• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.15-20
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• 2008

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to measure anthocyanin contents in black colored soybean by using NIRS system. Total 300 seed coat of black colored soybean samples previously analyzed by HPLC were scanned by NIRS and over 250 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed in which the coefficient of determination for anthocyanin pigment C3G, D3G and Pt3G content was 0.952, 0.936, and 0.833, respectively. Each calibration equation was applied to validation set that was performed with the remaining samples not included in the calibration set, which showed high positive correlation both in C3G and D3G content file. In case Pt3G, the prediction model was needed more accuracy because of low $R^2$ value in validation set. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of C3G and D3G contents in black colored soybean.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.699-717
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• 2021

South Korea is pushing for the advancement of crop production technology to achieve food self-sufficiency and meet the demand for safe food. A medium-sized satellite for agriculture is being launched in 2023 with the aim of collecting and providing information on agriculture, not only in Korea but also in neighboring countries. The satellite is to be equipped with various sensors, though reference data for ground information are lacking. Hyperspectral remote sensing combined with 1st derivative is an efficient tool for the identification of agricultural crops. In our study, we develop a system for hyperspectral analysis of the ground-based reflectance spectrum, which is monitored seven times during the cultivation period of three soybean crops using a PSR-2500 hyperspectral sensor. In the reflection spectrum of soybean canopy, wavelength variations correspond with stages of soybean growths. The spectral reflection characteristics of soybeans can be divided according to growth into the vegetative (V)stage and the reproductive (R)stage. As a result of the first derivative analysis of the spectral reflection characteristics, it is possible to identify the characteristics of each wavelength band. Using our developed monitoring system, we observed that the near-infrared (NIR) variation was largest during the vegetative (V1-V3) stage, followed by a similar variation pattern in the order of red-edge and visible. In the reproductive stage (R1-R8), the effect of the shape and color of the soybean leaf was reflected, and the pattern is different from that in the vegetative (V) stage. At the R1 to R6 stages, the variation in NIR was the largest, and red-edge and green showed similar variation patterns, but red showed little change. In particular, the reflectance characteristics of the R1 stage provides information that could help us distinguish between the three varieties of soybean that were studied. In the R7-R8 stage, close to the harvest period, the red-edge and NIR variation patterns and the visible variation patterns changed. These results are interpreted as a result of the large effects of pigments such as chlorophyll for each of the three soybean varieties, as well as from the formation and color of the leaf and stem. The results obtained in this study provide useful information that helps us to determine the wavelength width and range of the optimal band for monitoring and acquiring vegetation information on crops using satellites and unmanned aerial vehicles (UAVs)

• Journal of the Optical Society of Korea
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• v.20 no.1
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• pp.94-100
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• 2016

A novel optical design for high resolution, large field of view (FOV) and multispectral remote sensing is presented. An f/7.3 Korsch and two f/17.9 Cook three-mirror optical systems are integrated by sharing the primary and secondary mirrors, bias of the FOV, decentering of the apertures and reasonable structure arrangement. The aperture stop of the Korsch system is located on the primary mirror, while those of the Cook systems are on the exit pupils. High resolution image with spectral coverage from visible to near-infrared (NIR) can be acquired through the Korsch system with a focal length of 14 m, while wide-field imaging is accomplished by the two Cook systems whose focal lengths are both 13.24 m. The full FOV is 4°×0.13°, a coverage width of 34.9 km at the altitude of 500 km can then be acquired by push-broom imaging. To facilitate controlling the stray light, the intermediate images and the real exit pupils are spatially available. After optimization, a near diffraction-limited performance and a compact optical package are achieved. The sharing of the on-axis primary and secondary mirrors reduces the cost of fabrication, test, and manufacture effectively. Besides, the two tertiary mirrors of the Cook systems possess the same parameters, further cutting down the cost.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.353-365
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• 2019

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R², and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1613-1613
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• 2001

Fats and molasses are used, at the present time, in a considerable proportion as ingredients for the animal feed industry. They are mainly used as energy sources, but also they provide other characteristics of technological and nutritional interest (dust reduction, increase in palatability, etc). Both semi-liquid ingredients have numerous aspects in common from the point of view of their use in livestock feeds, as well as of their analytical control. Feed manufacturers use several criteria to evaluate the quality of fat and molasses. Furthermore, the traditional methods currently used, for their evaluation (eg. fatty acids, sugars, etc) are expensive and more sophisticated that the traditionally used for solid ingredients. The objective of the present work is to carry out a viability study to evaluate the ability of NIRS technology for the quality control of fat and molasses. Samples of liquid molasses (n = 42) and liquid fat ( n = 61), provided by a feed manufacturer, were scanned in a FOSS-NIR Systems 6500 monochromator equipped with a spinning module. The samples were analysed by folded transmission, using a sample cup of 0.1mm pathlength and gold surface reflector. For molasses, calibration equations were developed for the prediction of moisture (SECV=1.69%; $r^2$=0, 42), gross protein (SECV=0, 14%; $r^2$=0, 99), ashy (SECV=0, 60%; $r^2$=0, 84), NaCl (SECV=0, 05%; $r^2$=0, 99) and sugars (SECV=1, 04%; $r^2$=0, 86). For animal fats calibrations were obtained for the prediction of moisture (SECV=0, 14%, $r^2$=0, 88), acidity index (SECV=0, 83%, $r^2$=0, 82), MIU (SECV=0, 38%, $r^2$=0, 94) and unsaponifiables (SECV=0, 45%, $r^2$=0, 87). High accuracy calibration equations were also obtained for the prediction of the fatty acid profile. The equations have $r^2$values around 0.9 or highest. The results showed that NIRS technology could provide rapid and accurate results and reduce analytical costs associated to the quality control of two Important feed ingredients of a well known chemical variability.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1243-1243
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• 2001

During two consecutive years, it was developed global calibrations for the prediction of fatty acids on Iberian pig fat. These equations should analyse well samples of that animal fat because of their high accuracy (SECV/sub C16:0/ = 0.26%; SECV/sub C18:0/ = 0.28%; SECV/sub C18:1/ = 0.26%; SECV/sub C18:2/ = 0.15%) and their broad covering composition range. In some cases, when new samples are predicted H (Mahalanobis distance) values higher than 3 (recommended value for agricultural products by the ISI software) are obtained. However, there are not any obvious factors which tells that samples scanned are very different to the spectral mean of the calibration population. Furthermore, these samples are well predicted according to the SEP values. The objective of the present work is to deepen the understanding of the H statistic when analysing animal fats. Three different validation files were predicted with equations obtained from January '97 to April '98. The Set A has spectra of 20 samples not included on the calibration file and scanned in May of 1998. The Set B has spectra of 20 samples included on the calibration file and scanned again in November '99. The Set C contains 150 spectra of one sample representative of the mean values (for fatty acids composition) of the calibration file. This sample was analysed three times per week during June '99 to July '00. The H mean values for the Set A, Set B and Set C were respectively 1.35, 14.39 and 11.71. These anomalous values for the Set B and C make not sense because Set B contains replicate subsamples of the same samples scanned during calibration development and Set C only contains spectra of one sample which represent the mean spectrum of the calibration files. Results will be shown to demonstrate that small day to day variations are responsible of the high H values. When a PCA and LIB file are created with calibration samples and spectra of the Set C modelling day to day variations, the H values for Set A, Set B and Set C were respectively 1.83, 2.16 and 0.93.

• Applied Chemistry for Engineering
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• v.29 no.2
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• pp.138-146
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• 2018

Photodynamic therapy (PDT) is a great potential approach for the localized tumor removal with fewer metastatic potentials and side effects in treating the disease. In the treatment process, a photosensitizer (PS) that absorbs a light energy to generate reactive oxygen is essential. In general, a visible light is used as a light source of PDT, so that side effects from the light source are inevitable. For this reason, upconversion nanoparticles (UCNPs) using near-infrared (NIR) as an excitation source are attracting attention in the field of disease diagnosis and treatment. UCNPs have the low cytotoxicity and phototoxicity, and also advantages such as deep tissue penetration and low background autofluorescence. For PDT, UCNPs should be combined with a PS which absorbs the light energy from UCNPs and transfers it to the surrounding oxygen to produce reactive oxygen. In addition, the therapeutic efficacy can be improved by modifying nanoparticle surfaces, adding anti-cancer drugs, or combining with photothermal therapy (PTT). In this review, we summarize the recent research to improve the efficiency of PDT using UCNPs.

• Journal of The Korean Society of Grassland and Forage Science
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• v.29 no.1
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• pp.31-36
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• 2009

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near reflectance infrared spectroscopy (NIRS) was used to evaluate the possibility of forage analysis and collect 258 samples such as barley for whole crop silage, forage corn and sudangrass from 2002 to 2007. The samples were analyzed for CP (crude protein), CF (crude fiber), ADF (acid detergent fiber), NDF (neutral detergent fiber) and IVTD (in vitro true digestibility), and also scanned using NIRSystem with wavelength from $400{\sim}2,400nm$. Multiple linear regression was used with wet analysis data for developing the calibration model and validate unknown samples. The important index In this experiment was SEC and SEP $r^2$ for CF, CP, NDF, ADF and IVTD in calibration set were 0.70, 0.86, 0.94, 0.94 and 0.89, also 0.47, 0.39, 0.89, 0.90 and 0.61 in validation sample, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality, specially in CF, ADF and IVTD, sample should be included for respective forage samples to get accurate result. More robust calibrations can be made to cover every forage samples if added representative sample set.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.2
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• pp.254-265
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• 2017

This study examines the possibility of a neuro-scientific approach to fashion Visual Merchandising (VM), by researching the brain activation of customers about fashion stores in terms of VM. Study subjects were in 20's-30's residing in Busan and ten ordinary person or fashion industry related individuals, it measures the change of cerebral blood flow on positive/negative photo stimulus in terms of VM using a functional Near Infrared Spectroscopy (fNIRS) device, and then compared the brain activation to the difference of the fashion store VM. Photo stimuli utilized in the experiment were selected through a preliminary study in advance. The results of this study are as follows. First, the brain activation was found in all 16 channels of stimulus ranges of fashion store VM regardless of positive/negative stimulus. This means that the VM of fashion store causes changes to the cerebral blood flow of consumers, which implies that consumer behavior can be affected by store VM. It also shows that the brain is more active in negative VM stimulus than positive VM despite slight differences in the subjects. In terms of VM, this suggests that the negative factors of fashion stores have a greater effect on the brains of consumers compared to the positive factors. Second, the reaction of the brain channel is different according to the positive/negative VM stimulus of the fashion store by product group and confirms that positive/negative VM stimulus can be distinguished by brain-reaction for the three product groups except for the underwear group among four product groups (men's wear store, women's wear store, underwear store, and sportswear store). The results indicate that more objective scientific measure and decision-making are possible through neuro-science in the strategic execution of VM. This study verified the possibility for a neuro-scientific approach to fashion VM; therefore, there are expectations for the various activation of interdisciplinary research and subsequent development of VM that utilize neuroscience in fashion marketing.

• Journal of The Korean Society of Grassland and Forage Science
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• v.31 no.4
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• pp.409-414
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• 2011

This study was conducted to find out an alternative way of rapid and accurate analysis of forage quality. Near Infrared Reflectance Spectroscopy (NIRS) was used to evaluate the possibility of forage analysis. 175 samples consisted of Italian ryegrass, whole crop barley and pea seeded spring in 2009 were collected. The samples were analyzed for moisture, crude protein (CP), crude ash (CA), acid detergent fiber (ADF), and neutral detergent fiber (NDF), and also scanned using NIRSystem with wavelength from 400~2,500 nm. Multiple linear regression was used with wet analysis data for developing the calibration model and validated unknown samples. The important index in this experiment were SEC, SEP. The r2 value for moisture, CP, CA, ADF, and NDF in calibration set was 0.65, 0.97, 0.93, 0.99, and 0.97 and also was 0.15, 0.94, 0.96, 0.98 and 0.98 in validation set, respectively. The results of this experiment indicates that NIRS was reliable analytical method to assess forage quality for CP, CA ADF and NDF except moisture content in forage when proper samples incorporated into the equation development.