Faculty Profiles - MA Te

Papers - MA Te

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Production of Nanocellulose Film from Abaca Fibers Reviewed International coauthorship

Anniver Ryan Lapuz, Satoru Tsuchikawa, Tetsuya Inagaki, Te Ma, Veronica Migo

Crystals Vol. 12 ( 5 ) 2022.5

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

Abaca fibers were subjected to a TEMPO mediated oxidation to extract nanocellulose on a 500 L capacity locally fabricated reactor. A yield of 46.7% white gel material with 2.23% solid content was obtained from an overnight reaction. Transmission electron microscopy scan of the white gel material confirms the production of relatively short highly individualized cellulose nanofibril (CNF) as the diameter of abaca fiber was reduced from 16.28 mu m to 3.12 nm with fiber length in the range of 100 nm to 200 nm. Nanocellulose film was prepared using air drying (CNF-VC) and vacuum oven drying (CNF-OD). The effect of CNF concentration on the physical, morphological, thermal and mechanical properties were evaluated. FTIR spectra showed cellulose I spectra between abaca fiber with both the CNF-VC film and CNF-OD film with two distinct peaks at 1620 cm(-1) and 1720 cm(-1) attributed to the carboxyl group resulting from the TEMPO oxidation. In addition, the carboxyl group decreases in thermal stability of cellulose. Moreover, the XRD scan showed a decrease in crystallinity index of CNF films compared to abaca fibers. CNF-VC film showed the highest tensile strength at 0.4% concentration with 88.30 MPa, while a 89.72 MPa was observed for CNF-OD film at 0.8% concentration.

DOI： 10.3390/cryst12050601

Rapid and nondestructive prediction of firmness, soluble solids content, and pH in kiwifruit using Vis-NIR spatially resolved spectroscopy Reviewed

Te Ma, Jian Zhao, Tetsuya Inagaki, Yuan Su, Satoru Tsuchikawa

POSTHARVEST BIOLOGY AND TECHNOLOGY Vol. 186 2022.4

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

This paper reports an evaluation of firmness, soluble solids content (SSC), and acidity (pH) in kiwifruit using a newly designed visible-near-infrared (Vis-NIR) spatially resolved spectroscopic (SRS) system. The system mainly comprises a cost-effective Vis-NIR hyperspectral imaging camera, a halogen light source, and 36 light-receiving silica fibers which were divided into six groups (1, 2, 3, 4, 5, and 10 mm away from the light illumination) used to collect diffusely reflected light from sample surface. During the experiment, time-resolved spectroscopy (TRS) was used to validate the light scattering characteristics at a single wavelength of 846 nm by transmission measurement, which differed from the reflectance measurement of the SRS system. The TRS results show that firmer kiwifruits tended to have a lower transmitted light intensity and a higher full width at half maximum value. The SRS results indicate that the reflected light intensity decreased more with an increased distance from the illumination spot in firmer kiwifruits. The results of the two methods supported the same view, i.e., firmer kiwifruit indicated higher degrees of light scattering inside. Following on, the calibration models for kiwifruit properties were constructed using the SRS data coupled with partial least squares regression analysis. Finally, the prediction accuracies were benchmarked against standard diffuse reflectance spectroscopy using one fiber group position of the same SRS system. The overall results showed the benefits of using the SRS system to predict fruit firmness by enhancing light scattering effects and predicting the SSC required for reducing such effects

DOI： 10.1016/j.postharvbio.2022.111841

Application of near-infrared spectroscopy to agriculture and forestry Reviewed

Satoru Tsuchikawa, Te Ma, Tetsuya Inagaki

ANALYTICAL SCIENCES Vol. 38 ( 4 ) page： 635 - 642 2022.4

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

Depending on the uniformity of the quality attribute within agricultural products, there is often a need to develop non-destructive and efficient evaluation methods to assure their qualities. Near-infrared spectroscopy (NIRS) is a well-suited method to characterize organic compounds, particularly when coupled with multivariate analysis methods. This review article introduces scientific and technical reports using the NIRS to evaluate food, agriculture, and forest products. Overall, basic spectroscopic research is continuously progressing; indeed, in combination with big-data information technology and spectral imaging techniques, material analysis is improving to maximize performance. Portable and low-cost devices have also been designed and produced, enabling remote analysis. Future advancements are expected to result in its applications in even more fields for online or at-line quality monitoring.

DOI： 10.1007/s44211-022-00106-6

Moisture transport dynamics in wood during drying studied by long-wave near-infrared hyperspectral imaging Reviewed

Te Ma, Genki Morita, Tetsuya Inagaki, Satoru Tsuchikawa

Cellulose Vol. 29 ( 1 ) page： 133 - 145 2022.1

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

The complexities of wood microstructure cause difficulties in understanding water movement characteristics during drying. Here, the water transport dynamics in softwood (Japanese cypress) with different sample lengths (30 mm, 60 mm, and 90 mm) and various drying temperatures (30 degrees C, 60 degrees C, and 90 degrees C) were studied using a rapid and high-resolution moisture content (MC) mapping method based on long-wave near-infrared hyperspectral imaging (NIR-HSI). The observations of this study are as follows: slow drying at approximately 30 degrees C, the area near the subsurface of the wood samples tends to have higher MC than the central parts during drying, especially in the case of longer wood samples. For drying at higher temperatures, strongly bonded water appeared at the surface areas much earlier, which could easily cause sample deformation and cracking. Overall, the experimental results suggest the capillary effects could play a major role at the first stage of slow drying at fiber level; then, the transfers between bound and free water could play a significant power source in the second drying stage. It is expected that this study will be of help in providing a basis to study and simulate the drying characteristics of cellular and hydrophilic materials.

DOI： 10.1007/s10570-021-04290-y

Near-infrared spectroscopy and hyperspectral imaging can aid in the prediction and mapping of polyploid acacia hybrid wood properties in tree improvement programs Reviewed

Dang Duc Viet, Te Ma, Tetsuya Inagaki, Nguyen Tu Kim, Satoru Tsuchikawa

Holzforschung Vol. 75 ( 12 ) page： 1067 - 1080 2021.12

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：WALTER DE GRUYTER GMBH

Acacia, including Acacia hybrids, are some of the most important species grown as part of the Viet-namese wood industry. Rapid methods to identify the variations in the wood properties of Acacia hybrids how -ever, are a currently lacking and creating limits for their breeding programs. In this study, nine Acacia hybrid clones, including those that were diploid, triploid, and tetraploid were evaluated using near-infrared spectros-copy (NIR) and hyperspectral imaging (HSI). The standard normal variate (SNV) and second derivative (SP2D) were applied to compare the performances of NIR and HSI using partial least square regression. The HSI images were ac-quired at wavelengths from 1033 to 2230 nm and the SNV and SP2D described the variations in the wood properties. The NIR predicted the wood physical properties better than HSI, while they provided similar predictions for the mechanical properties. The mapping results showed low densities around the pith area and high densities near the bark. They also revealed that the air-dry moisture content changed at different positions within a disk and was dependent on its position within the tree. Overall, NIR and HSI were found to be potential wood property prediction tools, suitable for use in tree improvement programs.

DOI： 10.1515/hf-2021-0024

Measuring the tensile strain of wood by visible and near-infrared spatially resolved spectroscopy Reviewed

Te Ma, Tetsuya Inagaki, Masato Yoshida, Mayumi Ichino, Satoru Tsuchikawa

Cellulose Vol. 28 ( 17 ) page： 10787 - 10801 2021.11

Parameter Optimization of Vibrating and Comb-Brushing Harvesting of Lycium barbarum L. Based on FEM and RSM Reviewed

Jian Zhao, Te Ma, Tetsuya Inagaki, Yun Chen, Guangrui Hu, Zhiwei Wang, Qingyu Chen, Zening Gao, Jianguo Zhou, Miaohai Wang, Satoru Tsuchikawa, Jun Chen

Horticulturae Vol. 7 ( 9 ) page： 286 - 286 2021.9

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

The current mechanical harvesting methods of Lycium barbarum L. are labor intensive and cause too much damage, but vibrating and comb-brushing harvesting can increase the efficiency while minimizing the damage. However, optimizing the main factors and their parameter values of vibrating and comb-brushing harvesting is challenging. To achieve the high-efficiency and low-damage harvesting of L. barbarum, firstly, the mechanical models of the materials used in the experiments were established based on the physical tests. Then, the vibrating and comb-brushing harvesting simulations were conducted based on FEM to acquire the ranges of the parameter values. The effects of the rotating speed, material, and amplitude on the harvesting rate of ripe fruit and harvesting rate of unripe fruit, as well as the damage rate of ripe fruit were determined based on RSM. Finally, the optimized parameters were obtained and verified using the field experiments. The field experiments showed that the harvesting rate of ripe fruit was 85.8%, the harvesting rate of unripe fruit was 10.5%, and the damage rate of ripe fruit was 9.7%. The findings provided the optimal parameter values, which were a design basis for the vibrating and comb-brushing harvesters of L. barbarum.

DOI： 10.3390/horticulturae7090286

Modal Analysis and Experiment of a Lycium barbarum L. Shrub for Efficient Vibration Harvesting of Fruit Reviewed

Jian Zhao, Satoru Tsuchikawa, Te Ma, Guangrui Hu, Yun Chen, Zhiwei Wang, Qingyu Chen, Zening Gao, Jun Chen

Agriculture Vol. 11 ( 6 ) page： 519 - 519 2021.6

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

The most common harvesting method of Lycium barbarum L. (L. barbarum) is manual harvesting, resulting in low efficiency and high cost. Meanwhile, the efficiency of vibration harvesting, which is considered an efficient mechanical harvesting method, can be significantly improved if the optimized resonance frequency of the shrub can be obtained. To vibration harvest fruit efficiently, a 3D model of the shrub was established based on measurements of the shape parameters, and material mechanics models of the branches were established based on physical tests. The modal analysis of the shrub based on finite element method (FEM) simulation was performed to obtain the range of resonance frequency, and the modal experiment of the shrub using acceleration sensors and an impact hammer was conducted to obtain the accurate resonance frequency. Based on the results of the modal analysis and experiment, the optimized resonance frequency was determined to be 2 Hz. The field experiment showed that the fruit fell off when the branches were vibrated at this frequency. The results provide the design basis for the efficient vibration harvesting of L. barbarum.

DOI： 10.3390/agriculture11060519

Finite Element Method Simulations and Experiments of Detachments of Lycium barbarum L. Reviewed

Jian Zhao, Te Ma, Tetsuya Inagaki, Qingyu Chen, Zening Gao, Lijuan Sun, Haoxuan Cai, Chao Chen, Chuanlin Li, Shixia Zhang, Satoru Tsuchikawa, Jun Chen

Forests Vol. 12 ( 6 ) page： 699 - 699 2021.6

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

When harvesting Lycium barbarum L., excess amounts of detachments of the half-ripe fruit, unripe fruit, flowers, and leaves significantly affect the yield and adversely affect the subsequent processing, such as drying and grading. Finite element method (FEM) simulations and experiments of detachments were performed to harvest more ripe fruit and less half-ripe fruit, unripe fruit, flowers, and leaves. Three-dimensional (3D) models of the ripe fruit, half-ripe fruit, unripe fruit, flowers, leaves, fruit calyxes (flower calyx), fruit stems (flower stem), and branches were constructed using a 3D scanner, and material mechanics models of the above parts were established based on physical tests with universal testing machines. Detachment simulations and experiments of the ripe fruit, half-ripe fruit, unripe fruit, flowers, and leaves were performed to determine the detachment mechanisms and sequences. The detachment forces of each set of two parts were obtained. The field experiments showed that the detachment force between the fruit and calyx of ripe fruit was the lowest value of these forces, and only the ripe fruit was the first to detach from the calyx when harvesting. The results provided data support on the mechanics properties of wood and the optimization basis for the harvesting method of L. barbarum.

DOI： 10.3390/f12060699

Demonstration of the applicability of visible and near-infrared spatially resolved spectroscopy for rapid and nondestructive wood classification Reviewed

Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

Holzforschung Vol. 75 ( 5 ) page： 419 - 427 2021.5

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

© 2020 Walter de Gruyter GmbH, Berlin/Boston 2020. Although visible and near-infrared (Vis-NIR) spectroscopy can rapidly and nondestructively identify wood species, the conventional spectrometer approach relies on the aggregate light absorption due to the chemical composition of wood and light scattering originating from the physical structure of wood. Hence, much of the work in this area is still limited to further spectral pretreatments, such as baseline correction and standard normal variate to reduce the light scattering effects. However, it should be emphasized that the light scattering rather than absorption in wood is dominant, and this must be effectively utilized to achieve highly accurate and robust wood classification. Here a novel method based on spatially resolved diffuse reflectance (wavelength range: 600-1000 nm) was demonstrated to classify 15 kinds of wood. A portable Vis-NIR spectral measurement system was designed according to previous simulations and experimental results. To simplify spectral data analysis (i.e., against overfitting), support vector machine (SVM) model was constructed for wood sample classification using principal component analysis (PCA) scores. The classification accuracies of 98.6% for five-fold cross-validation and 91.2% for test set validation were achieved. This study offers enhanced classification accuracy and robustness over other conventional nondestructive approaches for such various kinds of wood and sheds light on utilizing visible and short-wave NIR light scattering for wood classification.

DOI： 10.1515/hf-2020-0074

Non-destructive and fast method of mapping the distribution of the soluble solids content and pH in kiwifruit using object rotation near-infrared hyperspectral imaging approach Reviewed

Te Ma, Yu Xia, Tetsuya Inagaki, Satoru Tsuchikawa

Postharvest Biology and Technology Vol. 174 2021.4

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

© 2020 Elsevier B.V. This work aimed to offer a non-destructive and fast approach to visualizing the soluble solids content (SSC) and acidity (pH) of the whole kiwifruit. Most of the visible-near-infrared spectral imaging techniques used in postharvest fruit and vegetables assessment exhibit issues related to the identification of the quality spatial distribution within intact samples, mainly due to sampling surface curvature effects. Here, a push-broom-type NIR hyperspectral imaging camera and a sample rotation stage were combined to scan entire kiwifruit surfaces. Then, key wavelengths in the range of 1002–2300 nm were extracted for constructing SSC and pH calibration models by partial least squares regression analysis. The resulting SSC prediction accuracy was sufficiently high: the coefficient of determination (R2cv) and the root mean square error (RMSEcv) of cross-validation set were 0.74 and 0.7 %, respectively. For pH, the R2cv and RMSEcv were 0.64 and 0.14, respectively. Finally, the SSC and pH 360˚mapping results surpassed earlier works in this area that they showed a distinct spatial distribution within each intact sample. It was concluded that the proposed object rotation hyperspectral imaging approach is promising for the non-destructive prediction mapping of SSC and pH in kiwifruit or other cylindrical-shaped samples.

DOI： 10.1016/j.postharvbio.2020.111440

Rapid and nondestructive evaluation of hygroscopic behavior changes of thermally modified softwood and hardwood samples using near-infrared hyperspectral imaging (NIR-HSI) Reviewed

Te Ma, Laurence Schimleck, Tetsuya Inagaki, Satoru Tsuchikawa

Holzforschung Vol. 75 ( 4 ) page： 345 - 357 2021.4

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

© 2020 Walter de Gruyter GmbH, Berlin/Boston 2020. The objective of this work was to provide a rapid and nondestructive imaging method for evaluating the hygroscopic behavior of thermally modified lignocellulosic materials (softwood and hardwood). The difference in the hygroscopic behavior was explained by moisture content (MC) mapping results and molecular association characteristics of absorbed water (i.e. weakly, moderately, and strongly hydrogen-bonded water molecules) with wood at various relative humidities (RH). To achieve this goal, near-infrared (NIR) spectral images in the wavelength range 1816-2130 nm (covering the combination of stretching and deformation vibrations for OH) were used to visualize MC distributions over the surface of Japanese cedar and European beech samples which had been thermally treated at different temperatures. A curve fitting method was utilized to explore changes in water-wood structure characteristics based on shifts to longer wavelength in spectral signals caused by increasing MC. The curve fitting results support the recent nuclear magnetic resonance (NMR) studies that different bound water stabilities may pool in different compartments of the wood cell wall. Furthermore, water was firmly bound to wood at low RHs and H-bonds gained mobility as the number of absorbed molecules increased. It is concluded that NIR hyperspectral imaging also has the potential to be a complementary methodology for studying the transient changes of wood-water interactions before equilibrium.

DOI： 10.1515/hf-2019-0298

Rapid and nondestructive evaluation of soluble solids content (SSC) and firmness in apple using Vis–NIR spatially resolved spectroscopy Reviewed

Te Ma, Yu Xia, Tetsuya Inagaki, Satoru Tsuchikawa

Postharvest Biology and Technology Vol. 173 2021.3

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

© 2020 Elsevier B.V. Visible–near infrared (Vis–NIR) spectroscopy is a rapid and nondestructive method used to characterize organic compounds in postharvest fruit and vegetable assessment. However, developing robust calibration models is a challenge as conventional spectrometers collect only the cumulative effects of light absorption and scattering. In this study, a multifiber-based Vis–NIR spatially resolved spectra measurement system was designed for simultaneous evaluation of soluble solid content (SSC) and firmness in apple. Thirty silica fibers separated into five groups at 1, 2, 3, 4, and 5 mm away from the light illumination point and connected to a cost-effective Vis–NIR hyperspectral imaging camera were used to acquire spectral data with an improved signal-to-noise ratio (S/N) by a two-step signal averaging process (i.e., 30 camera pixels per fiber and six optical fibers per group). Reflectance ratio spectra were then calculated by dividing the diffusely reflected light intensity detected at distance d +△ by that detected at distance d to realize a light reference-free approach. Finally, the useful explanatory variables were selected by competitive adaptive reweighted sampling (CARS) to construct individual calibration models for various regions. The coefficients of determination (Rcal2) and the root mean square errors (RMSEcal) of the best-performing calibration models were approximately 0.97 and 0.20 % for SSC and 0.96 and 0.37 N for firmness, respectively. Furthermore, the predicted results were 0.92 and 0.35 % for SSC and 0.87 and 0.71 N for firmness. Our method offers low-cost and portable detection of SSC and firmness for postharvest fruit evaluation.

DOI： 10.1016/j.postharvbio.2020.111417

Rapid and nondestructive evaluation of soluble solids content (SSC) and firmness in apple using Vis-NIR spatially resolved spectroscopy

Ma, T; Xia, Y; Inagaki, T; Tsuchikawa, S

POSTHARVEST BIOLOGY AND TECHNOLOGY Vol. 173 2021.3

Wooden Material and Environmental Sciences Invited Reviewed

Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki

Near-Infrared Spectroscopy: Theory, Spectral Analysis, Instrumentation, and Applications page： 361 - 379 2020.11

Authorship：Lead author Language：English Publishing type：Part of collection (book)

Near-infrared spectroscopy (NIRS) is suitable for both the qualification and quantification of organic properties associated with C-H, O-H, or N-H groups. There have been considerable efforts made toward proposing and developing various technologies and devices for the rapid and nondestructive measurement of various samples related to natural materials and environmental sciences. In this chapter, the utilizations of NIRS in the fields of wood material, soil, sediment, waste liquid, atmospheric gas detection, and archeological science will be explained through some representative studies.

DOI： 10.1007/978-981-15-8648-4_16

Rapid and non-destructive seed viability prediction using near-infrared hyperspectral imaging coupled with a deep learning approach Reviewed

Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki

Computers and Electronics in Agriculture Vol. 177 2020.10

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

© 2020 Elsevier B.V. Seeds are the basis of the agricultural food industry, greater insights into seed viability before sowing could improve storage management and field performance. In the present study, we aimed to address this issue by using highly cost-efficient near-infrared hyperspectral imaging (NIR-HSI) and a convolutional neural network (CNN) deep learning approach. An NIR-HSI camera was used because it can recognize both molecular vibration information (i.e. chemical component differences) and its spatial distribution in each seed sample; this camera is much more informative than a regular RGB digital camera. Using this technology, the emphasis of this study was firstly to provide a methodology for enhancing the interpretability of viable and non-viable seeds via principal component analysis (PCA) and support vector machine (SVM) viability classification analysis of NIR-HSI data. A CNN was then constructed to“cognize” the differences in viable and non-inviable seeds and classify them automatically. Experimental results indicate that the methodology produces a ~90% classification accuracy for both a five-fold cross-validation set and a test set of naturally aged Japanese mustard spinach seeds. Therefore, this study provides a new strategy for effective and practical seed viability prediction.

DOI： 10.1016/j.compag.2020.105683

Rapid and nondestructive evaluation of hygroscopic behavior changes of thermally modified softwood and hardwood samples using near-infrared hyperspectral imaging (NIR-HSI) Reviewed

Holzforschung 2020.8

Physical and mechanical properties of fast growing polyploid acacia hybrids (A. auriculiformis x A. mangium) from Vietnam Reviewed

Dang Duc Viet, Te Ma, Tetsuya Inagaki, Nguyen Tu Kim, Nghiem Quynh Chi, Satoru Tsuchikawa

Forests Vol. 11 ( 7 ) 2020.7

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

© 2020 by the authors. Acacia plants are globally important resources in the wood industry, but particularly in Southeast Asian countries. In the present study, we compared the physical and mechanical properties of polyploid Acacia (3x and 4x) clones with those of diploid (2x) clones grown in Vietnam. We randomly selected 29 trees aged 3.8 years from different taxa for investigation. BV10 and BV16 clones represented the diploid controls; X101 and X102 were the triploid clones; and AA-4x, AM-4x, and AH-4x represented neo-tetraploid families of Acacia auriculiformis, Acacia mangium, and their hybrid clones. The following metrics were measured in each plant: stem height levels, basic density, air-dry equilibrium moisture content, modulus of rupture (MOR), modulus of elasticity (MOE), compression strength, and Young's modulus. We found that the equilibrium moisture content significantly differed among clones, and basic density varied from pith-to-bark and in an axial direction. In addition, the basic density of AA-4x was significantly higher than that of the control clones. Furthermore, the MOR of AM-4x was considerably lower than the control clones, whereas the MOE of X101 was significantly higher than the control values. The compression strength of AM-4x was significantly lower than that of the control clones, but AH-4x had a significantly higher Young's modulus. Our results suggest that polyploid Acacia hybrids have the potential to be alternative species for providing wood with improved properties to the forestry sector of Vietnam. Furthermore, the significant differences among the clones indicate that opportunities exist for selection and the improvement of wood quality via selective breeding for specific properties.

DOI： 10.3390/f11070717

Rapidly visualizing the dynamic state of free, weakly, and strongly hydrogen-bonded water with lignocellulosic material during drying by near-infrared hyperspectral imaging Reviewed

Te Ma, Tetsuya Inagaki, Satoru Tsuchikawa

Cellulose 2020

Cognitive spectroscopy for wood species identification: Near infrared hyperspectral imaging combined with convolutional neural networks Reviewed

Hideaki Kanayama, Te Ma, Satoru Tsuchikawa, Tetsuya Inagaki

Analyst Vol. 144 ( 21 ) page： 6438 - 6446 2019.11

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

© 2019 The Royal Society of Chemistry. From the viewpoint of combating illegal logging and examining wood properties, there is a contemporary demand for a wood species identification system. Several nondestructive automatic identification systems have been developed, but there is room for improvement to construct a highly reliable model. The present study proposes cognitive spectroscopy that combines near infrared hyperspectral imaging (NIR-HSI) with a deep convolutional neural network approach. We defined "cognitive spectroscopy" as a protocol that extracts features from complex spectroscopic data and presents the best results without human intervention. Overall, 120 samples representing 38 hardwood species were scanned using an NIR-HSI camera. A deep learning prediction model was built based on the principal component (PC) images obtained from the PC scores of hyperspectral images (wavelength range: 1000-2200 nm at approximately 6.2 nm interval). The results showed that the accuracy of wood species identification based on 6PC (PC1-PC6) images was 90.5%, which was considerably higher than the accuracy of 56.0% obtained with conventional visible images.

DOI： 10.1039/c9an01180c

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