109 results on '"Yoshio Makino"'
Search Results
2. Nondestructive Detection of Decay in Vegetable Soybeans Stored at Different Temperatures Using Chlorophyll Fluorescence Imaging
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Zheng-Nan Duan, Masatoshi Yoshimura, Yu Li, Itaru Sotome, and Yoshio Makino
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Chromatography ,Chemistry ,Plant Science ,Ascorbic acid ,Agronomy and Crop Science ,Chlorophyll fluorescence - Published
- 2020
3. Early Detection of Anthracnose Infection on Mango Fruit Using Hyperspectral Imaging Coupled with Symptom Distribution Mapping
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Ubonrat Siripatrawan and Yoshio Makino
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- 2022
4. Evaluation of storage time and temperature on physicochemical properties of immersion vacuum cooled sausages stuffed in the innovative casings modified by surfactants and lactic acid
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Chao-Hui Feng, Wei Wang, Juan Francisco García-Martín, Yoshio Makino, Xiao-Yan Song, and Paloma Álvarez-Mateos
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chemistry.chemical_compound ,Materials science ,Moisture ,chemistry ,Vacuum cooling ,Immersion (virtual reality) ,Composition (visual arts) ,Texture (crystalline) ,Composite material ,Food Science ,Lactic acid - Abstract
The combined effects of different storage temperatures (0, 4, 10 °C) and days (3, 8, 16, 25, 35, 46 and 58 days), and the use of modified casings on sausages cooled by immersion vacuum cooling (IVC) were investigated. Sausages were firstly cooked at 72 °C and cooled to 4 °C by IVC. Texture profile, colour, pH, moisture and volatile composition of samples were measured during 58-d storage. Hardness of samples with modified casings stored at 4 °C (MIVC-4 oC) at d8 (75.28 ± 6.05 N) was significantly higher than that at d3 (38.09 ± 8.89 N) (P
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- 2019
5. Influence of Cold or Frozen Storage on Temporal Changes in Sulforaphane and Objective Taste Values of Broccoli (Brassica oleracea var. italica) Florets
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Kenji Okazaki, Surina Boerzhijin, Takeshi Yamada, Yoshio Makino, Masaru Hashizume, and Takashi Akihiro
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Brassica oleracea var italica ,chemistry.chemical_compound ,Horticulture ,Taste ,chemistry ,Cruciferous vegetables ,Postharvest ,Plant Science ,Frozen storage ,Agronomy and Crop Science ,Sulforaphane - Published
- 2019
6. Real-time nondestructive monitoring of Common Carp Fish freshness using robust vision-based intelligent modeling approaches
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Yoshio Makino, Ashkan Banan, Amin Taheri-Garavand, and Soodabeh Fatahi
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0106 biological sciences ,Artificial neural network ,Vision based ,business.industry ,Computer science ,Feature extraction ,Forestry ,Feature selection ,Pattern recognition ,04 agricultural and veterinary sciences ,Horticulture ,01 natural sciences ,Computer Science Applications ,Support vector machine ,Common carp ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Artificial intelligence ,business ,Agronomy and Crop Science ,Classifier (UML) ,010606 plant biology & botany ,Communication channel - Abstract
In the current research, the potential of a novel method based on the artificial neural network was investigated to diagnose the freshness of common carp (Cyprinus carpio) during ice storage. Fish as an aquaculture product has high nutrients and low-fat content. So, people have consumed it as a safe and high-value foodstuff in their daily diet. Investigation of fish freshness is proposed as a significant issue in the aquaculture industry since fish spoils rapidly. The applied system of this study is comprised of the following steps: First, images of samples were captured and the pre-processing operation was done on the images. Then, particular channels including R, G, B, H, S, I, L*, a*, and b* were computed. Next, feature extraction was performed to obtain 6 types of texture features from each channel. Afterward, the hybrid Artificial Bee Colony-Artificial Neural Network (ABC-ANN) algorithm was applied to select the best features. Finally, the Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) and Artificial Neural Network (ANN) algorithms as the most common methods were used to classify fish images. The best performance of the K-NN classifier was calculated in the k = 8 neighborhood size with the accuracy of 90.48. The best kernel function for the SVM algorithm was polynomial with C, sigma, and accuracy of 1, 2 and 91.52 percent, respectively. In this system, the input layer has consisted of 22 neurons based on the feature selection operation and 4 classes including most fresh, fresh, fairly fresh and spoiled have been used as the number of output layer. At the end, the best results of the MLP networks were achieved by LM learning algorithm and 6 neurons in the hidden layer with the 22–10–4 topology and accuracy of 93.01 percent. The achieved results demonstrate the high performance of the ANN classifier for evaluation of common carp freshness during ice storage as a rapid, accurate, non-destructive, real-time and automated method. It shows the potential of computer vision method in combination with artificial neural networks as an intelligent technique for evaluation of fish freshness.
- Published
- 2019
7. Effect of the storage atmosphere on metabolomics of harvested tomatoes ( Solanum lycopersicum L.)
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Takeshi Yamada, Surina Boerzhijin, Yoshio Makino, Takashi Akihiro, and Yuma Yokota
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Metabolic state ,environmental gas composition ,principal component analysis ,metabolomics ,modified atmosphere packaging ,tomato ,postharvest storage ,biology ,Chemistry ,lcsh:TX341-641 ,biology.organism_classification ,Anoxic waters ,Atmosphere ,Horticulture ,Metabolomics ,Score plot ,Modified atmosphere ,Composition (visual arts) ,Solanum ,lcsh:Nutrition. Foods and food supply ,Food Science - Abstract
Harvested tomatoes were stored under atmospheres that were normoxic, anoxic, or modified (altered O2 and CO2 concentrations). Each atmosphere was created by storing the tomatoes at 25°C for up to 8 days in different kinds of pouches. During storage, metabolites of the tomatoes were measured using metabolomics. We obtained score plots of the metabolites on eighth day of storage by principal component analysis. There was a tendency for groups to be divided on the basis of score plot according to the composition of each gas. PC1 and PC2 seemed to correspond to the influence of O2 and CO2 concentrations, respectively, and the total contribution rate of the two axes was 72%, so that we concluded that the metabolites were affected mainly by O2 and CO2 concentrations. The results indicate that metabolomics may be an effective tool to reveal the relationship between metabolic state of harvested fruits and the atmosphere.
- Published
- 2019
8. Effect of variable selection algorithms on model performance for predicting moisture content in biological materials using spectral data
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Mohammed Kamruzzaman, Dipsikha Kalita, Md. Toukir Ahmed, Gamal ElMasry, and Yoshio Makino
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Red Meat ,Spectroscopy, Near-Infrared ,Environmental Chemistry ,Least-Squares Analysis ,Zea mays ,Biochemistry ,Algorithms ,Spectroscopy ,Analytical Chemistry - Abstract
Variable selection is a critical step for designing a dedicated multispectral real-time system from multicollinearity spectral data. It improves the prediction ability of the calibration model and provides faster prediction by reducing the curse of dimensionality. The main objective of this study was to compare the effect of variables selection algorithms on model performance for predicting moisture content in red meat using visible and near-infrared (VNIR) hyperspectral imaging in the spectral range of 400-1000 nm and corn using near-infrared (NIR) spectroscopy in the spectral range of 1100-2498 nm. Six variable selection algorithms including the size of the regression coefficient (RC), variable importance in projection (VIP), genetic algorithm (GA), competitive adaptive reweighted sampling (CARS), successive projection algorithm (SPA), and stepwise regression (SWR) were tested and compared to realize their effects on the model performance for predicting moisture content in red meat and corn. The model based on competitive adaptive reweighted sampling-partial least squares regression (CARS-PLSR) was the best model to predict moisture content in red meat and corn. The results indicated the effectiveness of variable selection for providing the feature wavelengths to design a low-cost, real-time multispectral system.
- Published
- 2022
9. Digitization of Broccoli Freshness Integrating External Color and Mass Loss
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Genki Amino and Yoshio Makino
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Health (social science) ,Mass reduction ,Horticultural crops ,Brassica oleracea var. italica ,Plant Science ,Color space ,lcsh:Chemical technology ,Shelf life ,01 natural sciences ,Health Professions (miscellaneous) ,Microbiology ,Article ,computer vision ,Degree (temperature) ,Canonical variable ,statistical analysis ,image analysis ,Statistics ,vegetable ,lcsh:TP1-1185 ,040502 food science ,Mathematics ,evaluation ,010401 analytical chemistry ,04 agricultural and veterinary sciences ,Linear discriminant analysis ,0104 chemical sciences ,machine learning ,shelf life ,0405 other agricultural sciences ,Period length ,Food Science - Abstract
Yellowing of green vegetables due to chlorophyll decomposition is a phenomenon indicating serious deterioration of freshness, and it is evaluated by measuring color space values. In contrast, mass reduction due to water loss is a deterioration of freshness observed in all horticultural crops. Therefore, in this study, we propose a novel freshness evaluation index for green vegetables that combines the degree of greenness and mass loss. The green color retention rate was measured using a computer vision system, and the mass retention rate was measured by weighing. Linear discriminant analysis (LDA) was performed using both variables (greenness and mass) as covariates to obtain a single freshness evaluation value (first canonical variable). The correct classification of storage period length by LDA was 96%. Green color retention alone allowed for classification of storage durations between 0 day and 10 days, whereas LDA could classify storage durations between 0 day and 12 days. The novel freshness evaluation index proposed by this research, which integrates greenness and mass, has been shown to be more accurate than the conventional evaluation index that uses only greenness.
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- 2020
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10. Hyperspectral Imaging Coupled with Multivariate Analysis and Image Processing for Detection and Visualisation of Colour in Cooked Sausages Stuffed in Different Modified Casings
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Juan F. Martín, Yoshio Makino, Chao-Hui Feng, and Universidad de Sevilla. Departamento de Ingeniería Química
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Lightness ,Health (social science) ,Casings ,Image processing ,Plant Science ,lcsh:Chemical technology ,01 natural sciences ,Health Professions (miscellaneous) ,Microbiology ,Article ,chemistry.chemical_compound ,core colour ,0404 agricultural biotechnology ,Partial least squares regression ,lcsh:TP1-1185 ,Food science ,casings ,Core colour ,Canonical discriminant analysis ,SOY LECITHIN ,Chemistry ,010401 analytical chemistry ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,discriminant analysis ,040401 food science ,Discriminant analysis ,0104 chemical sciences ,Lactic acid ,Sausages ,Distilled water ,sausages ,Food Science - Abstract
A hyperspectral imaging system was for the first time exploited to estimate the core colour of sausages stuffed in natural hog casings or in two hog casings treated with solutions containing surfactants and lactic acid in slush salt. Yellowness of sausages stuffed in natural hog casings (control group, 20.26 ±, 4.81) was significantly higher than that of sausages stuffed in casings modified by submersion for 90 min in a solution containing 1:30 (w/w) soy lecithin:distilled water, 2.5% wt. soy oil, and 21 mL lactic acid per kg NaCl (17.66 ±, 2.89) (p <, 0.05). When predicting the lightness and redness of the sausage core, a partial least squares regression model developed from spectra pre-treated with a second derivative showed calibration coefficients of determination (Rc2) of 0.73 and 0.76, respectively. Ten, ten, and seven wavelengths were selected as the important optimal wavelengths for lightness, redness, and yellowness, respectively. Those wavelengths provide meaningful information for developing a simple, cost-effective multispectral system to rapidly differentiate sausages based on their core colour. According to the canonical discriminant analysis, lightness possessed the highest discriminant power with which to differentiate sausages stuffed in different casings.
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- 2020
- Full Text
- View/download PDF
11. Prediction of Degreening Velocity of Broccoli Buds Using Hyperspectral Camera Combined with Artificial Neural Networks
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Yumi Kousaka and Yoshio Makino
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spectroscopy ,Health (social science) ,Brassica oleracea var. italica ,Plant Science ,lcsh:Chemical technology ,01 natural sciences ,Health Professions (miscellaneous) ,Microbiology ,Article ,chemistry.chemical_compound ,0404 agricultural biotechnology ,statistical analysis ,vegetable ,chlorophyll ,lcsh:TP1-1185 ,Mathematics ,Second derivative ,Artificial neural network ,nondestructive analysis ,010401 analytical chemistry ,Nondestructive analysis ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,040401 food science ,Reflectivity ,0104 chemical sciences ,Chlorophyll concentration ,chemistry ,Green color ,Chlorophyll ,shelf life ,Biological system ,mathematical model ,Food Science - Abstract
Developing a noninvasive technique to estimate the degreening (loss of green color) velocity of harvested broccoli was attempted. Loss of green color on a harvested broccoli head occurs heterogeneously. Therefore, hyperspectral imaging technique that stores spectral reflectance with spatial information was used in the present research. Using artificial neural networks (ANNs), we demonstrated that the reduction velocity of chlorophyll at a site on a broccoli head was related to the second derivative of spectral reflectance data at 15 wavelengths from 405 to 960 nm. The reduction velocity was predicted using the ANNs model with a correlative coefficient of 0.995 and a standard error of prediction of 5.37 ×, 10&minus, 5 mg·, g&minus, 1·, d&minus, 1. The estimated reduction velocity was effective for predicting the chlorophyll concentration of broccoli buds until 7 d of storage, which was established as the maximum time for maintaining marketability. This technique may be useful for nondestructive prediction of the shelf life of broccoli heads.
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- 2020
12. Induction of Terminal Oxidases of Electron Transport Chain in Broccoli Heads under Controlled Atmosphere Storage
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Ko Noguchi, Masatoshi Yoshimura, Takeshi Yamada, Yoshio Makino, Hsiao-Wen Wang, Sachiko Funayama-Noguchi, Kensaku Maejima, and Jun Inoue
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0106 biological sciences ,Alternative oxidase ,Controlled atmosphere ,Health (social science) ,Sensitive index ,Brassica oleracea var. italica ,Plant Science ,Shelf life ,lcsh:Chemical technology ,01 natural sciences ,Health Professions (miscellaneous) ,Microbiology ,cytochrome c oxidase ,Article ,alternative oxidase ,0404 agricultural biotechnology ,Biological property ,Cytochrome c oxidase ,lcsh:TP1-1185 ,Food science ,biology ,Chemistry ,04 agricultural and veterinary sciences ,biology.organism_classification ,040401 food science ,Electron transport chain ,mass loss ,brassica oleracea var. italica ,oxygen isotope discrimination ,biology.protein ,Brassica oleracea ,010606 plant biology & botany ,Food Science - Abstract
Controlled atmosphere (CA) storage, that is, at low O2 and high CO2 concentrations, effectively extends the shelf life of horticultural products. The influence of CA storage (O2/CO2: 2.5%/6.0% or 2.5%/0.0%) and in normal air (both at 1 °, C for 21 d) on the physicochemical (O2 uptake, mass loss and L-ascorbate) and biological properties of broccoli (Brassica oleracea var. italica, Plenck, 1794) via amounts and activities of terminal oxidases of the electron transport chain was investigated. Mass loss, a sensitive index of freshness for broccoli heads under CA, was significantly lower under CA than under normoxia (p <, 0.05). Mass loss was depressed 7 d earlier under CA, including 6.0% CO2 than under CA without CO2. High CO2 effectively depressed the degradation of L-ascorbate. During storage, the activity of the alternative oxidase (AOX) was lower under CA than in normal air (p <, 0.05), while the amount of cytochrome c oxidase (COX), and the AOX/COX activity ratio (based on oxygen isotope discrimination), were not affected during storage. Our results indicate that CA storage effectively retained the freshness of broccoli heads by depressing the induction of AOX. However, depression of AOX amount was not associated with CO2 around broccoli heads.
- Published
- 2020
13. Efficient preservation of sprouting vegetables under simulated microgravity conditions
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Kanji Ichinose, Yumi Kawahara, Yoshio Makino, Louis Yuge, and Masatoshi Yoshimura
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0106 biological sciences ,Physiology ,Colony Count, Microbial ,Plant Science ,Plant Reproduction ,Plant Tropisms ,01 natural sciences ,Specimen Storage ,Vegetables ,Artificial Gravity ,Plant Growth and Development ,Multidisciplinary ,Moisture ,Chemistry ,Physics ,Eukaryota ,food and beverages ,Agriculture ,04 agricultural and veterinary sciences ,Plants ,Legumes ,040401 food science ,Horticulture ,Simulated microgravity ,Plant Physiology ,Physical Sciences ,Medicine ,Research Article ,Gravitation ,Sprouts ,Gravity (chemistry) ,Beans ,Science ,Germination ,Crops ,Brassica ,Research and Analysis Methods ,Shelf life ,Tropism ,Gravitropism ,0404 agricultural biotechnology ,Food Preservation ,Relative humidity ,Weightlessness Simulation ,Weightlessness ,Significant difference ,Organisms ,Biology and Life Sciences ,Food Storage ,Storage and Handling ,Modified atmosphere ,Food Microbiology ,Radish ,Soybeans ,Organism Development ,Crop Science ,Developmental Biology ,010606 plant biology & botany ,Sprouting - Abstract
The effectiveness of a simulated microgravity environment as a novel method for preserving the freshness of vegetables was investigated. Three types of vegetables were selected: vegetable soybean, mung bean sprouts, and white radish sprouts. These selected vegetables were fixed on a three-dimensional rotary gravity controller, rotated slowly. The selected vegetables were stored at 25°C and 66% of relative humidity for 9, 6, or 5 d while undergoing this process. The simulated microgravity was controlled utilizing a gravity controller around 0 m s−2. The mung bean sprouts stored for 6 d under simulated microgravity conditions maintained higher thickness levels than the vegetable samples stored under normal gravity conditions (9.8 m s−2) for the same duration. The mass of all three items decreased with time without regard to the gravity environment, though the samples stored within the simulated microgravity environment displayed significant mass retention on and after 3 d for mung bean sprout samples and 1 d for white radish sprout samples. In contrast, the mass retention effect was not observed in the vegetable soybean samples. Hence, it was confirmed that the mass retention effect of microgravity was limited to sprout vegetables. As a result of analysis harnessing a mathematical model, assuming that the majority of the mass loss is due to moisture loss, a significant difference in mass reduction coefficient occurs among mung bean sprouts and white radish sprouts due to the microgravity environment, and the mass retention effect of simulated microgravity is quantitatively evaluated utilizing mathematical models. Simulated microgravity, which varies significantly from conventional refrigeration, ethylene control, and modified atmosphere, was demonstrated effective as a novel method for preserving and maintaining the freshness of sprout vegetables. This founding will support long-term space flight missions by prolonging shelf life of sprout vegetables.
- Published
- 2020
14. Estimation of adenosine triphosphate content in ready-to-eat sausages with different storage days, using hyperspectral imaging coupled with R statistics
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Masatoshi Yoshimura, Francisco J. Rodríguez-Pulido, Chao-Hui Feng, and Yoshio Makino
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Chemical imaging ,Time Factors ,Coefficient of determination ,Ready to eat ,01 natural sciences ,Analytical Chemistry ,chemistry.chemical_compound ,Adenosine Triphosphate ,0404 agricultural biotechnology ,Partial least squares regression ,Linear regression ,Statistics ,Least-Squares Analysis ,Mathematics ,010401 analytical chemistry ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,General Medicine ,040401 food science ,0104 chemical sciences ,Meat Products ,chemistry ,Spectrophotometry ,Luminescent Measurements ,Content (measure theory) ,Adenosine triphosphate ,Food Science - Abstract
A hyperspectral imaging (HSI) system (380–1000 nm) was investigated for non-invasively estimating adenosine triphosphate (ATP) content in ready-to-eat sausages during 5 days storage at 35 °C. A set of pretreated combinations were carried out on preprocessing the spectra to improve the performance of partial least squares regression (PLSR). According to the regression coefficient values, ten important wavelengths (385, 390, 395, 505, 580, 670, 745, 780, 855, and 955 nm) were selected in this study. PLSR models developed using full wavelengths and optimal wavelengths showed the prediction coefficient of determination (rp2) up to 0.8324 and 0.8606, respectively. The concentration and location of the ATP content in sausages were for the first time displayed via chemical imaging developed by R statistics. Combining HSI and multivariate analysis can quantify and visualize ATP dynamic changes during storage and a great potential in the processed meat industry for real-time inspection.
- Published
- 2018
15. Maturity prediction of papaya using NIR spectroscopy
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Yohanes Aris Purwanto, Emmy Darmawati, Sutrisno, Yoshio Makino, P.M. Pandjahitan, and Seiichi Oshita
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0106 biological sciences ,Maturity (geology) ,Horticulture ,Near-infrared spectroscopy ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,04 agricultural and veterinary sciences ,Biology ,01 natural sciences ,010606 plant biology & botany - Published
- 2018
16. Hyperspectral imaging and multispectral imaging as the novel techniques for detecting defects in raw and processed meat products: Current state-of-the-art research advances
- Author
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Seiichi Oshita, Juan F. Martín, Yoshio Makino, and Chao-Hui Feng
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Computer science ,business.industry ,Multispectral image ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,040401 food science ,Rapid detection ,0404 agricultural biotechnology ,Non destructive ,Processed meat ,Computer vision ,Artificial intelligence ,Process engineering ,business ,Food Science ,Biotechnology - Abstract
In order to achieve rapid detection of defects and to increase the industrial operating efficiency of products without compromising their quality attributes, hyperspectral imaging (HSI) and multispectral imaging (MSI), as the technologies that simultaneously provides spectral and spatial information of foodstuffs, are now widely applied for inspecting both raw and processed meat items. This review first discusses the principles of HSI and MSI. Recent developments and applications of HSI and MSI directed at the raw and processed meat industry are then discussed. The advantages and disadvantages of hyperspectral imaging and its future prospects are also covered. This review provides a detailed overview of the recent efforts devoted to HSI and MSI technologies for evaluating the quality and safety of different meat products and the probability of its widespread application. Hyperspectral imaging, as a promising tool in developing rapid and non-invasive, is capable to detect defects in raw and processed meat products.
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- 2018
17. Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions
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Juan Francisco García-Martín, Chao-Hui Feng, Yoshio Makino, Masatoshi Yoshimura, and Dang Quoc Thuyet
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Coefficient of determination ,Mean squared error ,010401 analytical chemistry ,Multispectral image ,Hyperspectral imaging ,Image processing ,04 agricultural and veterinary sciences ,040401 food science ,01 natural sciences ,0104 chemical sciences ,Chemometrics ,0404 agricultural biotechnology ,Partial least squares regression ,Statistics ,Linear regression ,Food Science ,Mathematics - Abstract
The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 °C for 1 d, 35 °C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (Rp2) 0.909 and the root mean square error of prediction 0.035. The prediction map for illustrating pH indices in sausages was for the first time developed by R statistics. The overall results suggested that hyperspectral imaging combined with PLSR and R statistics are capable to quantify and visualize the sausages pH evolution under different storage conditions. In this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high Rp2(0.909) and a low root mean square error of prediction (0.035), which can be useful for the design of multispectral imaging systems.
- Published
- 2017
18. Real-time prediction of pre-cooked Japanese sausage color with different storage days using hyperspectral imaging
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Chao-Hui Feng, Masatoshi Yoshimura, Yoshio Makino, and Francisco J. Rodríguez-Pulido
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Nutrition and Dietetics ,Mean squared error ,business.industry ,Calibration (statistics) ,010401 analytical chemistry ,Hyperspectral imaging ,Pattern recognition ,04 agricultural and veterinary sciences ,Real time prediction ,Stepwise regression ,040401 food science ,01 natural sciences ,0104 chemical sciences ,0404 agricultural biotechnology ,Linear regression ,Partial least squares regression ,Computational statistics ,Artificial intelligence ,Food science ,business ,Agronomy and Crop Science ,Food Science ,Biotechnology ,Mathematics - Abstract
Redness can greatly influence the freshness of sausages. A precise, rapid and noncontact analytical method or tool is needed to quantify the color. Hyperspectral imaging (HSI) is an emerging technique that integrates spectroscopy and imaging to obtain the spectral and spatial information simultaneously. In the present study, the redness of cooked sausages stored up to 57 days was predicted using HSI in tandem with multivariate data analysis. The mean spectra of the sausages were extracted from the hyperspectral images. Partial least squares regression (PLSR) and forward stepwise multiple regression (FSMR) models were used to develop the relavent spectral profiles with the redness of the cooked sausages.; Results: Ten important wavelengths were selected based on the regression coefficient values from the PLSR model. The PLSR model established using the full wavelengths presented a good performance, with Rc of 0.934 and a root mean square error of calibration of 0.642 (redness ranged between 14.99 and 21.48). The prediction maps for demonstrating evolution of redness in sausages were developed for the first time using R statistics (R Foundation for Statistical Computing) and Matlab (MathWorks Inc., Natick, MA, USA).; Conclusion: HSI combined with PLSR and FSMR can be used to quantify and visualize evolution of sausage redness under different storage days. © 2017 Society of Chemical Industry.; © 2017 Society of Chemical Industry.
- Published
- 2017
19. Influence of a Modified Atmosphere on the Induction and Activity of Respiratory Enzymes in Broccoli Florets during the Early Stage of Postharvest Storage
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Yoshio Makino, Sachiko Funayama-Noguchi, Hsiao-Wen Wang, Ko Noguchi, Jun Inoue, Takeshi Yamada, and Kensaku Maejima
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0106 biological sciences ,0301 basic medicine ,Controlled atmosphere ,Alternative oxidase ,Brassica ,chemistry.chemical_element ,Oxygen Isotopes ,Shelf life ,01 natural sciences ,Oxygen ,Electron Transport Complex IV ,Mitochondrial Proteins ,03 medical and health sciences ,Oxygen Consumption ,Food Preservation ,Cytochrome c oxidase ,Food science ,Plant Proteins ,biology ,Food Packaging ,General Chemistry ,biology.organism_classification ,030104 developmental biology ,chemistry ,Biochemistry ,Modified atmosphere ,biology.protein ,Postharvest ,Oxidoreductases ,General Agricultural and Biological Sciences ,010606 plant biology & botany - Abstract
Modified atmosphere packaging and controlled atmosphere storage (hypoxia conditions) extend shelf lives of horticultural products by depressing the O2 uptake rate. We investigated the relationship between atmospheres and alternative oxidase (AOX) to cytochrome c oxidase (COX) activities (on the basis of oxygen isotope discrimination) and the relative amounts of two respiratory enzymes, AOX and COX, during the early stage of storage. Broccoli florets, with high O2 uptake rates, were stored under hypoxia and normoxia at 25 °C. O2 uptake rates, weight loss, and yellowing of broccoli florets were significantly lower when stored under hypoxia than when stored under normoxia. Significantly more AOX proteins were produced during storage under normoxia, but COX proteins were more consistent than those of AOX proteins. Hypoxia may depress the expression of AOX and prolong the shelf life. Oxygen isotope discrimination was elevated under hypoxia after 50.5 h. AOX production in broccoli was controlled more by changing atmospheres than by COX.
- Published
- 2017
20. Evaluation of modified casings and chitosan-PVA packaging on the physicochemical properties of cooked Sichuan sausages during long-term storage
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Chao-Hui Feng, Liu Yaowen, Juan F. Martín, Enda Cummins, and Yoshio Makino
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Chitosan ,chemistry.chemical_compound ,SOY LECITHIN ,0404 agricultural biotechnology ,chemistry ,Food spoilage ,04 agricultural and veterinary sciences ,Food science ,Bacterial growth ,040401 food science ,Industrial and Manufacturing Engineering ,Food Science ,Lactic acid - Abstract
Summary The effects of a modified casing and chitosan-poly-vinyl alcohol antimicrobial packaging (CP packaging) on sausage colour, texture, microbial spoilage and volatile compounds after 29-days storage were investigated. Casings were modified by surfactant solution (composed of soy lecithin and soy oil) and lactic acid. For samples stored in CP packaging, there were no significant differences between day 1 and day 29 in relation to sausage hardness and springiness (P > 0.05). Redness increased over storage time regardless of treatments and packagings. Total plate counts of samples packaged by CP packaging were lower than 1 log cfu g−1 during 29-days storage. Cyclohexene, 1-methyl-4-(1-methylethylidene)- and α-copaene were found in samples with control casings and CP packaging after 15-days storage. The improved characteristics of the natural casing will enable meat processors or manufactures to enhance sausage production with a low sausage burst incidence, while the CP packaging will inhibit the intensive microbial growth.
- Published
- 2017
21. Influence of low O
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Yoshio, Makino, Atsushi, Nishizaka, Masatoshi, Yoshimura, Itaru, Sotome, Kenji, Kawai, and Takashi, Akihiro
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Niacinamide ,Alanine ,Time Factors ,Atmosphere ,Food Packaging ,Color ,Carbon Dioxide ,Oxygen ,Food Storage ,Multivariate Analysis ,Seeds ,Vegetables ,Cluster Analysis ,Metabolomics ,Micronutrients ,Soybeans ,Inositol - Abstract
Influence of atmosphere and storage period on the physicochemical and biological properties of harvested vegetable soybeans stored for 10 d at 25 °C was investigated. Storing vegetable soybeans under modified atmosphere (low O
- Published
- 2019
22. Meat quality evaluation based on computer vision technique: A review
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Amin Taheri-Garavand, Yoshio Makino, Mahmoud Omid, and Soodabeh Fatahi
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Meat ,Meat packing industry ,Computer science ,Swine ,media_common.quotation_subject ,Standard of living ,Poultry ,0404 agricultural biotechnology ,Artificial Intelligence ,Fish Products ,Food Quality ,Production (economics) ,Animals ,Quality (business) ,Computer vision ,Poultry Products ,Quality characteristics ,media_common ,Alternative methods ,Consumption (economics) ,Sheep ,Quality assessment ,business.industry ,0402 animal and dairy science ,Fishes ,food and beverages ,04 agricultural and veterinary sciences ,040401 food science ,040201 dairy & animal science ,Cattle ,Artificial intelligence ,business ,Food Science - Abstract
Nowadays people tend to include more meat in their diet thanks to the improvement in standards of living as well as an increase in awareness of meat nutritive values. To ensure public health, therefore, there is a need for a rise in worldwide meat production and consumption. Further attention is also required as to how the safety and the quality of meat production process should be assessed. Classical methods of meat quality assessment, however, have some disadvantages; expensive and time-consuming. This study intends to introduce an alternative method known as Computer Vision (CV) for the assessment of various quality parameters of muscle foods. CV has several advantages over the traditional methods. It is non-destructive, easy, and quick, hence, more efficient in meat quality assessments. This study aims to investigate different quality characteristics of some muscle foods using CV. It closes with a discussion on the future challenges and expected opportunities of the practical application of CV in the meat industry.
- Published
- 2018
23. Recent Advances for Rapid Detection of Quality and Safety of Fish by Hyperspectral Imaging Analysis
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Francisco J. Rodríguez-Pulido, Masatoshi Yoshimura, Yoshio Makino, and Chao-Hui Feng
- Subjects
Human health ,business.industry ,media_common.quotation_subject ,Food spoilage ,Hyperspectral imaging ,%22">Fish ,Environmental science ,Quality (business) ,Fish products ,business ,Rapid detection ,media_common ,Biotechnology - Abstract
This chapter discusses the detection of fish freshness, evaluation of physical properties and chemical composition and inspection of microbial spoilage in fish by Hyperspectral imaging (HSI). Fish has been one of the most important components of several and nutritious diets in the world. Its contribution to human health is well documented, being an essential topic for researchers. Compared with traditional methods, HSI is a environmental friendly, toxic-free, noninvasive, time-saving technique. Fillets of cod under different programs of freezing, thawing, and storage were investigated by HSI. The blood in whitefish fillets was detected by HSI with a range of 430–1,000 nm. Significant efforts have been made by the industries to enhance the quality and safety of the aquatic and seafood products by using new technologies such as novel cooling. However, high-quality and safe fish products are also closely related to human health and dietary benefits.
- Published
- 2018
24. Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging
- Author
-
Seiichi Oshita, Mohammed Kamruzzaman, and Yoshio Makino
- Subjects
Multivariate statistics ,Meat packing industry ,Swine ,Multispectral image ,Analytical chemistry ,Analytical Chemistry ,0404 agricultural biotechnology ,Animals ,Water content ,Remote sensing ,Sheep ,Spectroscopy, Near-Infrared ,Moisture ,business.industry ,Spectrum Analysis ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,General Medicine ,040401 food science ,Red Meat ,Feature (computer vision) ,Multivariate Analysis ,Red meat ,Environmental science ,Cattle ,business ,Food Science - Abstract
A hyperspectral imaging system in the spectral range of 400-1000 nm was investigated to develop a multispectral real-time imaging system allowing the meat industry to determine moisture content in red meat including beef, lamb, and pork. Multivariate calibration models were developed using partial least-squares regression (PLSR) and least-squares support vector machines (LS-SVM) in the full spectral range. Instead of selection of different sets of feature wavelengths for beef, lamb, and pork, a set of 10 feature wavelengths was selected for convenient industrial application for the determination of moisture content in red meat. A quantitative linear function was then established using MLR based on these key feature wavelengths for predicting moisture content of red meat in an online system and creating moisture distribution maps. The results reveal that the combination of hyperspectral imaging and multivariate has great potential in the meat industry for real-time determination of moisture content.
- Published
- 2016
25. Hyperspectral imaging for real-time monitoring of water holding capacity in red meat
- Author
-
Mohammed Kamruzzaman, Seiichi Oshita, and Yoshio Makino
- Subjects
Pixel ,010401 analytical chemistry ,Multispectral image ,Hyperspectral imaging ,Image processing ,04 agricultural and veterinary sciences ,040401 food science ,01 natural sciences ,0104 chemical sciences ,Support vector machine ,0404 agricultural biotechnology ,Feature (computer vision) ,Full spectral imaging ,Calibration ,Food Science ,Mathematics ,Remote sensing - Abstract
A hyperspectral imaging system was investigated for determination of feature wavelengths to be used in a design of a multispectral system for real-time monitoring of water holding capacity (WHC) in red meat. Hyperspectral images of different red meat samples were acquired in the spectral range of 400–1000 nm and partial least-squares regression (PLSR) and least square support vector machine (LS-SVM) models were developed. Feature wavelengths were selected using regression coefficients (RCs) and competitive adaptive reweighted sampling (CARS). The best set of feature wavelengths was determined using RCs and the best calibration model obtained was based on RCs-LS-SVM. The model obtained an R2p of 0.93 and RPD of 4.09, indicating that the model is adequate for analytical purposes. An image processing algorithm was developed to transfer this model to each pixel in the image. The results showed that instead of selecting different sets of wavelengths for beef, lamb, and pork, a subset of feature wavelengths can be used for convenient industrial application for the determination of WHC in red meat. The pixel wise visualization of WHC obtained with the aid of image processing was another advantage of using hyperspectral imaging that cannot be obtained with either imaging or conventional spectroscopy.
- Published
- 2016
26. Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning
- Author
-
Seiichi Oshita, Mohammed Kamruzzaman, and Yoshio Makino
- Subjects
Adulterant ,Coefficient of determination ,Pixel ,business.industry ,010401 analytical chemistry ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,Machine learning ,computer.software_genre ,040401 food science ,01 natural sciences ,Minced beef ,food.food ,0104 chemical sciences ,VNIR ,Absorbance ,0404 agricultural biotechnology ,food ,Partial least squares regression ,Artificial intelligence ,business ,computer ,Food Science ,Mathematics ,Remote sensing - Abstract
The main objective of this study was to evaluate the potential of visible near-infrared (VNIR) hyperspectral imaging (400–1000 nm) and machine learning to detect adulteration in fresh minced beef with chicken. Minced beef samples were adulterated with minced chicken in the range 0–50% (w/w) at approximately 2% intervals. Hyperspectral images were acquired in the reflectance (R) mode and then transformed into absorbance (A) and Kubelka–Munck (KM) units. Partial least squares regression (PLSR) models were developed to relate the three spectral profiles with the adulteration levels of the tested samples. These models were then validated using different independent data sets, and obtained the coefficient of determination (R2p) of 0.97, 0.97, and 0.96 with root mean square error in prediction (RMSEP) of 2.62, 2.45, and 3.18% (w/w) for R, A and KM spectra, respectively. To reduce the high dimensionality of the hyperspectral data, some important wavelengths were selected using stepwise regression. PLSR models were again created using these important wavelengths and the best model was then transferred in each pixel in the image to obtain prediction map. The results clearly ascertain that hyperspectral imaging coupled with machine learning can be used to detect, quantify and visualize the amount of chicken adulterant added to the minced beef.
- Published
- 2016
27. Detection of fluorescence signals from ATP in the second derivative excitation–emission matrix of a pork meat surface for cleanliness evaluation
- Author
-
Seiichi Oshita, Hiroaki Shirai, and Yoshio Makino
- Subjects
Excitation emission matrix ,Chromatography ,Chemistry ,Analytical chemistry ,04 agricultural and veterinary sciences ,040401 food science ,Fluorescence ,Matrix (chemical analysis) ,Fluorescence intensity ,0404 agricultural biotechnology ,Pork meat ,Partial least squares regression ,Spectroscopy ,Food Science ,Second derivative - Abstract
We investigated the potential application of excitation–emission matrix (EEM) spectroscopy in the rapid, non-destructive evaluation of cleanliness in meat processing plants. ATP can be an indicator of microbial contamination. Thus, the fluorescent signal of ATP was detected at Ex = 286 nm and Em = 386 and 412 nm by applying two-dimensional Savitzky–Golay second-order differentiation of EEM obtained from the pork meat surface. The second derivative of the fluorescence intensity at Ex = 284 nm and Em = 412 nm, i.e., the wavelengths assigned to ATP, decreased with the ATP content. The ATP content and plate count were quantified using the second derivatives of EEMs by partial least squares regression in good agreement [coefficient correlation, 0.87; RMSEP, log10 (0.70, mol cm−2) for the predicted ATP content]. The model directly reflected the ATP fluorescent signal changes.
- Published
- 2016
28. Objective Evaluation of External Quality of Broccoli Heads Using a Computer Vision System
- Author
-
Genki Amino, Akari Sato, Yoshio Makino, Masato Tsukada, Aoi Wakatsuki, and Seiichi Oshita
- Subjects
Brassica oleracea var italica ,Horticulture ,Chemistry ,media_common.quotation_subject ,Nondestructive analysis ,Quality (business) ,Objective evaluation ,Industrial and Manufacturing Engineering ,Food Science ,media_common - Published
- 2016
29. A Grading Method for Mangoes on the Basis of Peel Color Measurement Using a Computer Vision System
- Author
-
Akari Sato, Kenjiro Goto, Yoshio Makino, Seiichi Oshita, and Masato Tsukada
- Subjects
Correlation coefficient ,business.industry ,04 agricultural and veterinary sciences ,General Medicine ,Color space ,040401 food science ,040501 horticulture ,chemistry.chemical_compound ,Pigment ,0404 agricultural biotechnology ,Light source ,chemistry ,Anthocyanin ,visual_art ,visual_art.visual_art_medium ,Image acquisition ,Computer vision ,Color measurement ,Artificial intelligence ,0405 other agricultural sciences ,business ,Hue ,Mathematics - Abstract
An objective grading method using a Computer Vision System (CVS) for mangoes is proposed. Red peel was selected using two types of color space values at chroma = 22 and hue angle = 52°. Eighteen out of 25 fully-ripened fruits were graded as “excellent,” determined by the share of red area per fruit being in the range of 80% - 100%. In contrast, all green-mature fruits were graded as “fair,” where the share of red area per fruit was - 0.0542x + 7.83), with a correlation coefficient accuracy of 0.94 and root mean square error of 1.31 mg·kg-1. This result may be effective for the visualization of anthocyanin distribution on mango skin. The threshold for red peel can be in the range of 131 - 186 mg·kg-1. This suggests that the pigment concentration is usable as a universal threshold. This value is unaffected by conditions for image acquisition or color measurement (e.g., light source, sensor, filter, and optical geometry), unlike color space values as hue angle.
- Published
- 2016
30. Oxidative Capacity of Nanobubbles and Its Effect on Seed Germination
- Author
-
Tsutomu Uchida, Shu Liu, Yoshinori Kawagoe, Yoshio Makino, Seiichi Oshita, and Qunhui Wang
- Subjects
chemistry.chemical_classification ,Reactive oxygen species ,Renewable Energy, Sustainability and the Environment ,General Chemical Engineering ,Analytical chemistry ,food and beverages ,chemistry.chemical_element ,02 engineering and technology ,General Chemistry ,Oxidative phosphorylation ,Metabolism ,010402 general chemistry ,021001 nanoscience & nanotechnology ,01 natural sciences ,Oxygen ,Nitrogen ,0104 chemical sciences ,chemistry.chemical_compound ,chemistry ,Distilled water ,Germination ,Environmental Chemistry ,0210 nano-technology ,Hydrogen peroxide ,Nuclear chemistry - Abstract
Nanobubbles (NBs) have been reported to be effective at accelerating the metabolism of living organisms, but the mechanism is not yet well understood. In this study, the production of reactive oxygen species (ROS) by NBs and its effect on seed germinations were investigated. The fluorescence response of APF to NB water was measured. It changed depending on the NB number density which decreased with storage time. This indicated that NBs could produce ROS and the amount of ROS had positive correlation with the NB number density. The fluorescence intensity of APF increases linearly with the concentration of H2O2 in the range of 0–1 mM. Just after the NB generation, the oxidative capacities represented by amount of ROS of oxygen NB water and gas-mixture (air + nitrogen) NB water were estimated to be equivalent to 0.5 and 0.3 mM H2O2 respectively. The seed germination tests were performed in the NB water, distilled water and H2O2 solutions. The germination rate at each observation times of seeds submerged in g...
- Published
- 2015
31. A combined method implementing both xenon hydrate formation and the freezing process for the preservation of barley as a simulated food
- Author
-
Thunyaboon Arunyanart, Satoshi Takeya, Yoshio Makino, Seiichi Oshita, Hiroko Noritake, and Ubonrat Siripatrawan
- Subjects
Ice crystals ,Chemistry ,Diffusion ,Clathrate hydrate ,food and beverages ,chemistry.chemical_element ,Plant cell ,Crystallography ,Coleoptile ,Xenon ,Scientific method ,Biophysics ,Hydrate ,Food Science - Abstract
Freezing clearly damages plant cells and tissues when ice crystals form, and these affect the quality and speed up the deterioration of frozen agricultural products. This study attempted to use a combined method of both xenon hydrate formation and the freezing process (CXF) to lengthen the preservation of barley coleoptile cells, as opposed to using the freezing alone process (FAP). Barley coleoptile cells were used in this study as the sample simulated food, and xenon hydrate formation was encouraged in samples at 1.0 MPa and 1 °C for 0.5, 1, 2, 3, 4 and 5 h, respectively. The results showed that the amount of xenon hydrate in barley coleoptile cells increased with storage time, and that their cellular structure could be destroyed when increasing the amounts of xenon hydrate. Therefore, conditions under a xenon pressure of 1.0 MPa at 1 °C for 1 h were used to control the amounts of implemented xenon hydrate. The process of CXF, including the introduction of xenon gas under a pressure of 1.0 MPa at 1 °C for 1 h frozen to −20 °C, was studied. Typical restricted diffusion phenomenon were determined using a nuclear magnetic resonance method, and it was found that CXF barley coleoptile cells were similar to those of fresh barley. In contrast, the FAP barley coleoptile cells showed unrestricted diffusion phenomenon. The results from X-ray radiographic images also suggested that the CXF process can preserve the shape of barley coleoptile tissues and, additionally, it was found that xenon hydrate formation occurred inside the cells and intercellular spacing of such cells. It can therefore be suggested that the assumed process of xenon hydrate formation in plant cells results in CXF being more effective for the preservation of plant cells and their tissues than the FAP process.
- Published
- 2015
32. Influence of low O2 and high CO2 environment on changes in metabolite concentrations in harvested vegetable soybeans
- Author
-
Atsushi Nishizaka, Kenji Kawai, Yoshio Makino, Masatoshi Yoshimura, Itaru Sotome, and Takashi Akihiro
- Subjects
Alanine ,Metabolite ,Nutritional content ,010401 analytical chemistry ,04 agricultural and veterinary sciences ,General Medicine ,040401 food science ,01 natural sciences ,0104 chemical sciences ,Analytical Chemistry ,chemistry.chemical_compound ,0404 agricultural biotechnology ,Nutrient ,chemistry ,Green color ,Biological property ,Modified atmosphere ,Food science ,Food Science - Abstract
Influence of atmosphere and storage period on the physicochemical and biological properties of harvested vegetable soybeans stored for 10 d at 25 °C was investigated. Storing vegetable soybeans under modified atmosphere (low O2 and high CO2), was more effective in maintaining its green color and mass than storing them under normoxia. Principal component 1 (PC1; contribution rate: 25%) was related to the atmospheres, whereas PC2 (contribution rate: 19%) was related to storage period. Cluster analysis showed that some types of sugars decreased, whereas some types of organic and amino acids increased with deterioration. Alanine, an indicator of low O2 stress, was maintained for 3 d under modified atmospheres, whereas alanine significantly decreased under normoxia. The concentrations of inositol and niacinamide (functional ingredients) under the modified atmospheres were significantly higher than those under normoxia. Thus, storage under modified atmospheres was effective in maintaining freshness and increasing the nutritional content of vegetable soybeans.
- Published
- 2020
33. Colour analysis in sausages stuffed in modified casings with different storage days using hyperspectral imaging – A feasibility study
- Author
-
Yoshio Makino and Chao-Hui Feng
- Subjects
Absorbance ,Coefficient of determination ,Chromatography ,Materials science ,Slush ,Partial least squares regression ,Hyperspectral imaging ,Casing ,Scatter correction ,Food Science ,Biotechnology ,Second derivative - Abstract
Colour evolution for sausage stuffed in casings modified by different concentrations of surfactant solution and slush salt with lactic acid was for the first time investigated during 68 days with 4 °C storage using a hyperspectral imaging system in the range of 380–1000 nm. Pre-treatments (normalization, standard normal variate (SNV), multiplicative scatter correction (MSC), first and second derivative) were conducted and performance after the pre-treatments was improved. No interactive effects between casing treatments and storage days were observed in accordance with two-way ANOVA. Partial least squares regression (PLSR) was developed from spectra with reflectance and absorbance modes and important wavelengths were selected with regard to each colour parameters. When predicted redness (a*), PLSR model derived from absorbance pre-treated by MSC for modified casing with treatment 1 showed the prediction coefficient of determination (Rp2) up to 0.78 while 0.61 for control casing using reflectance. This study innovatively showed a great potential in a cylinder shape sausage for real-time inspection and is competent to quantify and visualise the colour dynamic change of the sausages stuffed in modified casings.
- Published
- 2020
34. Effect of perforation-mediated modified atmosphere packaging on the quality and bioactive compounds of soft kale (Brassica oleracea L. convar. acephala (DC) Alef. var. sabellica L.) during storage
- Author
-
Surina Boerzhijin, Masami Yokota Hirai, Yoshio Makino, Masatoshi Yoshimura, and Itaru Sotome
- Subjects
0106 biological sciences ,Microbiology (medical) ,chemistry.chemical_classification ,Polymers and Plastics ,biology ,Chemistry ,Perforation (oil well) ,04 agricultural and veterinary sciences ,biology.organism_classification ,Ascorbic acid ,040401 food science ,01 natural sciences ,Biomaterials ,Horticulture ,0404 agricultural biotechnology ,Green color ,010608 biotechnology ,Modified atmosphere ,Brassica oleracea ,Safety, Risk, Reliability and Quality ,Carotenoid ,Food Science - Abstract
Perforation-mediated modified atmosphere packaging of soft kale (Brassica oleracea L. convar. acephala (DC) Alef. var. sabellica L.) was investigated to maintain freshness at 10 °C for 12 d. Kale was sealed in micro-perforated pouches with different oxygen transmission rates (OTRs: mL m–2 d–1 atm–1) at 1.66 × 106, 3.0 × 103 or 64. Headspace atmospheres (O2/CO2) of pouches at OTR 1.66 × 106, 3.0 × 103 and 64 were 21 %/0 % (normoxia), 1.9∼7.4 %/8.5∼9.6 % (modified atmosphere) and 0 %/> 20 % (hypoxia), respectively. Hue angles (degree of green color) of leaves in the OTR 3.0 × 103 and 64 pouches were significantly higher than that in the OTR 1.66 × 106 pouch. However, carotenoid and ascorbic acid concentrations in the leaf in the OTR 3.0 × 103 pouch was significantly higher than that in the OTR 64 pouch. The modified atmosphere created in the OTR 3.0 × 103 pouch was suitable for maintaining external (green color) and internal (bioactive compounds) qualities of soft kale.
- Published
- 2020
35. Effect of the storage atmosphere on metabolomics of harvested tomatoes (
- Author
-
Yuma, Yokota, Takashi, Akihiro, Surina, Boerzhijin, Takeshi, Yamada, and Yoshio, Makino
- Subjects
postharvest storage ,modified atmosphere packaging ,principal component analysis ,environmental gas composition ,tomato ,metabolomics ,Original Research - Abstract
Harvested tomatoes were stored under atmospheres that were normoxic, anoxic, or modified (altered O2 and CO2 concentrations). Each atmosphere was created by storing the tomatoes at 25°C for up to 8 days in different kinds of pouches. During storage, metabolites of the tomatoes were measured using metabolomics. We obtained score plots of the metabolites on eighth day of storage by principal component analysis. There was a tendency for groups to be divided on the basis of score plot according to the composition of each gas. PC1 and PC2 seemed to correspond to the influence of O2 and CO2 concentrations, respectively, and the total contribution rate of the two axes was 72%, so that we concluded that the metabolites were affected mainly by O2 and CO2 concentrations. The results indicate that metabolomics may be an effective tool to reveal the relationship between metabolic state of harvested fruits and the atmosphere.
- Published
- 2018
36. Simultaneous assessment of various quality attributes and shelf life of packaged bratwurst using hyperspectral imaging
- Author
-
Yoshio Makino and Ubonrat Siripatrawan
- Subjects
Adult ,Male ,Swine ,media_common.quotation_subject ,Color ,Shelf life ,Chemometrics ,0404 agricultural biotechnology ,Lactobacillales ,Partial least squares regression ,Image Processing, Computer-Assisted ,Image acquisition ,Animals ,Humans ,Quality (business) ,media_common ,Remote sensing ,Mathematics ,Spectroscopy, Near-Infrared ,Wavelength range ,Hyperspectral imaging ,04 agricultural and veterinary sciences ,040401 food science ,Meat Products ,Food Storage ,Odorants ,Female ,Canonical correlation ,Food Science - Abstract
A simultaneous evaluation of various quality attributes of packaged bratwurst using hyperspectral imaging (HSI) was developed. Changes in physicochemical (L*, a*, b* color values, pH and thiobarbituric acid (TBA)), microbiological (total viable counts (TVC) and lactic acid bacteria (LAB)) and sensory (color, odor and overall acceptability) characteristics of the packaged sausages were monitored during storage at 4 ± 1 °C. Reflectance spectra covering a wavelength range of 400–1000 nm of the samples were acquired using HSI. The relationships between the quality attributes and the spectroscopic reflectance were investigated using canonical correlation analysis. Among all quality attributes, L* color value, TBA, TVC, LAB, odor and overall acceptability appeared to be highly associated with the reflectance. To facilitate the HSI for rapid image acquisition and data processing, partial least squares regression (PLSR) analysis was employed for selection of optimal wavelengths. The selected wavelengths were then assembled into multispectral data and used as input variables to optimize the PLSR and artificial neural network models for the prediction of quality attributes of the sausage samples. The HSI technique can be used for rapid and nondestructive evaluation of the product's quality and shelf life.
- Published
- 2017
37. Rapid Method Based on Proton Spin-Spin Relaxation Time for Evaluation of Freezing Damage in Frozen Fruit and Vegetable
- Author
-
Ubonrat Siripatrawan, Thunyaboon Arunyanart, Seiichi Oshita, and Yoshio Makino
- Subjects
Microscope ,Ice crystals ,Chemistry ,General Chemical Engineering ,Analytical chemistry ,food and beverages ,General Chemistry ,law.invention ,Crystallography ,Coleoptile ,Membrane ,Optical microscope ,law ,Electrical resistivity and conductivity ,Microscopy ,Water content ,Food Science - Abstract
This study proposed the use of nuclear magnetic resonance (NMR) technique based on proton spin–spin relaxation time (T2) of water to indicate freezing damage in frozen fruit and vegetable. T2 value can be used to indicate water content in the cells of samples. The results showed that T2 values of frozen-thawed samples were lower than those of fresh (undamaged) samples. This is because of the cell membrane damage due to the formation of ice crystals, leading to leakage of water. The microstructural changes of frozen-thawed barley coleoptile tissue and apple parenchyma tissue were evident when observed using a high-resolution three-dimensional X-ray microscope and an optical microscope, respectively. Changes in the T2 value could be related directly to the microstructural changes of barley coleoptile tissue and apple parenchyma tissue. T2 value can be measured in far less time than conventional methods and is considered a rapid and effective method to indicate freezing damage in frozen foods. Practical Applications Freezing damage (e.g., cell shrinkage, membrane damage and loss of water holding capacity) caused by ice crystal formation affects the quality of frozen food products after thawing. This study proposed an alternative nuclear magnetic resonance (NMR) technique based on proton spin–spin relaxation time (T2) of water to indicate freezing damage in frozen fruit and vegetable. NMR measurement of T2 value can be performed in far less time than conventional freezing damage measurements (e.g., electrical conductivity and microscopy) and thus can be used as a rapid and reliable technique for determination of water in food samples and subsequently can be used to indicate freezing damage caused by ice crystal formation.
- Published
- 2015
38. Monitoring fungal growth on brown rice grains using rapid and non-destructive hyperspectral imaging
- Author
-
Ubonrat Siripatrawan and Yoshio Makino
- Subjects
Colony-forming unit ,Spectroscopy, Near-Infrared ,Coefficient of determination ,Aspergillus oryzae ,Food spoilage ,Fungi ,food and beverages ,Hyperspectral imaging ,Oryza ,General Medicine ,Biology ,biology.organism_classification ,Microbiology ,Horticulture ,Botany ,Partial least squares regression ,Food Microbiology ,Brown rice ,Least-Squares Analysis ,Algorithms ,Food Science ,Gram - Abstract
This research aimed to develop a rapid, non-destructive, and accurate method based on hyperspectral imaging (HSI) for monitoring spoilage fungal growth on stored brown rice. Brown rice was inoculated with a non-pathogenic strain of Aspergillus oryzae and stored at 30 °C and 85% RH. Growth of A. oryzae on rice was monitored using viable colony counts, expressed as colony forming units per gram (CFU/g). The fungal development was observed using scanning electron microscopy. The HSI system was used to acquire reflectance images of the samples covering the visible and near-infrared (NIR) wavelength range of 400-1000 nm. Unsupervised self-organizing map (SOM) was used to visualize data classification of different levels of fungal infection. Partial least squares (PLS) regression was used to predict fungal growth on rice grains from the HSI reflectance spectra. The HSI spectral signals decreased with increasing colony counts, while conserving similar spectral pattern during the fungal growth. When integrated with SOM, the proposed HSI method could be used to classify rice samples with different levels of fungal infection without sample manipulation. Moreover, HSI was able to rapidly identify infected rice although the samples showed no symptoms of fungal infection. Based on PLS regression, the coefficient of determination was 0.97 and root mean square error of prediction was 0.39 log (CFU/g), demonstrating that the HSI technique was effective for prediction of fungal infection in rice grains. The ability of HSI to detect fungal infection at early stage would help to prevent contaminated rice grains from entering the food chain. This research provides scientific information on the rapid, non-destructive, and effective fungal detection system for rice grains.
- Published
- 2015
39. Assessment of Visible Near-Infrared Hyperspectral Imaging as a Tool for Detection of Horsemeat Adulteration in Minced Beef
- Author
-
Mohammed Kamruzzaman, Seiichi Oshita, Shu Liu, and Yoshio Makino
- Subjects
Pixel ,Visible near infrared ,Process Chemistry and Technology ,Hyperspectral imaging ,Image processing ,Industrial and Manufacturing Engineering ,Minced beef ,food.food ,food ,Partial least squares regression ,Linear regression ,Calibration ,Safety, Risk, Reliability and Quality ,Food Science ,Remote sensing ,Mathematics - Abstract
For the first time, a visible near-infrared (Vis-NIR) hyperspectral imaging system (400–1000 nm) was investigated for rapid and non-destructive detection of adulteration in minced beef meat. Minced beef meat samples were adulterated with horsemeat at levels ranging from 2 to 50 % (w/w), at approximately 2 % increments. Calibration model was developed and optimized using partial least-squares regression (PLSR) with internal full cross-validation and then validated by external validation using an independent validation set. Several spectral pre-treatment techniques including derivatives, standard normal variate (SNV), and multiplicative scatter correction (MSC) were applied to examine the influence of spectral variations for predicting adulteration in minced beef. The established PLSR models based on raw spectra had coefficients of determination (R2) of 0.99, 0.99, and 0.98, and standard errors of 1.14, 1.56, and 2.23 % for calibration, cross-validation, and prediction, respectively. Four important wavelengths (515, 595, 650, and 880 nm) were selected using regression coefficients resulting from the best PLSR model. By using these important wavelengths, an image processing algorithm was developed to predict the adulteration level in each pixel in whole surface of the samples. The results demonstrate that hyperspectral imaging coupled with multivariate analysis can be successfully applied as a rapid screening technique for adulterate detection in minced meat.
- Published
- 2015
40. Nondestructive Evaluation of Anthocyanin Concentration and Soluble Solid Content at the Vine and Blossom Ends of Green Mature Mangoes during Storage by Hyperspectral Spectroscopy
- Author
-
Usman Ahmad, Yoshinori Kawagoe, Kenjiro Goto, Takehiro Suhara, Seiichi Oshita, Yoshio Makino, Yohanes Aris Purwanto, Shin-Ichiro Kuroki, Aiko Isami, and Sutrisno
- Subjects
Marketing ,Vine ,business.industry ,General Chemical Engineering ,Hyperspectral imaging ,Industrial and Manufacturing Engineering ,chemistry.chemical_compound ,Horticulture ,chemistry ,Agronomy ,Nondestructive testing ,Anthocyanin ,Partial least squares regression ,Postharvest ,Food quality ,Spectroscopy ,business ,Food Science ,Biotechnology - Abstract
) and 0.73 (RMSECV 0.98%), respectively, using partial least squares regression (PLSR) models. The proposed nondestructive method may be effective for evaluating internal and external qualities of mangoes simultaneously.
- Published
- 2015
41. Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review
- Author
-
Seiichi Oshita, Mohammed Kamruzzaman, and Yoshio Makino
- Subjects
Meat ,Chemistry ,Analytical technique ,Non invasive ,Fishes ,Digital imaging ,Hyperspectral imaging ,Food Contamination ,Contamination ,Biochemistry ,Poultry ,Analytical Chemistry ,Seafood ,Spectrophotometry ,Food products ,Food Microbiology ,Image Processing, Computer-Assisted ,Animals ,Environmental Chemistry ,%22">Fish ,Biochemical engineering ,Food science ,Spectroscopy - Abstract
The requirement of real-time monitoring of food products has encouraged the development of non-destructive measurement systems. Hyperspectral imaging is a rapid, reagentless, non-destructive analytical technique that integrates traditional spectroscopic and imaging techniques into one system to attain both spectral and spatial information from an object that cannot be achieved with either digital imaging or conventional spectroscopic techniques. Recently, this technique has emerged as one of the most powerful and inspiring techniques for assessing different meat species and building chemical images to show the distribution maps of constituents in a direct and easy manner. After presenting a brief description of the fundamentals of hyperspectral imaging, this paper reviews the potential applications of hyperspectral imaging for detecting the adulteration, contamination, and authenticity of meat, poultry, and fish. These applications envisage that hyperspectral imaging can be considered as a promising non-invasive analytical technique for predicting the contamination, adulteration, and authenticity of meat, poultry, and fish in a real-time mode.
- Published
- 2015
42. Hyperspectral imaging in tandem with multivariate analysis and image processing for non-invasive detection and visualization of pork adulteration in minced beef
- Author
-
Mohammed Kamruzzaman, Seiichi Oshita, and Yoshio Makino
- Subjects
Multivariate analysis ,General Chemical Engineering ,Non invasive ,General Engineering ,Hyperspectral imaging ,Image processing ,Minced beef ,food.food ,Analytical Chemistry ,food ,Linear regression ,Partial least squares regression ,Principal component regression ,Food science ,Mathematics - Abstract
Pork adulteration in minced beef was detected for the first time using a hyperspectral imaging (HIS) technique. Minced beef samples were adulterated with minced pork in the range of 2–50% (w/w) at approximately 2% intervals. Images were acquired using a visible near-infrared hyperspectral imaging (VNIR-HSI) system and their spectral data were extracted. Several data pre-treatments and different linear multivariate analyses, namely partial least squares regression (PLSR), principal component regression (PCR), and multiple linear regression (MLR), were investigated to determine the predictive ability of VNIR-HSI in detecting pork meat adulteration in minced beef. PLSR had a better performance than PCR for predicting pork adulteration in minced beef. Only four wavelengths centered at 430, 605, 665, and 705 nm were selected as the important wavelengths to build the MLR model for visualizing the distribution of adulteration. The results confirm that HSI can be used to provide a rapid, low cost, and nondestructive testing technique for detection of adulteration in minced meat.
- Published
- 2015
43. A new approach for the preservation of apple tissue by using a combined method of xenon hydrate formation and freezing
- Author
-
Seiichi Oshita, Thunyaboon Arunyanart, Ubonrat Siripatrawan, and Yoshio Makino
- Subjects
inorganic chemicals ,Ice crystals ,Chemistry ,Clathrate hydrate ,Turgor pressure ,Mineralogy ,chemistry.chemical_element ,General Chemistry ,Industrial and Manufacturing Engineering ,Xenon ,Restricted Diffusion ,Parenchyma ,Biophysics ,Hydrate ,Combined method ,Food Science - Abstract
Freezing usually causes cell and tissue damage in frozen fruits. This study attempted to use a combined method of xenon hydrate formation and freezing (CXF) for the preservation of apple parenchyma tissue and to compare it with the freezing alone process (FAP). CXF included two steps. The first step was to initiate a certain amount of xenon hydrate by introducing the apple parenchyma tissue to the xenon gas at 1.0 MPa and 1 °C for 0, 1, 2, 3, 4, 5, 6 and 7 d. It was found that the amount of xenon hydrate in apple parenchyma tissue increased with storage time and 2 d was optimum to obtain the certain amount of xenon hydrate. In the second step, the sample with optimum xenon hydrate formation was frozen at − 20 °C. The results showed that CXF was more effective in maintaining firmness, turgor pressure, and cell membrane integrity of the apple parenchyma tissue than FAP. A typical restricted diffusion phenomenon which indicates that water molecules are maintained in the apple parenchyma cells was found in the CXF samples, while the FAP samples showed an unrestricted diffusion phenomenon. In addition, firmness, turgor pressure, cell membrane integrity, and restricted diffusion phenomenon of the CXF samples were similar to those of the fresh samples. The CXF could preserve the apple parenchyma tissue because of the bulk water inside the cells and the water surrounding the cells which transformed to ice crystals is limited. Thus, cell and tissue damage due to the formation of ice crystals was reduced. The obtained results indicated that the CXF is effective for the preservation of the apple parenchyma tissue. Industrial relevance There has been an attempt to improve the quality of frozen fruit by using innovative techniques, in opposition to simply freezing. This present work proposed xenon hydrate formation for the reduction of bulk water before freezing in order to reduce freezing damage due to a large amount of ice crystal formation. The combined method of xenon hydrate formation and freezing has been proved to be able to reduce cell membrane damage usually occurring in frozen fruit. Thus this new technique has potential to be used for improving the quality of frozen fruit. The xenon hydrate formation is considered as an innovative technique for the preservation of fruit, which is expected to be useful for the frozen food industry.
- Published
- 2014
44. Hyperspectral Imaging in Tandem with R Statistics and Image Processing for Detection and Visualization of pH in Japanese Big Sausages Under Different Storage Conditions
- Author
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Chao-Hui, Feng, Yoshio, Makino, Masatoshi, Yoshimura, Dang Quoc, Thuyet, and Juan Francisco, García-Martín
- Subjects
Meat Products ,Spectroscopy, Near-Infrared ,Japan ,Food Handling ,Food Preservation ,Image Processing, Computer-Assisted ,Animals ,Hydrogen-Ion Concentration ,Least-Squares Analysis ,Models, Theoretical - Abstract
The potential of hyperspectral imaging with wavelengths of 380 to 1000 nm was used to determine the pH of cooked sausages after different storage conditions (4 °C for 1 d, 35 °C for 1, 3, and 5 d). The mean spectra of the sausages were extracted from the hyperspectral images and partial least squares regression (PLSR) model was developed to relate spectral profiles with the pH of the cooked sausages. Eleven important wavelengths were selected based on the regression coefficient values. The PLSR model established using the optimal wavelengths showed good precision being the prediction coefficient of determination (RIn this paper, hyperspectral imaging is for the first time used to detect pH in cooked sausages using R statistics, which provides another useful information for the researchers who do not have the access to Matlab. Eleven optimal wavelengths were successfully selected, which were used for simplifying the PLSR model established based on the full wavelengths. This simplified model achieved a high R
- Published
- 2017
45. Real-time prediction of pre-cooked Japanese sausage color with different storage days using hyperspectral imaging
- Author
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Chao-Hui, Feng, Yoshio, Makino, Masatoshi, Yoshimura, and Francisco J, Rodríguez-Pulido
- Subjects
Meat Products ,Quality Control ,Spectroscopy, Near-Infrared ,Food Storage ,Japan ,Swine ,Multivariate Analysis ,Animals ,Cooking ,Least-Squares Analysis - Abstract
Redness can greatly influence the freshness of sausages. A precise, rapid and noncontact analytical method or tool is needed to quantify the color. Hyperspectral imaging (HSI) is an emerging technique that integrates spectroscopy and imaging to obtain the spectral and spatial information simultaneously. In the present study, the redness of cooked sausages stored up to 57 days was predicted using HSI in tandem with multivariate data analysis. The mean spectra of the sausages were extracted from the hyperspectral images. Partial least squares regression (PLSR) and forward stepwise multiple regression (FSMR) models were used to develop the relavent spectral profiles with the redness of the cooked sausages.Ten important wavelengths were selected based on the regression coefficient values from the PLSR model. The PLSR model established using the full wavelengths presented a good performance, with RHSI combined with PLSR and FSMR can be used to quantify and visualize evolution of sausage redness under different storage days. © 2017 Society of Chemical Industry.
- Published
- 2017
46. Nondestructive Hygiene Monitoring on Pork Meat Surface Using Excitation–Emission Matrices with Two-Dimensional Savitzky–Golay Second-Order Differentiation
- Author
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Masatoshi Yoshimura, Junichi Sugiyama, Hiroaki Shirai, Seiichi Oshita, and Yoshio Makino
- Subjects
Protoporphyrin IX ,Chemistry ,Process Chemistry and Technology ,Analytical chemistry ,Tryptophan ,Riboflavin ,Fluorescence ,Industrial and Manufacturing Engineering ,Fluorescence spectroscopy ,Matrix (chemical analysis) ,chemistry.chemical_compound ,Linear regression ,NAD+ kinase ,Safety, Risk, Reliability and Quality ,Food Science - Abstract
To develop a rapid and nondestructive hygiene-monitoring system in meat-processing plants, plate count and ATP content on pork meat surfaces were quantitatively determined with particular attention to NAD(P)H fluorescence produced by microorganisms. An excitation (Ex)–emission (Em) matrix (EEM) was obtained, and the five fluorescence peaks of tryptophan, NAD(P)H, zinc protoporphyrin IX, protoporphyrin IX, and riboflavin were observed. Plate count and ATP content were predicted with good accuracy [r p = 0.90–0.94 and root mean square error of prediction (RMSEP) = log10 (0.68–0.79 CFU cm−2) for plate count and r p = 0.84–0.89 and RMSEP = log10 (0.61–0.71, mol cm−2) for ATP content]. Two-dimensional Savitzky–Golay second-order differentiation was found to be a powerful preprocessing tool of EEMs to improve prediction accuracy. Better prediction accuracy was obtained when the sensitivity of the fluorescence spectrophotometer was set to focus on fluorescence from NAD(P)H than that from both tryptophan and NAD(P)H. However, little linear relationship was observed between plate count and fluorescence intensity from NAD(P)H (R 2 = 0.31). The absolute value of regression coefficient (RC) of partial least-squares regression (PLSR) at the wavelength assigned to NAD(P)H, zinc protoporphyrin IX, protoporphyrin IX, and riboflavin was high. It can be concluded that a good prediction model was developed in which four fluorescence compounds of NAD(P)H, zinc protoporphyrin IX, protoporphyrin IX, and riboflavin contribute to the prediction model, and these compounds are probably produced by microorganisms.
- Published
- 2014
47. Electrorheological response of the interfacial layer between a liquid crystal and a polymer alignment sublayer
- Author
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Atsushi Kubono, Kenji Ishida, Masahiro Misaki, Yasukiyo Ueda, Yoshio Makino, Junji Gonda, and Masahiro Morimoto
- Subjects
chemistry.chemical_classification ,Materials science ,Metals and Alloys ,Analytical chemistry ,Response time ,Surfaces and Interfaces ,Polymer ,Quartz crystal microbalance ,Viscoelasticity ,Surfaces, Coatings and Films ,Electronic, Optical and Magnetic Materials ,Adsorption ,chemistry ,Liquid crystal ,Materials Chemistry ,Molecule ,Composite material ,Layer (electronics) - Abstract
The interfacial layer between a liquid crystal (LC) and a polymer alignment sublayer was investigated using the quartz crystal microbalance (QCM) method. The time variations in the optical transmittance through the LC cells and the interfacial viscoelasticity were monitored simultaneously using the QCM to provide a comprehensive picture of the interfacial phenomena associated with the motion of LC molecules both in the bulk and in the interfacial layer. The response time of shift in the resonant resistance associated with the director orientation in the interfacial layer was about 90 ms, while that in the LC bulk was about 5 ms. This indicates that the reorientation of the LC molecules in the vicinity of the interface is much slower than in the bulk. The response time for the changes in thickness of the adsorbed layer, as estimated from the QCM results, was found to be about 1000 ms. These results indicate that the electrorheological response, or the viscoelasticity, in the vicinity of the interface between the LC and the polymer should be taken into account for the development of LC devices.
- Published
- 2014
48. Prediction of hardness development in mangosteen peel using NIR spectroscopy during low temperature storage
- Author
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Wayan Budiastra, Yoshio Makino, Shin-Ichiro Kuroki, Usman Ahmad, Seiichi Oshita, Sutrisno, Y. Aris Purwanto, Yoshinori Kawagoe, and Dwi Dian Novita
- Subjects
Nir reflectance ,Horticulture ,Materials science ,Moisture ,General Chemical Engineering ,Near-infrared spectroscopy ,Hardening (metallurgy) ,Water content ,Industrial and Manufacturing Engineering ,Food Science - Abstract
Peel hardening, due to loss of moisture during low temperature storage, is a prevalent problem in mangosteen. This research develops a model for predicting peel hardening in mangosteen, using a correlation with moisture content as determined by NIR spectroscopy. Mangosteen fruit were stored and their NIR reflectance, moisture content, and peel hardness were measured over time. Additional fruit was also stored for monitoring, and their NIR reflectance measured. Peel hardness of mangosteen in storage initially decreased, and then increased from the middle to the end of the storage period. Changes in peel hardness, based on moisture content over the 28 days of storage at 13 °C can be predicted, as well as for the 16 days storage at room temperature.
- Published
- 2014
49. Identification of ROS Produced by Nanobubbles and Their Positive and Negative Effects on Vegetable Seed Germination
- Author
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Shu Liu, Saneyuki Kawabata, Takahiko Yoshimoto, Seiichi Oshita, and Yoshio Makino
- Subjects
0301 basic medicine ,Chlorophyll ,Iron ,Germination ,02 engineering and technology ,Superoxide dismutase ,03 medical and health sciences ,chemistry.chemical_compound ,Spinacia oleracea ,Superoxides ,Electrochemistry ,General Materials Science ,Hydrogen peroxide ,Spectroscopy ,chemistry.chemical_classification ,Reactive oxygen species ,Microbubbles ,biology ,Singlet Oxygen ,Superoxide ,Singlet oxygen ,Hydroxyl Radical ,Superoxide Dismutase ,food and beverages ,Water ,Surfaces and Interfaces ,Hydrogen Peroxide ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,Hypocotyl ,Daucus carota ,Nanostructures ,Solutions ,030104 developmental biology ,chemistry ,Distilled water ,Biochemistry ,Seedlings ,Reagent ,Seeds ,biology.protein ,Hydroxyl radical ,0210 nano-technology ,Oxidation-Reduction ,Nuclear chemistry - Abstract
Exogenous reactive oxygen species (ROS) produced by nanobubble (NB) water offer a reasonable explanation for NBs’ physiological promotion and oxidation effects. To develop and exploit the NB technology, we have performed further research to identify the specific ROS produced by NBs. Using a fluorescent reagent APF, a Fenton reaction, a dismutation reaction of superoxide dismutase and DMSO, we distinguished four types of ROS (superoxide anion radical (O2·–), hydrogen peroxide (H2O2), hydroxyl radical (·OH), and singlet oxygen (1O2)). ·OH was confirmed to be the specific ROS produced by NB water. The role of ·OH produced by NB water in physiological processes depends on its concentration. The amount of exogenous ·OH has a positive correlation with the NB number density in the water. Here, spinach and carrot seed germination tests were repeatedly performed with three seed groups submerged in distilled water, high-number density NB water, and low-number density NB water under similar dissolved oxygen concentr...
- Published
- 2016
50. CHILLING INJURY IN GREEN MATURE 'GEDONG GINCU' MANGO FRUITS BASED ON THE CHANGES IN ION LEAKAGE
- Author
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Yohanes Aris Purwanto, Shin-Ichiro Kuroki, Usman Ahmad, Yoshinori Kawagoe, Sutrisno Suro Mardjan, Yoshio Makino, Seiichi Oshita, and Henry Okvitasari
- Subjects
Horticulture ,Chemistry ,Leakage (electronics) - Published
- 2013
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