Dourou Dimitra, Grounta Athena, Argyri Anthoula A, Froutis George, Tsakanikas Panagiotis, Nychas George-John E, Doulgeraki Agapi I, Chorianopoulos Nikos G, Tassou Chrysoula C
Institute of Technology of Agricultural Products, Hellenic Agricultural Organization DIMITRA, Athens, Greece.
Laboratory of Food Microbiology and Biotechnology, Department of Food Science and Human Nutrition, School of Food and Nutritional Sciences, Agricultural University of Athens, Athens, Greece.
Front Microbiol. 2021 Feb 4;11:623788. doi: 10.3389/fmicb.2020.623788. eCollection 2020.
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.
鸡肝是一种极易腐坏的肉类产品，保质期相对较短，且容易被致病微生物污染。本研究旨在评估鸡肝上腐败微生物群和接种菌的行为。还探讨了通过开发机器学习工作流程，利用傅里叶变换红外光谱（FTIR）评估鸡肝微生物质量的可行性。鸡肝样本[未接种和接种了含10个菌落形成单位（CFU）/克的四菌株混合物]在等温（0、4和8°C）和动态温度条件下进行需氧储存。对样本进行微生物分析并同时进行FTIR测量。所开发的用于定量估计不同腐败微生物群的FTIR光谱分析工作流程包括稳健的数据归一化、基于极端随机树算法的特征选择以及支持向量机（SVM）回归分析。根据均方根误差（RMSE）、相关系数的平方（ ）、偏差（B ）和准确度（A ）因子评估所开发模型的性能。腐败主要由 菌属驱动，其次是 菌属，而乳酸菌（LAB）、 菌属和酵母/霉菌数量维持在较低水平。 菌属在0°C和动态条件下存活下来，在储存结束时，在4°C和8°C时分别增加了1.4和1.9 log CFU/克。所提出的模型在观察到的和预测的计数之间的A 和B 分别在1.071至1.145和0.995至1.029范围内，而 和RMSE值分别根据微生物和鸡肝样本在0.708至0.828 log CFU/克和0.664至0.949 log CFU/克范围内。总体而言，结果突出了 菌属不仅能在冷藏温度下存活而且能生长的能力，并证明了FTIR技术与所提出的光谱分析工作流程相结合在估计鸡肝上的总活菌数、 菌属、 菌属、LAB、 菌属和 菌属方面具有巨大潜力。
