文献类型：期刊文献

英文题名：Rapid discrimination of Chinese rice Wine (Huangjiu) from various regions using Benchtop-NIR and Micro-NIR spectrometers in conjunction with chemometrics

作者：Hu, Qiang[1];Feng, Xinxin[3];Wang, Lan[4];Zhang, Lili[3];Chen, Xueping[3];Wang, Yanyun[1];Xie, Guangfa[2];Peng, Qi[3]

机构：[1]Leshan Normal Univ, Coll Life Sci, Leshan 614000, Peoples R China;[2]Zhejiang Shuren Univ, Coll Biol & Environm Engn, Zhejiang Collaborat Innovat Ctr Full Proc Monitori, Hangzhou 310015, Peoples R China;[3]Shaoxing Univ, Natl Engn Res Ctr Chinese CRW, Branch Ctr, Sch Life & Environm Sci, Shaoxing 312000, Zhejiang, Peoples R China;[4]China Shaoxing Yellow Rice Wine Grp Co Ltd, Zhejiang Shaoxing Huangjiu Ind Innovat Serv Comple, Shaoxing 312000, Zhejiang, Peoples R China

年份：2025

卷号：149

外文期刊名：INFRARED PHYSICS & TECHNOLOGY

收录：SCI-EXPANDED(收录号：WOS:001491072500001)、、EI(收录号：20251918403242)、Scopus(收录号：2-s2.0-105004662740)、WOS

基金：This work was supported by the Zhejiang Shaoxing Huangjiu Industry Innovation Service Complex- Technological Innovation Project in Zhejiang Province (No.2023KJ082) ; Foundation of Public Projects of Zhejiang Province, China (No.LGN22C200008) ; Program Foundation of Public Projects of Shaoxing city, Zhejiang Province, China (No.2018C30010) ; Foundation of Public Projects of Zhejiang Province, China (No.2017C32101) ; Shaoxing University Fund (No.08021066) , Shaoxing University Fund (No.08220102213) , Shaoxing University Fund (No. 08240102300) .

语种：英文

外文关键词：Huangjiu; Benchtop-NIR; Micro-NIR; Rapid identification; Regionality

外文摘要：Near Infrared (NIR) technology plays a crucial role in food authenticity and origin identification. This study evaluates benchtop-NIR and Micro-NIR technologies, combined with chemometrics, to differentiate Huangjiu (Chinese rice wine) origins. Both models demonstrated strong performance, with Micro-NIR excelling in identification and prediction over benchtop-NIR. Spectral data from Huangjiu across various regions were used to develop a chemometric discrimination model. Benchtop-NIR's database utilized first derivative preprocessing, while the sub-database employed second derivative and vector normalization. Micro-NIR used Savitzky-Golay (S. Golay), Standard Normal Variate (SNV), and Normalize Peak preprocessing, achieving 100% accuracy. Benchtop-NIR's Q2 was 0.939, R2X [1] 0.738, R2X [2] 0.202, and R2 0.94. Micro-NIR outperformed with Q2 at 0.983, R2X [1] 0.981, R2X [2] 0.00627, and R2 at 0.988. This study significantly advances the geographical identification of Huangjiu using NIR technology.