Muthusamy Gayathri, Karthikeyan Subburamu, Arun Giridhari Veeranan, Alhimaidi Ahmad R, Balachandar Dananjeyan, Ammari Aiman A, Paranidharan Vaikuntavasan, Maruthamuthu Thirunavukkarasu
Department of Agricultural Microbiology, Tamil Nadu Agricultural University, Coimbatore 641003, India.
Centre for Post Harvest Technology, Agricultural Engineering College and Research Institute, Tamil Nadu Agricultural University, Coimbatore 641003, India.
Biology (Basel). 2024 Dec 16;13(12):1054. doi: 10.3390/biology13121054.
Microbial contamination and the prevalence of foodborne pathogens in mutton meat and during its slaughtering process were investigated through microbial source tracking and automated pathogen identification techniques. Samples from mutton meat, cutting boards, hand swabs, knives, weighing balances, and water sources were collected from four different retail sites in Coimbatore. Total plate count (TPC), yeast and mold count (YMC), coliforms, , , , and were examined across 91 samples. The highest microbial loads were found in the mutton-washed water, mutton meat, and cutting board samples. The automated pathogen identification system identified species as the predominant contaminant and also revealed a 57% prevalence of . Further analysis of goat meat inoculated with specific pathogens showed distinct volatile and metabolite profiles, identified using gas chromatography-mass spectrometry (GC-MS). Multivariate statistical analyses, including principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA), and sparse partial least squares discriminant analysis (sPLS-DA), identified potential biomarkers for pathogen contamination. The results highlight the significance of cross-contamination in the slaughtering process and suggest the use of volatile compounds as potential biomarkers for pathogen detection.
通过微生物源追踪和自动化病原体鉴定技术，对绵羊肉及其屠宰过程中的微生物污染和食源性病原体的流行情况进行了调查。从哥印拜陀的四个不同零售点采集了绵羊肉、砧板、手部拭子、刀具、秤和水源的样本。对91个样本进行了总平板计数（TPC）、酵母菌和霉菌计数（YMC）、大肠菌群、 、 、 和 的检测。在羊肉冲洗水、绵羊肉和砧板样本中发现了最高的微生物负荷。自动化病原体鉴定系统确定 种为主要污染物，还显示 的流行率为57%。对接种特定病原体的山羊肉进行的进一步分析显示，使用气相色谱-质谱联用仪（GC-MS）鉴定出了不同的挥发性和代谢物谱。包括主成分分析（PCA）、正交偏最小二乘判别分析（OPLS-DA）和稀疏偏最小二乘判别分析（sPLS-DA）在内的多变量统计分析确定了病原体污染的潜在生物标志物。结果突出了屠宰过程中交叉污染的重要性，并建议使用挥发性化合物作为病原体检测的潜在生物标志物。
