倪鸿飞,张建平,黄家鹏,金建江,车彦军,樊剑锋,江 云,陈 勇.近红外光谱技术快速检测黄酒的前发酵过程中总酸含量[J].食品安全质量检测学报,2020,11(20):7298-7303
近红外光谱技术快速检测黄酒的前发酵过程中总酸含量
Rapid determination of total acid content in pre-fermentation process of rice wine by near infrared spectroscopy
投稿时间:2020-06-18  修订日期:2020-07-30
DOI:
中文关键词:  黄酒  近红外光谱技术  偏最小二乘法  过程质量控制  前发酵  总酸
英文关键词:yellow rice wine  near infrared spectroscopy  partial least square method  process quality control  prior to fermentation  total acid
基金项目:
作者单位
倪鸿飞 浙江大学药学院 
张建平 苏州泽达兴邦医药科技有限公司 
黄家鹏 苏州泽达兴邦医药科技有限公司 
金建江 中粮孔乙己酒业有限公司 
车彦军 中粮孔乙己酒业有限公司 
樊剑锋 中粮孔乙己酒业有限公司 
江 云 中粮孔乙己酒业有限公司 
陈 勇 浙江大学药学院 
AuthorInstitution
NI Hong-Fei School of Pharmacy, Zhejiang University 
ZHANG Jian-Ping Suzhou Zeda Xingbang Pharmaceutical Technology Co., LTD 
HUANG Jia-Peng Suzhou Zeda Xingbang Pharmaceutical Technology Co., LTD 
JIN Jian-Jiang COFCO Kong Yiji Liquor Co., Ltd 
CHE Yan-Jun COFCO Kong Yiji Liquor Co., Ltd 
FAN Jian-Feng COFCO Kong Yiji Liquor Co., Ltd 
JIANG Yun COFCO Kong Yiji Liquor Co., Ltd 
CHEN Yong School of Pharmacy, Zhejiang University 
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中文摘要:
      目的 建立近红外光谱法快速检测黄酒的前发酵过程中总酸含量的方法。方法 利用近红外光谱仪对黄酒生产过程中前发酵工段所得样品进行扫描, 对其光谱进行预处理和波段选择, 并结合偏最小二乘法(partial least squares, PLS)建立各工段快速无损检测方法。结果 所建立的模型的决定系数R为0.9348, 交叉验证均方根差值为0.118, 对验证集样品进行预测并统计分析, 预测值与真实值之间无显著差异(P>0.05)。结论 所建立的模型准确度高, 适用于黄酒前发酵过程总酸含量的快速检测。
英文摘要:
      Objective To establish a method for the rapid determination of total acid content in pre-fermentation process of rice wine by near infrared spectroscopy (NIR). Methods The samples obtained from the pre-fermentation section of yellow rice wine production were scanned by near infrared spectrometry, the spectrum was preprocessed and the wave bands were selected. A rapid nondestructive detection method for each section was established based on partial least squares (PLS). Results The coefficient of determination R of the established model was 0.9348, and the root mean square difference of cross-validation was 0.118. The validation set samples were predicted and analyzed statistically, there was no significant difference between the predicted value and the true value(P>0.05). Conclusion The established model has high accuracy and is suitable for the rapid determination of total acid content in the pre-fermentation process of yellow rice wine.
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