The Geeraerd-tail model described the data well in only 69 of the

The Geeraerd-tail model described the data well in only 69 of the 75 conditions and generally showed poorer statistical fits ( Table 2). These results are consistent with previous studies showing non-linear models, particularly the Weibull model, describe the thermal resistance of Salmonella in low-moisture foods more accurately as compared to log-linear ones ( Podolak et al., 2010). Based on the previous analysis,

the Weibull model was selected for secondary modeling. The Weibull model satisfactorily described the greatest number of conditions and statistical parameters indicated the best fit. Moreover, the Weibull model could also produce linear fits (with β = 1 in Eq.  (5)) and thus also described linear inactivation kinetics as obtained at 21 °C. Table 3 presents δ and β parameter values (Eq.  Compound C research buy (5)) for the fits of the Weibull model for all conditions under study. Because δ values for data at distinct temperatures differed by several orders of magnitude,

these values were transformed to log scale. The log δ (log min) are presented in Table 3. Linear models relating the time required for first decimal reduction (log δ) and shape factor values (log β) to temperature, aw and water mobility were fit using multiple linear regression. The β values were log transformed to normalize the data. The analysis indicated that temperature was a significant factor influencing the time required for first decimal Talazoparib supplier reduction and the shape of the inactivation curve (p < 0.001). Water activity was also a significant factor in the model that related the time required for first decimal reduction to temperature (p < 0.001). Water activity did not significantly influence the shape of the inactivation curve (p = 0.279). Linifanib (ABT-869) Water mobility did not significantly influence the time required for first decimal reduction or the shape of the inactivation curve (p > 0.05). The secondary models developed for Salmonella spp. survival in low-moisture

foods are presented in Eqs.  (19) and (20). equation(19) logδ=−0.10×T−4.34×aw+9.91R2=0.96 equation(20) logβ=−0.006×TR2=0.74 In Eq. (19), the standard error (s.e.) of log δ was 0.35, that of the temperature parameter (T) was 0.003, that of the water activity parameter (aw) was 0.52 and that of the constant was 0.26. In Eq.  (20), the s.e. of log β was 0.22 and that of the T parameter was 0.001. Thirteen δ (time required for first decimal reduction) and β (shape factor) values for Salmonella survival were obtained from 151 CFU measurements. These correspond to survival in low-fat cocoa powder at 22 °C for 168 days (aw = 0.35), 35 °C for 168 days (aw = 0.32 and aw = 0.34) and 70 °C for 24 h (aw = 0.33 and aw = 0.35), low-fat peanut meal at 60 °C for 672 h (aw = 0.21 and aw = 0.35), non-fat dry milk at 50 °C for 96 h (aw = 0.28 and aw = 0.41), wheat flour at 36 °C for 84 days (aw = 0.20 and aw = 0.55) and whey protein at 80 °C for 60 min (aw = 0.21 and aw = 0.42).

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