Microbiological assessment of aerobically stored horse fillets through predictive microbiology and metabolomic approach. (February 2021)

• Record Type: Journal Article
• Authors: Pavlidis, Dimitrios E.; Mallouchos, Athanasios; Nychas, George John
• Is Part Of: Meat science. Volume 172(2021)
• Publication Date: 2021-02
• Subjects: Horsemeat spoilage -- Microbial association -- Metabolomics -- Shelf-life -- Predictive microbiology -- Machine learning; Meat -- Periodicals; Meat industry and trade -- Periodicals; Viande -- Périodiques; Viande -- Industrie -- Périodiques; Meat; Meat industry and trade; Periodicals; 641.36
• DOI: 10.1016/j.meatsci.2020.108323
• Languages: English
• ISSNs: 0309-1740

Abstract

Abstract: The aim of this work was to investigate the microbial association of horse fillets during aerobic storage at isothermal conditions (0-15 °C). Samples were analyzed microbiologically, and in parallel the metabolic profile of the samples was quantified by HS-SPME/GC–MS and HPLC-PDA-RI. Considering HPLC results, the concentration of propionic, formic, lactic and succinic acids decreased during aerobic storage of horse fillets, contrary to acetic, citric, butyric and isobutyric acids, which increased. As far as the volatilome formation during aerobic storage is concerned, pentanal, hexanal, octanal, nonanal, decanal, were correlated with fresh samples, while diacetyl, acetoin, 2-heptanone, 2-octanone, hexanoic acid, 3-methyl-butanol, 2-methy-butanol and 3-methyl-butanal detected in spoiled ones. Herein, a support vector machine regression model using data from 0, 5 and 15 °C predicted the responses of the dataset at 10 °C with a correlation coefficient 0.915 and 0.910 for training and testing, respectively. Highlights: Microbial association of horsemeat Microbial metabolites as potential biomarkers for ensuring quality Volatilomics a useful tool to measure meat quality Machine learning serving food quality