Fermentation and quality of yellow pigments from golden brown rice solid culture by a selected Monascus mutant.

A single peak (λmax 370) yellow pigment-producing mutant derived from Monascus sp. TISTR 3179 was used for the pigment production in solid rice culture. Various factors affecting yellow tones were investigated. Hom-mali rice variety was the best amongst five Thai local varieties used for fungus culture. It was also better than corn, mungbean, soybean, potato, sweet potato, or cassava tubers. The moisture content and temperature were the key environmental factors affecting the color tones of creamy, tangerine, and golden brown rice solid cultures. The golden brown rice culture gave the highest yellow pigment concentration. Under an optimum room temperature of 28-32 °C, an initial moisture content of 42 %, and 7-day-old inoculum size of 2 % (v/w) the maximum yield at 2,224.63 A370U/gdw of yellow pigment was produced. A mellow yellow powder at 550 A370U/gdw could be obtained using spray-drying techniques. The powder had a moisture content of 5.15 %, a water activity value of 0.398, a hue angle of 73.70 ° (yellowish orange), high lightness (L) of 74.63, color saturation (C) of 28.97, a neutral pH of 7.42, 0.12 % acidity and solubility of 0.211 g/10 ml. It was noteworthy that the Chinese fresh noodle with spray-dried yellow powder showed no discoloration during 8-day storage.

Optimizing time and temperature of enzymatic conversion of isoflavone glucosides to aglycones in soy germ flour.

Five factors (enzyme concentration, substrate concentration, pH, incubation temperature, and incubation time) were initially screened for the conversion of isoflavone glucosides to aglycones in soy germ flour. The incubation temperature/time most significantly affected aglycone yield; subsequently, a full 5 (35, 40, 45, 50, and 55 °C) × 6 (1, 2, 3, 4, 5, and 6 h) factorial design and response surface methodology were employed to attain an optimal incubation time/temperature condition. The optimum condition producing soy germ flour with a high concentration of daidzein, glycitein, and genistein was as follows: soy germ flour:deionized water (1:5, w/v), ß-glucosidase at 1 unit/g of soy germ flour, pH 5, and incubation temperature/time of 45 °C/5 h. Under this optimal condition, most isoflavone glucosides were converted to aglycones with daidzein, glycitein, and genistein of ≥ 15.4, ≥ 6.16, and ≥ 4.147 µmol/g, respectively. In contrast, the control soy germ flour contained 13.82 µmol/g daidzin, 7.11 µmol/g glycitin, 4.40 µmol/g genistin, 1.56 µmol/g daidzein, 0.52 µmol/g glycitein, and 0.46 µmol/g genistein.

Determination of total nitrogen content, pH, density, refractive index, and brix in Thai fish sauces and their classification by near-infrared spectroscopy with searching combination moving window partial least squares.

Near-infrared (NIR) transflectance spectra in the region of 1100-2500 nm were measured for 100 Thai fish sauces. Quantitative analyses of total nitrogen (TN) content, pH, refractive index, density and brix in the Thai fish sauces and their qualitative analyses were carried out by multivariate analyses with the aid of wavelength interval selection method named searching combination moving window partial least squares (SCMWPLS). The optimized informative region for TN selected by SCMWPLS was the region of 2264-2428 nm. A PLS calibration model, which used this region, yielded the lowest root mean square error of prediction (RMSEP) of 0.100% w/v for the PLS factor of 5. This prediction result is significantly better than those obtained by using the whole spectral region or informative regions selected by moving window partial least squares regression (MWPLSR). As for pH, density, refractive index and brix, the 1698-1722, and 2222-2258 nm regions, the 1358-1438 nm region, the 1774-1846, and 2078-2114 nm regions, and the 1322-1442, and 2000-2076 nm regions were selected by SCMWPLS as the optimized regions. The best prediction results were always obtained by use of the optimized regions selected by SCMWPLS. The lowest RMSEP for pH, density, refractive index and brix were 0.170, 0.007 g cm(-3), 0.0079 and 0.435 degrees Brix, respectively. Qualitative models were developed by using four supervised pattern recognitions, linear discriminant analysis (LDA), factor analysis-linear discriminant analysis (FA-LDA), soft independent modeling of class analog (SIMCA), and K neareat neighbors (KNN) for the optimized combination of informative regions of the NIR spectra of fish sauces to classify fish sauces into three groups based on TN. All the developed models can potentially classify the fish sauces with the correct classification rate of more than 82%, and the KNN classified model has the highest correct classification rate (95%). The present study has demonstrated that NIR spectroscopy combined with SCMWPLS is powerful for both the quantitative and qualitative analyses of Thai fish sauces.