Predicting the composition of aroma components in Baijiu using hyperspectral imaging combined with a replication allocation strategy-enhanced stacked ensemble learning model.

Journal: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Published Date: May 14, 2025

Abstract

Ester and acid aroma compounds are crucial components affecting the fragrance of Baijiu, and their composition can endow the Baijiu with a fruity, acidic, floral, or roasted aroma. This study aims to quantitatively detect the ester and acid content in Soy Sauce-Aroma Type Baijiu (SSAB) using hyperspectral imaging (HSI) technology and a stacked ensemble learning (SEL) model. To mitigate the impact of data imbalance, an improved oversampling technique known as the replication allocation strategy (RAS) was utilized. After comparing the study results, it was found that the established RF-RAS-SEL model yielded the best performance, with an Rp2 of 0.9803 and RMSEP of 0.3314 mg/L for predicting ester content and an Rp2 of 0.9914 and an RMSEP of 0.4565 mg/L for predicting acid content. These findings demonstrate that HSI can achieve the non-destructive and accurate detection of esters and acids in SSAB, providing a novel method for analyzing Baijiu aroma.

Authors

  • Yuexiang Huang
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Jianping Tian
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Xinjun Hu
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Haili Yang
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Liangliang Xie
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Yifei Zhou
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Yuanyuan Xia
    School of Mechanical Engineering, Sichuan University of Science and Engineering, Yibin, China.
  • Dan Huang
    Department of Anesthesiology, The Second Affiliated Hospital of Soochow University, Suzhou 215004, China.; Department of Anesthesiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200127, China.
  • Kaiping He
    Guizhou Xijiu Co., Ltd, China.

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