Existence of circadian rhythm and its response behavior under different storage conditions of soybean sprouts.

The circadian system plays an essential role in plant cells, and numerous physiological events are generally modulated by circadian clock genes. To further improve postharvest handling of fresh produce, it is vital to understanding the behavior of clock gene expression and its underlying interactions with changes in quality. In this study, the effect of temperature and controlled atmosphere storage on the expression of clock genes (GmLCL1, GmPRR7, GmGI, GmTOC1, and GmLUX), postharvest quality characteristics and their related genes in soybean sprouts were investigated. By fitting the obtained gene expression level using the qPCR method with the cosine curve equation, it was successfully found that the circadian rhythm existed under constant dark storage conditions of soybean sprouts. A significant rhythm in clock gene expression was observed in control soybean sprouts. In contrast, low temperature storage diminished the cyclic expression of GmLCL1, GmPRR7, and GmTOC1, which also affected GmGI and GmLUX expression. Additionally, high CO2 concentrations during storage disturbed the circadian clock by affecting the phase and amplitude of each gene; for low O2 concentrations, it was only affected by amplitude. Interestingly, low temperature, low O2, and high CO2 maintained postharvest quality, including reduced respiration, weight loss and browning incidence. The expression behaviors of postharvest quality attribute-related genes (GmFUM1, GmCS, Gm2-OGDH, GmPPO1, GmPAL) were also influenced by the storage treatments. Overall, the findings first suggest a possible link between clock disruption and postharvest quality maintenance of soybean sprouts.

Estimation of komatsuna freshness using visible and near-infrared spectroscopy based on the interpretation of NMR metabolomics analysis.

The objective of this study was to explore the potentiality and mechanism of visible and near-infrared (Vis-NIR) spectroscopy in estimating the freshness of komatsuna. We monitored the cumulative CO2 production of komatsuna stored under different conditions as a freshness indicator and measured the Vis-NIR spectra of komatsuna as the predictor. Using the informative wavelengths (IW) selected using the stepwise selectivity ratio method, we constructed an accurate freshness prediction model through PLSR analysis. The IW in the visible region were attributed to pigments such as chlorophyll. In the NIR region, ten amino acids were identified as directly or indirectly contributing to the IW and were highly related to freshness. They were confirmed on the basis of the strong correlations between the informative NIR signals and NMR signals, which were determined using statistical heterospectroscopy. The results demonstrate the feasibility of Vis-NIR spectroscopy in estimating the freshness of komatsuna using the IW.

Estimating the sensory qualities of tomatoes using visible and near-infrared spectroscopy and interpretation based on gas chromatography-mass spectrometry metabolomics.

The ability to estimate the sensory quality of intact tomatoes rapidly and non-destructively using visible and near-infrared spectroscopy (Vis-NIRS) is important for the tomato industry. In this study, a combination of partial least squares regression (PLSR) analysis and the stepwise selectivity ratio (SWSR) method was used to study the ability of Vis-NIRS to predict 19 sensory attributes in intact tomatoes. The PLSR models constructed based on the informative wavelengths selected by the SWSR method predicted 8 sensory attributes well, particularly the sweetness attribute (correlation coefficient of validation of 0.92). Moreover, based on the tomato metabolites determined by GC-MS analysis, high intercorrelations between sensory attributes, metabolites, and the selected informative wavelengths were found through principal component analysis, as well as the high correlation coefficients between them. The results confirm the feasibility and reliability of Vis-NIRS and the informative wavelengths selected by SWSR to predict the sensory quality of whole tomatoes.

Identification of a freshness marker metabolite in stored soybean sprouts by comprehensive mass-spectrometric analysis of carbonyl compounds.

The objective of this study was to identify metabolites that quantitatively indicate degrees of freshness of soybean sprouts. Self-cultivated soybean sprouts were stored at 5 °C, 10 °C or 20 °C, and respiratory CO2 production rates were monitored using gas chromatography during storage. Carbonyl compounds (CCs) were analyzed comprehensively using mass-spectroscopic metabolomics analyses. CCs were derivatized using dansyl hydrazine (DH) and were then analyzed using high performance liquid chromatography-electrospray ionization tandem mass spectrometry (HPLC-MS/MS) with multiplexed multiple reaction monitoring (MRM). In the MRM chromatogram, 171 to 358 peaks were observed from stored soybean sprouts. Principle component analysis and discriminant analysis (PCA-DA) selected the CC-DH derivative ion with a m/z 512 at a retention time of 9.34 min as the most significant metabolite. Searching online metabolomics databases and matching fragment patterns of product ion mass spectra of an authentic standard revealed abscisic acid is a freshness marker of soybean sprouts.

Simultaneous estimation of scavenging capacities of peach extract for multiple reactive oxygen species by fluorescence fingerprint method.

In this study, the potential of using fluorescence fingerprint, also known as fluorescence excitation-emission matrix, for estimating the scavenging capacity of peach extract on reactive oxygen species (ROS) was investigated. Samples from each of the five cultivars (Asama Hakuto, Hakuho, Kawanakajima Hakuto, Natsukko and Ougonto) were freeze-dried and crushed. The scavenging capacities of peach extracts for the target ROS (hydroxyl, superoxide, alkoxyl radicals and singlet oxygen) were measured by electron paramagnetic resonance spin trapping method. Fluorescence fingerprints of the same samples were obtained. Partial least squares regression analysis was carried out to develop prediction models for ROS scavenging capacity. The models were assessed by external validation. Fluorescence fingerprint was found to accurately estimate the scavenging capacity for the alkoxyl and superoxide radicals with the prediction error of 0.06mmoltroloxeq./mL and 0.31mmolα-lipoicacideq./mL with a coefficient of determination of prediction (R2P) of 0.78 and 0.91, respectively.

Fluorescence fingerprint as an instrumental assessment of the sensory quality of tomato juices.

BACKGROUND: Sensory analysis is an important standard for evaluating food products. However, as trained panelists and time are required for the process, the potential of using fluorescence fingerprint as a rapid instrumental method to approximate sensory characteristics was explored in this study. RESULTS: Thirty-five out of 44 descriptive sensory attributes were found to show a significant difference between samples (analysis of variance test). Principal component analysis revealed that principal component 1 could capture 73.84 and 75.28% variance for aroma category and combined flavor and taste category respectively. Fluorescence fingerprints of tomato juices consisted of two visible peaks at excitation/emission wavelengths of 290/350 and 315/425 nm and a long narrow emission peak at 680 nm. The 680 nm peak was only clearly observed in juices obtained from tomatoes cultivated to be eaten raw. The ability to predict overall sensory profiles was investigated by using principal component 1 as a regression target. Fluorescence fingerprint could predict principal component 1 of both aroma and combined flavor and taste with a coefficient of determination above 0.8. CONCLUSION: The results obtained in this study indicate the potential of using fluorescence fingerprint as an instrumental method for assessing sensory characteristics of tomato juices.

Freshness estimation of intact frozen fish using fluorescence spectroscopy and chemometrics of excitation-emission matrix.

The current study attempted to provide a convenient, non-invasive and time-saving method to estimate the freshness of intact horse mackerel (Trachurus japonicus) fish in a frozen state using autofluorescence spectroscopy in tandem with multivariate analysis of fluorescence excitation-emission matrices (EEM). The extracted fluorescence data from different freshness conditions were pretreated, masked and reorganized to resolve fish fluorescence spectra from overlapping signals and scattering profiles for detecting and characterizing freshness changes. The real freshness values of the examined fish samples were then traditionally determined by the hard chemical analysis using the high performance liquid chromatography (HPLC) method and expressed as K-values. The fluorescence EEM data and the real freshness values were modeled using partial least square (PLS) regression and a novel algorithm was proposed to identify the ideal combinations of excitation and emission wavelengths being used as perfect predictors. The results revealed that freshness of frozen fish could be accurately predicted with R(2) of 0.89 and root mean square error estimated by cross validation (RMSECV) of 9.66%. This work substantially demonstrated that the autofluorescence spectroscopy associated with the proposed technical approaches has a high potential in non-destructive sensing of fish freshness in the frozen state.

Method of determining the optimal dilution ratio for fluorescence fingerprint of food constituents.

Quantitative determination by fluorescence spectroscopy is possible because of the linear relationship between the intensity of emitted fluorescence and the fluorophore concentration. However, concentration quenching may cause the relationship to become nonlinear, and thus, the optimal dilution ratio has to be determined. In the case of fluorescence fingerprint (FF) measurement, fluorescence is measured under multiple wavelength conditions and a method of determining the optimal dilution ratio for multivariate data such as FFs has not been reported. In this study, the FFs of mixed solutions of tryptophan and epicatechin of different concentrations and composition ratios were measured. Principal component analysis was applied, and the resulting loading plots were found to contain useful information about each constituent. The optimal concentration ranges could be determined by identifying the linear region of the PC score plotted against total concentration.

Optimization of excitation-emission band-pass filter for visualization of viable bacteria distribution on the surface of pork meat.

A novel method of optically reducing the dimensionality of an excitation-emission matrix (EEM) by optimizing the excitation and emission band-pass filters was proposed and applied to the visualization of viable bacteria on pork. Filters were designed theoretically using an EEM data set for evaluating colony-forming units on pork samples assuming signal-to-noise ratios of 100, 316, or 1000. These filters were evaluated using newly measured EEM images. The filters designed for S/N = 100 performed the best and allowed the visualization of viable bacteria distributions. The proposed method is expected to be a breakthrough in the application of EEM imaging.

Supercontinuum laser based optical characterization of Intralipid® phantoms in the 500-2250 nm range.

A supercontinuum laser based double integrating sphere setup in combination with an unscattered transmittance measurement setup was developed and carefully validated for optical characterization of turbid samples in the 500-2250 nm wavelength range. A set of 57 liquid optical phantoms, covering a wide range of absorption and scattering properties, were prepared and measured at two sample thicknesses. The estimated bulk optical properties matched well for both thicknesses, and with theory and literature, without significant crosstalk between absorption and scattering. Equations were derived for the bulk scattering properties µ(s), µ(s)' and g of Intralipid® 20% which can be used to calculate the bulk scattering properties of intralipid-dilutions in the 500-2250 nm range.

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.

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.

The potential of spatially resolved spectroscopy for monitoring angiogenesis in the chorioallantoic membrane.

Over the last decade, the poultry sector has sought to develop ways to monitor chicken embryonic development as to optimize the incubation conditions. One of the parameters of development which may change under different incubation conditions is the angiogenesis in the chorioallantoic membrane (CAM). To be able to quantify these changes in the angiogenesis and detect long-term effects on health, a non-destructive technique is necessary. In this article, the first steps toward such a non-destructive technique are successfully taken. A spatially resolved spectroscopy set-up is built and tested for its potential to measure changes in angiogenesis with incubation time, and differences between a normal and hypercapnic incubation. In this first study, reflectance measurements are performed directly on the CAM as the eggshell considerably complicates the analysis. This issue should be addressed in future research to come to a really non-destructive technique. An experiment was conducted in which one group was incubated under normal conditions, and another under early prenatal hypercapnic conditions (i.e., increased CO(2) concentrations). The angiogenesis in the CAM was measured at embryonic day (ED) 10, 13, and 16. The measurements showed a clear blood spectrum with an increasing amount of blood in time, and significant differences in the reflectance as function of the source-detector distances. However, no significant differences between the hypercapnia and the control group could be detected.

Predicting the buckwheat flour ratio for commercial dried buckwheat noodles based on the fluorescence fingerprint.

A rapid method for predicting the buckwheat flour ratio of dried buckwheat noodles was developed by using the fluorescence fingerprint and partial least squares regression. Fitting the calibration model to validation datasets showed R(2)=0.78 and SEP=12.4%. The model was refined for a better fit by deleting several samples containing additional ingredients. The best fit was finally obtained (R(2)=0.84 and SEP=10.4%) by deleting the samples containing vinegar, green tea, seaweed, polysaccharide thickener, and yam. This result demonstrates that a calibration model with high accuracy could be constructed based on samples similar in material composition. The developed methodology requires no complex preprocessing, enables rapid measurement with a small sample amount, and would thus be suitable for practical application to the food industry.

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 microm 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 microm at the pick-up stage, 9.7 microm at the clean-up stage, 9.0 microm at the final stage, and 10.2 microm 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.

Near-infrared imaging spectroscopy based on sugar absorption band for melons.

A method for visualizing the sugar content in the flesh of melons was developed. This method was based on the sugar absorption band in the near-infrared (NIR) region to avoid bias caused by the color information of a sample. NIR spectroscopic analysis revealed that each of the two second-derivative absorbances at 874 and 902 nm had a high correlation with the sugar content of melons. A high-resolution cooled charged couple device camera with band-pass filters, which included the above two wavelengths, was used to capture the spectral absorption image of a half-cut melon. A color distribution map of the sugar content on the surface of the melon was constructed by applying the NIR spectroscopy theory to each pixel of the acquired images.