*4.6. Spoilage*

Spoilage developed by microbiological activity has been the greatest concern for consumers in terms of meat safety. Meat spoilage is developed through microbial growth during meat cutting, storage, and distribution processes after the slaughter of animals. Microbial growth causes chemical changes that result from changes in the microorganism itself and the metabolic output on meat. Therefore, chemical information acquired by metabolomics is expected to be utilized to quantify the

degree of spoilage and predict the number or activity of microorganisms [103]. As a candidate of such compound set, volatile organic compounds (VOC) have been focused on in metabolomic studies of spoilage. In an attempt targeting microorganism-associated VOC, metabolome profiling, combined with a multivariate analysis utilizing total ion currents, was able to distinguish naturally spoiled pork samples from those artificially contaminated with *Salmonella typhimurium*, a food poisoning pathogen commonly recovered from pork products [62]. Levels of a total of 16 compounds, including phenylethyl alcohol and dimethyl disulfide, differed between the contaminated and non-contaminated pork samples. However, the identified compounds in such approaches to microorganism-associated VOC may depend on the multivariate analysis algorithm or other factors originating from meat samples [63]. Impact of other microorganisms (*Pseudomonas* spp., *Brochothrix thermosphacta*, lactic acid bacteria, *Enterobacteriaceae*, and yeasts/molds) on minced beef under the various temperature and packaging conditions was also investigated by a LC–MS approach [64].

With high sensitivity and good selectivity, HS/SPME GC–MS was applied in a study to assess spoilage of minced beef [65]. In this study, the authors focused on influences of temperature and atmosphere in packaging during storage of minced beef with indigenous microorganisms. According to the result, identified compounds such as 2-pentanone and 2-heptanone significantly contributed to unacceptable sensory scores and were associated with spoiled samples. This study showed that the GC–MS-based approach has a potential to estimate microbial counts of the different microorganisms and sensory scores of a meat samples independently of storage conditions.
