Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.infrared.2022.104149

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

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Authorship：Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

The soon spoiled strawberries need to be classified from healthy fruits in an early stage. In this research, a machine vision system is proposed for inspecting the quality of strawberries using ultraviolet (UV) light based on the excitation-emission matrix (EEM) results. Among the 100 fruits which were harvested and stored under 10 °C condition for 7 days, 7 fruits were confirmed to be spoiled by using a firmness meter. The EEM results show the fluorescence compound contributes to a whitish surface on the spoiled fruits. Based on the EEM results, UV fluorescence images from the bottom view of strawberries were used to classify the spoiled fruits and healthy fruits within 1 day after harvest. These results demonstrate the UV fluorescence imaging can be a fast, non-destructive, and low-cost method for inspecting the soon spoiled fruits. The proposed index related to the spoiling time can be a new indicator for qualifying strawberry.

DOI： 10.1016/j.foodchem.2021.130776

PubMed

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

To investigate the potential of fluorescence spectroscopy in evaluating soybean protein and oil content, excitation emission matrix (EEM) was measured on 34 samples of soybean flours using a front-face measurement, and the accuracy of the protein and oil content prediction was evaluated. The EEM showed four main peaks at excitation/emission (Ex/Em) wavelengths of 230/335, 285/335, 365/475, and 435/495 nm. Furthermore, second derivative synchronous fluorescence (SDSF) spectra were extracted from the EEMs, and partial least square regression and support vector machine models were developed on each of the EEMs and SDSF spectra. The R2 values reached 0.86 and 0.74 for protein and oil, respectively. From the loading spectra, fluorescence at Ex/Em of 230-285/335 nm and 350/500 nm mainly contribute to the protein and oil content prediction, respectively. Those results revealed the potential of fluorescence spectroscopy as a tool for a rapid prediction of soybean protein and oil content.

DOI： 10.1016/j.foodchem.2021.130403

PubMed

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)  

J-GLOBAL

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：農業食料工学会事務局  

CiNii Article

CiNii Books

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Asian Agricultural and Biological Engineering Association  

DOI： 10.1016/j.eaef.2017.12.001

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Authorship：Lead author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)  

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Authorship：Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.saa.2024.124243

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Authorship：Lead author,　Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：ELSEVIER SCI LTD  

In the food supply chain, vegetable traceability holds significant importance. Conventional methods for traceability rely on tag-based systems such as barcodes, QR codes, or RFID tags. However, these methods face challenges when it comes to tracing single vegetables, such as green peppers between the grading facility and greenhouse harvesting. Unlike fruits like melons and watermelons, green peppers lack visible unique features on their surface that can be used to identify individual vegetables. Through our research, we have discovered that the fluorescence images of green peppers display a unique texture on the surface, which provides the possibility of identifying single green pepper. We proposed a single pepper traceable method that combines pepper images from the greenhouse and postharvest stage under UV light using imaging features. Our experiments aimed to evaluate the method's performance, including feature description, tracing success rate, performance change with storage, and changes with different length of the green peppers. The results showed that the KAZE feature was suitable for describing the surface feature of a green pepper under UV light, achieving a feature-matching performance of 81.3 % success rate in tracking individual peppers in each of the 15 packages, each with 10 peppers, using images from the day after harvest and greenhouse images. Furthermore, the method's performance could be affected by the storage time and length of the peppers. The proposed method could be a cost-effective, accurate, and label-free method to achieve single green pepper level traceability in smart agriculture.

DOI： 10.1016/j.compag.2023.107960

Web of Science

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Springer Science and Business Media LLC  

DOI： 10.1007/s43630-023-00459-5

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Other Link： https://link.springer.com/article/10.1007/s43630-023-00459-5/fulltext.html

Authorship：Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.saa.2023.123194

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Asian Agricultural and Biological Engineering Association  

DOI： 10.37221/eaef.15.1_24

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

Although fish and its related products are good sources of protein and unsaturated fatty acids, like omega-3 in the human diet, their shelf-life is limited by biochemical and microbial changes. In this study, a front-face fluorescence spectroscopy technique was used to acquire Excitation-emission matrices (EEM) to monitor Japanese dace (Tribolodon hakonensis) fish freshness degradation during storage. EEM of Japanese dace fish parts (intact eyeball and surface-containing scales), excitation from 220 to 585 nm and emissions from 250 to 600 nm, were measured at different times during storage. To simplify the acquired complex spectra datasets from each fish part, the variables were reduced to those that were only significant/important (those with higher positive or negative correlation) for K value prediction, and as an index of freshness. Partial least square regression (PLSR) results demonstrated that combining the fluorescence EEM of the eyeball and surface-containing scales the best monitoring of fish freshness; excitation at 280 and 350 nm for both the eyeball and surface-containing scales, with 2.84 and 0.96 as RMSE and R2, respectively. These findings demonstrate that multiple excitation fluorescence approaches can be convenient for the freshness evaluation of fish. (C) 2022 Elsevier B.V. All rights reserved.

DOI： 10.1016/j.saa.2022.121209

Web of Science

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Language：Japanese  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

This research aimed at providing a quick, and non-destructive method for estimating freshness of intact Japanese dace (Tribolodon hakonensis) fish refrigerated below 5 degrees C using multispectral imaging technique coupled with multivariate analysis techniques. The fluorescence excitation-emission matrices (EEMs) for outside parts of the fish (eyeball, scales) were taken to establish the proper excitation wavelengths. Afterwards, four lighting devices; white, 395 nm, 365 nm and 280 nm LEDs were used to illuminate the sample for capturing images using both the UV camera and a common color camera. Biochemical analysis (electrophoresis measurement) was carried out to examine fish freshness and then expressed using a reference method as K values. Both EEM and imaging data were modelled with the measured K value using partial least square (PLS) regression. A novel algorithm based on multispectral imaging data was proposed as a potential fish freshness indicator during storage. From the results, R2 of 0.94 and RMSE of 2.42% were achieved. This research demonstrated that the fluorescence multispectral imaging technique is a powerful tool with great potential in non-destructive monitoring and examining fish freshness during storage.

DOI： 10.1016/j.lwt.2021.112207

Web of Science

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.foodcont.2021.107906

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.foodchem.2019.02.119

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

Tofu is an ancient soybean product that is produced by heating soymilk containing a coagulation agent. Owing to its benefits to human health, it has become popular all over the world. An important index that determines the final product’s (tofu’s) quality is firmness. Coagulants such as CaSO4 and MgCl2 affect the firmness. With the increasing demand for tofu, a monitoring methodology that ensures high-quality tofu is needed. In our previous paper, an opportunity to monitor changes in the physical properties of soymilk by studying its optical properties during the coagulation process was implied. To ensure this possibility, whether soymilk and tofu can be discriminated via their optical properties should be examined. In this study, a He–Ne laser (Thorlabs Japan Inc., Tokyo, Japan, 2015) with a wavelength of 633 nm was emitted to soymilk and tofu. The images of the scattered light on their surfaces were discriminated using a type of deep learning technique. As a result, the images were classified with an accuracy of about 99%. We adjusted the network architecture and hyperparameters for the learning, and this contributed to the successful classification. The construction of a network that is specific to our task led to the successful classification result. In addition to this monitoring method of the tofu coagulation process, the classification methodology in this study is worth noting for possible use in many relevant agricultural fields.

DOI： 10.3390/agriengineering1020017

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

To produce high-quality citrus, the harvest time of citrus should be determined by considering its maturity. To evaluate citrus maturity, the Brix/acid ratio, which is the ratio of sugar content or soluble solids content to acid content, is one of the most commonly used indicators of fruit maturity. To estimate the Brix/acid ratio, fluorescence spectroscopy, which is a rapid, sensitive, and cheap technique, was adopted. Each citrus peel was extracted, and its fluorescence value was measured. Then, the fluorescent spectrum was analyzed using a convolutional neural network (CNN). In fluorescence spectroscopy, a matrix called excitation and emission matrix (EEM) can be obtained, in which each fluorescence intensity was recorded at each excitation and emission wavelength. Then, by regarding the EEM as an image, the Brix/acid ratio of juice from the flesh was estimated via performing a regression with a CNN (CNN regression). As a result, the Brix/acid ratio absolute error was estimated to be 2.48, which is considerably better than the values obtained by the other methods in previous studies. Hyperparameters, such as depth of layers, learning rate, and the number of filters used for this estimation, could be observed using Bayesian optimization, and the optimization contributed to the high accuracy.

DOI： 10.3390/horticulturae5010002

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.foodcont.2017.07.024

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：MDPI AG  

Monitoring the maturation process of Satsuma mandarin (Citrus unshiu Marc.) by determining the soluble solids (SS) and acid content non-destructively is needed. Fluorescence components potentially offer such means of accessing fruit maturity characteristics in the orchard. The aim of this study was to determine the potential of fluorescence spectroscopy for monitoring the stage of citrus maturity. Four major fluorescent components in peel and/or flesh were found including chlorophyll-a (excitation (Ex) 410 nm, emission (Em) 675 nm) and chlorophyll-b (Ex 460 nm, Em 650 nm),polymethoxyflavones (PMFs) (Ex 260 nm and 370 nm, Em 540 nm), coumarin (Ex 330 nm, Em 400 nm), and a tryptophan-like compound (Ex 260 nm, Em 330 nm). Our results indicated a significant (R-2 = 0.9554) logarithmic ratio between tryptophan-like compoundsExEm and chlorophyll-aExEm with the SS:acid ratio. Also, the log of the ratio of PMFs from the peel (ExExEm was significantly correlated with the SS:acid ratio (R-2 = 0.8207). While the latter correlation was not as strong as the former, it does demonstrate the opportunity to develop a non-destructive field measurement of fluorescent peel compounds as an indirect index of fruit maturity.

DOI： 10.3390/horticulturae3040051

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