Fresh bovine manure was mechanically incorporated into loamy sand and silty clay loam Wisconsin soils in April 2004. At varying fertilization-to-planting intervals, radish, lettuce, and carrot seeds were planted; crops were harvested 90, 100, 110 or 111, and 120 days after manure application. As an indicator of potential contamination with fecal pathogens, levels of Escherichia coli in the manure-fertilized soil and presence of E. coli on harvested vegetables were monitored. From initial levels of 4.0 to 4.2 log CFU/g, E. coli levels in both manure-fertilized soils decreased by 2.4 to 2.5 log CFU/g during the first 7 weeks. However, E. coli was consistently detected from enriched soil samples through week 17, perhaps as a result of contamination by birds and other wildlife. In the higher clay silty clay loam soil, the fertilization-to-planting interval affected the prevalence of E. coli on lettuce but not on radishes and carrots. Root crop contamination was consistent across different fertilization-to-harvest intervals in silty clay loam, including the National Organic Program minimum fertilization-to-harvest interval of 120 days. However, lettuce contamination in silty clay loam was significantly (P < 0.10) affected by fertilization-to-harvest interval. Increasing the fertilization-to-planting interval in the lower clay loamy sand soil decreased the prevalence of E. coli on root crops. The fertilization-to-harvest interval had no clear effect on vegetable contamination in loamy sand. Overall, these results do not provide grounds for reducing the National Organic Program minimum fertilization-to-harvest interval from the current 120-day standard.

A computer-based tool (available at: www.wisc.edu/foodsafety/meatresearch) was developed for predicting pathogen growth in raw pork, beef, and poultry meat. The tool, THERM (temperature history evaluation for raw meats), predicts the growth of pathogens in pork and beef (Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus) and on poultry (Salmonella serovars and S. aureus) during short-term temperature abuse. The model was developed as follows: 25-g samples of raw ground pork, beef, and turkey were inoculated with a five-strain cocktail of the target pathogen(s) and held at isothermal temperatures from 10 to 43.3ЊC. Log CFU per sample data were obtained for each pathogen and used to determine lag-phase duration (LPD) and growth rate (GR) by DMFit software. The LPD and GR were used to develop the THERM predictive tool, into which chronological time and temperature data for raw meat processing and storage are entered. The THERM tool then predicts a ⌬ log CFU value for the desired pathogen-product combination. The accuracy of THERM was tested in 20 different inoculation experiments that involved multiple products (coarse-ground beef, skinless chicken breast meat, turkey scapula meat, and ground turkey) and temperature-abuse scenarios. With the time-temperature data from each experiment, THERM accurately predicted the pathogen growth and no growth (with growth defined as ⌬ log CFU Ն 0.3) in 67, 85, and 95% of the experiments with E. coli O157:H7, Salmonella serovars, and S. aureus, respectively, and yielded failsafe predictions in the remaining experiments. We conclude that THERM is a useful tool for qualitatively predicting pathogen behavior (growth and no growth) in raw meats. Potential applications include evaluating process deviations and critical limits under the HACCP (hazard analysis critical control point) system.

The U.S. Department of Agriculture has established standards for the composition and shelf stability of various readyto-eat meat products. These standards may include product pH, moisture:protein ratio, and water activity (a w ) values. It is unclear how closely these standards are based on the potential for pathogen growth or toxin production. Because the vacuum packaging used on most ready-to-eat meat products inhibits mold, Staphylococcus aureus is the pathogen most likely to grow on products with reduced a w and increased percentage of water-phase salt. In this study, 34 samples of various ready-to-eat meat products were inoculated with a three-strain mixture of S. aureus, vacuum packaged, and stored at 21ЊC for 4 weeks. S. aureus numbers decreased by 1.1 to 5.6 log CFU on fermented products (pH Յ 5.1) with a wide range of salt concentrations and moisture content. Similarly, S. aureus numbers decreased by 3.2 to 4.5 log CFU on dried nonacidified jerky (a w Յ 0.82; moisture:protein ratio of Յ0.8). Products that were not fermented or dried clearly supported S. aureus growth and cannot be considered shelf stable. The product pH and moisture:protein ratio were the two compositional factors most highly correlated (R 2 ϭ 0.84) with S. aureus survival and growth for the types of products tested, but pH and a w or pH and percentage of water-phase salt also may provide useful predictive guidance (R 2 ϭ 0.81 and 0.77, respectively).Several federal standards exist for the composition of ready-to-eat (RTE) meat products. The standards are used to define both product characteristics and shelf stability. The compositional factors commonly used by regulators in establishing compositional and shelf-stability standards are moisture:protein ratio (MPR), water activity (a w ), and pH. For example, nonrefrigerated semidry shelf-stable sausage must (i) have an MPR of Յ3.1 and a pH value of Յ5.0, (ii) have an MPR of Յ1.9 at any pH, or (iii) have a pH of Յ4.5 (or 4.6 with an a w of Յ0.91) and an internal brine concentration of Ն5% and must be intact (or vacuum packaged if sliced), cured, and smoked (19). With experience, processors can establish the relationship between MPR and product ''shrink'' or yield, which is relatively easy to determine. Similarly, a pH meter is relatively affordable for processors and can easily be used to determine product pH. Small-scale processors may be less likely to measure a w , however, because of the relatively high price of an a w meter. Food microbiologists, when evaluating the potential for pathogenic bacterial growth on meat products, commonly consider pH and either a w or percentage of water-phase salt (%WPS). Small-scale processors could build up a database relating product formulation and yield to %WPS, but this approach would require expenditures for analyses of water and salt percentages by a commercial laboratory. Because

Food regulatory agencies advise against thawing frozen meat and poultry at room temperature. In this study, whole chickens (1,670 g) and ground beef (453 and 1,359 g) were inoculated with Salmonella serovars, Escherichia coli O157:H7, and Staphylococcus aureus on the surface (all products) and in the center (ground beef). After freezing at Ϫ20ЊC for 24 h, products were thawed at 22 or 30ЊC for 9 h. Pathogen growth was predicted using product time and temperature data and growth values from the U.S. Department of Agriculture Agricultural Research Service Pathogen Modeling Program 7.0 predictive models of pathogen growth. No pathogen growth was predicted for whole chicken or 1,359 g of ground beef thawed at 30ЊC or 453 g of ground beef thawed at 22ЊC. Growth (Յ5 generations) was predicted for 453 g of ground beef at 30ЊC. Inoculation study data corroborated the predictions. No growth occurred on whole chickens or 1,359-g portions of ground beef thawed at 30ЊC for 9 h. Pathogen numbers increased an average of 0.2 to 0.5 log on the surface of 453-g ground beef portions thawed for 9 h at 22 or 30ЊC. Our results suggest that thawing Ն1,670 g of whole chicken at Յ30ЊC for Յ9 h and thawing Ͼ453 g ground beef portions at Յ22ЊC for Յ9 h are not particularly hazardous practices. Thawing smaller portions at higher temperatures and/or for longer times cannot be recommended, however. Use of values derived from the Pathogen Modeling Program 7.0 model provided realistic predictions of pathogen growth during thawing of frozen ground beef and chicken.

The recently developed 3M Petrifilm Staph Express Count plate (PFSE) method was compared with the U.S. Food and Drug Administration Bacteriological Analytical Manual's Baird-Parker agar spread plate (B-P) method for enumeration of Staphylococcus aureus in naturally contaminated, mechanically separated poultry (MSP; n = 92) and raw milk (n = 12). In addition, mozzarella and Parmesan cheeses and hot-smoked rainbow trout and chub were surface inoculated with a three-strain mixture of S. aureus, stored at 5 degrees C, and periodically analyzed with both methods for numbers of S. aureus. For naturally contaminated raw milk and MSP samples, the PFSE method yielded counts that were not significantly different (P > 0.05) from counts obtained using the B-P method. From raw milk and MSP samples, 60% (21 of 35) and 55% (124 of 226), respectively, of confirmed (DNAse-positive) isolates from PFSE plates were identified by further testing as S. aureus. Corresponding S. aureus identification rates for isolates forming typical colonies on B-P plates were 53% (19 of 36) and 50% (125 of 248). For both methods, other staphylococci composed the vast majority of tested isolates that were not identified as S. aureus. For inoculated hot-smoked fish, S. aureus counts from the PFSE method were not significantly different from counts from the B-P method. Compared to the B-P method, significantly lower numbers of inoculated S. aureus were recovered using the PFSE method in analyses of mozzarella cheese stored 28 and 42 days at 4 degrees C. The PFSE and B-P methods were not significantly different for inoculated cheeses at all other sampling times. DNAse-positive isolates from PFSE analyses of inoculated cheeses and smoked fish were identified as S. aureus 98% (51 of 52) and 86% (36 of 42) of the time, respectively, as compared with 100% (58 of 58) and 95% (40 of 42) of the time for typical B-P isolates. Overall, the PFSE and B-P methods appeared to perform similarly in enumeration of S. aureus in animal-derived foods.