Food and Fermentation Industries >

2025 , Vol. 51 >Issue 10: 336 - 343

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.040024

Place of origin identification for air-dried yak meat from Tibet based on portable near-infrared spectroscopy

  • HAN Yuanxi ,
  • HU Yun ,
  • ZHANG Erhao ,
  • LIU Zhendong ,
  • LI Liang ,
  • LUO Zhang
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  • (Food Science College, Tibet Agriculture & Animal Husbandry University;R & D Center of Agricultural Products with Tibetan Plateau Characteristics;The Provincial and Ministerial Co-founded Collaborative Innovation Center for R&D in Tibet Characteristic Agricultural and Animal Husbandry Resources, Nyingchi 860000, China)

Received date: 2024-05-28

  Revised date: 2024-08-12

  Online published: 2025-06-11

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Abstract

Place of origin is one important factor affecting the quality of yak meat.To quickly identify the place of origin of air-dried yak meat from Tibet, this study utilized a portable near-infrared spectrometer to trace the origin of air-dried yak meat samples from different Tibet regions.A total of 240 air-dried yak meat samples from 4 Tibet regions were collected, which were randomly assigned into the training set and the test set at a ratio of 3∶1.Initially, abnormal near-infrared spectra were eliminated by Mahalanobis distance, and 3 classification models, namely partial least-squares discrimination analysis, support vector machine (SVM), and random forest, were created separately using 7 pre-processing methods, including Smooth, Savitzky-Golay, standard normal variate, multiplicative scatter correction, second derivative, mean centralization (MC), and de-trend.Results showed that the MC-SVM model had the optimal classification effect, with the accuracies on the training and prediction sets being 95.24% and 91.67%, respectively.To further simplify the model, methods like competitive adaptive reweighted sampling, variable iterative space shrinkage approach, and bootstrapping soft shrinkage (BOSS) were adopted for feature wavelength screening.Through multivariate data analysis, the MC-BOSS-SVM model was found to display the best effect, with the accuracies on the training and prediction sets being 88.10% and 91.67%, respectively.This study offers a theoretical basis for rapid and non-destructive identification of the place of origin for air-dried yak meat from Tibet.

Key words： portable near-infrared spectroscopy; Tibetan air-dried yak meat; place of origin identification; machine learning; modelling

Cite this article

HAN Yuanxi , HU Yun , ZHANG Erhao , LIU Zhendong , LI Liang , LUO Zhang . Place of origin identification for air-dried yak meat from Tibet based on portable near-infrared spectroscopy[J]. Food and Fermentation Industries, 2025 , 51(10) : 336 -343 . DOI: 10.13995/j.cnki.11-1802/ts.040024

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