基于HS-SPME-GC-MS结合近红外技术鉴别黄酒不同陈酿状态

IF 6.5 1区农林科学 Q1 CHEMISTRY, APPLIED

Food Chemistry: X Pub Date : 2025-06-20 DOI:10.1016/j.fochx.2025.102676

Guangfa Xie , Junhao Xie , Dongsheng Qian , Lan Wang , Guochang Sun , Qingzhong Mao , Zhifang Yu , Mengsha Hu , Qi Peng

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引用次数: 0

摘要

由于黄酒在陈酿过程中感官特性的发展，确定其陈酿状态对其商业和科学意义至关重要。以中国顶级酒庄古岳龙山酒庄的黄酒为研究对象，采用近红外光谱仪、气相色谱-质谱联用顶空固相微萃取技术进行分析。化学计量学分析解释了数据，能够预测和分类年龄为1、5、8、10和20年的样本。主成分分析（PCA）和代谢物筛选显示了样品之间的系统性差异。因子分析和偏最小二乘回归分析构建的子库模型识别准确率超过95%，PLS模型的R2超过98%，RPD超过5，便于准确识别样本年份。研究结果为进一步了解绍兴黄酒的陈年过程提供了重要的技术支持，为保持绍兴黄酒这一地理标志保护产品的质量提供了重要的技术支持。

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Differentiation of Chinese rice wine(Huangjiu) from different aging status based on HS-SPME-GC–MS combined with near infrared

This study investigates the crucial task of determining the aging state of Huangjiu, which is vital for its commercial and scientific significance due to the development of sensory characteristics during aging. Focused on Huangjiu from Guyue Longshan winery, China's top producer, the analysis employed a near-infrared spectrometer and gas chromatography–mass spectrometry coupled with headspace-solid phase microextraction. Stoichiometric analysis interpreted the data, enabling prediction and classification of samples aged for 1, 5, 8, 10, and 20 years. Principal component analysis (PCA) and metabolite screening revealed systematic differences among the samples. Factor analysis and partial least squares regression analysis constructed a sublibrary model with an identification accuracy exceeding 95 %, PLS model's R² surpassing 98 %, and RPD exceeding 5, facilitating precise sample year identification. These findings enhance understanding of the Huangjiu aging process and provide crucial technical support for maintaining the quality of Shaoxing Huangjiu, a product protected by geographical indication.

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来源期刊

Food Chemistry: X CHEMISTRY, APPLIED-

CiteScore

4.90

自引率

6.60%

发文量

315

审稿时长

55 days

期刊介绍： Food Chemistry: X, one of three Open Access companion journals to Food Chemistry, follows the same aims, scope, and peer-review process. It focuses on papers advancing food and biochemistry or analytical methods, prioritizing research novelty. Manuscript evaluation considers novelty, scientific rigor, field advancement, and reader interest. Excluded are studies on food molecular sciences or disease cure/prevention. Topics include food component chemistry, bioactives, processing effects, additives, contaminants, and analytical methods. The journal welcome Analytical Papers addressing food microbiology, sensory aspects, and more, emphasizing new methods with robust validation and applicability to diverse foods or regions.