Rapid Microbial Quality Assessment of Chicken Liver Inoculated or Not With Using FTIR Spectroscopy and Machine Learning.

Chicken liver is a highly perishable meat product with a relatively short shelf-life and that can get easily contaminated with pathogenic microorganisms. This study was conducted to evaluate the behavior of spoilage microbiota and of inoculated on chicken liver. The feasibility of Fourier-transform infrared spectroscopy (FTIR) to assess chicken liver microbiological quality through the development of a machine learning workflow was also explored. Chicken liver samples [non-inoculated and inoculated with a four-strain cocktail of . 10 colony-forming units (CFU)/g ] were stored aerobically under isothermal (0, 4, and 8°C) and dynamic temperature conditions. The samples were subjected to microbiological analysis with concomitant FTIR measurements. The developed FTIR spectral analysis workflow for the quantitative estimation of the different spoilage microbial groups consisted of robust data normalization, feature selection based on extra-trees algorithm and support vector machine (SVM) regression analysis. The performance of the developed models was evaluated in terms of the root mean square error (RMSE), the square of the correlation coefficient ( ), and the bias (B ) and accuracy (A ) factors. Spoilage was mainly driven by spp., followed closely by , while lactic acid bacteria (LAB), , and yeast/molds remained at lower levels. managed to survive at 0°C and dynamic conditions and increased by 1.4 and 1.9 log CFU/g at 4 and 8°C, respectively, at the end of storage. The proposed models exhibited A and B between observed and predicted counts within the range of 1.071 to 1.145 and 0.995 to 1.029, respectively, while the and RMSE values ranged from 0.708 to 0.828 and 0.664 to 0.949 log CFU/g, respectively, depending on the microorganism and chicken liver samples. Overall, the results highlighted the ability of not only to survive but also to grow at refrigeration temperatures and demonstrated the significant potential of FTIR technology in tandem with the proposed spectral analysis workflow for the estimation of total viable count, spp., , LAB, , and on chicken liver.