Foods (Jun 2022)

Shelf-Life Prediction and Critical Value of Quality Index of Sichuan Sauerkraut Based on Kinetic Model and Principal Component Analysis

  • Jie Du,
  • Min Zhang,
  • Lihui Zhang,
  • Chung Lim Law,
  • Kun Liu

DOI
https://doi.org/10.3390/foods11121762
Journal volume & issue
Vol. 11, no. 12
p. 1762

Abstract

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Kinetic models and accelerated shelf-life testing were employed to estimate the shelf-life of Sichuan sauerkraut. The texture, color, total acid, microbe, near-infrared analysis, volatile components, taste, and sensory evaluation of Sichuan sauerkraut stored at 25, 35, and 45 °C were determined. Principal component analysis (PCA) and Fisher discriminant analysis (FDA) were used to analyze the e-tongue data. According to the above analysis, Sichuan sauerkraut with different storage times can be divided into three types: completely acceptable period, acceptable period, and unacceptable period. The model was found to be useful to determine the critical values of various quality indicators. Furthermore, the zero-order kinetic reaction model (R2, 0.8699–0.9895) was fitted better than the first-order kinetic reaction model. The Arrhenius model (Ea value was 47.23–72.09 kJ/mol, kref value was 1.076 × 106–9.220 × 1010 d−1) exhibited a higher fitting degree than the Eyring model. Based on the analysis of physical properties, the shelf-life of Sichuan sauerkraut was more accurately predicted by the combination of the zero-order kinetic reaction model and the Arrhenius model, while the error back propagation artificial neural network (BP-ANN) model could better predict the chemical properties. It is a better choice for dealers and consumers to judge the shelf life and edibility of food by shelf-life model.

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