食品与发酵工业2024，Vol.50Issue(1)：272-278,285,8.DOI:10.13995/j.cnki.11-1802/ts.035300
基于傅立叶变换中红外光谱技术的浓香型基酒快速检测
Research on rapid detection of strong-flavor base Baijiu by Fourier transform mid-infrared spectroscopy
摘要
Abstract
To monitor the quality of different distillates in the brewing process of strong-flavor Baijiu online,rapid detection models of eight compounds from strong-flavor base Baijiu in the process of picking were established through Fourier transform mid-infrared spectros-copy combined with partial least square method.The eight compounds include ethanol,ethyl acetate,ethyl butyrate,ethyl caproate,ethyl lactate,acetic acid,caproic acid and butyrate.The determination coefficients R2 of the prediction model of alcohol content,ethyl acetate and ethyl lactate were 0.99,that of ethyl caproate was 0.95,that of ethyl butyrate,acetic acid caproic acid are about 0.90,and that of butyrate was 0.79.The predicted results of infrared spectra on eight compounds had good linear correlation with chemical values,and the wider range of compound content,the more uniform content distribution,the better fitting degree of the model.The temperature difference in different seasons caused the fluctuation of infrared absorption spectrum of base Baijiu,which will reduce the accuracy of model detec-tion.The detection model established by the method of temperature compensation global correction can solve this problem and provide a feasible scheme for realizing automatic online Baijiu picking.关键词
傅立叶变换中红外光谱/偏最小二乘法/浓香型基酒/温度补偿全局校正/检测模型Key words
Fourier transform mid-infrared spectroscopy/partial least square method/strong-flavor base Baijiu/temperature compensa-tion global correction/detection model引用本文复制引用
韩云翠,吕志远,刘玉涛,张梦梦,张晨曦,卢春玲,邱振清,汪俊卿..基于傅立叶变换中红外光谱技术的浓香型基酒快速检测[J].食品与发酵工业,2024,50(1):272-278,285,8.基金项目
山东省重点研发计划(重大科技创新工程)项目(2022CXGC020206) （重大科技创新工程）
齐鲁工业大学(山东省科学院)科教产重大创新专项(2022JBZ01-06) （山东省科学院）
