Storage time effect on inoculated, osmodehydrated chicken meat-microbiological and chemical characteristics

Abstract

In this research chicken meat was inoculated with selected microorganisms and subjected to the osmotic dehydration process in two osmotic solutions, in an effort to investigate the effect of storage time duration on its' microbiological and chemical characteristics. Total viable counts, numbers of Enterobacteriaceae, Salmonella spp., Listeria monocytogenes, Escherichia coli, proteolytic bacteria, psychotropic bacteria, of microbiological, and biogenic amine content, TBARS and DPPH, of chemical analyses were conducted on meat samples stored at 22?C, during 14 days. During storage, number of all tested microorganisms on meat samples decreased. The highest reduction occurred in the first 4 days. The meat dehydrated in molasses achieved better results of microbiological profile during storage. Results of TBARS and DPPH analyses indicated on lipid oxidation after 14 days of storage, while the results after 10 days were satisfactory. Developed mathematical models allows good prediction of microbiological and chemical responses of dehydrated chicken meat during the investigated storage duration.

Modeling the Effects of Osmotic Dehydration Pretreatment Parameters and Lyophilization Kinetics on Mass Transfer and Selected Nutritive Parameters of Peaches

“…The same a w values of peach samples subjected to these two different dehydration methods were obtained for osmotic dehydration parameters of: τ = 5 h, C = 80% and lowest t = 20 °C, while lower a w values were obtained in processes of: τ = 5 h, C = 70%, t = 50 °C and: τ = 3 h, C = 80%, t = 50 °C (all of these osmotic dehydration parameters were not in the highest range of tested parameters). These results indicate good starting point, regarding obtaining low a w values of molasses osmodehydrated material, for further technological processing [24][25][26], such as lyophilization.…”

Formation of Predictive-Based Models for Monitoring the Microbiological Quality of Beef Meat Processed for Fast-Food Restaurants

“…Many empirical models are used for understanding microbiological profiles of meat and meat products, but a step forward in advanced mathematical and statistical modelling is still not widely applied. Only a few studies included using predictive tools for an explanation of microbiological experimental data, such as partial least squares regression analysis [ 47 ], growth kinetics modelling [ 48 , 49 ], nonlinear least square regression analysis with the Levenberg–Marquardt method of estimation [ 50 ], Lorentzian distribution function and Nonlinear regression [ 51 ], etc. On the other hand, when attempting to build a mathematical model in the area of predictive microbiology, the artificial neural network (ANN) model is perceived as one of the most relevant and universal anticipating tools [ 52 , 53 ].…”