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This study investigated the enzymatic detection of histidine among the 20 amino acids using histidyl-tRNA synthetase (HisRS) as the histidine recognition element. Previously, we studied the binding ability of HisRS and used it as the recognition element in a biosensor; however, in this study, we focused on improving the sensitivity and expanding the dynamic range of histidine analysis using HisRS, as well as analyzing the histidine concentration in real food samples for practical application. Previous studies, as well as our own, have indicated that the binding of HisRS, is strongly affected by the concentrations of 5′-triphosphate (ATP) and magnesium chloride (MgCl2) in the HisRS reaction buffer. Ammonium molybdate or Trinder’s reagent was used for the coloring reaction. Upon optimization of the reaction conditions, we found that 40 mM ATP and 50 mM MgCl2yielded a linear relationship from 1 to 150 μM histidine (correlation coefficient: r= 0.960). Compared to our previous methods, this method detected histidine over a wider range and with higher sensitivity. Moreover, in real food samples, the plots of spiked histidine were in good agreement with the histidine calibration curve, with a measurement error range of within ± 4.9%.

Microbiological treatment of wastewater discharged from purification processes of biodiesel fuel (BDF) produced from waste edible oil with alkaline catalyst was carried out in a 3L jar-fermentor. Wastewater treatment was started by the addition of the seed culture of Rhodotorula mucilaginosaHCU-1 to the medium prepared from oil-removed wastewater. Methanol and glycerol concentrations in the wastewater were predicted simultaneously using near infrared (NIR) spectroscopy. The wastewater containing the microorganism cells in a 1 mm light path length cuvette was placed in an NIR spectrophotometer and the absorbance at wavelengths between 400 nm and 2500 nm was measured at 2 nm intervals. Simple or multiple linear regression analysis was used to obtain calibration equations relating to the NIR spectral data and the content of a calibration sample set (n=66) obtained by the conventional methods. The wavelengths at 2264 nm, and 2274 nm and 2256 nm were selected to make calibration equations for methanol and glycerol, respectively. Prediction of methanol and glycerol contents (n=45) was successfully carried out using NIR spectroscopy with r2=0.996 and SEP=0.637 gL−1and r2=0.996 and SEP=0.31 gL−1respectively.

Microbiological treatment of wastewater discharged from purification processes of biodiesel fuel (BDF) produced from waste edible oil with alkaline catalyst was carried out in a 3L jar-fermentor. Wastewater treatment was started by the addition of the seed culture of Rhodotorula mucilaginosa HCU-1 to the medium prepared from oil-removed wastewater. Methanol and glycerol concentrations in the wastewater were predicted simultaneously using near infrared (NIR) spectroscopy. The wastewater containing the microorganism cells in a 1 mm light path length cuvette was placed in an NIR spectrophotometer and the absorbance at wavelengths between 400 nm and 2500 nm was measured at 2 nm intervals. Simple or multiple linear regression analysis was used to obtain calibration equations relating to the NIR spectral data and the content of a calibration sample set (n=66) obtained by the conventional methods. The wavelengths at 2264 nm, and 2274 nm and 2256 nm were selected to make calibration equations for methanol and glycerol, respectively. Prediction of methanol and glycerol contents (n=45) was successfully carried out using NIR spectroscopy with r^2=0.996 and SEP=0.637 gL^−1 and r^2=0.996 and SEP=0.31 gL^−1 respectively.

Biodiesel fuel (BDF) made from edible oil or its waste is widely used as a renewable and environmentally friendly energy source. The crude BDF produced with alkali catalyst is washed with water to remove a by-product, glycerol. The BDF wastewater discharged from this washing process has to be appropriately treated. The microbial treatment of the BDF wastewater is promising because glycerol is difficult to separate from the BDF wastewater. The addition of some nutrients is essential for the efficient microbial treatment of the BDF wastewater. Measurement of the glycerol concentration in the microbial-treated BDF wastewater is very important because the amount of nutrients which should be added depends on the glycerol concentration. The prediction of the glycerol concentration in the BDF wastewater using near infrared (NIR) spectroscopy was investigated. Oil degradable yeast and some nutrients were added to the BDF wastewater. The microbial-treated wastewater was used as the source for calibration and validation set samples. Calibration equations relating the NIR spectral data to the glycerol concentration measured with the enzymatic method were obtained. The prediction of the glycerol concentration was successfully carried out using NIR spectroscopy regardless of the presence or absence of the microbial cells. A good result was observed for the calibration equation made with optical data in the presence of the microbial cells at the wavelengths of 2264 nm and 1052 nm. This result suggests that the glycerol concentration in the microbial-treated BDF wastewater can be predicted even in the presence of the microbial cells. The simple, rapid and on-line prediction of the glycerol concentration in the BDF wastewater using NIR spectroscopy will allow more efficient microbial treatment of the BDF wastewater.

Biodiesel fuel (BDF) made from edible oil or its waste is widely used as a renewable and environmentally friendly energy source. The crude BDF produced with alkali catalyst is washed with water to remove a by-product, glycerol. The BDF wastewater discharged from this washing process has to be appropriately treated. The microbial treatment of the BDF wastewater is promising because glycerol is difficult to separate from the BDF wastewater. The addition of some nutrients is essential for the efficient microbial treatment of the BDF wastewater. Measurement of the glycerol concentration in the microbial-treated BDF wastewater is very important because the amount of nutrients which should be added depends on the glycerol concentration. The prediction of the glycerol concentration in the BDF wastewater using near infrared (NIR) spectroscopy was investigated. Oil degradable yeast and some nutrients were added to the BDF wastewater. The microbial-treated wastewater was used as the source for calibration and validation set samples. Calibration equations relating the NIR spectral data to the glycerol concentration measured with the enzymatic method were obtained. The prediction of the glycerol concentration was successfully carried out using NIR spectroscopy regardless of the presence or absence of the microbial cells. A good result was observed for the calibration equation made with optical data in the presence of the microbial cells at the wavelengths of 2264 nm and 1052 nm. This result suggests that the glycerol concentration in the microbial-treated BDF wastewater can be predicted even in the presence of the microbial cells. The simple, rapid and on-line prediction of the glycerol concentration in the BDF wastewater using NIR spectroscopy will allow more efficient microbial treatment of the BDF wastewater.

To prepare and maintain the optimal biodegradation conditions of wastewater discharged from a biodiesel fuel (BDF) production process with alkali–catalysis transesterification, rapid and simple methods were investigated to measure oil (carbon source of microorganisms) and urea (nitrogen source) concentrations and solids content (indicator of growth inhibition of microorganism) of the wastewater. Two non-destructive methods were investigated. First, physical properties of the BDF wastewater such as electric conductivity (EC), specific gravity (Sp.Gr.) and Brix values were measured and the values were analysed with multiple liner regression (MLR). Only solids content could be predicted by measured physical properties. However, adjustment of the C/N ratio of the BDF wastewater was also necessary to prepare the optimal condition for the microorganism growth in the wastewater treatment process. Therefore, near infrared (NIR) spectroscopy was applied to simultaneous, non-destructive and rapid measurement of the constituents of the wastewater. The dominant absorptions caused by oil, urea and solids material in the wastewater were observed at 1718, 2154 and 2286 nm, respectively. These were used as the first wavelength to formulate calibration equations, a MLR analysis was carried out between the NIR spectral data and the values of conventional analyses, such as hexane extraction, enzymatic and oven-drying methods, in the calibration sample set (sample number, n= 50). To validate the calibration equations obtained, the predicted values of the oil, urea and solids in the validation sample set (n= 40), which was not used for formulating the calibration equations, were calculated using the calibration equations. Good agreement was observed between the values of the conventional analyses and the values predicted using NIR; the multiple correlation coefficients of determination (r2) for the validation equations for oil, solids and urea were 0.993, 0.877 and 0.960, respectively. Prediction of the solids content of the BDF wastewater using EC and Brix values is also possible with the handy EC and Brix meters which are inexpensive and easy to handle. However, these do not allow total management of the BDF production and BDF wastewater treatment processes. On the other hand, the NIR method is potentially suitable for automated process management of a BDF wastewater treatment system.

To prepare and maintain the optimal biodegradation conditions of wastewater discharged from a biodiesel fuel (BDF) production process with alkali–catalysis transesterification, rapid and simple methods were investigated to measure oil (carbon source of microorganisms) and urea (nitrogen source) concentrations and solids content (indicator of growth inhibition of microorganism) of the wastewater. Two non-destructive methods were investigated. First, physical properties of the BDF wastewater such as electric conductivity (EC), specific gravity (Sp.Gr.) and Brix values were measured and the values were analysed with multiple liner regression (MLR). Only solids content could be predicted by measured physical properties. However, adjustment of the C/N ratio of the BDF wastewater was also necessary to prepare the optimal condition for the microorganism growth in the wastewater treatment process. Therefore, near infrared (NIR) spectroscopy was applied to simultaneous, non-destructive and rapid measurement of the constituents of the wastewater. The dominant absorptions caused by oil, urea and solids material in the wastewater were observed at 1718, 2154 and 2286 nm, respectively. These were used as the first wavelength to formulate calibration equations, a MLR analysis was carried out between the NIR spectral data and the values of conventional analyses, such as hexane extraction, enzymatic and oven-drying methods, in the calibration sample set (sample number, n = 50). To validate the calibration equations obtained, the predicted values of the oil, urea and solids in the validation sample set (n = 40), which was not used for formulating the calibration equations, were calculated using the calibration equations. Good agreement was observed between the values of the conventional analyses and the values predicted using NIR; the multiple correlation coefficients of determination (r^2) for the validation equations for oil, solids and urea were 0.993, 0.877 and 0.960, respectively. Prediction of the solids content of the BDF wastewater using EC and Brix values is also possible with the handy EC and Brix meters which are inexpensive and easy to handle. However, these do not allow total management of the BDF production and BDF wastewater treatment processes. On the other hand, the NIR method is potentially suitable for automated process management of a BDF wastewater treatment system.

In a glycolipid fermentation, mannosyl erythritol lipid (MEL) is produced from soybean oil added to a medium as a source of carbon. A measurement system for the concentrations of MEL and soybean oil in the fermentation process has been developed using near infrared (NIR) spectroscopy. MEL and soybean oil in the culture broth were extracted with ethyl acetate. NIR spectra of the ethyl acetate extract were measured in the wavelength range between 400 and 2500 nm at 2 nm intervals. The absorption caused by MEL was observed at 1436, 1920 and 2052 nm. To obtain a calibration equation, a multiple linear regression (MLR) was carried out between the second derivative NIR spectral data at 2040 and 1312 nm and MEL concentrations obtained using thin-layer chromatography with a flame-ionisation detector (TLC/FID) method. The values of the regression coefficient (R) and the standard error of calibration (SEC) were 0.994 and 0.48 g L−1, respectively. The absorption caused by soybean oil was observed at 1208, 1716, 1766, 2182 and 2302 nm. A calibration equation for soybean oil was formulated with the second derivative NIR spectral data at 2178 and 2090 nm. The values of Rand SECwere 0.974 and 0.77 g L−1, respectively. After validation of the calibration equation, good agreement was observed between the results of the TLC/FID method and those of the NIR method for both constituents. The values of the correlation coefficient (r) for MEL and the standard error of prediction (SEP) were 0.994 and 0.45 g L−1, respectively. The values of rand SEPfor soybean oil were 0.979 and 0.56 g L−1, respectively. The NIR method was applied to the measurement of the concentrations of MEL and soybean oil in an actual fermentation process and good results were obtained. The study indicates that NIR spectroscopy is a useful method for the measurement of the raw material and product in glycolipid fermentation.

In a glycolipid fermentation, mannosyl erythritol lipid (MEL) is produced from soybean oil added to a medium as a source of carbon. A measurement system for the concentrations of MEL and soybean oil in the fermentation process has been developed using near infrared (NIR) spectroscopy. MEL and soybean oil in the culture broth were extracted with ethyl acetate. NIR spectra of the ethyl acetate extract were measured in the wavelength range between 400 and 2500 nm at 2 nm intervals. The absorption caused by MEL was observed at 1436, 1920 and 2052 nm. To obtain a calibration equation, a multiple linear regression (MLR) was carried out between the second derivative NIR spectral data at 2040 and 1312 nm and MEL concentrations obtained using thin-layer chromatography with a flame-ionisation detector (TLC/FID) method. The values of the regression coefficient (R) and the standard error of calibration (SEC) were 0.994 and 0.48 g L^−1, respectively. The absorption caused by soybean oil was observed at 1208, 1716, 1766, 2182 and 2302 nm. A calibration equation for soybean oil was formulated with the second derivative NIR spectral data at 2178 and 2090 nm. The values of R and SEC were 0.974 and 0.77 g L^−1, respectively. After validation of the calibration equation, good agreement was observed between the results of the TLC/FID method and those of the NIR method for both constituents. The values of the correlation coefficient (r) for MEL and the standard error of prediction (SEP) were 0.994 and 0.45 g L^−1, respectively. The values of r and SEP for soybean oil were 0.979 and 0.56 g L^−1, respectively. The NIR method was applied to the measurement of the concentrations of MEL and soybean oil in an actual fermentation process and good results were obtained. The study indicates that NIR spectroscopy is a useful method for the measurement of the raw material and product in glycolipid fermentation.

Near infrared (NIR) spectroscopy was employed for the simultaneous prediction of the concentrations of glucose and citric acid in the aqueous solution of a blood anticoagulant solution. The solution was placed in an NIR spectrophotometer and the absorbance at wavelengths between 400 and 2500 nm was measured at 2 nm intervals. Multiple linear regression (MLR) was used to obtain calibration equations relating the NIR spectral data and the glucose and citric acid concentrations of a calibration sample set obtained by enzymatic methods. The value of the multiple correlation coefficient (R) was 0.993 when using the wavelengths of 2274 and 1674 nm for glucose. The value of the simple correlation coefficient (r) for citric acid was 0.993 when using the wavelength 1690 nm. To validate the calibration equations obtained, glucose and citric acid concentrations in a prediction sample set were compared with the concentrations measured by the enzymatic methods. Excellent agreement between the results of the enzymatic method and those of NIR spectroscopy was observed for both constituents. The procedure of NIR spectroscopy was simple and the operation time required to predict the concentrations was a few minutes. These results indicate that NIR spectroscopy may be a useful method for monitoring the production process of the blood anticoagulant.

Near infrared (NIR) spectroscopy was used to determine the carbon and nitrogen content of compost during compost fermentation of tofu (soybean-curd) refuse. Reflectance measurements in the wavelength range between 400 and 2500 nm were made at 2 nm intervals. The NIR absorption of the carbon components was observed at two wavelengths, 1584 and 1024 nm in the second derivative spectrum. The NIR absorption of nitrogen components was observed at two wavelengths, 2174 and 900 nm in the second derivative spectrum. To formulate a calibration equation, a multiple linear regression analysis was carried out between the NIR spectral data and the carbon and nitrogen content in the calibration sample set (sample number, n = 60) obtained using a Pregie–Dumas combustion method. The values of the multiple correlation coefficient were 0.988 and 0.984, respectively. To validate the calibration equations obtained, the carbon and nitrogen content in the prediction sample set (n = 48), not used for formulating the calibration equation, were calculated using the calibration equations and compared with the values obtained using the Pregie–Dumas combustion method. Good agreement was observed between the results of the Pregie–Dumas combustion method and the NIR method. The values of the simple correlation coefficient were 0.986 and 0.972, respectively. The study indicates that NIR is a useful method for process management of the compost fermentation of tofu refuse.

Near infrared (NIR) spectroscopy was employed for the simultaneous prediction of the concentrations of glucose and citric acid in the aqueous solution of a blood anticoagulant solution. The solution was placed in an NIR spectrophotometer and the absorbance at wavelengths between 400 and 2500 nm was measured at 2 nm intervals. Multiple linear regression (MLR) was used to obtain calibration equations relating the NIR spectral data and the glucose and citric acid concentrations of a calibration sample set obtained by enzymatic methods. The value of the multiple correlation coefficient (R) was 0.993 when using the wavelengths of 2274 and 1674 nm for glucose. The value of the simple correlation coefficient (r) for citric acid was 0.993 when using the wavelength 1690 nm. To validate the calibration equations obtained, glucose and citric acid concentrations in a prediction sample set were compared with the concentrations measured by the enzymatic methods. Excellent agreement between the results of the enzymatic method and those of NIR spectroscopy was observed for both constituents. The procedure of NIR spectroscopy was simple and the operation time required to predict the concentrations was a few minutes. These results indicate that NIR spectroscopy may be a useful method for monitoring the production process of the blood anticoagulant.

Near infrared (NIR) spectroscopy was used to determine the carbon and nitrogen content of compost during compost fermentation of tofu (soybean-curd) refuse. Reflectance measurements in the wavelength range between 400 and 2500 nm were made at 2 nm intervals. The NIR absorption of the carbon components was observed at two wavelengths, 1584 and 1024 nm in the second derivative spectrum. The NIR absorption of nitrogen components was observed at two wavelengths, 2174 and 900 nm in the second derivative spectrum. To formulate a calibration equation, a multiple linear regression analysis was carried out between the NIR spectral data and the carbon and nitrogen content in the calibration sample set (sample number, n= 60) obtained using a Pregie–Dumas combustion method. The values of the multiple correlation coefficient were 0.988 and 0.984, respectively. To validate the calibration equations obtained, the carbon and nitrogen content in the prediction sample set (n= 48), not used for formulating the calibration equation, were calculated using the calibration equations and compared with the values obtained using the Pregie–Dumas combustion method. Good agreement was observed between the results of the Pregie–Dumas combustion method and the NIR method. The values of the simple correlation coefficient were 0.986 and 0.972, respectively. The study indicates that NIR is a useful method for process management of the compost fermentation of tofu refuse.

Near infrared (NIR) spectroscopy was applied to the prediction of the growth rate of mushroom, Ganoderma lucidum, in a solid culture. Cell mass is conventionally measured by analysing the concentration of glucosamine which is a component of the cell wall. The correlation between the concentration of glucosamine obtained by the conventional method and that obtained by NIR spectroscopy was examined by multiple regression analysis. The value predicted by NIR spectroscopy was in fairly good agreement with that obtained by the conventional method. This result suggests that NIR spectroscopy is applicable to the prediction of growth rate in the solid culture and gives a useful method for the control of mushroom production.

Near infrared spectroscopy (NIR) was applied to the prediction of the growth rate of mushroom, Ganoderma lucidum, in the solid fermentation process. In order to produce a calibration equation, Spectral data of solid medium were analyzed by multiple linear regression with a computer. Cell mass is conventionally measured by analyzing concentration of glucosamine which is a component of the cell wall. The concentration of glucosamine obtained by NIR was compared with that obtained by the conventional method. The values predicted by NIR were fairly in good agreement with those obtained by the conventional method. This result suggests that the NIR is applicable to prediction of growth rate in the solid culture and gives a useful method for the process management of mushroom production.

Brightness luminous-efficiency functions for point sources and for 2° and 10° fields are based on 6, 63, and 76 subjects, respectively. The function for point sources can be approximated by Judd’s 1951 modification of the CIE V(λ) function. The 2° and 10° functions differ greatly from V(λ). The two functions differ from each other only at wavelengths from 410 through 520 nm, where the differences are attributed to absorption by the macular pigment.

The influence of the illuminance and spectral composition of monochromatic surround fields on spatially induced blackness was investigated. The amount of induced blackness in a white 50′ central field was measured as a function of the illuminance of monochromatic 64′–120′ surround fields with a color-naming method. The function relating induced blackness to log surround illuminance was described by either the logistic function or the Weibull function. Action spectra for blackness were determined from those functions and were also measured directly with the method of adjustment. These action spectra indicated that blackness induction was determined only by the illuminance of the surround, regardless of the blackness level at the criteria and the wavelength of the surround. It was concluded that there is no chromatic contribution from the chromatic surround to blackness induction.

Near infrared (NIR) spectroscopy was applied to the prediction of the growth rate of mushroom, Ganoderma lucidum, in a solid culture. Cell mass is conventionally measured by analysing the concentration of glucosamine which is a component of the cell wall. The correlation between the concentration of glucosamine obtained by the conventional method and that obtained by NIR spectroscopy was examined by multiple regression analysis. The value predicted by NIR spectroscopy was in fairly good agreement with that obtained by the conventional method. This result suggests that NIR spectroscopy is applicable to the prediction of growth rate in the solid culture and gives a useful method for the control of mushroom production.

Hypothalamic hamartoma is a rare tumor with onset of symptoms in infancy or early childhood. Clinical presentation includes precocious puberty, laughing spells, and seizures. Computed tomography of two cases of hypothalamic hamartomas revealed a mass lesion in the suprasellar-inter-peduncular cisterns (with the density of) the surrounding normal brain. The mass was not enhanced by injection of contrast material.