傅立叶变换近红外光谱法检测白酒总酸和总酯  

Determination of total acid and total ester in liquor based on Fourier transform near-infrared spectroscopy

作　　者：彭帮柱[1] 龙明华[2] 岳田利[1] 袁亚宏[1] 

机构地区：[1]西北农林科技大学食品科学与工程学院,杨凌712100 [2]杨凌职业技术学院农学系,杨凌712100

出　　处：《农业工程学报》2006年第12期216-219,共4页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家"十五"科技攻关项目(2001BA501A5-2.3)

摘　　要：该文研究白酒总酸和总酯的快速检测技术，通过解析不同白酒样品的近红外光谱图，对光谱数据进行不同的处理，结果表明：用一阶导数预处理光谱，谱区选择6102-5446cm^-1，利用人工神经网络与傅立叶变换近红外光谱相结合，采用内部交叉验证法建立模型，效果较好。其中，总酸模型的决定系数为96．73％，内部交叉验证均方根差为0．048g／L,总酯模型的决定系数为99．58％，内部交叉验证均方根差为0．085g／L，进一步对总酸和总酯的模型进行验证和评价，结果表明总酸模型验证集的相关系数为99．2％，预测标准偏差为0．074g／L；总酯模型验证集的相关为99．7％，预测标准偏差为0．134g／L，表明建立的模型可靠，预测效果好，能满足白酒生产中总酸和总酯的快速检测要求。In order to measure total acid （TA） and total ester （TE） accurately and quickly in liquor, calibration models were established based on Fourier-transform near-infrared spectroscopy with artifical neural network by Cross-Validation after the spectra were analyzed and discussed. Results show that according to the selected spectral ranges of 6102-5446 cm^-1, coefficients of the models （R^2） for TA and TE are 96.73% and 99. 58% respectively, and the root mean square errors of cross validation （RMSECV） for TA and TE are 0. 048 g/L and 0. 085 g/L respectively. Then the models were tested. Results show that R^2 for TA and TE are 99.2% and 99.7% respectively, and the root mean square errors of prediction （RMSEP） are 0. 074 g/L, 0. 134 g/L respectively. These suggest the models of TA and TE are reliable with good predictability and can meet the requirement of quick determination of TA and TE in liquor production.

关 键 词：傅立叶变换 近红外光谱 白酒 总酸 总酯 人工神经网络 

分 类 号：TS261.7[轻工技术与工程—发酵工程]