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Screening of risk markers in pork storage process based on high resolution mass spectrometry combined with chemometrics
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Juan-Hua YANG1, Yun-Fan WANG1, *, Liang-Hong YUAN2, Le XU2, Fei-Fan YANG2, Jun-Hua WU1, Yu-Cong LIANG1
Journal of Food Safety & Quality | 2025, 16(10) : 239 - 246
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Journal of Food Safety & Quality | 2025, 16(10): 239-246
Food Analysis and Detection
Screening of risk markers in pork storage process based on high resolution mass spectrometry combined with chemometrics
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Juan-Hua YANG1, Yun-Fan WANG1, *, Liang-Hong YUAN2, Le XU2, Fei-Fan YANG2, Jun-Hua WU1, Yu-Cong LIANG1
Affiliations
  • 1. Chinese Academy of Inspection and Quarantine Greater Bay Area, Special Food Safety Research Center, Zhongshan 528437, China
  • 2. Guangdong Yuanji Food Group Co., Ltd., Quality Management Center, Foshan 528315, China
Published: 2025-05-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250106004
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Objective To screen risk markers in the storage process of pork using ultra performance liquid chromatography-quadrupole-orbitrap high resolution mass spectrometry (UPLC-Q-Orbitrap HRMS) combined with chemometrics. Methods After sample pretreatment, UPLC-Q-Orbitrap HRMS was employed to detect metabolites in pork, obtaining high precision chromatographic and mass spectrometric data. Principal component analysis (PCA) was applied for dimensionality reduction to explore the distribution characteristics among samples. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was then used to screen differential metabolites with a variable importance factor (VIP)>1.0. The statistical significance of the differences was further evaluated using T-tests (P<0.05), and the final key metabolites were confirmed by combining fold change analysis (fold change, FC>2 or FC<0.5). Results PCA revealed that storage temperature significantly influenced metabolite distribution in different pork cuts (loin, belly, and ham), with samples under different temperatures showing clear separation in the principal component space (total variance R2=0.861, predictive ability Q2=0.478). The OPLS-DA model further optimized the separation of intergroup differences (R2=0.811, Q2=0.653), making the impact of storage temperature on metabolite abundance and type more evident. The R2 and Q2 values of the real model were significantly higher than those of the permutation model, confirming the reliability of the analysis. Through screening conditions (VIP>1, P<0.05, FC>2 or FC<0.5) and structural verification, N-acetylputrescine and 6-methylquinoline were identified as risk markers. Conclusion UPLC-Q-Orbitrap HRMS combined with chemometrics effectively screens risk markers in pork during storage.

ultra performance liquid chromatography-quadrupole-orbitrap high resolution mass spectrometry  /  chemometrics  /  pork  /  markers
Juan-Hua YANG, Yun-Fan WANG, Liang-Hong YUAN, Le XU, Fei-Fan YANG, Jun-Hua WU, Yu-Cong LIANG. Screening of risk markers in pork storage process based on high resolution mass spectrometry combined with chemometrics[J]. Journal of Food Safety & Quality, 2025 , 16 (10) : 239 -246 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250106004
Year 2025 volume 16 Issue 10
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Article Info
doi: 10.19812/j.cnki.jfsq11-5956/ts.20250106004
  • Receive Date:2025-01-06
  • Online Date:2025-07-15
  • Published:2025-05-25
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  • Received:2025-01-06
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Affiliations
    1. Chinese Academy of Inspection and Quarantine Greater Bay Area, Special Food Safety Research Center, Zhongshan 528437, China
    2. Guangdong Yuanji Food Group Co., Ltd., Quality Management Center, Foshan 528315, China
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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