Recall event timing: Measures of managerial performance in U.S. meat and poultry plants

This study investigates the performance of meat and poultry plant managers in discovering and responding effectively to food safety problems that lead to product recalls. Timing is used as a performance measure of managers' response to recalls of food, using survival distributions of times between production and recall, and recall case duration. The objectives are to understand how these time periods vary across plants and to determine factors explaining such variability. Survival distributions are estimated using the Kaplan-Meier and life table methods. Subgroups of the population are compared using plots of the estimated survival functions and statistically compared using log-rank and Wilcoxon tests. Managers at large plants, in multi-plant firms, and at plants with prior recall experience do not perform better. Cox regressions indicate that government agency sampling programs enhanced the speed of discovery, and that national distribution networks contributed to the risk that cases remained open for a longer period. [EconLit citations: D210, Q180.] © 2005 Wiley Periodicals, Inc. Agribusiness 21: 351-373, 2005.

Hyperspectral imaging of common foodborne pathogens for rapid identification and differentiation

Hyperspectral imaging (HSI) provides both spatial and spectral information of a sample by combining imaging with spectroscopy. The objective of this study was to generate hyperspectral graphs of common foodborne pathogens and to develop and validate prediction models for the classification of these pathogens. Four strains of Cronobacter sakazakii, five strains of Salmonella spp., eight strains of Escherichia coli, and one strain each of Listeria monocytogenes and Staphylococcus aureus were used in the study. Principal component analysis and kNN (k‐nearest neighbor) classifier model were used for the classification of hyperspectra of various bacterial cells, which were then validated using the cross‐validation technique. Classification accuracy of various strains within genera including C. sakazakii, Salmonella spp., and E. coli, respectively, was 100%; except within C. sakazakii, strain BAA‐894, and E. coli, strains O26, O45, and O121 had 66.67% accuracy. When all strains were studied together (irrespective of their genus) for the classification, only C. sakazakii P1, E. coli O104, O111, and O145, S. Montevideo, and L. monocytogenes had 100% classification accuracy, whereas E. coli O45 and S. Tennessee were not classified (classification accuracy of 0%). Lauric arginate treatment of C. sakazakii BAA‐894, E. coli O157, S. Senftenberg, L. monocytogenes, and S. aureus significantly affected their hyperspectral signatures, and treated cells could be differentiated from the healthy, nontreated cells