Yoshinori Kamitani

In vitro inactivation of Escherichia coli, Staphylococcus aureus and Salmonella spp. using slightly acidic electrolyzed water

In the current study, the effectiveness of slightly acidic electrolyzed water (SAEW) on an in vitro inactivation of Escherichia coli (E. coli), Staphylococcus aureus (S. aureus) and Salmonella spp. was evaluated and compared with other sanitizers. SAEW (pH 5.6, 23mg/l available chlorine concentration; ACC; and 940mV oxidation reduction potential; ORP) was generated by electrolysis of dilute solution of HCl (2%) in a chamber of a non-membrane electrolytic cell. One milliliter of bacteria suspension (ca. 10-11 log(10)CFU/ml) was mixed with 9ml of SAEW, strong acidic electrolyzed water (StAEW; ca. 50mg/l ACC), sodium hypochlorite solution (NaOCl; ca.120mg/l ACC) and distilled water (DW) as control and treated for 60s. SAEW effectively reduced the population of E. coli, S. aureus and Salmonella spp. by 5.1, 4.8, and 5.2 log(10)CFU/ml. Although, ACC of SAEW was more than 5 times lower than that of NaOCl solution, they showed no significant bactericidal difference (p>0.05). However, the bactericidal effect of StAEW was significantly higher (p<0.05) than SAEW and NaOCl solution in all cases. When tested with each individual test solution, E. coli, S. aureus and Salmonella spp. reductions were not significantly different (p>0.05). These findings indicate that SAEW with low available chlorine concentration can equally inactivate E. coli, S. aureus and Salmonella spp. as NaOCl solution and therefore SAEW shows a high potential of application in agriculture and food industry as an environmentally friendly disinfection agent.

Development of a common calibration model for determining the Brix value of intact apple, pear and persimmon fruits by near infrared spectroscopy

Calibrations developed using near infrared (NIR) spectroscopy to determine the quality of fruits or vegetables are usually applicable to a single species. The ability to determine the quality of several species using a common calibration would have advantages in some situations. A method to develop a common NIR calibration model that could be applied to many fruit species was examined. NIR spectra of apples, pears and persimmons were measured in the short-wavelength region using an interactance method. Partial least-squares (PLS) regressions based on second-derivative spectra were performed for Brix-value determination using calibration samples comprising each fruit species independently and the three species combined. Each single species calibration model predicted the Brix value in validation samples of the same species with a low standard error of performance (SEP) (0.34–0.40°Brix (°Bx) and with low bias (0.01–0.08 °Bx) but with much higher SEP and bias errors when used to predict the Brix value in other species. The common calibration model developed from the combined sample set predicted Brix values in the apples, pears and persimmons with an SEP = 0.43 °Bx and a bias of −0.03 °Bx.

Development of a near infrared calibration model with temperature compensation using common temperature-difference spectra for determining the Brix value of intact fruits

In order to create a calibration model with temperature compensation, the calibration method using the partial least squares regression based on the combined spectra measured at some different temperatures is promising. However, the method is time-consuming since it requires spectra acquisition at different temperatures. In addition, the sample quality may change during the period for the different temperature adjustment of samples. The spectra of the target fruit species of peaches, pears, and persimmons were measured at 25℃ using the interactance method. Spectra for 20℃ and 30℃ were created artificially using temperature-difference second derivative spectra from the 25℃-second derivative spectra. Then, the possibility of temperature-difference second derivative spectra of fruit(s) to create the correct 20℃ and 30℃ artificial second derivative spectra was evaluated. The temperature-difference second derivative spectra created from each target fruit species could be useful for each target fruit species while the common temperature-difference second derivative spectra created from the three target fruit species were useful for not only each target fruit species but also the other fruit species of apples. The calibration model for apples developed using the common temperature-difference second derivative spectra showed low standard error of performance and bias of 0.45°Brix and 0.09°Brix, respectively. The model could be applied well to the prediction sets of apples at 20℃, 25℃, and 30℃ with non-significant biases.

A simple method of system response compensation of a near infrared instrument for determining Brix value of peaches

Abstract A system response of a near infrared (NIR) instrument sometimes changes depending on measuring conditions such as warming up time, room temperature and the others. In the last peach experiment, we measured NIR spectra over 3 days and spectral differences were observed between spectra measured at the first day and those at the second and third days. Therefore, a simple method of system response compensation was examined. As a result of principle component analysis (PCA) of second derivative (2D) spectra of peaches, samples were separated into two groups, the first-day measured samples and the second and third-day measured ones on the plane consisted of PC1 and PC2. On the hypothesis that average 2D spectrum of each group should be almost the same, the difference of the average 2D spectra (D2D spectrum) was calculated. Using D2D spectrum, 2D spectra of the first-day samples were adjusted to those of the other samples. The data set including the adjusted one is called “compensated 2D data set” hereafter as compared with “original 2D data set”. As results of partial least square (PLS) regressions based on the original and compensated 2D data sets and Brix value of peaches, good SEPs of 0.98 °Brix for both cases could be obtained. The number of factors for the calibration model in case of compensated 2D data set was smaller than that in case of original one. It was concluded that the method using D2D spectrum could be used to compensate the difference of system response of an NIR instrument.