• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.49 no.3
• /
• pp.211-215
• /
• 2004

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 determine tocopherol and tocotrienol contents in rice bran by using NIRS system. Total 80 rice bran samples previously analyzed by HPLC were scanned by NIRS and over 60 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and coefficient of determination for tocopheyol and tocotyienol content were 0.975 and 0.984, respectively, in calibration sets. Each calibration equation was fitted to validation set that was performed with the remaining samples not included is the calibration set, which showed high positive correlation both in tocopherol and tocotrienol content file. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of tocopherol and tocotrienol contents in rice bran.

• Journal of the Korean Wood Science and Technology
• /
• v.43 no.3
• /
• pp.311-319
• /
• 2015

Near infrared (NIR) reflectance spectroscopy was employed to develop moisture content prediction model of pitch pine (Pinus rigida), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), yellow poplar (Liriodendron tulipifera) wood below fiber saturation point. NIR reflectance spectra of specimens ranging from 1000 nm to 2400 nm were acquired after humidifying specimens to reach several equilibrium moisture contents. To determine the optimal moisture contents prediction model, 5 mathematical preprocessing methods (moving average (smoothing point: 3), baseline, standard normal variate (SNV), mean normalization, Savitzky-Golay $2^{nd}$ derivatives (polynomial order: 3, smoothing point: 11)) were applied to reflectance spectra of each specimen as 8 combinations. After finishing mathematical preprocessings, partial least squares (PLS) regression analysis was performed to each modified spectra. Consequently, the mathematical preprocessing methods deriving optimal moisture content prediction were 1) moving average/SNV for pitch pine and red pine, 2) moving average/SNV/Savitzky-golay $2^{nd}$ derivatives for Korean pine and yellow poplar. Every model contained three principal components.

• Asian Journal of Turfgrass Science
• /
• v.23 no.1
• /
• pp.77-90
• /
• 2009

Near Infrared Reflectance Spectroscopy(NIRS) is a quick, accurate, and non-destructive method to measure multiple nutrient components in plant leaves. This study was to acquire a liner regression equation by evaluating the nutrient contents of 'CY2' creeping bentgrass rapidly and accurately using NIRS. In particular, nitrogen fertility is a primary element to keep maintaining good quality of turfgrass. Nitrogen, moisture, carbohydrate, and starch were assessed and analyzed from 'CY2' creeping bentgrass clippings. A linear regression equation was obtained from accessing NIRS values from NIR spectrophotometer(NIR system, Model XDS, XM-1100 series, FOSS, Sweden) programmed with WinISI III project manager v1.50e and ISIscan(R) (Infrasoft International) and calibrated with laboratory values via chemical analysis from an authorized institute. The equation was formulated as MPLS(modified partial least squares) analyzing laboratory values and mathematically pre-treated spectra. The accuracy of the acquired equation was confirmed with SEP(standard error of prediction), which indicated as correlation coefficient($r^2$) and prediction error of sample unacquainted, followed by the verification of model equation of real values and these monitoring results. As results of monitoring, $r^2$ of nitrogen, moisture, and carbohydrate in 'CY2' creeping bentgrass was 0.840, 0.904, and 0.944, respectively. SEP was 0.066, 1.868, and 0.601, respectively. After outlier treatment, $r^2$ was 0.892, 0.925, and 0.971, while SEP was 0.052, 1.577, and 0.394, respectively, which totally showed a high correlation. However, $r^2$ of starch was 0.464, which appeared a low correlation. Thereof, the verified equation appearing higher $r^2$ of nitrogen, moisture, and carbohydrate showed its higher accuracy of prediction model, which finally could be put into practical use for turf management system.

• Journal of the Korea Convergence Society
• /
• v.12 no.12
• /
• pp.323-330
• /
• 2021

In this study, we intended to examine the difference in brain activation due to dominant and non-dominant hands using functional near-infrared spectroscopy(fNIRS) in 10 healthy adults. Box & Block Test(BBT) was conducted under two conditions: dominant hand and non-dominant hand. During the experiment, brain activity was measured using fNIRS and signals were analyzed using nirsLAB v2019.04 software after the experiment was completed. As a result, 6 out of 10 people showed activation of the cerebral hemisphere related to the dominant hand, and only 3 out of 10 people showed activation of the cerebral hemisphere related to the non-dominant hand. In other words, both dominant and non-dominant hand cconfirmed that the cerebral hemispheres related to dominant hands were more active. Therefore, it is believed that fNIRS can be used as a fundamental data applicable to children with sensory processing disorders that are difficult to identify dominant hand.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.26 no.1
• /
• pp.101-112
• /
• 2015

II~VI compound semiconductors, $Zn_xCd_{1-x}S$ thin films have been synthesized onto indium-tin-oxide(ITO) coated glass substrates using thermal evaporation technique. The composition ratio x($0{\leq}x{\leq}1$) was varied to fabricate different kinds of $Zn_xCd_{1-x}S$ thin films including CdS(x=0) and ZnS(x=1) thin films. Then, the deposited thin films were thermally annealed at $400^{\circ}C$ to enhance their crystallinity. The chemical composition and electronic structure of films were investigated by using X-ray photoelectron spectroscopy(XPS). The optical energy gaps of the samples were determined by ultra violet-visible-near infrared(UV-Vis-NIR) spectroscopy and were found to vary in the range of 2.44 to 3.98 eV when x changes from 0 to 1. Finally, we measured the THz characteristics of the $Zn_xCd_{1-x}S$ thin films using THz-TDS(time domain spectroscopy) system to identify the capability for electronic and optical devices in THz region.

• Analytical Science and Technology
• /
• v.15 no.2
• /
• pp.102-107
• /
• 2002

This paper describes a rapid determination of phenobarbital in intact phenobarbital tablets using partial least squares regression(PLSR) method of transmittance spectrum of near infrared (NIR) compared with the analytical data of liquid chromatograpy. The linearity, concentration range and precision of this analytical method are studied. The correlation coefficient of the calibration curve is 0.9983 and the standard error of calibration(SEC) is 0.14 %. Intra-day precision and Inter-day precision obtained in this method are CV = 0.45, CV =0.56, respectively.

• Applied Biological Chemistry
• /
• v.41 no.2
• /
• pp.153-159
• /
• 1998

A possibility of evaluation of the major internal quality factors-Brix, moisture contents, firmness and acid content in the Korean domestic 'Fuji'apple fruits by near-infrared reflectance spectroscopic (NIRS) methods were investigated. A multiple linear regression(MLR) analysis between the data obtained by physico- chemical analysis method using refractometer, freeze drier, texture analyzer and titrater and NIR spectral data was carried out to make a calibration. The standard error of prediction(SEP) of Brix, moisture, firmness and acid content were $0.50^{\circ}Brix,\;0.64%,\;0.14kg/cm^2$ and 0.07%. It is concluded that NIRS methods can be used to evaluate Brix and moisture contents of in a apple non-destructive and rapid way but the accuracy for determination of firmness and acid content was slightly low.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1154-1154
• /
• 2001

Near infra-red (NIR) spectroscopy has been used for the non-invasive assessment of intact fruit for eating quality attributes such as total soluble solids (TSS) content. However, little information is available in the literature with respect to the robustness of such calibration models validated against independent populations (however, see Peiris et al. 1998 and Guthrie et al. 1998). Many studies report ‘prediction’ statistics in which the calibration and prediction sets are subsets of the same population (e. g. a three year calibration validated against a set from the same population, Peiris et al. 1998; calibration and validation subsets of the same initial population, Guthrie and Walsh 1997 and McGlone and Kawano 1998). In this study, a calibration was developed across 84 melon fruit (R$^2$= 0.86$^{\circ}$Brix, SECV = 0.38$^{\circ}$Brix), which predicted well on fruit excluded from the calibration set but taken from the same population (n = 24, SEP = 0.38$^{\circ}$Brix with 0.1$^{\circ}$Brix bias), relative to an independent group (same variety and farm but different harvest date) (n = 24, SEP= 0.66$^{\circ}$ Brix with 0.1$^{\circ}$Brix bias). Prediction on a different variety, different growing district and time was worse (n = 24, SEP = 1.2$^{\circ}$Brix with 0.9$^{\circ}$Brix bias). Using an ‘in-line’ unit based on a silicon diode array spectrometer, as described in Walsh et al. (2000), we collected spectra from fruit populations covering different varieties, growing districts and time. The calibration procedure was optimized in terms of spectral window, derivative function and scatter correction. Performance of a calibration across new populations of fruit (different varieties, growing districts and harvest date) is reported. Various calibration sample selection techniques (primarily based on Mahalanobis distances), were trialled to structure the calibration population to improve robustness of prediction on independent sets. Optimization of calibration population structure (using the ISI protocols of neighbourhood and global distances) resulted in the elimination of over 50% of the initial data set. The use of the ISI Local Calibration routine was also investigated.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1265-1265
• /
• 2001

The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.1617-1617
• /
• 2001

It is well known now that near infrared spectroscopy (NIRS) is a fast, no destructive, and inexpensive analytical technique that could be used to classify, identify, and authenticate a wide range of foods and food items. Therefore, the main aims of this study were to provide a new insight into the authentication of five strawberry (Fragaria x ananassa) varieties and to correlate them with geographical zones and the propagating methods used. Three weeks plants of five different strawberry varieties (F. x ananassa Duch. cv Camarosa, Seascape, Chandler, F. Chiloensis, and F. Virginiana) were cultivated in vitro first and then transferred to pots with special soil, and grown in a greenhouse at CINVESTAV, all varieties were acquired from California (USA). After 18 months, ten leaves from each variety were collected. Transmission spectra from each leave were recorded over a range of 10, 000-4, 000 cm$-^{1}$, 32 scans of each strawberry leave were collected using a resolution of 4 cm$-^{1}$ with a Paragon IdentiCheck FT-NIR System Spectrometer. Triplicates of each strawberry leave were used. All spectra were analyzed using principal component analysis (PCA) and soft independent modeling class analogy (SIMCA). The optimum number of components to be used in the regression was automatically determined by the software. Camarosa was the only variety grown from the same shoot but propagated by a different method (direct or in vitro). Five different classes (varieties) or clusters were observed among samples, however, larger inter class distances were presented by the two wildtype samples (F. Chiloensis and F. Virginiana). Camarosa direct and Camarosa in vitro displayed a small overlapping region between them. On the other hand, Seascape variety presented the smallest rejection percentage among all varieties (more similarities with the rest of the samples). Therefore, it can be concluded that the application of NIRS technique allowed the authentication of all strawberry varieties and geographical origin as well. It was also possible to form subclasses of the same materials. The results presented here demonstrate that NIRS is a very powerful and promising analytical tool since all materials were authenticated and classified based on their variety, origin, and treatment. This is of a tremendous relevance since the variety and origin of a plant material can be established even before it gives its typical fruit or flower.