Language：English   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

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Language：English   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

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

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

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

DOI： 10.1016/j.postharvbio.2022.112231

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

DOI： 10.1080/05704928.2022.2098759

Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Infrared Physics and Technology  

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 (NIR-HSI) 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

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

DOI： 10.3390/foundations2030035

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

DOI： 10.1515/hf-2021-0203

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

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

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Language：English  

DOI： 10.3390/cryst12050601

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

DOI： 10.1007/s44211-022-00106-6

PubMed

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

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 °C, 60 °C, and 90 °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 °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

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Holzforschung  

Acacia, including Acacia hybrids, are some of the most important species grown as part of the Vietnamese wood industry. Rapid methods to identify the variations in the wood properties of Acacia hybrids however, 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 spectroscopy (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 acquired 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

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

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 (R2) of 0.81 with a root mean squared error (RMSE) of 343.54 με for leave-one-out cross-validation; for test validation, the validation accuracy was characterized by an R2 of 0.76 and an RMSE of 395.35 με. For the validation accuracy of the 5-mm samples, R2val was 0.69 with 440.78 με 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

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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

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Agriculture (Switzerland)  

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

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Forests  

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

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Language：Japanese   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

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Language：Japanese   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

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Language：Japanese   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

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

DOI： 10.1016/j.compag.2020.105683

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

DOI： https://doi.org/10.1515/hf-2019-0298

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

DOI： 10.3390/f11070717

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

DOI： 10.1007/s10570-020-03117-6

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

DOI： 10.1515/hf-2020-0074

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

DOI： 10.1039/c9an01180c

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

DOI： 10.1515/hf-2018-0273

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

DOI： 10.1177/0967033518808053

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

DOI： 10.1515/hf-2017-0213

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

DOI： 10.1515/hf-2018-0060

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

DOI： 10.1016/j.jfoodeng.2017.12.028

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

DOI： 10.1177/0967033518757233

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

DOI： 10.1080/10942912.2018.1476378

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

DOI： 10.1515/hf-2018-0128

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

DOI： 10.3389/fpls.2017.01937

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

DOI： 10.1515/hf-2016-0153

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

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

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

DOI： 10.1255/jnirs.1237

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Event date： 2016.10

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