Microbes in Rough Rice – Prevalence, Growth Kinetics and Links to Dry Matter Loss

• Main Author: Thote, Supriya
• Format: Text
• Language: unknown
• Published: ScholarWorks@UARK 2016
• Subjects: Biological sciences; Applied sciences; Aerobic plate counts; Arkansas; dry matter loss; Microbial growth kinetics; Mold; Rice; Food Biotechnology; Food Microbiology; DML
• Online Access: https://scholarworks.uark.edu/etd/1753; https://scholarworks.uark.edu/context/etd/article/3292/viewcontent/Thote_uark_0011O_12317.pdf

The prevalence of microorganisms on freshly-harvested long-grain hybrid, long-grain pureline, and medium-grain rice has not been elucidated. The first objective of this two-part study was to determine the relative prevalence of microbes on freshly-harvested, high moisture content rice of different types and cultivars. The total and surface aerobic plate counts (APC) and mold counts were determined in terms of log10 colony forming units per gram of rice (log10 CFU/g) for six rice cultivars over two years. In 2013, among harvested samples of all the studied rice cultivars, the long-grain hybrid cultivars had the lowest APC levels (M = 8.10, SD = 0.09) (M and SD symbolize mean and standard deviation, respectively). Similarly, for the 2014 harvested samples the long-grain hybrid cultivars had the lowest mold count levels (M = 5.97, SD =0.27). After harvest, depending on storage conditions, some molds growing on stored rice may produce aflatoxins. For the second part of the study, mold and APC counts were enumerated for three long-grain hybrid rice cultivars, XL753 (2014) and CL XL745 (2014, 2015) and XL760 (2015) stored in rough rice form in sealed glass jars at moisture contents (MC) of 21%, 19%, 16%, and 12.5% (wet-basis) at temperatures of 10°C, 15°C, 20°C, 27°C, and 40°C for a total of 16 weeks, with samples taken every two weeks. For all cultivars, a direct relationship between mold counts and MC was observed – whereas more complex trends were observed for the effect of temperature and the duration of storage on mold growth. Kinetic models Baranyi, Weibull, Gompertz, Richard and Buchanan were successfully modified and fitted using non-linear regression and were used to predict the mold counts (log10 CFU/g) for varying conditions (correlations=0.65-0.76). Additionally, dry matter loss (DML) constants for hermetic storage conditions were found to be significantly different than the typical constants for the DML equation provided for long-grain rice in the literature.