Faculty Profiles - TSUCHIKAWA, Satoru

Papers - TSUCHIKAWA, Satoru

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Development of a three-dimensional near-infrared hyperspectral imaging technique for non-destructive visualization of soluble solids content in kiwifruit Reviewed

Yamaguchi, K; Li, B; Inagaki, T; Tsuchikawa, S; Ma, T

JOURNAL OF FOOD COMPOSITION AND ANALYSIS Vol. 143 2025.7

Language：English Publishing type：Research paper (scientific journal) Publisher：Journal of Food Composition and Analysis

Although recent advances in near-infrared hyperspectral imaging (NIR-HSI) have shown promise for non-invasive quality assessment of various agricultural products, challenges remain in correcting the effects caused by curvature and variability in sample shapes. This study has investigated a novel approach that combines a push-broom line-scanning NIR-HSI camera, sample rotator, and 3D laser profiler to simultaneously capture the spectral imaging and surface geometry data of kiwifruit. Subsequently, angle and height corrections were applied to the hyperspectral data using Lambert-based and calibration-based methods, respectively. Finally, partial least squares (PLS) regression analysis was employed to develop soluble solid content (SSC) calibration models for further mapping analysis. Overall, the coefficients of determination (R2) and the root mean squared error (RMSE) were 0.61 and 0.54 % for the calibration set, 0.52 and 0.52 % for the validation set, respectively. In contrast to previous NIR-HSI studies, although the enhancement of the average SSC prediction accuracy through PLS regression analysis was not truly achieved, the corrected models effectively mitigated the influence of geometric shape distortions. This adjustment enabled the non-destructive 3D visualization of the SSC distribution across the entire surface of the kiwifruit. In the mapping test, despite variations in sample sizes, the differences in SSC among the samples were clearly identifiable, which also underscores the importance of shape correction in spectral image data. These findings demonstrate that this method has the potential to revolutionize the quality evaluation of irregularly shaped agricultural products.

DOI： 10.1016/j.jfca.2025.107556

Improvement of hyperspectral imaging signal quality using filtering technique Reviewed Open Access

Zhou, JS; Ma, T; Tsuchikawa, S; Inagaki, T

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS Vol. 261 2025.6

Language：English Publishing type：Research paper (scientific journal) Publisher：Chemometrics and Intelligent Laboratory Systems

This paper proposes to improve signal quality in hyperspectral imaging (HSI) on the basis of noise analysis and filtering method. HSI technology enables nondestructive and precise analysis in agriculture and food industries by acquiring high-resolution images over multiple wavelengths, but the identification and removal of noise in the signal is a challenge. In this study, HSI measurement data of sucrose solution samples of different concentrations were used as experimental subjects. The outliers outside the three-fold standard deviation range of all data were identified as noise and a filtering method using noise mask and Wavelet transform was proposed. By evaluating the effect of the filtering method on noise reduction, we conducted qualitative and quantitative analysis and comparison, mainly through statistical methods and the limits of detection (LOD), LODmin and LODmax. The experiment results show that the proposed method is useful in removing noise, reducing the detection limit when applying Partial Least Squares (PLS) and improving the HSI signal quality. This is expected to improve the accuracy of nondestructive analysis using HSI data.

DOI： 10.1016/j.chemolab.2025.105386

Evaluating goji berry<i> (Lycium</i><i> barbarum</i> L.) quality change during storage using color and fluorescence imaging system Reviewed

Chen, QY; Ma, T; Wei, NS; Fan, YL; Zhang, W; Wang, ZY; Tsuchikawa, S; Chen, Y; Chen, J

JOURNAL OF FOOD COMPOSITION AND ANALYSIS Vol. 141 2025.5

Language：English Publishing type：Research paper (scientific journal) Publisher：Journal of Food Composition and Analysis

The consumption of fresh goji berries has become an increasingly popular trend in China. However, they have a relatively short shelf life and are highly susceptible to rapid deterioration. This study measured the excitation-emission matrix (EEM) of goji berries during storage. Based on these results, a system was developed that integrates UVA LED light sources and an industrial camera to capture both color and fluorescence images. In the experiment, color and fluorescence images of the berries were captured at 24-hour intervals, and their firmness was assessed. The HSV, RGB, and Lab color space components of the images were extracted. The relationships between these color components and goji berry quality were analyzed using simple linear regression and partial least squares regression (PLSR). A regression model was developed to evaluate berry firmness. The PLSR model's coefficients of determination (R²) for calibration, prediction, and cross-validation were 0.91, 0.89, and 0.86, respectively, with corresponding root mean square errors (RMSE) of 0.11, 0.13, and 0.14. The results show that the proposed imaging detection system enables non-contact firmness measurement of fresh goji berries, offering a cost-effective solution with significant potential for broader applications.

DOI： 10.1016/j.jfca.2025.107342

Design and development of a portable Vis-NIR spatially resolved spectroscopic device for nondestructive and rapid evaluation of growth stress in standing trees Reviewed Open Access

Te Ma, Hiroyuki Yamamoto, Takusu Kajimura, Tetsuya Inagaki, Satoru Tsuchikawa

Computers and Electronics in Agriculture Vol. 231 page： 110014 - 110014 2025.4

Examination of SWIR hyperspectral imaging for estimating corewood – outerwood transition age for Douglas-fir grown at different planting densities Reviewed

Ighoyivwi Onakpoma, Te Ma, Laurence R. Schimleck, Tetsuya Inagaki, Satoru Tsuchikawa

Holzforschung Vol. 79 ( 2-3 ) page： 93 - 101 2025.3

Language：English Publishing type：Research paper (scientific journal) Publisher：Walter de Gruyter GmbH

Abstract

Silvicultural practices, particularly planting density (PD), significantly affect the wood quality of plantation-grown trees by influencing the age of transition from corewood to outerwood. Determining transition age (TA) is challenging. Near infrared hyperspectral imaging was used to assess the age of transition from corewood to outerwood in Douglas-fir (Pseudotsuga menziesii) grown under different PD. Wood samples were taken from permanent research plots with six PD ranging from 2,990 to 248 stems/hectare. Twenty trees were destructively sampled at age 25, and wood discs were collected at 10 % of total tree height. Pith-to-bark radial strips obtained from each disc were scanned using a compovision hyperspectral imaging system (1,002–2,350 nm). Partial least square discriminant analysis (PLS-DA) models were fitted to approximate TA using hyperspectral data representative of corewood and outerwood. PD influenced TA and the duration over which it occurred. Average age of transition was estimated to vary from 10 (closest spacing) to 14 years (widest). Closely spaced trees exhibited an abrupt transition, while widely spaced trees had a more gradual transition. However, PLS-DA likely underestimated the transition duration for widely spaced trees, as their average ring densities did not yet match those typical of outerwood based on X-ray densitometry data.

DOI： 10.1515/hf-2024-0058

Other Link： https://www.degruyter.com/document/doi/10.1515/hf-2024-0058/pdf

Intelligent monitoring of post-processing characteristics in 3D-printed food products: A focus on fermentation process of starch-gluten mixture using NIR and multivariate analysis Reviewed

Jiang, Q; Bao, YR; Ma, T; Tsuchikawa, S; Inagaki, T; Wang, H; Jiang, H

JOURNAL OF FOOD ENGINEERING Vol. 388 2025.3

Language：English Publishing type：Research paper (scientific journal) Publisher：Journal of Food Engineering

The production of three-dimensional (3D)-printed food products requires not only optimal 3D-printing adaptability but also appropriate post-processing characteristics. This study aimed to use near infrared (NIR) spectroscopy to predict the rheological properties of 3D-printed dough, enabling intelligent monitoring of the dough's fermentation process. Utilizing support vector machine (SVM) classification model, the fermentation stages can be classified as under-fermentation, complete fermentation, and over-fermentation. Employing preprocessing methods with Synergy Interval Partial Least Square-Competitive Adaptive Reweighted Sampling (SIPLS-CARS) algorithm, 27, 39, 23, and 27 key wavelengths were filtered from the raw NIR spectral data, corresponding to the prediction of storage modulus (G′), loss modulus (G″), complex viscosity (η∗), and loss factor (tan δ), respectively. Quantitatively, SVM (Support Vector Machine) regression outperformed Partial Least Squares (PLS) with Rc2 values (0.95, 0.94, 0.94) and Rp2 values (0.93, 0.93, 0.94) for G′, G″, and η∗. NIR spectra-based predictive models demonstrated superior performance compared to rheo-fermentation properties models. In summary, these findings show the potential of NIR spectroscopy as a rapid tool for predicting the fermentation progress of 3D-printed doughs.

DOI： 10.1016/j.jfoodeng.2024.112357

Development of a time-resolved laser-induced fluorescence fingerprinting method for detecting low-level adulteration in extra virgin olive oil Reviewed Open Access

Te Ma, Hao Jiang, Satoru Tsuchikawa, Tetsuya Inagaki

Food Chemistry Vol. 465 ( Pt 2 ) page： 142125 - 142125 2025.2

Enhanced detection of early bruises in apples using near-infrared hyperspectral imaging with geometrical influence correction for universal size adaptation Reviewed Open Access

Bin Li, Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

Postharvest Biology and Technology Vol. 219 page： 113282 - 113282 2025.1

The Detection of Pest Contaminants in Chocolate Using Visible-Near-Infrared Single-Pixel Imaging Technology Reviewed Open Access

Hidemasa Taketoshi, Tetsuya Inagaki, Satoru Tsuchikawa, Te Ma

Foods Vol. 14 ( 2 ) 2025.1

Language：English Publishing type：Research paper (scientific journal)

Food safety is gaining increasing attention worldwide. Currently, low-density organic foreign objects such as insects are extremely challenging to detect using conventional metal detectors and X-ray inspection systems. This study aimed to develop a visible-near-infrared single-pixel imaging (Vis-NIR-SPI) method to detect small insects inside food. The advantages of Vis-NIR light include its ability to analyze samples non-destructively and measure multiple components simultaneously and quickly, while SPI is robust against dark noise, high scattering, and high equipment costs. The experimental results demonstrated that (1) the newly designed system effectively reduces scattering effects from the highly scattering sample (intralipid 20%), allowing for the capture of information beyond the capabilities of a charge-coupled-device camera; (2) insects positioned behind ham and bread were readily detectable using the imaging reconstruction algorithm; and (3) even for chocolate samples with very high light absorption, only 1 uncontaminated sample out of 100 was mistakenly classified as contaminated, yielding an overall accuracy of 99%. This high level of accuracy underscores the potential of the Vis-NIR-SPI method to provide reliable detection while maintaining sample integrity. Furthermore, this method is cost-effective, offering a practical and efficient solution to improve quality control processes and consumer trust in the food industry.

DOI： 10.3390/foods14020206

The effects of growth rate on the age dependent variation of wood properties evaluated by differential geometry Reviewed

Takaaki Fujimoto, Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

Industrial Crops and Products Vol. 222 2024.12

Language：English Publishing type：Research paper (scientific journal)

A correct understanding of the variations seen in wood properties with tree age is of great importance for both the forestry and timber industries. However, this phenomenon is complex because of the differences between individuals and the variations associated with multiple wood properties. In this study, we have identified age-dependent changes in the state of wood as a surface that contains comprehensive information on the coupled variation of multiple properties in many individuals. By comparing the geometric quantities of the surface between sample groups with different growth rates caused by silvicultural treatments, we have discussed the ideal forest management in terms of wood quality and forest ecosystems. The slow-growing group showed larger Gaussian curvatures of the surface and a more tortuous and longer geodesic than the fast-growing group, resulting in less energy loss during tree growth. Assuming that processes with high symmetry are more sustainable, the characteristic class representing the global structure of the growth process indicates that the slow-growing group follows a more sustainable process than the fast-growing group. These results indicate that it is ideal for trees to grow slowly, in terms of variation of wood properties and forest ecosystem. Because the geometric quantities are invariant under coordinate transformations, the proposed methods provide us with the intrinsic behavior of the tree growth process independent of a specific coordinate system, that is, a concrete space spanned by the measured wood properties.

DOI： 10.1016/j.indcrop.2024.119596

Enhanced quantification of chlorophyll a and its degradation products in olive oil using time-resolved laser-induced fluorescence fingerprint analysis Reviewed Open Access

Te Ma, Hao Jiang, Satoru Tsuchikawa, Tetsuya Inagaki

Food Chemistry Vol. 460 ( Pt 3 ) page： 140656 2024.12

Language：English Publishing type：Research paper (scientific journal)

Potential errors in the fluorescence analysis of chlorophylls and their degradation products, primarily due to spectral overlap and inner filter, are widely acknowledged. This study aimed to devise a sensitivity-enhanced technique for the concurrent quantification of chlorophyll a and its degradation products while minimizing effects from type-B chlorophylls. Initially, a time-resolved laser-induced fluorescence spectroscopic system was designed and tested on stardard chlorophyll samples. The origins, implications, and mitigation strategies of spectral overlap and the inner filter effect on the measured fluorescence intensity were thoroughly examined. Then, this methodology was proved to be efficacious within complex liquid matrices derived from olive oil. The experimental outcomes not only shed additional light on the mechanisms of chlorophyll fluorescence overlap and the inner filter effect, but also establish a general framework for developing spectrally and timely resolved fluorescence fingerprint analysis for the simultaneous quantification of chlorophylls and their degradation products at high concentrations.

DOI： 10.1016/j.foodchem.2024.140656

Validation Study on the Practical Accuracy of Wood Species Identification via Deep Learning from Visible Microscopic Images Reviewed Open Access

Te Ma, Fumiya Kimura, Satoru Tsuchikawa, Miho Kojima, Tetsuya Inagaki

BioResources Vol. 19 ( 3 ) page： 4838 - 4851 2024.8

Language：English Publishing type：Research paper (scientific journal)

This study aimed to validate the accuracy of identifying Japanese hardwood species from microscopic cross-sectional images using convolutional neural networks (CNN). The overarching goal is to create a versatile model that can handle microscopic cross-sectional images of wood. To gauge the practical accuracy, a comprehensive database of microscopic images of Japanese hardwood species was provided by the Forest Research and Management Organization. These images, captured from various positions on wood blocks, different trees, and diverse production areas, resulted in substantial intra-species image variation. To assess the effect of data distribution on accuracy, two datasets, D1 and D2, representing a segregated and a non-segregated dataset, respectively—from 1,000 images (20 images from each of the 50 species) were compiled. For D1, distinct images were allocated to the training, validation, and testing sets. However, in D2, the same images were used for both training and testing. Furthermore, the influence of the evaluation methodology on the identification accuracy was investigated by comparing two approaches: patch evaluation and E2 image evaluation. The accuracy of the model for uniformly sized images was approximately 90%, whereas that for variably sized images it was approximately 70%.

DOI： 10.15376/biores.19.3.4838-4851

Analysis of the Pomelo Peel Essential Oils at Different Storage Durations Using a Visible and Near-Infrared Spectroscopic on Intact Fruit Reviewed Open Access

Sirisomboon, P; Duangchang, J; Phanomsophon, T; Lapcharoensuk, R; Shrestha, BP; Kasemsamran, S; Thanapase, W; Pornchaloempong, P; Tsuchikawa, S

FOODS Vol. 13 ( 15 ) 2024.8

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

Pomelo fruit pulp mainly is consumed fresh and with very little processing, and its peels are discarded as biological waste, which can cause the environmental problems. The peels contain several bioactive chemical compounds, especially essential oils (EOs). The content of a specific EO is important for the extraction process in industry and in research units such as breeding research. The explanation of the biosynthesis pathway for EO generation and change was included. The chemical bond vibration affected the prediction of EO constituents was comprehensively explained by regression coefficient plots and x-loading plots. Visible and near-infrared spectroscopy (VIS/NIRS) is a prominent rapid technique used for fruit quality assessment. This research work was focused on evaluating the use of VIS/NIRS to predict the composition of EOs found in the peel of the pomelo fruit (Citrus maxima (J. Burm.) Merr. cv Kao Nam Pueng) following storage. The composition of the peel oil was analyzed by gas chromatography–mass spectrometry (GC-MS) at storage durations of 0, 15, 30, 45, 60, 75, 90, 105 and 120 days (at 10 °C and 70% relative humidity). The relationship between the NIR spectral data and the major EO components found in the peel, including nootkatone, geranial, β-phellandrene and limonene, were established using the raw spectral data in conjunction with partial least squares (PLS) regression. Preprocessing of the raw spectra was performed using multiplicative scatter correction (MSC) or second derivative preprocessing. The PLS model of nootkatone with full MSC had the highest correlation coefficient between the predicted and reference values (r = 0.82), with a standard error of prediction (SEP) of 0.11% and bias of 0.01%, while the models of geranial, β-phellandrene and limonene provided too low r values of 0.75, 0.75 and 0.67, respectively. The nootkatone model is only appropriate for use in screening and some other approximate calibrations, though this is the first report of the use of NIR spectroscopy on intact fruit measurement for its peel EO constituents during cold storage.

DOI： 10.3390/foods13152379

Evaluating Soluble Solids in White Strawberries: A Comparative Analysis of Vis-NIR and NIR Spectroscopy Reviewed Open Access

Hayato Seki, Haruko Murakami, Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki

Foods Vol. 13 ( 14 ) 2024.7

Language：English Publishing type：Research paper (scientific journal)

In recent years, due to breeding improvements, strawberries with low anthocyanin content and a white rind are now available, and they are highly valued in the market. Strawberries with white skin color do not turn red when ripe, making it difficult to judge ripeness. The soluble solids content (SSC) is an indicator of fruit quality and is closely related to ripeness. In this study, visible–near-infrared (Vis-NIR) spectroscopy and near-infrared (NIR) spectroscopy are used for non-destructive evaluation of the SSC. Vis-NIR (500–978 nm) and NIR (908–1676 nm) data collected from 180 samples of “Tochigi iW1 go” white strawberries and 150 samples of “Tochigi i27 go” red strawberries are investigated. The white strawberry SSC model developed by partial least squares regression (PLSR) in Vis-NIR had a determination coefficient R2p of 0.89 and a root mean square error prediction (RMSEP) of 0.40%; the model developed in NIR showed satisfactory estimation accuracy with an R2p of 0.85 and an RMSEP of 0.43%. These estimation accuracies were comparable to the results of the red strawberry model. Absorption derived from anthocyanin and chlorophyll pigments in white strawberries was observed in the Vis-NIR region. In addition, a dataset consisting of red and white strawberries can be used to predict the pigment-independent SSC. These results contribute to the development of methods for a rapid fruit sorting system and the development of an on-site ripeness determination system.

DOI： 10.3390/foods13142274

Cellulose crystalline structure and thermal properties under heat treatment: An investigation by two-dimensional correlation of near infrared spectroscopy and differential scanning calorimetry Reviewed

Siti Hanifah Mahdiyanti, Masaki Asaoka, Tetsuya Inagaki, Satoru Tsuchikawa

Journal of Near Infrared Spectroscopy Vol. 32 ( 3 ) page： 113 - 124 2024.6

Language：English Publishing type：Research paper (scientific journal)

This study investigated the thermal behavior and crystallinity of microcrystalline cellulose (MCC) under heat treatment using near infrared (NIR) spectroscopy and differential scanning calorimetry (DSC). The results showed that heat treatment reduced the crystallinity and thermal stability of MCC at a certain point, and that the changes in the chemical components and structure of MCC were correlated with the heat flow measured by DSC. The analysis was performed using two-dimensional correlation spectroscopy (2DCOS), which revealed the simultaneous changes in the NIR second-derivative spectra and the DSC thermograms of heat-treated MCC. Linear regression analysis showed a high r2 value of 0.90 between the DSC enthalpy change at 270 °C–400°C and the PC1 score of NIR second-derivative spectra at 7500–4100 cm−1. The 2DCOS synchronous map showed a positive correlation at 6656–6229 cm−1 with a r value of 0.70–0.98 for the endothermic reaction, and a negative correlation at 6229; 5620; 5401; 4844; 4535 cm−1 with a r value of −0.90 to −0.99 for the exothermic reaction. This study extended the knowledge on the thermal behavior and decomposition mechanisms of heat-treated MCC, and provided a useful method for cellulose characterization and identification.

DOI： 10.1177/09670335241257649

Effect of dielectric barrier discharge (DBD) plasma treatment on physicochemical and 3D printing properties of wheat starch Reviewed

Ma, S; Ma, T; Tsuchikawa, S; Inagaki, T; Wang, H; Jiang, H

INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES Vol. 269 ( Pt 2 ) page： 132159 2024.6

Language：English Publishing type：Research paper (scientific journal) Publisher：International Journal of Biological Macromolecules

In recent years, the focus has shifted towards carbohydrate-based hydrogels and their eco-friendly preparation methods. This study involved an investigation into the treatment of wheat starch using dielectric barrier discharge (DBD) plasma technology over varying time gradients (0, 2, 5, 10, 15, and 20 min). The objective was to systematically examine the impact of different treatment durations on the physicochemical properties of wheat starch and the suitability of its gels for 3D printing. Morphology of wheat starch remained intact after DBD treatment. However, it led to a reduction in the amylose content, molecular weight, and crystallinity. This subsequently resulted in a decrease in the pasting temperature and viscosity. Moreover, the gels of the DBD-treated starch exhibited superior 3D printing performance. After a 2-min DBD treatment, the 3D printed samples of the wheat starch gel showed no significant improvements, as broken bars were evident on the surface of the 3D printed graphic, whereas DBD-20 showed better printing accuracy and surface structure, compared to the original starch without slumping. These results suggested that DBD technology holds potential for developing new starch-based gels with impressive 3D printing properties.

DOI： 10.1016/j.ijbiomac.2024.132159

Terahertz time-domain spectroscopy as a novel tool for crystallographic analysis in cellulose: tracking lattice changes following physical treatments Reviewed Open Access

Wang, H; Aoki, D; Teramoto, Y; Tsuchikawa, S; Inagaki, T

CELLULOSE Vol. 31 ( 7 ) page： 4085 - 4098 2024.5

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

The authors’ series of studies aimed to explore the potential of terahertz time-domain spectroscopy (THz-TDS) in cellulose crystallographic studies, since THz radiation can detect most intermolecular vibrations and respond to lattice phonons. In this study, we tracked changes in four types of cellulose after ball milling. As the planetary ball milling time increases, it is observed through electron microscopy that the four types of cellulose particles are gradually destroyed into finer particles, while gel permeation chromatography can prove that the molecular weight gradually decreases after ball milling and the dispersity gradually approaches one, which indicates that the dispersion of the material was reduced. The most fascinating observation was made by THz-TDS, that is we have confirmed that after ball milling, the absorption characteristics of cellulose I and II in cellulose I treated with 10% NaOH (crystalline partial transition from cellulose I to II) exhibited an opposite trend. Specifically, the absorption of cellulose II at 2.40THz and 2.77THz increased, while the absorption of cellulose I at 2.11THz and 3.04THz decreased after ball milling, which suggests an increased conversion rate of cellulose I to cellulose II post-milling. Cellulose with different crystalline allomorphs shows different characteristic absorption in the THz region, and the peak position will not change even after the ball milling, only the absorption intensity changes. Although it can be observed through the most traditional X-ray diffraction method that the crystallinity index of all cellulose samples gradually decreases after ball milling. However, different from the THz results, the change after ball milling of cellulose I treated with 10% NaOH is only reflected in very subtle pattern changes, that is, the peak close to the 200 crystalline plane position is slightly shifted after ball milling.

DOI： 10.1007/s10570-024-05834-8

Development of a sensitivity-enhanced fluorescence lifetime spectroscopic method for nondestructive quality monitoring of mature tomatoes during storage Reviewed

Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

Scientia Horticulturae Vol. 330 2024.4

Language：English Publishing type：Research paper (scientific journal)

The decay of fluorescence lifetime (FLT) is an absolute indication for observing the environment surrounding the fluorescent molecules. This study presents the characterization of fluorescence intensity and the FLT in tomatoes, spanning from the green to the red stage, using a novel time-resolved and laser-induced fluorescence (TRLIF) spectroscopic system. Furthermore, the applicability of this method was assessed for evaluating the postharvest quality of commercially acquired red tomatoes. The results collectively indicate a progressive decrease in the FLT of the red tomatoes throughout shelf-life storage. The average FLT loss decreased by approximately 17, 26, 32, and 38% after 1, 2, 3, and 4 d, respectively. Furthermore, the first principal component scores of the time-resolved spectra were confirmed to be stable for early quality degradation monitoring purposes. This investigation highlights that the devised TRLIF spectroscopic technique is a non-destructive and robust method for studying the degradation of fluorescent compounds. It facilitates an in-depth exploration of the underlying mechanisms behind the fluorescent phenomena in postharvest research.

DOI： 10.1016/j.scienta.2024.113059

Three-dimensional visualization and detection of early bruise in apple based on near-infrared hyperspectral imaging coupled with geometrical influence correction Reviewed

Li, B; Ma, T; Bai, LS; Inagaki, T; Seki, H; Tsuchikawa, S

POSTHARVEST BIOLOGY AND TECHNOLOGY Vol. 210 2024.4

Language：English Publishing type：Research paper (scientific journal) Publisher：Postharvest Biology and Technology

Visible-near-infrared (Vis-NIR) spectral imaging holds great promise for the automatic detection of fruit defects. However, uneven brightness resulting from fruit geometry and the limitations of one-directional imaging significantly restrict the current detection to a limited area. This study presents a rotation measurement system that combines a line-scan NIR-hyperspectral imaging (HSI) camera with a laser profile. A total of 72 apple samples with bruises in the central and edge regions were prepared. A 360° scanning approach was employed to collect HSI and shape data from the entire surface of the samples over a 6-h post-bruising period. Height and angle corrections were applied to eliminate the surface geometric influences on the HSI data, resulting in improved reflectance spectrum uniformity. A two-step principal component analysis method was employed for image enhancement, followed by a straightforward bruise detection technique using global segmentation and connected-domain selection. The results demonstrated an overall improvement in bruise detection over time. Moreover, the correction significantly enhanced the detection accuracy. After 6 h of bruising, the corrected data achieved a classification accuracy of 90.3% and an identification rate of 83.3% for central bruises and 61.1% for edge bruises, whereas the uncorrected data yielded 70.8%, 58.3%, and 31.9%, respectively. Thus, this study successfully detected early bruising across the entire surface of apples and improved the detection in low-intensity edge areas. The proposed method has the potential to contribute to the comprehensive evaluation of agricultural products with irregular geometries.

DOI： 10.1016/j.postharvbio.2023.112753

Non-Destructive Near-Infrared Moisture Detection of Dried Goji (<i>Lycium barbarum</i> L.) Berry Reviewed Open Access

Kang, R; Ma, T; Tsuchikawa, S; Inagaki, T; Chen, J; Zhao, J; Li, DD; Cui, GP

HORTICULTURAE Vol. 10 ( 3 ) 2024.3

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

To detect the moisture of dried Goji (Lycium barbarum L.) berries nondestructively, a near-infrared (NIR) hyperspectral imager was used for experiments. NIR hyperspectral data were obtained and processed by standard normal variate (SNV) calculation using the MATLAB software v.R2016a. On the basis of the actual moisture of dried Goji berries, the predicted moisture was obtained based on the partial least squares (PLS) algorithm and a prediction model for the moisture of dried goji berries was established. It was found that the moisture of dried Goji berries was responsive to the NIR hyperspectral imager. The established prediction model could accurately predict the moisture of dried goji berries, and its R2-value was 0.9981. The results provide a theoretical basis for the design of non-destructive moisture-detecting equipment for dried Goji berries.

DOI： 10.3390/horticulturae10030302

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