基于二维相关近红外光谱的白酒酒龄鉴别
CSTR:
作者:
作者单位:

作者简介:

周涛,男,山西农业大学在读硕士研究生

通讯作者:

中图分类号:

基金项目:

山西省自然科学基金项目(编号:201701D121103);国家重点研发计划项目(编号:2016YFD0701801)


Identification of the age of Baijiu based on two-dimensional correlation near infrared spectroscopy
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    目的:杜绝以低龄酒冒充高龄酒,实现对白酒酒龄的判别。方法:利用近红外光谱仪采集白酒样品的近红外透射光谱,以酒龄作为外扰,构建各白酒样品的同步和异步二维相关谱;在此基础上,提取每个样品的自相关谱,并结合马氏距离法建立白酒酒龄判别模型。结果:1400~1800 nm波段范围内包含白酒样品随酒龄变化的有效信息;模型校正集判别正确率为93.3%,预测集判别正确率为92.0%。结论:二维相关谱结合马氏距离法能够对白酒酒龄进行有效鉴别。

    Abstract:

    Objective: To avoid young liquor as old liquor and realize the discrimination of Baijiu age. Methods: The near infrared transmission spectra of Baijiu samples were collected by near infrared spectrometer, and the synchronous and asynchronous two-dimensional correlation spectra of Baijiu samples were constructed with the wine age as the external disturbance. On this basis, the autocorrelation spectrum of each sample was extracted, and the age discrimination model of Baijiu was established by combining Markov distance method. Results: The wave band from 1400 nm to 1800 nm contained the effective information about the changes of Baijiu samples on age. The discrimination accuracy of model correction set was 93.3%, and that of prediction set was 92.0%. Conclusion: Two dimensional correlation spectrum combined with Mahalanobis distance method can effectively identify the age of Baijiu.

    参考文献
    相似文献
    引证文献
引用本文

周涛,张志勇,韩宁,等.基于二维相关近红外光谱的白酒酒龄鉴别[J].食品与机械,2022,(12):56-59,98.
ZHOU Tao, ZHANG Zhi-yong, HAN Ning, et al. Identification of the age of Baijiu based on two-dimensional correlation near infrared spectroscopy[J]. Food & Machinery,2022,(12):56-59,98.

复制
相关视频

分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2023-02-28
  • 出版日期:
文章二维码
×
《食品与机械》
友情提示
友情提示 一、 近日有不少作者反应我刊官网无法打开,是因为我刊网站正在升级,旧网站仍在百度搜索排名前列。请认准《食品与机械》唯一官方网址:http://www.ifoodmm.com/spyjx/home 唯一官方邮箱:foodmm@ifoodmm.com; 联系电话:0731-85258200,希望广大读者和作者仔细甄别。