<p>The aroma characteristics of Jiangxiang-type baijiu are primarily formed during the third to fifth production rounds. Given the complexity of its aroma compounds, quality assessment currently depends mainly on manual sensory evaluation, with limited objective and scientific methodologies available. This study presents a rapid classification approach using atmospheric pressure solid analysis probe-time of flight (ASAP-TOF) mass spectrometry that requires no sample pretreatment. The method enables real-time discrimination of three aroma types (Jiangxiang-type, Chuntian-type, and Jiaodi-type) and two quality grades (grade I/II), with the entire workflow from sample introduction to classification completed within minutes. A total of 233 baijiu samples, validated by sensory evaluation from the production enterprise, were divided into seven representative groups. Mass-to-charge ratio (m/z) data were acquired using ASAP-TOF mass spectrometry to identify characteristic ions. A recognition model for aroma type and quality grade classification was then developed using LiveID software with principal component analysis and linear discriminant analysis, and its robustness was assessed through fivefold cross-validation. The model achieved a classification accuracy of 90.37% for grade I Jiangxiang-type baijiu from rounds 3 to 5, and demonstrated applicability to unknown samples. Analysis of the m/z data revealed several differential peaks. Based on comparison with literature data and gas chromatography-mass spectrometry (GC-MS) results, guaiacol, 2-methylfuran, 2,3-dimethylpyrazine, and isovaleric acid were identified as potential key flavor compounds distinguishing grade I Jiangxiang-type baijiu across different production rounds. In summary, this study establishes a real-time classification model for grade I Jiangxiang-type baijiu, providing a chemometric tool applicable to quality control and process optimization.</p>

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Rapid Classification of Jiangxiang-Type Baijiu: Differentiating Quality Grades and Aroma Types Across Production Rounds Using ASAP-TOF-MS

  • Li Zhu,
  • Kun Pang,
  • Lanlan Wang,
  • Lei Lin,
  • Li Deng,
  • Qiuyun Wang,
  • Ji Zhang,
  • Ming Yu,
  • Jianyong Zhang

摘要

The aroma characteristics of Jiangxiang-type baijiu are primarily formed during the third to fifth production rounds. Given the complexity of its aroma compounds, quality assessment currently depends mainly on manual sensory evaluation, with limited objective and scientific methodologies available. This study presents a rapid classification approach using atmospheric pressure solid analysis probe-time of flight (ASAP-TOF) mass spectrometry that requires no sample pretreatment. The method enables real-time discrimination of three aroma types (Jiangxiang-type, Chuntian-type, and Jiaodi-type) and two quality grades (grade I/II), with the entire workflow from sample introduction to classification completed within minutes. A total of 233 baijiu samples, validated by sensory evaluation from the production enterprise, were divided into seven representative groups. Mass-to-charge ratio (m/z) data were acquired using ASAP-TOF mass spectrometry to identify characteristic ions. A recognition model for aroma type and quality grade classification was then developed using LiveID software with principal component analysis and linear discriminant analysis, and its robustness was assessed through fivefold cross-validation. The model achieved a classification accuracy of 90.37% for grade I Jiangxiang-type baijiu from rounds 3 to 5, and demonstrated applicability to unknown samples. Analysis of the m/z data revealed several differential peaks. Based on comparison with literature data and gas chromatography-mass spectrometry (GC-MS) results, guaiacol, 2-methylfuran, 2,3-dimethylpyrazine, and isovaleric acid were identified as potential key flavor compounds distinguishing grade I Jiangxiang-type baijiu across different production rounds. In summary, this study establishes a real-time classification model for grade I Jiangxiang-type baijiu, providing a chemometric tool applicable to quality control and process optimization.