Shuso Kawamura

Development of an automatic rice-quality inspection system

The need has arisen in rice-drying facilities in Japan for an automatic method to measure quality aspects of rice when it arrives at the drying facility. A near-infrared (NIR) transmission instrument was used to obtain NIR spectra of damp rough rice and damp brown rice. Calibration models were developed from the original spectra and reference analysis data to determine moisture and protein content of the samples. A visible light (VIS) segregator was used to determine sound whole kernel of brown rice. The precision and accuracy of the NIR instrument and the VIS segregator were found to be sufficiently high to determine moisture and protein content, and sound whole kernel ratio. An automatic rice-quality inspection system was consequently developed. The system consisted of a rice huller, a rice cleaner, an NIR instrument and a VIS segregator, and it was controlled by a computer. Based on the rice-quality information, this system enabled rough rice transported to a rice-drying facility to be classified into six qualitative grades.

Effects of Ohmic Heating, Including Electric Field Intensity and Frequency, on Thermal Inactivation of Bacillus subtilis Spores

Methods for microbial inactivation are important in the food industry; however, conventional external heating (CH) reduces food quality. Accordingly, the nonthermal effects of ohmic heating (OH) on Bacillus subtilis spores in a sodium chloride aqueous solution at 101°C (i.e., the boiling point), as well as the effects of electric field intensity and frequency during OH, were investigated. Survival kinetics were compared between OH and external CH. The inactivation effect on B. subtilis was greater for all electric field conditions (5, 10, and 20 V/cm) than for CH. In particular, 20 V/cm showed a significantly higher inactivation effect (P < 0.05) on B. subtilis than those of CH at 8, 10, 12, 14, and 16 min. The survival data were fitted to various primary kinetic models. In the Weibull model and the log-linear model, there were significant differences (P < 0.05) in the rate parameters δ and kmax between OH at 20 V/cm and CH. However, there were no significant differences (P > 0.05) in survival kinetics between 20, 40, and 60 kHz; B. subtilis spores were inactivated more efficiently as the frequency increased. B. subtilis spores were almost completely inactivated at 14 to 16 min for the 60-kHz treatment, but spores were still alive at 20 and 40 kHz for the same treatment times. These results demonstrated that OH inactivates B. subtilis spores more effectively than CH. OH conditions with high electric field intensities and high frequencies resulted in efficient B. subtilis spore inactivation.

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment

ABSTRACT Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process. IMPORTANCE We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation.

Survival Kinetics of Salmonella enterica and Enterohemorrhagic Escherichia coli on a Plastic Surface at Low Relative Humidity and on Low–Water Activity Foods

We investigated the survival kinetics of Salmonella enterica and enterohemorrhagic Escherichia coli under various water activity (aw) conditions to elucidate the net effect of aw on pathogen survival kinetics and to pursue the development of a predictive model of pathogen survival as a function of aw. Four serotypes of S. enterica (Stanley, Typhimurium, Chester, and Oranienburg) and three serotypes of enterohemorrhagic E. coli ( E. coli O26, E. coli O111, and E. coli O157:H7) were examined. These bacterial strains were inoculated on a plastic plate surface at a constant relative humidity (RH) (22, 43, 58, 68, or 93% RH, corresponding to the aw) or on a surface of almond kernels (aw 0.58), chocolate (aw 0.43), radish sprout seeds (aw 0.58), or Cheddar cheese (aw 0.93) at 5, 15, or 25°C for up to 11 months. Under most conditions, the survival kinetics were nonlinear with tailing regardless of the storage aw, temperature, and bacterial strain. For all bacterial serotypes, there were no apparent differences in pathogen survival kinetics on the plastic surface at a given storage temperature among the tested RH conditions, except for the 93% RH condition. Most bacterial serotypes were rapidly inactivated on Cheddar cheese when stored at 5°C compared with their inactivation on chocolate, almonds, and radish sprout seeds. Distinct trends in bacterial survival kinetics were also observed between almond kernels and radish sprout seeds, even though the aws of these two foods were not significantly different. The survival kinetics of bacteria inoculated on the plastic plate surface showed little correspondence to those of bacteria inoculated on food matrices at an identical aw. Thus, these results demonstrated that, for low-aw foods and/or environments, aw alone is insufficient to account for the survival kinetics of S. enterica and enterohemorrhagic E. coli .

Online Real-time Monitoring of Milk Quality during Milking by Near-infrared Spectroscopy

Recently, there has been a need by dairy farmers for a method to assess milk quality in real time during milking. We have constructed an on-line near-infrared (NIR) spectroscopic sensing system on an experimental basis. The NIR system can be used for real-time monitoring of milk quality items such as fat, protein, lactose, somatic cell count, and milk urea nitrogen during milking with sufficient precision and accuracy. We tried to improve the robustness of calibration (CAL) models for measurement of milk quality items using NIR spectrum data obtained from two dairy herds. When CAL models developed from data obtained from one herd were used for validation of data obtained from the same herd, the milk quality items could be measured with high levels of accuracy. On the other hand, when the CAL models were used for validation of data obtained from the other herd, the levels of accuracy in measurements of all milk quality items except fat were low. The low levels of accuracy may be caused by factors such as differences in cow individuality, lactation stage, calving times, feeding stage and experimental period (temperatures in the dairy barn). To develop robust calibration models for measurement of milk quality items, therefore, data acquisition from various milk spectra caused by these factors is necessary.

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation.

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process.

The Use of Colors as an Alternative to Size in Fusarium graminearum Growth Studies

Size-based fungal growth studies have limitations. For example, the growth in size stops in closed systems once it reaches the borders and poorly describes metabolic status, especially in the stationary phase. This might lead mycotoxin studies to unrealistic results. Color change could be a viable alternative, as pigments result from a mold’s metabolic activity. This study aimed to verify the possibility of using gray values and the RGB system to analyze the growth of Fusarium graminearum. It consisted of color and area measurements using ImageJ software for specimens grown in yeast extract agar (YEA). The results suggest the utility of color and gray values as reliable tools to analyze the growth of F. graminearum.

Near-infrared Spectroscopy for Determining Grain Constituent Contents at Grain Elevators

Near-infrared spectroscopy (NIRS) calibration models for determining grain constituent contents at grain elevators were developed using rice and wheat grown in Hokkaido. The coefficient of determination (r2), standard error of prediction (SEP) and ratio of standard error of prediction to standard deviation (RPD) of the validation statistics were r2 > 0.99, SEP = 0.19 % and RPD = 25.2 for brown rice moisture content, r2 = 0.99, SEP = 0.09 % and RPD = 9.8 for milled rice protein content, r2 > 0.99, SEP = 0.34 % and RPD = 23.1 for wheat moisture content and r2 = 0.97, SEP = 0.31 % and RPD = 5.4 for wheat protein content. These results indicated that the accuracy of NIRS was sufficiently high for practical use at grain elevators.

Ohmic Heating for Milk Pasteurization: Effect of Electric Current on Nonthermal Injury to Streptococcus thermophilus

Experiments on milk pasteurization were conducted with cells of Streptococcus thermophilus 21072 to confirm the lethal effect of electric current using combination treatment (sublethal ohmic and conventional heating treatment) and control treatment (conventional heating treatment only). Bacteria counts and calculated decimal reduction times (D value) of combination treatment indicated that combination treatment had significantly higher lethality than that of control treatment under the condition of the same temperature histories (p<0.05). However, no pasteurizing effect of the electric current on bacteria cells was observed during the sublethal ohmic treatment. The results suggested that sublethal ohmic treatment decreased the heat resistance of bacteria probably due to nonthermal injury of bacteria caused by the electric current.

On-line Near Infrared Spectroscopic Sensing Technique for Assessing Milk Quality during Milking

There has been a need in recent years for a method that will enable dairy farmers to assess milk quality of individual cows during milking. We constructed on-line near-infrared (NIR) spectroscopic sensing system on an experimental basis. This system enables NIR spectra of unhomogenized milk to be obtained during milking over a wavelength range of 600 nm to 1050 nm. We also developed calibration models for predicting three major milk constituents (fat, protein and lactose), somatic cell count (SCC) and milk urea nitrogen (MUN) of unhomogenized milk, and we validated the precision and accuracy of the models. The coefficient of determination (r2) and standard error of prediction (SEP) of the validation set for fat were 0.95 and 0.42%, respectively. The values of r2 and SEP for protein were 0.91 and 0.09%, respectively; the values of r2 and SEP for lactose were 0.94 and 0.05%, respectively; the values of r2 and SEP for SCC were 0.82 and 0.27 log SCC/mL, respectively; and the values of r2 and SEP for MUN were 0.90 and 1.33 mg/dL, respectively. These results indicated that the NIR sensing system developed in this study could be used to assess milk quality in real time during milking. The system can provide dairy farmers with information on milk quality and physiological condition of individual cows and therefore give them feedback control for optimizing dairy farm management.