Submitted to: Food Microbiology
Publication Type: Peer reviewed journal
Publication Acceptance Date: 5/9/2002
Publication Date: 5/9/2002
Citation: HUANG, L. DESCRIPTION OF GROWTH OF CLOSTRIDIUM PERFRINGENS IN COOKED BEEF WITH MULTIPLE LINEAR MODELS. FOOD MICROBIOLOGY. 2002. V. 19. P. 577-587. Interpretive Summary: The traditional linear model used in food microbiology employs three linear segments to describe the process of food spoilage and categorize a growth curve into lag, exponential, and stationary phases. The linear model is accurate only within certain portions of each phase of a growth process, and can underestimate or overestimate the transitional phases. While sigmoid functions can be used to more accurately fit the growth data, they fail to indicate of the physiological state of bacteria. The objective of this paper was to develop a new methodology that could accurately describe and categorize bacterial growth as a process using Clostridium perfringens as a test organism. This methodology utilized five linear segments represented by five multiple linear models to accurately categorize bacterial growth into lag, 1st transitional, exponential, 2nd transitional, and stationary phases. Growth curves described by the method were more accurate than the traditional linear counterparts, and were statistically equivalent to the Gompertz models. Also, the durations of each growth phase in a growth curve were linearly correlated. Such linear relationship allows generation of a complete five-segment growth curve from the maximum growth rate and a known duration of the first four growth phases. Moreover, the lag phase defined by the new method was a linear function of the traditional lag phase calculated from Gompertz equation. With this relationship, the two traditional parameters (lag phase and maximum growth rate) used in a three-segment linear model can be used to generate a more accurate five-segment growth curve without involving complicated mathematical procedures.
Technical Abstract: A new methodology was developed to describe and categorize the growth process of foodborne pathogens (such as Clostridium perfringens) in meat products. This methodology was tested using C. perfringens spores in cooked ground beef, and has been proven more accurate than the traditional linear method. Using multiple linear models, an entire growth process was progressively divided into five different phases according to the physiological states of microorganisms. With this new method, the food processors, food service industry, and retail food business owners will be equipped not only to predict the development of microbial food spoilage caused by foodborne pathogens, but also to tell the physiological states of pathogens in foods. As a result, more appropriate food intervention technologies can be adopted to curtail the progress of food spoilage and to prevent food poisoning.