for rapid determination of potato powder composition in noodles by NIR spectroscopy and stoichiometry. The method was that 236 potato noodles studied by near infrared spectroscopy and stoichiometry were used to establish prediction model. The result indicated that the prediction model based on wave number of 9403.6~5446.2 cm-1 and spectral pretreatment by minimum-maximum normalization showed an excellent prediction accuracy. The external validation determinant (R2val) was 0.9775, the root mean square error of prediction (RMSEP) was 1.28%, the slope was 0.95, and the relative prediction deviation (RPD) was 4.74. The results indicated that near infrared spectroscopy can be used as an efficient way to detect the potato powder content in potato noodles.
Keywords:NIR   potato   noodles   quantification
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