Master of Science / Food Science Institute / Karen A. Schmidt / Radio frequency dielectric heating (RFDH) can provide rapid and uniform heating throughout the products' mass, and can be used to bake, dry, and defrost foods. Studies have shown that when RFDH induced a 5-log reduction of Salmonella spp. in nonfat dry milk (NDM), whey protein nitrogen index (WPNI) decreased, suggesting that functional properties of the NDM might be impacted. This research was conducted to determine if RFDH affected the functional properties of NDM [high-heat (HH) and low-heat (LH)]. Nonfat dry milk were treated to 75, 80 and 85°C in the RFDH unit, then were held for 125, 63 and 43 min for LH-NDM or 115, 52 and 43 min for HH-NDM, and cooled to ~23 ± 1°C. Powders were evaluated for WPNI , nitrogen solubility index, and color. Maillard browning and functional properties of NDM samples were evaluated after NDM was rehydrated to 3.5% protein with deionized water, and adjusted to pH 7.00. Glucono-delta-lactone was added in rehydrated NDM (3.5% protein; natural pH) as an acidifying agent to form milk gels, and the physical properties of the gels were determined. Two replications were conducted and data were analyzed with two-way ANOVA (RFDH and NDM) and Tukey mean differentiations (p ≤ 0.05). Results showed that LH-NDM (collapsed for RFDH treatments) had 5.7% less viscosity, 20.9% less overrun, 27.4% less foam stability, as well as 15% less water holding capacity compared with HH-NDM (collapsed for RFDH treatments). This can be explained by the natural whey protein denaturation differences in the HH-NDM and LH-NDM. Viscosity and surface tension were impacted by the RFDH treatment. NDM (HH and LH) treated to 85°C had 10% greater viscosity than the control, and the NDM treated to 75°C had less surface tension compared with samples treated to 80°C, 85°C and the control. Overall, RFDH decreased WPNI in LH-NDM, but not HH-NDM. The SDS-PAGE gel images provided supportive evidence to the WPNI results. RFDH is a processing technology that could change a few functional properties of NDM in this study, which makes it a promising method that may be further exploited for various food applications, such as emulsifiers, foaming agents, etc. However, potential negative impacts, such as color change caused by Maillard reaction, loss of WPNI in LH-NDM, cannot be neglected.

Thesis (Ph. D.)--Washington State University, May 2010. / Title from PDF title page (viewed on June 18, 2010). "Department of Biological Systems Engineering." Includes bibliographical references.

Doctor of Philosophy / Department of Food Science / Randall K. Phebus / Intervention techniques to control foodborne pathogens, and rapid identification of pathogens in food are of vital importance to ensure food safety. Therefore, the first objective of this research was to study the efficacy of radio frequency dielectric heating (RFDH) against C. sakazakii and Salmonella spp. in nonfat dry milk (NDM) at 75, 80, 85, or 90°C. Using thermal-death-time (TDT) disks, D-values of C. sakazakii in high heat (HH)- and low heat (LH)-NDM were 24.86 and 23.0 min at 75°C, 13.75 and 7.52 min at 80°C, 8.0 and 6.03 min at 85°C, and 5.57 and 5.37 min at 90°C, respectively. D-values of Salmonella spp. in HH- and LH-NDM were 23.02 and 24.94 min at 75°C, 10.45 and 12.54 min at 80°C, 8.63 and 8.68 min at 85°C, and 5.82 and 4.55 min at 90°C, respectively. The predicted (TDT) and observed (RFDH) destruction of C. sakazakii and Salmonella spp. were in agreement, indicating that the organisms' behavior was similar regardless of the heating system (conventional vs. RFDH). However, RFDH can be used as a faster and more uniform heating method for NDM to achieve the target temperatures. The second objective of this research was to study if hyperspectral imaging can be used for the rapid identification and differentiation of various foodborne pathogens. Four strains of C. sakazakii, 5 strains of Salmonella spp., 8 strains of E. coli, and 1 strain each of L. monocytogenes and S. aureus were used in the study. Principal component analysis and kNN (k-nearest neighbor) were used to develop classification models, which were then validated using a 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 within E. coli, strains O26, O45 and O121 had 66.67% accuracy. When all strains were studied together (irrespective of their genera) 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%).