Effects of drying time on physicochemical properties and volatile organic compounds of pork jerky revealed by GC-IMS and interpretable machine learning.
6 affiliations
- 1School of Photoelectric Engineering of Changzhou Institute of Technology, Changzhou, Jiangsu 213002, China.
- 2College of Chemical Engineering, Xiangtan University, Xiangtan 411105, China.
- 3Shandong Hanon Science Instrument Co., Ltd, Dezhou, Shandong 253000, China.
- 4College of Light Industry and Food Engineering, Nanjing Forestry University. Nanjing, Jiangsu 210037, China.
- 5State Key Laboratory for Development and Utilization of Forest Food Resources, Nanjing Forestry University, Nanjing 210037, China.
- 6School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
Abstract
Drying time affects dehydration, color development, Maillard reactions, and volatile organic compounds (VOCs) in pork jerky. Pork jerky was dried at 80 °C for 4-6 h, with marinated undried samples as the RAW control. Physicochemical properties, free amino acids, and volatile fingerprints were evaluated. Gas chromatography-ion mobility spectrometry (GC-IMS) detected 53 volatile signals, whose profiles changed markedly during drying. Support vector regression (SVR) and extra trees regression (ETR) were developed to predict moisture content, absorbance at 420 nm, fluorescence intensity, and L*, a*, and b* values from GC-IMS. Both models achieved strong test-set performance, with R² values of 0.996-0.998 for SVR and 0.989-0.995 for ETR. SHapley Additive exPlanations (SHAP) analysis identified shared and model-specific volatile markers, including pentanal, furaneol, ethyl propanoate, heptanal, 2-hexenal, 2-butanone, and 3-isobutyl-2-methoxypyrazine. These results demonstrate the potential of GC-IMS combined with interpretable machine learning for quality prediction and volatile-marker screening during pork jerky drying.
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BibTeX
@article{chen2026effects,
title = {{Effects of drying time on physicochemical properties and volatile organic compounds of pork jerky revealed by GC-IMS and interpretable machine learning.}},
author = {Xinyu Chen and Haoran Huang and Huangyu Chen and Siying Wang and Zeyuan Zang and Yujia Huo and Zhixin Xiong and DaoLi Lu and Yan Li},
journal = {Food chemistry: X},
year = {2026},
month = oct,
doi = {10.1016/j.fochx.2026.104562},
url = {https://europepmc.org/article/MED/42908884},
note = {CC BY},
}
RIS
TY - JOUR
TI - Effects of drying time on physicochemical properties and volatile organic compounds of pork jerky revealed by GC-IMS and interpretable machine learning.
AU - Xinyu Chen
AU - Haoran Huang
AU - Huangyu Chen
AU - Siying Wang
AU - Zeyuan Zang
AU - Yujia Huo
AU - Zhixin Xiong
AU - DaoLi Lu
AU - Yan Li
PY - 2026
DA - 2026/10/08
JO - Food chemistry: X
DO - 10.1016/j.fochx.2026.104562
UR - https://europepmc.org/article/MED/42908884
AB - Drying time affects dehydration, color development, Maillard reactions, and volatile organic compounds (VOCs) in pork jerky. Pork jerky was dried at 80 °C for 4-6 h, with marinated undried samples as the RAW control. Physicochemical properties, free amino acids, and volatile fingerprints were evaluated. Gas chromatography-ion mobility spectrometry (GC-IMS) detected 53 volatile signals, whose profiles changed markedly during drying. Support vector regression (SVR) and extra trees regression (ETR) were developed to predict moisture content, absorbance at 420 nm, fluorescence intensity, and L*, a*, and b* values from GC-IMS. Both models achieved strong test-set performance, with R² values of 0.996-0.998 for SVR and 0.989-0.995 for ETR. SHapley Additive exPlanations (SHAP) analysis identified shared and model-specific volatile markers, including pentanal, furaneol, ethyl propanoate, heptanal, 2-hexenal, 2-butanone, and 3-isobutyl-2-methoxypyrazine. These results demonstrate the potential of GC-IMS combined with interpretable machine learning for quality prediction and volatile-marker screening during pork jerky drying.
SN - 2590-1575
ER -