期刊
MEAT SCIENCE
卷 78, 期 1-2, 页码 77-89出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.meatsci.2007.06.020
关键词
meat spoilage; quantitative microbiology; chemometrics; bioinformatics; predictive modelling; chill chain; ANN; machine learning; meat chemistry; metabolomics
Meat spoilage during distribution can be considered as an ecological phenomenon that encompasses the changes of the available substrata (e.g., low molecular compounds), during the prevailing of a particular microbial association, the so-called specific spoilage organisms (SSO). In fact, spoilage of meat depends on an even smaller fraction of SSO, called ephemeral spoilage organisms (ESO). These ESO are the consequence of factors that dynamically persist or imposed during, e.g., processing, transportation and storage in the market. Meanwhile spoilage is a subjective judgment by the consumer, which may be influenced by cultural and economic considerations and background as well as by the sensory acuity of the individual and the intensity of the change. Indeed, when spoilage progresses, most consumers would agree that gross discoloration, strong off-odors, and the-development of slime would constitute the main qualitative criteria for meat rejection. On the other hand, meat industry needs rapid analytical methods or tools for quantification of these indicators to determine the type of processing needed for their raw material and to predict remaining shelf life of their products. The need of an objective evaluation of meat spoilage is of great importance. The use of metabolomics as a potential tool for the evaluation of meat spoilage can be of great importance. The microbial association of meat should be monitored in parallel with the estimation of changes occurring in the production and/or assimilation of certain compounds would allow us to evaluate spoilage found or produced during the storage of meat under different temperatures as well as packaging conditions. (c) 2007 Elsevier Ltd. All rights reserved.
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