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<p>The demand for meat products has increased significantly due to changes in people’s lifestyles and rising meat prices. The study aims to investigate the potential use of an accurate and reliable method for detecting adulteration and ensuring the quality of meat products. The sausages are made with various meat from 5 to 100% pure meat. The samples are then analyzed using Fourier-transform Near-Infrared (FT-NIR) spectroscopy. This research used a NIR spectrophotometer, Principal component analysis (PCA), and Linear discriminant analysis (LDA) to identify beef, chicken, donkey, and horse handmade sausage samples. Using PCA, two principal components were extracted that covered 99 percent of the data variance and accurately distinguished sausage samples from different animal meats. Following this, the LDA model can confidently classify the sausage samples and achieved 100% accuracy in classifying all test samples. To conclude, NIR spectroscopy is a reliable tool for sausage quality evaluation and species identification, which can identify different animal species in meat products. </p>

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Species identification in sausage samples using near-infrared spectroscopy and linear discriminant analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月4日

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  • Mohadeseh Pirhadi,
  • Nabi Shariatifar,
  • Gholamreza Jahed Khaniki,
  • Massoud Amanlou,
  • Parisa Sadighara,
  • Ebrahim Molaee-Aghaee,
  • Sohrab Pirhadi

摘要

The demand for meat products has increased significantly due to changes in people’s lifestyles and rising meat prices. The study aims to investigate the potential use of an accurate and reliable method for detecting adulteration and ensuring the quality of meat products. The sausages are made with various meat from 5 to 100% pure meat. The samples are then analyzed using Fourier-transform Near-Infrared (FT-NIR) spectroscopy. This research used a NIR spectrophotometer, Principal component analysis (PCA), and Linear discriminant analysis (LDA) to identify beef, chicken, donkey, and horse handmade sausage samples. Using PCA, two principal components were extracted that covered 99 percent of the data variance and accurately distinguished sausage samples from different animal meats. Following this, the LDA model can confidently classify the sausage samples and achieved 100% accuracy in classifying all test samples. To conclude, NIR spectroscopy is a reliable tool for sausage quality evaluation and species identification, which can identify different animal species in meat products.