Country：Japan

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

Scopus

Publishing type：Research paper (scientific journal)  

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

Scopus

Publishing type：Research paper (scientific journal)  

Particle size ratio, tablet thickness, and compaction pressure are three important tableting parameters that affect the obtained tablet spectrum. In this study, the single-factor test and response surface analysis (RSM) were adopted to examine how these three parameters and their interactions affect the analytical measurements performed over terahertz time-domain spectroscopy (THz-TDS). Tablet samples were composed of a different percent (wt-%) of acetylsalicylic acid within microcrystalline cellulose. Results indicate that change in absorption coefficient was found to be more obvious for a larger particle size ratio. Thinner tablets were sensitive to absorption coefficient effects created as the transmitted THz radiation propagates through the tablet interfaces. Compression pressure has a limited effect on the absorption coefficient. The particle size ratio had the largest effect on the coefficient of correlation of the quantitative regression model, followed by the compaction pressure, and the tablet thickness. In this study, the optimized tableting parameters were determined: tablet thickness of 0.48 mm, particle size ratio of about 1:1, and compaction pressure of 30 MPa. Under this condition, the R2 of the quantitative regression model of acetylsalicylic acid content was 0.971 and 0.998 at the range of acetylsalicylic acid mass fraction between 10 and 90 wt-%, 1 and 30 wt-%, respectively. This study provides a method to effectively reduce the scattering effect of spectral detection of tablets by improving the sample’s properties, to provide a reference for enhancing the reliability and accuracy of quantitative measurements.

DOI： 10.1007/s00339-024-07302-3

Scopus

Publishing type：Research paper (scientific journal)  

Farmers would be able to regulate fertilization and produce quality durian if they knew the nutrient concentration in durian leaves. A long period of time for traditional nutritional content determination is needed. Therefore, near-infrared spectroscopy is a good method for nondestructive and quick nutrient content evaluation. The leaf sample matrices (fresh leaves, dried ground leaves, and dried ground leaf pellets) were scanned by Fourier transform near-infrared (FT-NIR) with a wavelength of 12,500–3,600 cm−1. Regression models were developed using partial least squares (PLS) with full wavelength, short wavelength, and selected wavelength by successive projections algorithm (SPA). In this study, the model for N and K concentration was acceptable and the prediction was considered good but for P content not had succeeded. As a result, the PLS-SPA model using fresh leaf samples for evaluating N content in durian leaves exhibited performance of r2 = 0.852, SEP = 0.14%, RPD = 2.63 and bias = −0.020%. The PLS-SPA model using dried ground leaf samples for evaluating K content in durian leaves exhibited performance of r2 = 0.820, SEP = 0.13%, RPD = 2.36 and bias = 0.006%. This research found that it is possible to apply NIR waves to predict N and K concentrations in durian leaves. It is not necessary to predict directly from the wavelengths associated with -N or -K bonds. Instead, NIR can measure them indirectly from the bonding of proteins, which are products formed by N and K. In addition, selecting the wavelength that is related to the value to be measured can produce results that are not significantly different from using full or short wavelengths. These models can assist farmers in rapidly predicting N and K content in durian leaves for immediate fertilizer adjustment.

DOI： 10.1016/j.saa.2023.123398

Scopus

Publishing type：Research paper (scientific journal)  

Visible and near-infrared spectroscopy has been well studied for characterizing the organic compounds in fruit and vegetables from pre-harvest to late harvest. However, due to the challenge of decoupling of optical properties, the relationship between the collected samples’ spectral data and their properties, especially their mechanical properties (e.g., firmness, hardness, and resilience) is hard to understand. This study developed a time-resolved transmittance spectroscopic method to validate the light scattering changing characteristics in kiwifruit during shelf-life and in cold storage conditions. The experimental results demonstrated that the reduced scattering coefficient (μs′) of 846 nm inside kiwifruit decreased steadily during postharvest storage and is more evident under shelf-life than in cold storage conditions. Moreover, the correlation between the μs′ and the storage time was confirmed to be much higher than that using the external color indexes measured using a conventional colorimeter. Furthermore, employing time-resolved profiles at this single wavelength, an efficacious mathematical model has been successfully formulated to classify the stages of kiwifruit softening, specifically early, mid-, and late stages. Notably, classification accuracies of 84% and 78% were achieved for the shelf-life and cold storage conditions, respectively.

DOI： 10.1038/s41598-023-43777-5

Scopus

PubMed

Publishing type：Research paper (scientific journal)  

Heat treatment of wood can decrease its heat capacity and thermal transitions, which are thermal behavior properties of wood. A calorimetric study that highlights the thermal behavior of the molecular mobility of materials is necessary to investigate the thermal degradation of wood. Furthermore, combining it with a nondestructive measurement technique would widen its scope of applicability, especially for wood in service or historical wood that cannot be altered or damaged by invasive methods. Neolamarckia cadamba (Roxb.) Bosser, also known as burflower-tree, a tropical fast-growing hardwood species that has become popular for light-construction works in the past decade, is treated at 90, 120, and 150 ℃ for a duration of 8 h to 3.5 months, scheduled logarithmically. Near-infrared spectroscopy and differential scanning calorimetry (DSC) were used to measure the chemical changes and thermal behavior of the wood before and after heat treatment. Two-dimensional correlation spectroscopy (2DCOS) analysis was then applied to assess the NIR second-derivative spectra and DSC thermograms. The results showed that 2DCOS analysis could assess NIR second-derivative spectra and DSC thermograms under careful observation, as DSC thermograms comprise both qualitative and quantitative information. It provides a new point of view in the non-destructive analysis of wood thermal degradation.

DOI： 10.1007/s00226-023-01506-1

Scopus

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

Abstract

Conventional fluorescence spectroscopy has been suggested as a valuable tool for classifying wood species rapidly and non-destructively. However, because it is challenging to conduct absolute emission intensity measurements, fluorescence analysis statistics are difficult to obtain. In this study, another dimension of fluorescence, that is, fluorescence lifetime, was further evaluated to address this issue. A time-resolved fluorescence spectroscopic measurement system was first designed, mainly using a streak camera, picosecond pulsed laser at 403 nm, and a spectroscope, to collect the fluorescence time-delay (FTD) profiles and steady-state fluorescence intensity (FI) spectra simultaneously from 15 wood species. For data analysis, principal component analysis was used to “compress” the mean-centered FTD and FI spectra. Then, support vector machine classification analysis was utilized to train the wood species classification model based on their principal component scores. To avoid overfitting, ten-fold cross-validation was used to train the calibration model using 70 % of the total samples, and the remaining 30 % hold-out validation was used to test its reproducibility. The cross-validation accuracies were 100 % (5 softwoods) and 96 % (10 hardwoods), with test-validation accuracies of 96 % and 89 %.

DOI： 10.1515/hf-2023-0017

Scopus

Other Link： https://www.degruyter.com/document/doi/10.1515/hf-2023-0017/pdf

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

Nondestructive monitoring of the environmental changes around fluorescent molecules in postharvest fruit is highly informative for monitoring their ripening and early decay process. In this study, a time-resolved laser-induced fluorescence (TRLIF) spectroscopic system, including a streak camera, spectrometer, and 403 nm picosecond-pulsed laser, was first developed. Then, representative pigments in photosynthesis (chlorophyll a, chlorophyll b, and carotenoids liquid samples) were initially measured and studied to determine whether the developed TRLIF spectroscopic system could produce the characteristics of chlorophyll fluorescence decay traces. Finally, the same approach was tested to monitor the ripening and early decay processes of each three samples of avocado and strawberry. The overall findings demonstrated that the fluorescence lifetime (FLT) of the fruit samples declined steadily during the shelf-life storage. For the avocados samples, the average FLT loss at the wavelength range of 706-749 nm decreased by approximately 23 % and 31 % at 1 and 2 d under shelf-life storage, respectively. For the strawberry samples, the average FLT loss at the wavelength range of 631-706 nm decreased by approximately 22 %, 46 %, 68 %, and 73 % at 0.5, 1, 1.5, and 2 d under the same shelf-life storage condition. This study indicates that the developed TRLIF spectroscopic method is potentially robust and accurate for assessing the ripening and early decay process of various climacteric and non-climacteric fruit.

DOI： 10.1016/j.postharvbio.2022.112231

Web of Science

Scopus

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

In this study, an approach to visualize the spatial distribution of sugar content in white strawberry fruit flesh using near-infrared hyperspectral imaging (NIR-HSI; 913–2166 nm) is developed. NIR-HSI data collected from 180 samples of “Tochigi iW1 go” white strawberries are investigated. In order to recognize the pixels corresponding to the flesh and achene on the surface of the strawberries, principal component analysis (PCA) and image processing are conducted after smoothing and standard normal variate (SNV) pretreatment of the data. Explanatory partial least squares regression (PLSR) analysis is performed to develop an appropriate model to predict Brix reference values. The PLSR model constructed from the raw spectra extracted from the flesh region of interest yields high prediction accuracy with an RMSEP and (Formula presented.) values of 0.576 and 0.841, respectively, and with a relatively low number of PLS factors. The Brix heatmap images and violin plots for each sample exhibit characteristics feature of sugar content distribution in the flesh of the strawberries. These findings offer insights into the feasibility of designing a noncontact system to monitor the quality of white strawberries.

DOI： 10.3390/foods12050931

Scopus

PubMed

Language：English   Publisher：TAYLOR & FRANCIS INC  

Hyperspectral imaging is a technique that combines spectroscopy and imaging. Originally utilized in the 1980's by the remote sensing community it is now utilized in a wide variety of applications. Spectral imaging was first used for the detection of compression wood in the late 1990's and since that time research focused on wood and wood products has steadily increased with a variety of applications reported. While there are several reviews of wood related research utilizing near infrared spectrometers a comprehensive summary of wood-hyperspectral imaging research is lacking. Near infrared hyperspectral imaging systems (NIR-HSI) typically have a wavelength range of 900-1700 nm, whereas short-wave infrared hyperspectral imaging (SWIR-HSI) systems range from 1000 to 2500 nm. We provide a detailed account of the various studies that have been published utilizing both camera types.

DOI： 10.1080/05704928.2022.2098759

Web of Science

Scopus

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

Substantial efforts have been undertaken for visualizing and simulating the characteristics of water movement in wood. However, three-dimensional (3D) thermo-hygric simulations still pose challenges, not only because wood has a heterogeneous microstructure that results in complex computational models but also because there is a lack of proper experimental techniques to support and validate the model constructions. In this study, the moisture distribution in wood during the water adsorption and desorption processes was first visualized using a near-infrared hyperspectral imaging (NIR-HSI) method that has high resolution, sensibility, and stability. Then, based on the moisture visualization results, the main parameters of a mass transfer simulation code were varied. The visualization and simulation results were confirmed to match well with the main characteristics; e.g., drying speed was slower in the wood parts with higher densities. Additionally, there was a relatively large gradient over the surface layer of the wood samples as the drying progressed, whereas this was not an obvious feature in the water adsorption process. Hence, this study proposes that the NIR-HSI method can be combined with thermo-hygric and 3D simulation model construction. Such an approach provides the basis for optimizing drying conditions and providing high-quality wood products.

DOI： 10.1515/hf-2021-0203

Web of Science

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

Rapid and non-destructive detection of genuine Thai Jasmine rice (Khao Dawk Mali 105 (KDML105)) from Pathum Thani1 (PTT1) and Phitsanulok2 (PSL2) under either milled or brown conditions is required to disrupt fraudulent. This study aimed to resolve this real issue using long-wave near infrared hyperspectral imaging (NIRHSI) coupled with machine learning and deep learning approaches. The best classification accuracy for the milled rice was achieved using the spectral imaging-based analysis on the NIR-HSI data with selected wavelength, approximately 95% for the test set either by convolutional neural network or support vector machine (SVM), whereas for the brown rice, the SVM model based on the averaged NIR spectra could achieve the best classification accuracy of 95.4%. It suggests the chemical component difference and its spatial distribution in the milled rice could contribute higher classification accuracy. Additionally, the surface bran effects of brown rice could be reduced by using averaged spectral data coupled with the SVM method.

DOI： 10.1016/j.infrared.2022.104100

Web of Science

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

Web of Science

Language：English   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

Web of Science

Language：English   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

Web of Science

PubMed

Language：English   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

Web of Science

Authorship：Corresponding author   Language：English  

Language：English   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

Web of Science

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

Strain measurement is critical for wood quality evaluation. Using conventional strain gauges constantly is high cost, also challenging to measure precious wood materials due to the use of strong adhesive. This study demonstrates the correlation between the light scattering degrees inside the wood during tension testing and their macroscopic strain values. A multifiber-based visible-near-infrared (Vis-NIR) spatially resolved spectroscopy (SRS) system was designed to rapidly and conveniently acquire such light scattering changes. For the preliminary experiment, samples with different thicknesses, from 2 to 5 mm, were measured to evaluate the influence of sample thickness. The differences in Vis-NIR SRS spectral data diminished with an increase in sample thickness, suggesting that the SRS method can successfully measure the wood samples' whole strain (i.e., surface and inside). Then, for the primary experiment, 18 wood samples were each prepared with approximately the same sample thickness of 2 mm and 5 mm to construct strain calibration models, respectively. The prediction accuracy of the 2-mm samples was characterized by a determination coefficient (R-2) of 0.81 with a root mean squared error (RMSE) of 343.54 mu epsilon for leave-one-out cross-validation; for test validation, the validation accuracy was characterized by an R-2 of 0.76 and an RMSE of 395.35 mu epsilon. For the validation accuracy of the 5-mm samples, R-val(2) was 0.69 with 440.78 mu epsilon RMSEval. Overall, the presented calibration results of the SRS approach were confirmed to be superior to the standard diffuse reflectance spectroscopy.

DOI： 10.1007/s10570-021-04239-1

Web of Science

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

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

Web of Science

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

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

Web of Science

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

Given that terahertz (THz) radiation responds to intermolecular forces such as hydrogen bonds, THz time-domain spectroscopy (THz-TDS) has expanded possibilities in cellulose research. In this study, THz-TDS was used to investigate the crystallinity of three types of cellulose-based materials. Microcrystalline cellulose (MCC) and wood were ball milled at different times, and pseudo-wood was a mixture of MCC and lignin of different mass fractions. All the samples showed peaks at 3.04 THz in the THz mass absorption coefficient spectra. Further, the spectra from 2.79 THz to 3.32 THz were cut out and detrended by subtraction from a baseline. The integrated intensity of the detrended spectra showed a correlation with the mass fraction of lignin of the pseudo-wood samples, and ball milling time of the MCC and wood samples. The correlation was similar with the crystallinity index calculated from X-ray powder diffraction. Moreover, the original wood sample without ball milling had an integrated intensity that was about 30% that of the original MCC sample, matching with the cellulose concentration of the wood (about 30% to 40%). We normalized the integrated intensity of 2.79 THz to 3.32 THz into 1 to 0 by a min-max algorithm and proposed a new "index" for evaluating crystallinity.

DOI： 10.1007/s10570-021-03902-x

Web of Science

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

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

Web of Science

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

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. wealdy, 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

Web of Science

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

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 (R-cv(2)) and the root mean square error (RMSEcv) of cross-validation set were 0.74 and 0.7 %, respectively. For pH, the R-cv(2) and RMSEcv were 0.64 and 0.14, respectively. Finally, the SSC and pH 360mapping 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

Web of Science

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

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 distanced d + Delta 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 (R-cal(2)) 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/jpostharvbio.2020.111417

Web of Science

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

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

Terahertz (THz) radiation is responsive to optical phonons in crystal lattices; therefore, THz time-domain spectroscopy (THz-TDS) has potential utility in crystallographic analysis. In this study, THz-TDS was used to investigate cellulose samples extracted from different sources with varying ratios of I(alpha)and I(beta)fractions. This is the first study to report that the absorption coefficient in the THz region of cellulose I(alpha)and I(beta)presents different characteristic absorption peaks around 2 THz. This can be used to distinguish the cellulose I allomorph, which exhibits differences in its crystalline structure. The absorption coefficient at 2.11 and 2.38 THz showed a considerable linear correlation with the I(alpha)fraction of the cellulose samples. The absorption coefficient spectra of 1.88-3.40 THz were further detrended and separated into three Gaussian peaks. The correlations between the parameters of these separated peaks (integrated intensities, peak positions) and the crystalline structural values (d-spacing, crystalline size, crystallinity index) that calculated from the X-ray diffraction (XRD) pattern were investigated.

DOI： 10.1007/s10570-020-03508-9

Web of Science

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

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 similar to 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

Web of Science

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

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 polyploidAcacia(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 ofAcaciaauriculiformis, Acaciamangium,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 polyploidAcaciahybrids 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

Web of Science

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

Real-time monitoring of the dynamic state of water molecular structure in lignocellulosic material is challenging, but important for both theoretical studies and industrial applications. In the present study, three typical wood samples which have a fundamental difference in the anatomical structure were scanned in the near-infrared spectral range, and images were acquired from wavelengths of 1002-1847 nm during drying. Then, partial least squares regression was used to determine the water content by mass, and principal component analysis was utilized to characterize the variance of NIR difference spectral data between 1340 and 1610 nm after baseline correlation for showing the distribution changing from free water to bound water during air drying. It was clarified that the PC1 loading mainly correlates with simple water content by mass, whereas the PC2 loading contains information about water-wood hydrogen structure interactions. The three loading curve peaks of PC2 could be correlated with free, weakly bound, and strongly bound water based on longer wavelength shifting. Finally, PC1 and PC2 scores were comprehensively applied to show the distribution changing from free water to bound water in each wood sample with a 62.5 mu m/pixel high spatial resolution.

DOI： 10.1007/s10570-020-03117-6

Web of Science

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

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

Web of Science

PubMed

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SAGE PUBLICATIONS LTD  

Wood changes its properties, especially color, as a result of thermal degradation. In this study, change in wood properties due to thermal degradation have been studied using the nondestructive test methods of near infrared spectroscopy, CIELAB color measurement, visible-light spectroscopy, and Arrhenius time-temperature superposition. Arrhenius time-temperature superposition allowed analysis of near infrared and visible-light spectra, and color parameters to predict thermal degradation and color change of wood at 120-180celcius for 6 min to nine months duration. Two-dimensional correlation spectroscopy for the complementary analysis of near infrared and visible-light spectroscopy was applied to investigate chemical changes during wood thermal degradation that cause the observed color change. Visible-light spectroscopy with CIELAB color measurement was used to obtain information on color changes, and near infrared spectroscopy was applied in the measurement of chemical changes during thermal degradation. Changes in spectral intensities in 2D correlation spectroscopy indicated that different chemical components are responsible for color change during heat treatment and accelerated aging of wood. With dry-thermal treatment, the hemicellulose content decreased following a color change, whereas cellulose and lignin/extractives decreased with hygro-thermal treatment.

DOI： 10.1177/0967033519863878

Web of Science

Language：Japanese  

DOI： 10.1002/jcc.25865

Web of Science

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

As the strength of wood is greatly affected by its three-dimensional (3D) grain angles (the dive angle and the surface angle), the wood industry today requires automatic, rapid, and robust measurement techniques for measuring them simultaneously. In the present study, a near infrared spatially and spectrally resolved imaging (NIR-SSRI) system was designed in a line scan model, mainly including an NIR hyperspectral imaging camera and a halogen spotlight source (empty set 1 mm). Spatially resolved diffuse reflectance images at three target wavelengths (1002 nm, 1217 nm, and 1413 nm) were obtained from Hinoki cypress [Chamaecyparis obtusa (Siebold & Zucc.) Endl.] samples at various (0 degrees, 3 degrees, 6 degrees, ... 45 degrees) dive angles and surface angles (0 degrees, 3 degrees, 6 degrees, ... 45 degrees). The scattering patterns caused by the "tracheid effect" were almost elliptical. Subsequently, nonlinear least squares fitting was used to determine their eccentricities (e) and rotation angles (theta). The e values at each selected wavelength were highly correlated with the dive angle reference values; and the global identification model developed using Gaussian process regression (GPR) under five-fold cross-validation (CV) reached a determination coefficient (r(2)) of 0.98 with a root mean square error (RMSE) of 2.2 degrees. On the other hand, local surface angle identification models developed using linear regression analysis achieved determination coefficients higher than 0.90 on r(2) and an RMSE of CV lower than 3.8 degrees when the dive angle was lower than 30 degrees.

DOI： 10.1515/hf-2018-0273

Web of Science

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

This report follows up previous work that presented a model for the simultaneous detection of moisture content and density of wood using Terahertz time-domain spectroscopy. A significant improvement in the prediction accuracy of the model is demonstrated by including a moisture content-dependent dielectric function for the water within the wood samples. Justification for using the dielectric function is presented, the prediction accuracy is quantified, and the results compared with prior work.

DOI： 10.1007/s10762-019-00594-0

Web of Science

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

The moisture content (MC) of wood influences its material properties. Determination of MC is essential in both the research and manufacturing fields. This study examined a nondestructive method for estimating MC rapidly and effectively. A capacitance sensor and a near-infrared (NIR) spectrometer were used to measure the MC of Japanese cedar and Japanese cypress timber. High-frequency capacitance (20MHz) and NIR spectral absorption (908-1676nm) data were collected for cross section and tangential section, as well as for the whole-sample average, in two MC ranges: from the green to the fiber saturation point (FSP) and from FSP to air-dried state. The results indicated that when standard error of prediction (SEP) is compared, the performance in [FSP to air-dried state] was better; when coefficient of determination in cross-validation (Rval2) and residual predictive deviation in cross-validation (RPDval) were compared, the performance in [Green to FSP] was better. Statistical analysis was performed using multiple linear regression and partial least squares. Combining capacitance and NIR absorbance at two wavelengths (Capacitance+NIR-MLR calibration) from the green to FSP was the best calibration yielding the most promising results: Rval2=0.96, SEP=5.20% and RPDval=4.97 on the cross section of samples. The results were higher than those of other calibrations in R-2 and SEP and RPD values. The NIR-PLS calibration performed better than others with quite good R-2, lower SEP and higher RPD in the MC range from FSP to air-dried state. The first calibration using only capacitance of wood was good in the first range of MC, but it is not good in the second range (R-2 under 0.5). Depending on the MC range, the performance of each calibration was different. In both MC ranges, the results on the cross section were higher than on the tangential section due to the anisotropic characteristics of wood material. From Capacitance+NIR-MLR calibration, the predicted models were developed using multiple linear regression and logarithmic regression. Results suggest the possibility of developing a new portable device combining a capacitance sensor and NIR spectroscopy to accurately predict the MC of wood.

DOI： 10.1007/s00226-019-01077-0

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SAGE PUBLICATIONS LTD  

In this study, the feasibility of near infrared reflectance spectroscopy for the quality evaluation of the main bioactive compounds, ginsenosides, in Panax ginseng was examined. Second derivative NIR spectra of standard reagents of ginsenoside Rg(1), Re, Rb-1, Rc, Rb-2 and Rd were used for analysis. Characteristic bands were observed at around 5250 cm(-1) in the spectra of ginsenoside Rg(1) group (including Rg(1) and Re); however, this was not to be observed on the spectra of ginsenoside Rb-1 group (including Rb-1, Rc, Rb-2 and Rd). PLS regression models were constructed of air-dry ginseng powder samples and ginsenoside content in ginsengs was determined by HPLC methods. The calibration models covered various types of ginseng (white ginseng, red ginseng and bleached ginseng) from various cultivated areas (Japan, China and Korea) and were well established for each kind of ginsenoside. It was shown that NIR spectroscopy can be used for the accurate prediction of ginsenoside.

DOI： 10.1177/0967033518814851

Web of Science

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

Conventional near-infrared (NIR) spectroscopy has shown its potential to separate wood species nonde-structively based on the aggregate effect of light absorption and scattering values. However, wood has an aligned microstructure, and there is a large refractive index (RI) mismatch between the wood cell wall substance (n approximate to 1.55) and the cell lumen (air approximate to 1.0, water approximate to 1.33). Light scattering is dominant over absorption (mu(s)' >> mu(a)) in wood, and this fact can be utilized for complex classification purposes. In this study, an NIR hyperspectral imaging (HSI) camera combined with one focused halogen light source (empty set 1 mm) was designed to evaluate the light scattering patterns of five softwood (SW) and 10 hardwood (HW) species in the wavelength range from 1002 to 2130 nm. Several parameters were combined to improve the data quality, such as image histogram plots of defined spaced bins (associated with diffuse reflectance values of light), variance calculation on the frequency (the number of pixels in each bin) of each histogram and the principal component analysis (PCA) of all the variance values at each wavelength. The identification accuracy of the quadratic discriminant analysis (QUA) under the five-fold cross-validation method was 94.1%, based on the first three principal component (PC) scores.

DOI： 10.1515/hf-2018-0128

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：GEOMATE INT SOC  

Crude palm oil (CPO) is a rich source of carotenoids which are a precursor of vitamin A as an important antioxidant. Carotenoids and Deterioration Of Bleachability Index (DOBI) are important factors to indicated quality of CPO. The conventional method for DOBI and carotenoids determination use UV-Vis spectrophotometry and HPLC, respectively which methods use solvents and spend time for analysis. This research interests Raman and FT-NIR spectroscopy for carotenoids and DOBI determination due to those techniques are an alternative technique for rapid measurement, non-destruction of material, and environmental suitability. The results indicated that Raman is better for determination than FT-NIR spectrometry. In Raman analysis, multiplicative scatter correction (MSC) and standard normal variate (SNV) treated methods were the best models for carotenoids and DOBI, respectively. The bands of carotenoids were at 1,100 and 1,500 cm(-1) wavenumber. Validation on carotenoids produced 0.94 of correlation coefficient (R), 0.88 of coefficient of determination (R-2), 40.65 ppm of root mean square error of prediction (RMSEP) and 3.25 of the ratio of standard error of prediction to standard deviation (RPD). The validation of DOBI produced 0.76 of R, 0.57 of R-2, 0.31 of RMSEP, 1.92 of RPD of 1.92. The limitation of carotenoids and DOBI determination using FT-NIR is having sufficient concentration of carotenoids for analysis. In addition, data for various samples regarding location, season, and oil palm species are important to build models for precise prediction.

DOI： 10.21660/2019.55.4813

Web of Science

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

Naturally occurring knots reduce the mechanical strength of wood. Veneers from sugi (Cryptomeria japonica) served as research material to study the effect of knots and holes. Veneer samples were first subjected to a three-point bending test to obtain measured modulus of elasticity (MOE) values. Then, near-infrared (NIR) hyperspectral imaging (HSI) was used to construct a prediction model and map the predicted MOE values. This is the first attempt for MOE prediction from the entire veneer surface based on NIR-HSI technology, while the mathematical part relies on chemometrics and cross-validation partial least squares regression (CV-PLSR). Maps of MOE prediction values could distinguish between latewood (LW) and earlywood (EW), as well as between a sound knot and a dead knot.

DOI： 10.1515/hf-2018-0060

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SAGE PUBLICATIONS LTD  

Near infrared hyperspectral imaging combined with partial least squares regression analysis was used to evaluate wood stiffness (modulus of elasticity) and fiber coarseness. Five samples with normal wood and compression wood collected from two Japanese Cedar (Cryptomeria japonica) trees were analyzed. To achieve high reliability of the prediction values, a SilviScan system (X-ray densitometry, X-ray diffractometry, and optical microscopy) with the high spatial resolution was used for measuring reference data. The measurement interval for modulus of elasticity and fiber coarseness was 1 mm and 25 mu m, respectively. After spectral pre-treatment and key wavelengths selection, partial least squares analysis was applied to calibrate near infrared data to reference values. The determination coefficient (R-CV(2)) of modulus of elasticity was 0.66 with a root mean square error of cross validation (RMSECV) of 1.80 GPa. For the constructed fiber coarseness calibration model, R-CV(2) and RMSECV were 0.62 and 35.02 mu m/g, respectively. Finally, modulus of elasticity and fiber coarseness mapping results show detailed information (156 mu m/pixel) at the grown ring level. The differences among earlywood, latewood, and compression wood were all well identifiable.

DOI： 10.1177/0967033518808053

Web of Science

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

A near-infrared spatially resolved spectroscopy (NIR-SRS) system, also called the hyperspectral imaging system, was applied in a line scanning model combined with a concentrated halogen light source (empty set 1 mm), and spatially resolved reflectance images of Douglas fir [Pseudotsuga menziesii (Mirb.) Franco] wood were obtained. The samples with various densities, grain directions and thicknesses were observed in the NIR range of 1000-1600 nm. Then, a nonlinear curve-fitting algorithm was applied based on the steady-state diffusion theory model to estimate the absorption coefficient (mu'(s)), and reduced scattering coefficients (mu(a)),( )both parallel and perpendicular to the grain direction at each measurement position. The absorption scattering coefficients at 1457 nm and two kinds of reduced scattering coefficients at 1002 nm were highly correlated with wood densities measured by an X-ray densitometer. The correlation coefficients were 0.953 and 0.987 for 3 mm and 5 mm samples, respectively, while three optical profiles were combined. It can be concluded that NIR-SRS is a fast and simple method for measuring the optical characteristics of softwood, although it has a non-homogeneous cellular structure. Sub-surface density and grain direction could be predicted with satisfactory accuracy based on a few key wavelengths without relying on multivariate statistical analysis.

DOI： 10.1515/hf-2017-0213

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER JAPAN KK  

Here, we evaluated the application of near-infrared (NIR) spectroscopy for estimating the degradation level of archeological wood samples from the Tohyamago area, the dendrochronological ages of which were also determined. The wood samples were radially cut from three logs obtained from the Tohyamago area. NIR reflectance spectra were measured from the tangential faces of air- and oven-dried wood samples using a Fourier transform NIR spectrophotometer. The second derivative spectra within the wavenumber range of 6400-5200 cm(-1), in which the effect of moisture content in wood is suspected to be insignificant, showed a characteristic behavior with age. By comparing the second derivative spectral change in our wood samples with that in wood degraded by aging, thermal treatment, fungal attack, and lightning reported in the literature, we found that the second derivative spectra of wood samples from one log was similar to those of wood degraded by hygro-thermal treatment, whereas those of wood samples from another log was similar to those of wood degraded by brown-rot fungi. The physical and chemical properties of archeological wood were well predicted using a combination of partial least square regression analysis and NIR spectroscopy.

DOI： 10.1007/s10086-018-1718-8

Web of Science

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

Near-infrared (NIR) hyperspectral imaging was used to evaluate soluble solids content (SSC) in 'Fuji' apples [Malus sylvestris (L.) Mill. var. domestica (Borkh. Mansf.)]. Eighty 'Fuji' apples were analyzed by collecting four small block samples from each one (approximately 2.0 cm x 2.0 cm x 1.5 cm). Partial least squares (PLS) regression analysis was performed to determine the relation between SSC reference data and NIR spectral data measured from each sample. The cross-validation coefficient of determination (r(2)) between predicted and measured SSC values is 0.89 with a root mean squared error of cross-validation (RMSECV) of 0.55%. Then, we successfully mapped SSC at a high spatial resolution (375 mu m per pixel). In addition, the absorption and reduced scattering coefficients of the measured samples were determined based on a diffusion theory model. The absorption coefficients are positively correlated to the SSC values (chemical information), whereas water cored tissue content (physical information) causes a characteristic change in light scattering coefficients. The fitting results were validated by Monte Carlo simulation, and the light penetration depth in 'Fuji' apples was estimated to be around 033 cm at 1198 nm and 0.17 cm at 1450 nm, respectively. (C) 2017 Elsevier Ltd. All rights reserved.

DOI： 10.1016/j.jfoodeng.2017.12.028

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SPRINGER JAPAN KK  

We selectively assessed the thermal and hygrothermal treatment times of duplex heat-treated samples from the softwood hinoki cypress (Chamaecyparis obtusa) and the hardwood Japanese zelkova (Zelkova serrata) using near-infrared (NIR) spectroscopy with principal component analysis (PCA) and spectral-kinetic analysis. Wood samples from each species were thermally or hygrothermally treated at 120, 130, 150, and 180 A degrees C, and the second-derivative spectra of these samples in the 6300-5450 cm(-1) range, where moisture content has the smallest effect, were then subjected to PCA. The master curve that was calculated by kinetic analysis successfully explained changes in the first principal component (PC1) scores with thermal treatment time for all temperatures. The angles between the PC1 loadings that explained the spectral variation due to thermal and hygrothermal treatment were 79A degrees for hinoki and 80A degrees for zelkova. Thus, calculation of the inner product between the second-derivative spectra of duplex heat-treated wood and a loading vector that explained the spectral variation due to thermal or hygrothermal treatment allowed us to selectively assess the thermal and hygrothermal treatment times.

DOI： 10.1007/s10086-017-1670-z

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SAGE PUBLICATIONS LTD  

To construct robust calibrations of wood properties by near infrared spectroscopy, one must independently evaluate the spectral contributions of light absorption and light scattering. However, the light propagation in wooden cellular structures is difficult to interpret because these structures are complex, heterogeneous, and anisotropic. This study investigates the reduced scattering coefficients of softwood and hardwood (with ring-porous or diffuse-porous vessels) at 846 nm by time-resolved spectroscopy. It also evaluates the effect of wooden cellular structure and air-dry density on the light propagation. After determining the reduced scattering coefficients, we observed cross-sectional microscopic images of the wood samples. Eighty-five percent of the variation in the reduced scattering coefficients was explainable by the air-dry density, area ratio of the cell wall, and the median pore area. Monte Carlo simulations of the light propagation through wood revealed that most of the photon transport occurs in the cell-wall substance.

DOI： 10.1177/0967033518757233

Web of Science

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

The use of a capacitive method and near-infrared (NIR) spectroscopy to simultaneously predict the density and moisture content (MC) of wood samples was investigated. Prediction accuracy of both methods was individually investigated by multivariate analyses. The capacity and absorbance at two wavelengths in the NIR range were combined to predict both the properties by the specific models. All wavelength combinations in the range of 908-1676 nm were tested, and the best combination yielding the highest coefficient of determination (R (2)) was chosen. This novel method showed a strong correlation between predicted and measured data, independent of sample thickness and wood species. The prediction accuracy of the wood samples, from green wood to oven-dried conditions, showed promising results for all thicknesses, with R (2) = 0.79, root-mean-square error of cross-validation (RMSECV) = 0.10 g/cm(3), and residual predictive deviation (RPD) = 2.22 for density and R (2) = 0.80, RMSECV = 25.70%, and RPD = 2.22 for MC. In the case of below fiber saturation point to oven-dried state, R (2) value was slightly decreased in the prediction of MC and slightly increased in the prediction of density, but RMSECV of MC declined significantly (maximum 5.46%) compared to the range of MC from saturated point (maximum 39.56%). These results were considerably better than those obtained by modeling the capacitive or NIR method individually, and improvement was particularly apparent in estimating density. The results suggest the possibility of a new device combining the capacitive method and NIR spectroscopy to predict density and MC more accurately.

DOI： 10.1007/s00226-017-0974-x

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS INC  

Hard mung bean seeds pose a problem in the sprouting process as they develop mold and infect neighboring seeds. Near-infrared hyperspectral imaging combined with partial least squares discriminant analysis was applied to develop a classifying model to separate hard mung beans from normal ones. The orientation of the measured beans was found to affect the classification result. The optimal partial least squares discriminant analysis model based on all orientations resulted in a correlation coefficient (R) of 0.919 with a root mean squared error of prediction of 0.197. The non-germinative parts were mapped and were concentrated at one end of the bean. Finally, a germinability index was proposed according to the proportion of colored areas between the germinative and non-germinative parts from the hyperspectral imaging results.

DOI： 10.1080/10942912.2018.1476378

Web of Science

Language：English   Publishing type：Research paper (international conference proceedings)   Publisher：IEEE  

This study attempts simultaneous prediction of grain angle, density and moisture content by THz time domain spectroscopy (THz-TDS) which has sufficient spatial resolution and transparency for wood. Terahertz waves transmitted through wood contain information on moisture content, density, grain angle and crystallinity of the sample. In this study, we measured spectra of 14 kinds of wood (5 soft wood, 9 hard woods) at various moisture contents and air-dried douglas fir while rotating the sample against the polarization of the terahertz wave. It was shown that the fiber orientation, density and moisture content of wood can be predicted simultaneously from the calculated complex permittivity.

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：SAGE PUBLICATIONS LTD  

This study examined the dynamic behavior of wood chemical components during the drying process using near infrared spectroscopy. Principal component analysis and generalized two-dimensional correlation spectroscopy were applied to identify significant absorption bands from the heavily overlapping near infrared spectra. The near infrared spectra were successively acquired over the moisture content range of 60-11%. The principal component analysis scores indicated that the wood-water interaction in the moisture content range of 60-46% significantly differed from that in the range of 45-11%. The synchronous 2D correlation spectrum constructed from the spectra in the moisture content range of 60-46% revealed that the cell wall components and water molecules responded to the drying process even though the wood exceeded the fiber saturation point. In the moisture content range of 45-11%, the H-bonded OH groups in the crystalline region of cellulose clearly increased with the decrease in bound water. Moreover, the sequential order of events was also clarified from the asynchronous spectrum.

DOI： 10.1177/0967033517733379

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：FRONTIERS MEDIA SA  

Nitrate is an important component of the nitrogen cycle and is therefore present in all plants. However, excessive nitrogen fertilization results in a high nitrate content in vegetables, which is unhealthy for humans. Understanding the spatial distribution of nitrate in leaves is beneficial for improving nitrogen assimilation efficiency and reducing its content in vegetables. In this study, near-infrared (NIR) hyperspectral imaging was used for the non-destructive and effective evaluation of nitrate content in spinach (Spinacia oleracea L.) leaves. Leaf samples with different nitrate contents were collected under various fertilization conditions, and reference data were obtained using reflectometer apparatus RQflex 10. Partial least squares regression analysis revealed that there was a high correlation between the reference data and NIR spectra (r(2) = 0.74, root mean squared error of cross-validation = 710.16 mg/kg). Furthermore, the nitrate content in spinach leaves was successfully mapped at a high spatial resolution, clearly displaying its distribution in the petiole, vein, and blade. Finally, the mapping results demonstrated dynamic changes in the nitrate content in intact leaf samples under different storage conditions, showing the value of this non-destructive tool for future analyses of the nitrate content in vegetables.

DOI： 10.3389/fpls.2017.01937

Web of Science

Language：English   Publishing type：Research paper (scientific journal)   Publisher：PUBLIC LIBRARY SCIENCE  

Near infrared (NIR) spectroscopy is a common means of non-invasively determining the concentrations of organic compounds in relatively transparent aqueous solutions. Rigorous determination for limit of detection (LOD) is of importance for the application use of NIR spectroscopy. The work reported herein determined the LOD with the analysis of potassium hydrogen phthalate (KHP) in water with partial least square (PLS) calibration in the range of 6300 - 5800 cm (-1) between the two strong absorption bands of water, in which the C-H overtone bands of KHP are located. A comparison of the LOD estimated when using various condition (path length, aperture and co-added scan times) showed that the lowest LOD for KHP obtained with a fiber optic cable attachment equipped NIR spectrometer is approximately 150 ppm.

DOI： 10.1371/journal.pone.0176920

Web of Science

PubMed

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

Wood density and microfibril angle (MFA) are strongly correlated with wood stiffness, swelling/shrinkage, and its anisotropy. Understanding the spatial distribution of these data is critical for solid timber applications. In this study, near-infrared (NIR) hyperspectral imaging has been calibrated for evaluation of wood density and MFA in an effective manner. Briefly, five wood samples collected from both normal wood (NW) and compression wood (CW) moieties of two different Cryptomeria japonica trees were analyzed. Partial least squares (PLS) regression analysis was performed to determine the relationship between X-ray densitometry data obtained by SilviScan and NIR spectra, and cross-validation (leave-one-out) approach served for prediction performances. The validation coefficient of determination (r(2)) between the predicted densities by the NIR technique and the X-ray data was 0.83 with a root mean squared error of cross-validation (RMSECV) of 105.2 kg m(-3). Regarding MFA, the r(2) was 0.77 and RMSECV 5.36 degrees. Wood density was successfully maped as well as the MFA at a high spatial resolution. As a result, the detection of annual growth ring features and evaluation of aspects of heterogeneous wood quality has been facilitated. The mapping results were visually checked by looking at the difference between earlywood (EW) and latewood (LW) for density and by means of the Maule color reaction indicating high lignin contents in CW in terms of MFA validation as CWs have high MFA values.

DOI： 10.1515/hf-2016-0153

Web of Science

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

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

Language：English  

Language：English   Publishing type：Research paper (scientific journal)   Publisher：TAYLOR & FRANCIS LTD  

In this study, static bending measurements and online NIR spectra acquisitions were combined to construct modulus of elasticity (MOE) prediction model for sugi lumber. NIR spectra were acquired from tangential surface of sugi lumbers at a speed of 120 m min(-1) to assess its effectiveness in the wood industry. Cross-validation partial least squares regression (CV-PLSR) and test-set-validation partial least squares regression (TSV-PLSR) analyses were employed for analysing the data. The second derivative (2d) spectra with 19 smoothing points (Savitzky-Golay algorithm, second polynomial) gave the best result as spectral pre-processing treatment with the lowest root mean square error of cross-validation and the highest coefficient of determination for cross-validation based on the optimum number of latent variables as assessed from the minimum validation residual variance value in the CV-PLSR analysis. These 2d spectra were then used in the TSV-PLSR analysis for 100 repetitions to check the robustness of the calibration.

DOI： 10.1080/20426445.2017.1378398

Web of Science

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DOI： 10.1007/s00339-016-9763-x

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DOI： 10.1080/17480272.2014.923937

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DOI： 10.1007/s10762-014-0095-7

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DOI： 10.1007/s00226-010-0379-6

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