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Kono S.,Mayekawa Manufacturing Co. | Kawamura I.,Mayekawa Manufacturing Co. | Araki T.,University of Tokyo | Sagara Y.,Food Kansei Communications Corporation
International Journal of Refrigeration | Year: 2016

The optimum frozen condition of cooked rice has been predicted by artificial neural network (ANN) based on the data obtained from sensory evaluations as well as viscoelastic measurements. Cooked rice was frozen and stored at -5, -15, and -45 °C for 0, 10, 30, 60 and 90 days. Then, after the samples were thawed by natural convection air at room temperature or microwave heating, the viscoelastic parameters were measured with the Tensipresser and sensory scores were evaluated by a 7-point scale. The sensory scores were predicted with high accuracy from the viscoelastic parameters by ANN models. In addition, the ANN model analysis using the dataset of storage conditions and palatability scores showed that to achieve palatability score greater than the central value of 4.0 after 40 days, storage temperature must be below -25°C if air thawing by natural convection is used and below -15 °C if microwave thawing and heating are used. © 2016 Elsevier Ltd and International Institute of Refrigeration. All rights reserved. Source


Do G.,Nihon University | Araki T.,University of Tokyo | Bae Y.,Sunchon National University | Ishikura K.,Mayekawa Manufacturing Co. | Sagara Y.,Food Kansei Communications Corporation
Drying Technology | Year: 2015

A novel technique was developed to recognize ice crystals in biological materials and to analyze their three-dimensional morphology using a Cryogenic Micro-Slicer Spectral Imaging System with a micro-slicer unit and a near-infrared spectral imaging unit. Consecutive cross-sections of a frozen sample were exposed by the multi-slicing operations with a minimum thickness of 1 µm, and their images were taken by the imaging unit. Spectroscopic analysis using a near-infrared spectrum meter showed an absorption peak at 1460 nm for pure water. Based on the observations of the absorption band of ice crystals in the wavelength range of 1450–1570 nm and its peak at 1495 nm, a commodity-type bandpass filter with a central wavelength of 1500 nm was adopted to identify ice crystals in near-infrared images. The absorption peak of water exhibited a tendency to move toward longer wavelengths with decreasing sample temperature from 25 °C to −15 °C. The filtered images of ice crystals in frozen samples were darker than the other components at the peak wavelength of ice crystals. The three-dimensional reconstructed morphology of ice crystals revealed that they were formed along the direction of heat transfer while freezing. The proposed method provides a novel tool to investigate the effects of freezing conditions on the size, morphology and distribution of ice crystals. © 2015, Copyright © Taylor & Francis Group, LLC. Source


Kono S.,Mayekawa Manufacturing Co. | Kawamura I.,Mayekawa Manufacturing Co. | Yamagami S.,Mayekawa Manufacturing Co. | Araki T.,University of Tokyo | Sagara Y.,Food Kansei Communications Corporation
International Journal of Refrigeration | Year: 2015

Optimum temperature conditions of frozen cooked rice during storage have been predicted by artificial neural network (ANN) using the dataset of ice crystal measurement and sensory evaluation. Cooked rice samples were frozen and preserved at -5, -15, -30, and -45°C for 1, 5, 10, 30 and 90 days. Then the cross-sectional images of the samples were captured using a fluorescence staining method to measure the equivalent diameters of ice crystals in the samples. Textural and sensory attributes of the samples thawed by microwave heating and air at room temperature were evaluated by 690 consumer panelists. The equivalent diameters of ice crystals were highly correlated with the sensory scores of textural attributes and comprehensive palatability. The ANN model analysis revealed that the room temperature thawing required the storage temperature range below -25°C and microwave heating below -15°C to maintain the palatability of the samples for 40 days or more. © 2014 Elsevier Ltd and IIR. All rights reserved. Source


Onishi M.,San Ei Gen F.F.I. Inc. | Inoue M.,University of Tokyo | Araki T.,University of Tokyo | Iwabuchi H.,San Ei Gen F.F.I. Inc. | Sagara Y.,Food Kansei Communications Corporation
Food and Bioprocess Technology | Year: 2012

The sampling parameters to simulate retronasal aroma during the mastication of white bread has been optimized using a retronasal aroma simulator (RAS) to compare the retronasal bread aroma with the conventional headspace aroma. The volatile composition in breath was compared with that in the effluent from a RAS using proton transfer reaction mass spectrometry, and the optimized RAS parameters were as follows: 2. 5 g of bread sample, 250 mL of buffer, 1 L/min of N 2 gas stream, 350 rpm of rotating speed, and 38 °C of water jacket temperature. The increased sensitivity and high reproducibility of RAS enabled detailed measurements of flavor release in the mouth during the mastication of bread. The simulated retronasal aroma was compared with the conventional headspace aromas by gas chromatography/olfactometry (GC/O), and the results demonstrated that the caramel note odorant of 2,5-dimethyl-4-hydroxy-3(2H)-furanone was found to show the highest contribution to the headspace aroma; however, it showed little contribution to the simulated retronasal aroma. These differences appeared to be caused by the volume of buffer added in RAS experiments. The odorant concentrations in the RAS effluent were found to decrease with the increase of the buffer volume, and the decreasing rates appeared to be associated with the chemical types of odorants. Flavor release of typical odorants in a RAS was measured at various ratios of buffer volume, and the results indicated that flavor release in mouth appeared to be influenced by the physicochemical properties of odorants. The results would help flavor chemists to make better prediction of bread aroma in mouth during the mastication. © 2010 Springer Science + Business Media, LLC. Source


Onishi M.,San Ei Gen F.F.I. Inc. | Inoue M.,University of Tokyo | Araki T.,University of Tokyo | Iwabuchi H.,San Ei Gen F.F.I. Inc. | Sagara Y.,Food Kansei Communications Corporation
Bioscience, Biotechnology and Biochemistry | Year: 2011

The effect of heating conditions on the crust color formation was investigated during the baking of white bread. The surface temperatures were monitored with thermocouples attached to the inside surface of the loaf pan cover. The trace of the surface color in the L*a*b* color coordinate system is defined as the characteristic coloring curve. The overall baking process was classified into the following four stages based on the characteristic coloring curve: i) pre-heating (surface temperature < 110 °C), ii) Maillard reaction (110-150 °C), iii) caramelization (150-200 °C), and iv) over-baking (surface temperature > 200 °C). A linear relationship was observed between the L* decrease and the increase in weight loss of a sample at each oven air temperature. The L* value appeared to be suitable as an indicator to control the surface color by baking conditions. Source

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