食品与发酵工业 >

2024 , Vol. 50 >Issue 20: 335 - 340

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.039301

分析与检测

基于理化、风味物质和化学计量学的窖泥质量分级方法

  • 倪兴婷 ,
  • 孙细珍 ,
  • 刘怀臣 ,
  • 陈杰 ,
  • 郭铮祥 ,
  • 沈蕊 ,
  • 汪咏曾 ,
  • 曹珏珏 ,
  • 黄智安 ,
  • 李强 ,
  • 杨强
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  • 1(劲牌有限公司,湖北 黄石,435100)
    2(宜宾南溪酒业有限公司,四川 宜宾,644100)
第一作者:硕士,工程师(孙细珍高级工程师为通信作者,E-mail:347739489@qq.com)

收稿日期: 2024-03-21

  修回日期: 2024-05-08

  网络出版日期: 2024-11-01

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A quality classification method of pit mud based on physicochemical, flavor substance and stoichiometry

  • NI Xingting ,
  • SUN Xizhen ,
  • LIU Huaichen ,
  • CHEN Jie ,
  • GUO Zhengxiang ,
  • SHEN Rui ,
  • WANG Yongzeng ,
  • CAO Juejue ,
  • HUANG Zhian ,
  • LI Qiang ,
  • YANG Qiang
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  • 1(Jing Brand Co.Ltd., Huangshi 435100, China)
    2(Yibin Nanxi Distillery Co.Ltd., Yibin 644100, China)

Received date: 2024-03-21

  Revised date: 2024-05-08

  Online published: 2024-11-01

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摘要

窖泥质量的优劣与浓香型白酒的产量和品质密切相关,科学的窖泥质量分级方法可以为窖泥新窖配方优化和老窖养护提供理论依据。但目前窖泥质量标准仍以感官评价、理化指标和简单的微生物指标(细菌总数和芽孢杆菌数)为主,无法全面、客观地反映窖泥质量。该研究运用多种检测技术对不同质量等级窖泥理化指标及风味物质进行检测,基于偏最小二乘法(partial least squares,PLS)建立一种准确、可靠的窖泥分级方法。该研究采用理化分析、电感耦合等离子体质谱和GC-MS技术对以感官分析与对应酒质分级的不同质量等级窖泥为研究对象进行分析,采用PLS对检测结果进行分析,筛选出与窖泥质量等级相关的潜在标记物共27种,包括钠、水分、氨态氮、钾、钙、己酸、己酸乙酯、4-甲基苯酚等。采用训练集基于这27种潜在标记物建立窖泥等级快速预测模型,不同等级窖泥在PLS得分图中完全分开,利用训练集和验证集数据对模型进行验证,结果表明该模型稳定可靠,预测准确率较高。该方法在窖泥质量分级中具有较高的准确性,可用于窖泥等级分析预测。

关键词： 窖泥; 质量分级; 理化指标; 风味物质; 偏最小二乘法

本文引用格式

倪兴婷 , 孙细珍 , 刘怀臣 , 陈杰 , 郭铮祥 , 沈蕊 , 汪咏曾 , 曹珏珏 , 黄智安 , 李强 , 杨强 . 基于理化、风味物质和化学计量学的窖泥质量分级方法[J]. 食品与发酵工业, 2024 , 50(20) : 335 -340 . DOI: 10.13995/j.cnki.11-1802/ts.039301

Abstract

The quality of pit mud is closely related to the yield and quality of Luzhou flavor Baijiu.Scientific pit mud quality grading method can provide a theoretical basis for the optimization of new pit mud formula and the maintenance of old pits.However, the current quality standards for pit mud still mainly rely on sensory evaluation, physical and chemical indicators, and simple microbial indicators (total bacterial count and spore count), which cannot comprehensively and objectively reflect the quality of pit mud.This study used multiple detection techniques to detect the physicochemical indicators and flavor substances of pit mud with different quality grades and established an accurate and reliable pit mud classification method based on partial least squares (PLS).This article used physical and chemical analysis, inductively coupled plasma mass spectrometry (ICP-MS), and gas chromatography-mass spectrometry (GC-MS) techniques to analyze pit mud with different quality grades based on sensory analysis and corresponding wine quality grading.PLS was utilized to analyze the detection results, and a total of 27 potential markers related to the quality grade of pit mud were selected, including sodium, water, ammonia nitrogen, potassium, calcium, hexanoic acid, ethyl hexanoate, 4-methylphenol, etc.A fast prediction model for pit mud grade was established based on these 27 potential markers using a training set.Pit mud with different grades were completely separated in the PLS score map, and the model was validated using training and validation set data.Results showed that the model was stable, reliable, and had a high prediction accuracy.This method has high accuracy in the classification of pit mud quality and can be used for analyzing and predicting pit mud grades.

Key words： pit mud; quality grading; physicochemical indicators; flavor substances; partial least squares

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