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<p>This study aimed to investigate the effect of sesame flour and clove on the physico-chemical, colorimetric and structural quality of sausages during their fermentation stage. The results indicated that clove could be used as an antioxidant source in sausages produced with sesame flour. The principal component analysis (PCA) applied to the physicochemical and colorimetric data set allowed to clearly differentiate sausage samples according to the fermentation stage and, to a lesser extent, their recipes. This trend was confirmed by factorial discriminant analysis (FDA), since 97.22% of correct classification was noted. The PCA applied on the mid infrared (MIR) spectra allowed to differentiate sausage according to their formulations; this trend was confirmed by the FDA since 100% of correct classification of the samples were obtained. The partial least squares regression (PLSR) allowed a perfect prediction of the physicochemical parameters from the MIR spectra, since R<sup>2</sup> higher than 0.85 were found for the calibration and validation model, respectively.</p>

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Impact of the incorporation of clove and sesame flour in the formulation of dry chicken sausages on their quality during the fermentation stage

  • 期刊论文

  • 发表日期：

    2025年1月15日

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  • Moriken Sangaré,
  • Jérôme Bony,
  • Christine Chèné,
  • Romdhane Karoui

摘要

This study aimed to investigate the effect of sesame flour and clove on the physico-chemical, colorimetric and structural quality of sausages during their fermentation stage. The results indicated that clove could be used as an antioxidant source in sausages produced with sesame flour. The principal component analysis (PCA) applied to the physicochemical and colorimetric data set allowed to clearly differentiate sausage samples according to the fermentation stage and, to a lesser extent, their recipes. This trend was confirmed by factorial discriminant analysis (FDA), since 97.22% of correct classification was noted. The PCA applied on the mid infrared (MIR) spectra allowed to differentiate sausage according to their formulations; this trend was confirmed by the FDA since 100% of correct classification of the samples were obtained. The partial least squares regression (PLSR) allowed a perfect prediction of the physicochemical parameters from the MIR spectra, since R2 higher than 0.85 were found for the calibration and validation model, respectively.