Faculty Profiles - INAGAKI Tetsuya

Papers - INAGAKI Tetsuya

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Determination of true optical absorption and scattering coefficient of wooden cell wall substance by time-of-flight near infrared spectroscopy Reviewed Open Access

Ryunosuke Kitamura, Tetsuya Inagaki and Satoru Tsuchikawa

Optic Express Vol. 24 page： 3999-4009 2016

Prediction of oven-dry density of wood by time-domain terahertz spectroscopy Reviewed

Tetsuya Inagaki, Ian D. Hartley, Satoru Tsuchikawa Matthew Reid

Holzforschung 2013

Difference of Cellulosic Crystalline Structure in Wood between Hydrothermal and Ageing Degradation Observed by NIRs and XRD Reviewed

Tetsuya Inagaki, Heinz W. Siesler, Katsuya Mitsui and Satoru Tsuchikawa

Biomacromolecules Vol. 11 page： 2300 2010

Enabling moisture monitoring and deformation analysis in wood during drying by 4D-CT imaging coupled with deep learning

Zeng W., Inagaki T., Tsuchikawa S., Schajer G., Gao L., Ma T.

Industrial Crops and Products Vol. 241 2026.3

Publisher：Industrial Crops and Products

The pivotal role of wood in promoting a sustainable future is underscored by its renewable properties, carbon sequestration capabilities, and versatility across applications such as construction, furniture, and energy production. Despite these advantages, the large energy consumption involved in the wood-drying process poses substantial challenges that must be overcome to realize its sustainability potential fully. To address these challenges, we have introduced an innovative method employing U-net deep learning image registration coupled with four-dimensional computed tomography (4D-CT). This approach enables three-dimensional (3D), time-resolved visualization of moisture migration and deformation on a pixel-level resolution during the wood-drying process. Our findings reveal the intricate details of the anisotropic nature of wood and its varying behaviors within and between annual rings. These insights lay a crucial foundation for advanced modeling, simulations, and predictions, ultimately facilitating the optimization of drying schedules and enhancing wood quality. This cutting-edge methodology represents an influential advancement in nondestructive wood analysis, which is promising for revolutionizing industrial practices and contributing to more sustainable wood utilization.

DOI： 10.1016/j.indcrop.2026.122729

A field-deployable spectroscopic approach for optimizing kiwifruit harvest timing and postharvest quality management

Ma T., Inagaki T., Tsuchikawa S., Jiang H.

Postharvest Biology and Technology Vol. 231 2026.1

Publisher：Postharvest Biology and Technology

Extensive research has focused on using visible-near-infrared (Vis-NIR) spectroscopy for laboratory-based quality assessment of postharvest agricultural products. Recently, field-deployable solutions are becoming increasing available, however, assessing fruit firmness remains challenging. Along with sugar content, firmness is a critical factor because of its strong influence on fruit taste and postharvest shelf life. This study designed a portable Vis–NIR spatially resolved spectroscopic (SRS) system by integrating three modules: (1) a 36-channel fiber array was arranged in six radial distances to acquire spatially resolved diffuse reflectance profiles of 108 kiwifruit samples from each of the two kiwifruit species ‘Cuixiang’ and ‘Ruiyu’ with different forchlorfenuron (CPPU) treatments, (2) a cost-effective hyperspectral imaging camera within a wavelength range of 600–1100 nm, with a resolution of 4.5 nm combined with halogen illumination was employed to reduce the measurement time of spectral data, and (3) partial least squares (PLS) regression analysis coupled with the competitive adaptive reweighted sampling technique were developed to optimize scattering-enhanced firmness prediction and scattering-suppressed soluble solids content (SSC) quantification. Field validation using the ‘Cuixiang’ species demonstrated the operational robustness of the system, with R<inf>val</inf><sup>2</sup> = 0.65 and RMSE<inf>val</inf> = 1.23 N for firmness and R<inf>val</inf><sup>2</sup> = 0.65 and RMSE<inf>val</inf> = 1 % for SSC. In contrast, for ‘Ruiyu’ species, R<inf>val</inf><sup>2</sup> and RMSE<inf>val</inf> were 0.14 and 2.18 N for firmness, R<inf>val</inf><sup>2</sup> and RMSE<inf>val</inf> values of 0.39 and 1.45 % for SSC. This could be because ‘Ruiyu’ have thicker skin and more fine hairs, which may have interfered the light reflectance measurements of the designed device. These results highlight the potential of contact SRS as an useful tool for assessing the ripeness of ‘Cuixiang’ kiwifruit, particularly in terms of firmness.

DOI： 10.1016/j.postharvbio.2025.113888

Colour Changes of Wood Veneer as a Function of Heat Treatment Open Access

Kobori H., Salca E.A.M., Inagaki T., Suzuki S., Saad S., Chotikhun A.

Journal of Renewable Materials Vol. 14 ( 2 ) 2026

Publisher：Journal of Renewable Materials

Heat treatment is applied to wood to improve various properties of the material. The present study focuses on the colour changes of wood veneer samples due to heat treatment. Native wood species from Japan and Europe, such as Japanese oak (Quercus mongolica var. crispula), field maple (Acer campestre) and Scots pine (Pinus sylvestris) were used in the experiments. A laboratory-type oven was used to apply the heat at a temperature of 190◦C, in the presence of oxygen, for different periods, gradually increasing from 5 to 40 min. The CIELab system (a colour space defined by the International Commission on Illumination) and Near Infrared Spectroscopy (NIR) were employed to evaluate the colour modifications on the samples. As expected, the heat treatment affected the colour of the samples. The lightness index decreased across the three wood species during the treatment. The chroma coordinates changed for pine and maple, while little change occurred in Japanese oak. The overall total colour differences reached their maximum at the final 40-min interval for all wood types. Based on the NIR evaluation, it was found that drastic thermal denaturation of cellulose was unlikely to occur, and the changes in the intermolecular interaction of water affected the colour of the specimens. The data and information of this study could be useful for industrial applications where the veneer of such species is desired. Such heat-treated veneers can be considered as value-added products in furniture manufacturing as well as restoration of furniture units where such veneer is used as an overlay.

DOI： 10.32604/jrm.2025.02025-0152

Integrating image analysis and ensemble learning for predictive modeling of wood density and MC using line scanner and camera systems Open Access

Hartanto B.R., Ma T., Kurata Y., Kobori H., Tsuchikawa S., Inagaki T.

Information Processing in Agriculture 2026

Publisher：Information Processing in Agriculture

Conventional wood quality assessments often involve invasive methods that increase costs and weaken material integrity. Recent studies using machine learning, particularly convolutional neural networks (CNNs) and ensemble learning, have shown high accuracy in predicting wood density and mechanical properties from images. However, real-time evaluation of moisture content (MC) across different species remains underexplored. This research introduces a non-destructive approach that integrates 2D image analysis with an advanced ensemble learning model to predict both wood density and MC, using high-resolution images from Line Scanner and Camera Systems to extract key color features and wood attributes. A novel real-time MC determination method employing a gravimetric formula based on actual sample dimensions and weights further enhances immediate wood evaluation. The model achieves reliable predictions with a Coefficient of Determination (R<sup>2</sup>) of 0.94 for oven-dry density and 0.85 for MC, and Root Mean Square Errors (RMSE) of 0.01 g/cm<sup>3</sup> and 8.33 %, respectively, offering a precise, viable tool for real-time wood quality and moisture assessment, and advancing sustainable industry practices.

DOI： 10.1016/j.inpa.2025.11.008

Enhanced PLS subspace-based calibration transfer method for multiple spectrometers using small standardization sample sets

Li B., Taira E., Inagaki T.

Chemometrics and Intelligent Laboratory Systems Vol. 267 2025.12

Publisher：Chemometrics and Intelligent Laboratory Systems

Near-infrared spectroscopy (NIRS) calibration transfer faces significant challenges when deploying models across multiple instruments from different manufacturers, particularly because the inherently low molar absorptivity makes spectral data highly sensitive to minor variations in optical setup. This study presents two enhanced calibration transfer methods (ICTWM1 and ICTWM2) operating within the PLS latent variable space, utilizing dimensionality reduction to preserve analytically relevant variance while reducing noise interference. ICTWM1 employs spectral space transformation (SST) to correct PLS component scores between different instruments, while ICTWM2 selectively corrects the regression coefficients of the principal components with the highest variability. The methods were validated using wheat protein analysis (7 secondary instruments from manufacturers A and B) and industrial sugarcane Brix determination (8 secondary instruments across geographically distributed facilities). ICTWM1 demonstrated superior performance, achieving 79.3 % relative performance compared to the primary instrument model using only 10 standardization samples on the wheat dataset, with improved cross-instrument consistency (standard deviations of 6.9 %) compared to traditional methods (>15 %). The method exhibited no manufacturer-dependent performance bias and maintained consistent performance across sample sizes ranging from 10 to 110. Under severely constrained sugarcane dataset with only 5 training samples, both ICTWM1 and ICTWM2 achieved good performance with mean RMSEP values of 0.14°Bx and 0.15°Bx, respectively, outperforming traditional calibration transfer methods. ICTWM1 demonstrates improved sample efficiency and cross-manufacturer robustness through optimized transformation within PLS subspace. These characteristics make it a practical method for industrial NIRS applications requiring reliable calibration transfer with minimal standardization samples.

DOI： 10.1016/j.chemolab.2025.105545

Storage domains of coniferin in cell wall forming tracheid cells in Pinus thunbergii stems evaluated by cryo microscopic chemical analyses Open Access

Aoki D., Iwamaru K., Nishida S., Uchida T., Li B., Isomura Y., Yoshida M., Inagaki T., Fukushima K.

Scientific Reports Vol. 15 ( 1 ) 2025.12

Publisher：Scientific Reports

We investigated how lignin precursors are stored and used during secondary-wall formation in Pinus thunbergii stems, addressing the current lack of quantitative, spatially resolved information, especially on monolignols and their glucosides. Two complementary cryogenic workflows, microdissection (CryoMD) for µm-scale fractionation and secondary ion mass spectrometry with gas cluster ion beam (Cryo-GCIB-SIMS) for sub-µm imaging, were developed to quantify and visualize monolignols and their glucosides across defined cell-wall formation stages in compression and opposite woods of P. thunbergii. Coniferin (CF) and p-glucocoumaryl alcohol were the dominant storage forms, while free coniferyl alcohol was in trace amounts, and p-coumaryl alcohol was detected mainly in the mature xylem region; CF concentration peaked near the cambial zone and declined with cell wall thickening. GCIB-SIMS visualized CF in domains adjacent to the cell wall at the cell expansion–cell wall thickening boundary and revealed a continuous distribution over 10–20 μm along the cell axis direction. These findings indicate that monolignol glucosides reside in spatially restricted, possibly mobile storage domains that supply precursors precisely where and when lignification proceeds, refining current models of monolignol transport. The integrated cryo approach provides a framework for linking intracellular metabolism to cell and tissue-level cell wall architecture.

DOI： 10.1038/s41598-025-22822-5

Effect of Plasma Treatment on Grain Seed Preservation: Promotion and Inhibition

Yuan S., Tsuchikawa S., Inagaki T., Ma T., Hu Y., Jiang H.

Plasma Chemistry and Plasma Processing Vol. 45 ( 6 ) page： 1629 - 1659 2025.11

Publisher：Plasma Chemistry and Plasma Processing

Plasma technology has emerged as a promising approach for regulating grain seed germination, offering dual effects of promotion and inhibition depending on treatment parameters. This review synthesizes mechanisms by which cold plasma (CP) and plasma-activated water (PAW) influence seed physiology. Reactive oxygen and nitrogen species (RONS) generated during plasma treatment modify seed coat hydrophilicity through etching, enhance water uptake, and alter metabolic pathways. Moderate RONS levels stimulate antioxidant systems, hormone balance (e.g., GA/ABA ratio), and enzyme activities (e.g., amylase, superoxide dismutase), accelerating germination. Conversely, excessive RONS induce oxidative damage, inhibit enzyme function, and impair DNA/protein integrity. PAW, enriched with nitrate, nitrite, and H₂O₂, further enhances germination by improving nutrient absorption and microbial decontamination. Notably, plasma efficacy varies with seed type, treatment duration, voltage, and gas composition. Short-term, low-dose CP promotes germination in crops like maize, wheat, and rice, while prolonged exposure or high-intensity treatment suppresses it. CP also mitigates abiotic stresses (e.g., drought, salinity) by enhancing stress-responsive pathways. Despite advantages such as residue-free processing and scalability, challenges persist, including equipment costs, inconsistent treatment efficacy, and unresolved safety concerns regarding long-term environmental and health impacts. Future research should prioritize elucidating molecular interactions, optimizing protocols for diverse crops, and advancing scalable plasma systems. With further refinement, plasma technology holds significant potential to revolutionize sustainable agriculture by improving seed storage, stress resilience, and crop productivity.

DOI： 10.1007/s11090-025-10596-7

Pretreatment Technologies for Feedstock in Melt Extrusion-Based Food Additive Manufacturing: Advances and Perspectives

Ma S., Tsuchikawa S., Inagaki T., Ma T., Jiang H.

Comprehensive Reviews in Food Science and Food Safety Vol. 24 ( 6 ) 2025.11

Publisher：Comprehensive Reviews in Food Science and Food Safety

Although additive manufacturing (AM) has found widespread applications in the food industry, there are still very few food materials that can be directly printed, resulting in a scarcity of finished printed products available on the market. To broaden the applications of food AM, it is essential to pre-treat food materials to enhance their physicochemical, nutritional, and flavor properties. This review comprehensively examines the existing literature on technologies related to the preparation of feedstock for AM, highlighting advances in food pre-treatment technologies within this field. It also proposes unresolved issues and outlines future research prospects. The development of pre-treatment technologies for food AM signifies a broader integration of AM within the food industry. The materials used in food AM must possess suitable rheological properties to ensure smooth extrusion from the nozzle, as well as adequate mechanical properties to maintain the shape fidelity of the printed products. We summarize innovative treatment techniques, including novel physical field treatments, enzymatic methods, and chemical treatments, while explaining the underlying mechanisms involved. The future trajectory of 3D food products is geared towards commercialization, necessitating more advanced pre-treatment techniques to meet evolving market demands.

DOI： 10.1111/1541-4337.70326

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

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

Journal of Food Composition and Analysis Vol. 143 2025.7

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 (R<sup>2</sup>) 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

Jiasheng Zhou, Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki

Chemometrics and Intelligent Laboratory Systems Vol. 261 page： 105386 - 105386 2025.6

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

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

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

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

Growth stress (growth strain) is caused by internal stresses that develop within the wood during expansive growth and maturation. Although growth stress evaluations are critical for predicting and mitigating problems such as warping, cracking, and deformation during processing and use, conventional methods have several disadvantages, including notably high operational costs, time-consuming, and relatively destructive. This study aimed to develop a nondestructive, portable, and rapid technique that can evaluate local growth stress in standing trees. A multifiber-based visible-near-infrared (Vis-NIR) spatially resolved spectroscopic (SRS) device was, therefore, designed and used to collect light scattering and absorption information from standing trees. Principal component analysis revealed that the collected Vis-NIR SRS spectra were highly correlated with anatomical features related to growth stress, such as the difference in light scattering (particularly at approximately 846 nm) and moisture content (approximately 970 nm) inside the wood, as well as the wood surface color (approximately 660 nm). The determination coefficient for the cross-validation set was found to be 0.84 with a root mean square error of 333 με using partial least squares regression analysis. In addition to the high prediction accuracy achieved by machine learning algorithms, the results of Monte Carlo modeling of photon migration in 3D wood structure models also demonstrated that the Vis-NIR SRS approach has great potential for on-site applications, offering a new and cost-effective method for evaluating growth stress in green trees.

DOI： 10.1016/j.compag.2025.110014

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

Qian Jiang, Yanru Bao, Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki, Han Wang, Hao Jiang

Journal of Food Engineering Vol. 388 2025.3

Publishing type：Research paper (scientific journal)

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

Te Ma, Hao Jiang, Satoru Tsuchikawa, Tetsuya Inagaki

Food Chemistry Vol. 465 page： 142125 - 142125 2025.2

Authorship：Last author,　Corresponding author Publishing type：Research paper (scientific journal) Publisher：Elsevier BV

Adulteration identification in extra virgin olive oil (EVOO) is a significant concern in the olive oil industry. This study aimed to detect low-level adulteration of EVOO with other edible oils by using a novel time-resolved laser-induced fluorescence (TRLIF) fingerprinting method. Five EVOO brands were first analyzed to assess its potential for classification based on their differing fluorophore content. The developed method effectively reduces the effects associated with the optical path length and excitation light intensity. Subsequently, three sets of binary mixtures were tested: EVOO adulterated with refined olive oil, soybean oil, and sunflower oil. Quantitative analysis was performed using parallel factor analysis, which achieved a cross-validation coefficient of determination (R2) exceeding 0.90, with a prediction error < 1.40 %. These findings demonstrate that this method has the potential to determine the purity and quality of EVOO.

DOI： 10.1016/j.foodchem.2024.142125

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

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

Holzforschung Vol. 79 ( 2-3 ) page： 93 - 101 2025.1

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

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

Hidemasa Taketoshi, Tetsuya Inagaki, Satoru Tsuchikawa, Te Ma

Foods Vol. 14 ( 2 ) 2025.1

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

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

Bin Li, Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

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

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

Near-infrared (NIR) imaging is effective in monitoring the optical property changes of fruit arising from mechanical damage. However, differences in fruit geometry and size severely limit the application of bruise detection solutions. By integrating NIR hyperspectral imaging (NIR-HSI) with geometrical influence correction (GIC), this paper presents a universal bruise enhancement and detection method for early-stage bruises inspection across apple cultivars with large size variations. HSI and shape data were collected via 360° rotational scanning of Sun Fuji, Shinano Sweet, and Esopus Spitzenburg apples before and during the first 24 h post-bruising. GIC was applied as a pretreatment method. For comparison, we applied whiteboard reflectance calibration (WRC) and WRC combined with the standard normal variate (SNV) approach. Using principal component analysis (PCA), a set of effective wavelength-loading coefficients for bruise enhancement was extracted across pooled datasets of average sound and bruise spectra from different samples. The optimal coefficients, determined using logistic regression, were applied uniformly across all HSI datasets for bruise enhancement. Finally, the local Otsu method combined with connected-domain screening was applied for bruise identification. Based on spectral analysis, PCA successfully extracted bruise-related wavelength coefficients with consistent trends across cultivars, facilitating universal bruise enhancement. GIC reduced shape-related interference, improving the use of the light scattering-related PC for bruise identification. GIC coupled with the universal enhancement emerged as the most effective method, consistently achieving the highest classification accuracy, superior identification accuracies for both central and edge bruises, and the earliest peak accuracy.

DOI： 10.1016/j.postharvbio.2024.113282

Investigation of crystallinity changes in thermally-treated wood using THz time-domain spectroscopy

Wang H., Asaoka M., Tsuchikawa S., Inagaki T.

Cellulose 2025

Publisher：Cellulose

Wood is attracting attention as an environmentally friendly resource that does not burden the environment and is indispensable for the realization of a low-carbon society. In the field of construction, the use of heat-treated wood has been gaining traction in recent years for the purpose of improving dimensional stability and decay resistance. However, there have been few studies on the non-destructive measurement of the strength of heat-treated wood. Only cellulose, which accounts for about half of the major chemical components of wood, has a crystalline form, and changes in the interior of wood due to thermal treatment are thought to result from changes in this crystalline structure. Terahertz time-domain spectroscopy (THz-TDS) is suitable for crystallographic studies as the radiation energy in the THz region (0.1–10 THz; wave number 3.3–333 cm<sup>−1</sup>) corresponds to lattice vibrations (phonons) of cellulose crystals. In this study, THz-TDS was used to evaluate the crystallinity of heat-treated cellulose and heat-treated wood powder. Wood pellets were measured by THz-TDS and X-ray diffraction (XRD) before and after the thermal treatment. The absorption peaks and XRD patterns were compared, and the effects of varying the temperature and duration of thermal treatment were investigated. Results indicated that crystallinity decreased rapidly at 250 °C, while at 200 °C, the reduction was more gradual, with signs of recrystallization. These findings suggest that factors such as temperature, humidity, and removal of non-crystalline components (e.g., hemicellulose, amorphous cellulose) are key in determining crystallinity during thermal treatment of wood.

DOI： 10.1007/s10570-025-06894-0

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