Microbiological and chemical spoilage prediction of high and low fat raw ground meat.

Meat is subjected to chemical and microbiological deterioration, caused by oxidative degradation of meat fat and by the presence of microbial populations, particularly Pseudomonas spp.. Therefore spoilage can be monitored through their growth and changes in TBARS, thiols and carbonyls. The aim of the current study is to evaluate the correlation between chemical and microbiological data by PCA analysis and predict meat spoilage by pseudomonads contamination under isothermal and dynamic conditions or by chemical parameters in high and low fat ground meat by multivariate statistical analysis. Beef ground meat containing a total fat amount of about 5% or 15% of fat was divided into 150 g portions, stored under isothermal conditions (0, 5, 10 and 15°C) and checked for the presence of Pseudomonas spp., Brochothrix spp., total viable count (TVC). Water loss, pH, thiols, carbonyls, TBARS, metmyoglobin, deoxymioglobin, oxymioglobin and colour changes were determined on all samples. All data were subjected to PCA analysis to evaluate the correlation between microbiological and chemical variables. Subsequently, a square root model was fitted to the growth rates of pseudomonads and used to predict spoilage of ground meat under isothermal and dynamic conditions. Additionally, multivariate statistical analysis was applied to fit a PLS (Partial Least Square Regression) model, aiming at predicting microbial counts of minced meat, based on chemical data, regardless of time-temperature storage profile. Growth models allow to predict the evolution of food spoilage during storage as a function of extrinsic conditions food characteristics. Results by the PCA analysis showed that, among microbiological and chemical indexes monitored during refrigerated storage, a positive correlation was found between increase in TBARS (0.70) and levels of pseudomonads, which were inversely correlated with thiols (-0.71) and oxymioglobin (-0.81). Moreover, results demonstrated that the fat level of ground meat did not influence the growth rate of pseudomonads allowing the application of a single model for predicting the growth of pseudomonads and time to spoilage of ground meat given dynamic temperature conditions, regardless of fat content. PLS analysis was performed considering all the microbiological parameters as Y-variables, while the chemical data were used as X-variables. The model (R2CV 0.81, RMSECV of 0.68 for pseudomonads prediction) can allow to use chemical data to predict the microbial load of ground meat during refrigerated shelf life, regardless of fat content and time-temperature conditions. Moreover, the PLS model can allow to discriminate acceptable (TVC<7 log cfu/g; TBARS 0.28-3.37 mg/kg; thiols 29.89-69.39 nmol/mg protein) from unacceptable (TVC> 7 log cfu/g; TBARS 0.13-1.33 mg/kg; thiols 52.94-73.06 nmol/mg protein) samples. Knowledge of perishability of food matrices associated to the storage history provide important information on the quality and edibility of food.