基于傅里叶变换近红外光谱量质摘酒模型的初步探索及应用研究  

Preliminary exploration and application research on the model of gathering distillate according to the quality based on Fourier transform near infrared spectroscopy

作　　者：廖丽 张贵宇 邹永芳 朱雪梅 彭厚博 张维 李雁 LIAO Li;ZHANG Guiyu;ZOU Yongfang;ZHU Xuemei;PENG Houbo;ZHANG Wei;LI Yan(SHEDE Spirits Co.,Ltd.,Shehong 629200,China;Artificial Intelligence Key Laboratory of Sichuan Province,School of Automation&Information Engineering,Sichuan University of Science&Engineering,Yibin 644000,China)

机构地区：[1]舍得酒业股份有限公司,四川遂宁629200 [2]四川轻化工大学自动化与信息工程学院人工智能四川省重点实验室,四川宜宾644000

出　　处：《中国酿造》2025年第4期190-196,共7页China Brewing

基　　金：四川省科技计划项目(2022YFS0554)。

摘　　要：为建立一种快速、高效、准确的量质摘酒技术,该研究利用气相色谱-质谱联用仪(GC-MS)对不同等级原酒(酒头、中段酒、尾酒)中的挥发性风味物质进行检测,采用主成分分析(PCA)法提取主成分。通过傅里叶变换近红外光谱(FT-NIR)获取光谱,对其进行光谱预处理及波长筛选,结合主成分建立回归预测模型,并采用随机森林(RF)算法构建量质摘酒模型。结果表明,PCA提取出17种主成分,采用多元散射校正(MSC)、竞争性自适应重加权采样法(CARS)及支持向量回归(SVR)方法构建回归预测模型较优,其决定系数R^(2)与均方根误差(RMSE)均值分别为0.8951、0.03;结合RF构建的量质摘酒模型效果较好,其准确率、精确率、召回率分别为99.10%、99.62%、99.78%。In order to establish a fast,efficient and accurate technology based on gathering distllate according to the quality,the volatile flavor compo-nents in different grades of original liquor(initial distilate,middle distillate,last distilate)were analyzed by gas chromatography-mass spectrometry(GC-MS),the principal components were selected by principal component analysis(PCA).The spectrum was obtained by Fourier transform near-in-frared spectroscopy(FT-NIR),and the spectrum pretreatment and wavelength screening were performed,the regression prediction model was estab-lished based on the principal components,and the model of gathering distillate according to the quality was constructed by random forest(RF).Results showed that 17 principal components were selected by PCA,Multiplicative scatter correction(MSC),competitive adaptive reweighting algorithms sampling(CARS)and support vector regression(SVR)were better methods to construct the regression prediction model,with coefficient of determi-nation R?and root mean square error(RMSE)mean values of 0.8951 and 0.03,respectively.The model of combining with RF was the optimal,and the accuracy rate,precision and recall rates of the model were 99.10%,99.62%and 99.78%.

关 键 词：傅里叶变换近红外光谱 气相色谱-质谱联用 挥发性风味物质 量质摘酒 

分 类 号：TS262.3[轻工技术与工程—发酵工程]