Tetsuya Araki

Gas chromatography/olfactometry and electronic nose analyses of retronasal aroma of espresso and correlation with sensory evaluation by an artificial neural network.

To develop a method for evaluating and designing the retronasal aroma of espresso, sensory evaluation data was correlated with data obtained from gas chromatography/olfactometry (GC/O, CharmAnalysis™) and from an electronic nose system αFOX4000 (E-nose). The volatile compounds of various kinds of espresso (arabica coffee beans from 6 production countries: Brazil, Ethiopia, Guatemala, Colombia, Indonesia, and Tanzania; 3 roasting degrees for each country: L values, 18, 23, and 26) were collected with a retronasal aroma simulator (RAS) and examined by GC/O and E-nose. In addition, sensory descriptive analysis using a 7-point scale for RAS effluent gas was performed by 5 trained flavorists using sensory descriptors selected based on the frequency in use and coefficient of correlation. The charm values of 10 odor descriptions obtained from GC/O analysis exhibited the significant (P < 0.05) differences among both roasting degrees and origins. Also, linear discriminant analysis (LDA) on the E-nose-sensor resistances and factor analysis on the sensory evaluation scores showed that the differences of aroma characteristics among the roasting degrees were larger than those among the origins. Based on an artificial neural network (ANN) model applied to the data from GC/O analyses and sensory evaluations, the perceptual factor of the RAS aroma was predicted to be mainly affected by sweet-caramel, smoke-roast, and acidic odors. Also, 3 metal oxide semiconductor sensors (LY2/Gh, P30/1, and T40/1) of E-nose were selected for analyses of RAS aroma and correlated with the sensory descriptive scores by the ANN to support sensory evaluation.

Visualization of Gluten and Starch Distributions in Dough by Fluorescence Fingerprint Imaging

A novel method combining imaging techniques and fluorescence fingerprint (FF) data measurement was developed to visualize the distributions of gluten and starch in dough without any preprocessing. Fluorescence images of thin sections of gluten, starch, and dough were acquired under 63 different combinations of excitation and emission wavelengths, resulting in a set of data consisting of the FF data for each pixel. Cosine similarity values between the FF of each pixel in the dough and those of gluten and starch were calculated. Each pixel was colored according to the cosine similarity value to obtain a pseudo-color image showing the distributions of gluten and starch. The dough sample was then fluorescently stained for gluten and starch. The stained image showed patterns similar to the pseudo-color FF image, validating the effectiveness of the FF imaging method. The method proved to be a powerful visualization tool, applicable in fields other than food technology.

Development of a Quantitative Visualization Technique for Gluten in Dough Using Fluorescence Fingerprint Imaging

The distribution of constituents in food affects its end qualities such as texture, and there is a growing demand to develop a method for studying this distribution easily, accurately, and nondestructively. The objective of this study was to develop an imaging method that visualizes the precise quantity of constituents, using the fluorescence fingerprint (FF). The FF is a set of fluorescence spectra acquired at consecutive excitation wavelengths, and its pattern contains abundant information on the constituents of the sample measured. In this study, the target for visualization was the distribution of gluten in dough samples. Dough samples were prepared with different ratios of gluten, starch, and water, and fluorescence images at multiple combinations of excitation and emission wavelengths were acquired. The fluorescence intensities of a pixel at these different wavelengths constructed its FF, reflecting the constituents of the corresponding point in the sample. A partial least squares regression (PLSR) model was built using the average FFs of the samples and the corresponding gluten ratios as the explanatory and objective variables, respectively. The importance of each wavelength in the PLSR model was assessed using the selectivity ratio, and optimum wavelengths for the accurate prediction of gluten ratio were selected. Finally, the gluten ratio of each pixel was predicted with the PLSR model using the selected wavelengths, and each pixel was colored according to the predicted gluten ratio. The imaging method developed enables the distribution of constituents to be visualized with colors corresponding to their actual quantities or ratios.

Characteristic coloring curve for white bread during baking.

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.

Changes in the Texture and Viscoelastic Properties of Bread Containing Rice Porridge during Storage

The objective of this study was to investigate the effects of rice porridge on the texture and viscoelastic properties of bread during storage. Three types of bread, wheat flour bread, 15% rice flour bread, and 15% rice porridge bread, were prepared. After baking and storing the bread for 24 h, 48 h, and 72 h at room temperature, we measured the texture and viscoelastic properties of the bread crumbs by texture profile analysis (TPA) and creep test. The 15% rice porridge bread showed a significantly higher specific volume and maintained softer crumbs than the other two types (p<0.05). It also had a slightly stickier texture than the others. It can be concluded that rice porridge improves the specific volume, texture, and viscoelastic properties of bread crumbs during storage.

A PTR-MS-Based Protocol for Simulating Bread Aroma During Mastication

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: 2.5xa0g of bread sample, 250xa0mL of buffer, 1xa0L/min of N2 gas stream, 350xa0rpm of rotating speed, and 38xa0°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.

Development of a Novel Staining Procedure for Visualizing the Gluten–Starch Matrix in Bread Dough and Cereal Products

ABSTRACT A novel staining procedure has been developed to visualize the gluten– starch matrix in wheat flour dough. Dough samples mixed to the final stage were stained with 26 fluorescent reagents, and each stained sample was observed with three sets of fluorescence filters (blue, green, and red). Of all the combinations of reagents and filters, the combination of acid magenta and the blue fluorescent filter set was the most effective in distinguishing starch granules from gluten network structure. Its effectiveness was further demonstrated with gluten and starch granule samples, in which the contrast was clearer when observed with the blue fluorescent filter set than without any fluorescent filter. Visualizing the gluten–starch matrix in dough samples at four mixing stages with the same procedure resulted in clear identification of the changes in gluten network structure because of the differences in mixing stages. The same procedure also enabled us to distinguish starch from gluten in white salted noodl...

Package Design of Ready-to-Drink Coffee Beverages Based on Food Kansei Model—Effects of Straw and Cognition Terms on Consumer’s Pleasantness

To design a consumer-oriented package that complements the taste and aroma of ready-to-drink chilled-cup coffee beverages by using the food kansei model, the effects of the diameter and the color of drinking straws as well as the cognition terms of coffee on consumer sensory characteristics and preferences were investigated. Variance and factor analyses of the sensory scores for chilled-cup coffee with milk and sugar using straws of different diameters, as rated by consumer panelists, extracted two perceived factors (F1, contribution ratio 36.5%, and F2, 28.6%). A two-dimensional plot of the average F1 and F2 scores of 123 panelists showed that the perceived characteristics of the same taste and aroma varied according to the straw diameter. An image investigation of different straw colors and another sensory evaluation using “black,” “brown,” and “green” straws were also performed. A principal component analysis of the image data revealed that the sensory characteristics of coffee with milk and sugar were imaged from the straw color. The second evaluation suggested that the images of straw colors affected the sensory characteristics. In addition, cluster and multiple-comparison analyses of Internet research data from consumers regarding the cognition terms for coffee exhibited three clusters representing the cognitive characteristics of terms by consumers and by developers and the differences of attractiveness degree on the cognition terms due to the consumers’ personal attributes. These studies provide useful information for the development of packages of chilled-cup coffee beverages.

Image Analysis of Bread Crumb Structure in Relation to Mechanical Properties

Abstract To correlate the mechanical properties with the crumb structure of bread, a simple and objective method of measuring air bubbles of crumb samples was developed using an image scanner and digital image processing. Four images of the sample scanned in four orthogonal directions were aligned and combined to obtain an enhanced image in which air bubble regions were emphasized by min-operation, selecting the minimum gray level among the four images for each pixel. Next, Otsu’s method was applied to threshold each sub-image of the enhanced image in order to quantify the geometries of the air bubbles precisely, and then the black regions of the image were found to be air-bubbles. As a result, the four air-bubble parameters of the bread samples were determined to be mean bubble area, mean bubble perimeter, number of bubbles, and bubble area ratio. In addition, the viscoelastic properties of the samples were measured by the creep test and determined to significantly correlate with the bubble area ratio (r > 0.59, p < 0.05). This indicates that with increasing air-bubble area, crumb hardness increases. The proposed method is inexpensive and easy to operate, and thus is considered to be applicable to the quality assessment in food factories.

Visualization and quantification of three-dimensional distribution of yeast in bread dough.

A three-dimensional (3-D) bio-imaging technique was developed for visualizing and quantifying the 3-D distribution of yeast in frozen bread dough samples in accordance with the progress of the mixing process of the samples, applying cell-surface engineering to the surfaces of the yeast cells. The fluorescent yeast was recognized as bright spots at the wavelength of 520 nm. Frozen dough samples were sliced at intervals of 1 μm by an micro-slicer image processing system (MSIPS) equipped with a fluorescence microscope for acquiring cross-sectional images of the samples. A set of successive two-dimensional images was reconstructed to analyze the 3-D distribution of the yeast. The average shortest distance between centroids of enhanced green fluorescent protein (EGFP) yeasts was 10.7 μm at the pick-up stage, 9.7 μm at the clean-up stage, 9.0 μm at the final stage, and 10.2 μm at the over-mixing stage. The results indicated that the distribution of the yeast cells was the most uniform in the dough of white bread at the final stage, while the heterogeneous distribution at the over-mixing stage was possibly due to the destruction of the gluten network structure within the samples.