Comparison of Mathematical Models of Lactic Acid Bacteria Growth in Vacuum‐Packaged Raw Beef Stored at Different Temperatures

Abstract

The lactic acid bacteria grown in vacuum-packaged raw beef under 7, 10, 15, and 20 °C has been studied in this paper. Four primary models, the modified Gompertz, logistic, Baranyi, and Huang model were used for data fitting. Statistical criteria such as the bias factor and accuracy factor, mean square error, Akaike's information criterion, and the residual distribution were used for comparing the models. The result showed that all of the 4 models can fit the data well and they were not significantly different in the performance. They were equally capable of describing bacterial growth, but the growth rate and lag time estimated from the modified Gompertz model were a little higher than other models. The estimate for the lag time was not accurate as the growth rate.

Modelling the growth parameters of lactic acid bacteria and total viable count in vacuum‐packaged Irish cooked sausages cooled by different methods

“…Lactic acid bacteria (LAB) are very difficult to control as they are facultative anaerobic (Bjorkroth & Korkeala, ; Samelis et al ., ; Calo‐Mata et al, ; García‐Parra et al, ; Pérez‐Chabela et al, ; Sánchez‐Zapata et al, ). They are regarded as a specific spoilage organism (SSO) in vacuum‐packaged cooked meat products during long‐term storage, probably due to its dominance in the total viable microflora (Cayré et al ., ; Slongo et al ., ; Kreyenschmidt et al ., ; Dissing et al, ; Li et al ., ). As LAB are heat resistant and ubiquitously distributed in the environment (Hongpattarakere et al ., ), cooked foodstuffs can be easily contaminated from either air or equipment surfaces during slicing or packaging (Hamasaki et al ., ; Feng et al ., ).…”

“…Predictive mathematical modelling, as an alternative to time-consuming and expensive traditional microbial enumeration methods, has gained increasing interest in the food industry and regulatory agencies in recent years (Mataragas et al, 2007;Zanoni et al, 2007;Marc et al, 2008;Slongo et al, 2009;Li et al, 2013;Grassi et al, 2014). To date, several studies have extensively addressed the use of predictive modelling to calculate LAB growth parameters of meat products treated by different vacuum-packaged conditions (Liu et al, 2006;Slongo et al, 2009) or stored at different temperatures (Cayr e et al, 2003(Cayr e et al, , 2005Li et al, 2013). Although growth model developed under different storage temperatures may interest the food processing industries as temperature abuse often occurs during storage, modelling bacteria growth during cooling process allowed for industry to comply with regulatory performance standards and to ensure microbiological safety of cooked products.…”

Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions

“…The metabolite for some bacteria influences the pH value. Lactic acid bacteria, as facultative anaerobes, are ubiquitously distributed in the environment and regarded as specific spoilage organisms (SSO) in the packaged cooked meat products (Kreyenschmidt and others ; Li and others ). The generation of the lactic acid bacteria decreases the pH values of the meat products.…”

Microbial quality and shelf life prediction of vacuum-packaged ready to eat beef rounds containing gum arabic

“…Cured meats processed as RTE are mostly populated by LAB in very low amounts. LAB are thus regarded as SSO in vacuum packaged cooked RTE meat products, probably due to their dominance in the total bacterial count (Slongo et al, 2009;Kreyenschmidt et al, 2010;Li et al, 2013). When properly cooked, meat products will have minimal contaminating microorganisms.…”

“…Therefore, understanding the growth parameters of LAB in cured meat products will facilitate their effective control as well as the determination of the viable shelf life of such cured RTE meat products. Such determinations have been achieved through predictive mathematical modeling which is an upcoming alternative to time consuming and expensive traditional microbial enumeration methods for studying bacterial growth (Mataragas, Skandamis, Nychas, & Drosinos, 2007;Slongo et al, 2009;Li et al, 2013). LAB growth in vacuum packaged cooked meat products has been used in many modeling studies to predict the shelf life of meat products treated by divergent vacuum packaging conditions (Liu, Yang, & Li, 2006;Slongo et al, 2009) or stored at diverse temperatures (Cayre, Vignolo, & Garro, 2003;Li et al, 2013).…”