• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1263-1263
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• 2001

The amounts of organic matter present in soil and the rate of soil organic matter (SOM) turnover are influenced by agricultural management practice, such as rotation, tillage, forage plow down direct seeding and manure application. The amount of nutrients released from SOM is highly dependent upon the state of the organic matter. If it contains a large proportion of light fractions (low-density) more nutrients will be available to the glowing crops. However, if it contains mostly heavy fractions (high-density) that are difficult to breakdown, then lesser amounts of nutrients will be available. The state of the SOM and subsequent release of nutrients into the soil can be predicted by NIRS as long as a robust regression equation is developed. The NIRS method is known for its rapidity, convenience, simplicity, accuracy and ability to analyze many constituents at the same time. Our hypothesis is that the NIRS technique allows researchers to investigate fully and in more detail each field for the status of SOM, available moisture and other soil properties in Alberta soils for precision farming in the near future. One hundred thirty one (131) Alberta soils with various levels (low 2-6%, medium 6-10%, and high >10%) of organic matter content and most of dry land soils, including some irrigated soils from Southern Alberta, under various management practices were collected throughout Northern, Central and Southern Alberta. Two depths (0- 15 cm and 15-30 cm) of soils from Northern Alberta were also collected. These air-dried soil samples were ground through 2 mm sieve and scanned using Foss NIR System 6500 with transport module and natural product cell. With particle size above 150 microns only, the “Ludox” method (Meijboom, Hassink and van Noorwijk, Soil Biol. Biochem.27: 1109-1111, 1995) which uses stable silica, was used to fractionate SOM into light, medium and heavy fractions with densities of <1.13, 1.13-1.37 and >1.37 respectively, The SOM fraction with the particle size below 150 microns was discarded because practically, this fraction with very fine particles can't be further separated by wet sieving based on density. Total organic matter content, mechanical texture, ash after 375$^{\circ}C$, and dry matter (DM) were also determined by “standard” soil analysis methods. The NIRS regression equations were developed using Infra-Soft-International (ISI) software, version 3.11.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.08a
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• pp.100-100
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• 2020

Wheat is mainly composed of carbohydrate but it contains a moderate amount of protein, which gives a very useful characteristics to flour food such as the unique elasticity and stickiness of the dough. We developed a calibration equation for analyzing crude protein content using Near Infrared Spectroscopy to quick analyze the crude protein content of wheat germplasm stored in the National Agrobiodiversity Center, RDA, Korea. The 1,798 wheat germplasms were used to draw up the calibration formula. The crude protein's interval distribution of 1,798 wheat germplasms used for the calibration was 7.04-20.84%, the average content was 13.2%, and standard deviation was 2.6%. The germplasms distribution was composed of a suitable group for the preparation of the calibration formula because the content distribution was a normal, excluding the 13.0-15.5% content section. In order to verify the applicability of the NIRS prediction model, we measured the crude protein content of the 300 wheat germplasms that were not used for the calibration using both Kjeldahl analysis and NIR spectrum. The analysis value calculated using each method were statistically processed, and the test results and statistical indicators of the predictive model were compared. As a result, The R² value of the optimized NIRS prediction model was 0.997, and the Standard error of Calibration value(SEC) was 0.132, and slope value was 1.000. With prediction model selection, compared to Kjeldahl method, R² values were 0.994(Kjeldahl), 0.998(NIRS), and the SEC value were 0.191 and 0.132, respectively, comparing the statistical indices of the forecast model. And slope value were 1.013, 1.000, respectively. The analysis of crude protein content by the NIRS predictive model developed by each statistical index showing similar figures is judged to show a high degree of correlation with the Kjeldahl analysis. The proven calibration equation will be used to measure the crude protein content of wheat germplasms held by the National Agrobiodiversity Center, and by dividing the wheat germplasms by their use according to the crude protein content, it will provide useful information to relevant researchers.

• Food Science and Preservation
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• v.19 no.1
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• pp.95-103
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• 2012

The objective of this study was to develop models for the predict of the milk properties (fat, protein, SNF, lactose, MUN) of unhomogenized milk using the visible and near-infrared (NIR) spectroscopic technique. A total of 180 milk samples were collected from dairy farms. To determine optimal measurement temperature, the temperatures of the milk samples were kept at three levels ($5^{\circ}C$, $20^{\circ}C$, and $40^{\circ}C$). A spectrophotometer was used to measure the reflectance spectra of the milk samples. Multilinear-regression (MLR) models with stepwise method were developed for the selection of the optimal wavelength. The preprocessing methods were used to minimize the spectroscopic noise, and the partial-least-square (PLS) models were developed to prediction of the milk properties of the unhomogenized milk. The PLS results showed that there was a good correlation between the predicted and measured milk properties of the samples at $40^{\circ}C$ and at 400~2,500 nm. The optimal-wavelength range of fat and protein were 1,600~1,800 nm, and normalization improved the prediction performance. The SNF and lactose were optimized at 1,600~1,900 nm, and the MUN at 600~800 nm. The best preprocessing method for SNF, lactose, and MUN turned out to be smoothing, MSC, and second derivative. The Correlation coefficients between the predicted and measured fat, protein, SNF, lactose, and MUN were 0.98, 0.90, 0.82, 0.75, and 0.61, respectively. The study results indicate that the models can be used to assess milk quality.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.258-263
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• 2019

Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages. The objective of this study was to evaluate the potential of NIRS, applied to imported forage, to estimate the moisture and chemical parameters for imported hays. A population of 392 imported hay representing a wide range in chemical parameters was used in this study. Samples of forage were scanned at 1 nm intervals over the wavelength range 680-2500nm and the optical data was recorded as log 1/Reflectance(log 1/R), which scanned in intact fresh condition. The spectral data were regressed against a range of chemical parameters using partial least squares(PLS) multivariate analysis in conjunction with spectral math treatments to reduced the effect of extraneous noise. The optimum calibrations were selected based on the highest coefficients of determination in cross validation(R²) and the lowest standard error of cross-validation(SECV). The results of this study showed that NIRS predicted the chemical parameters with very high degree of accuracy. The R² and SECV for imported hay calibration were 0.92(SECV 0.61%) for moisture, 0.98(SECV 0.65%) for acid detergent fiber, 0.97(SECV 0.40%) for neutral detergent fiber, 0.99(SECV 0.06%) for crude protein and 0.97(SECV 3.04%) for relative feed value on a dry matter(%), respectively. Results of this experiment showed the possibility of NIRS method to predict the moisture and chemical composition of imported hay in Korea for routine analysis method to evaluate the feed value.

• 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.

• Polymer(Korea)
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• v.27 no.3
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• pp.210-216
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• 2003

4-Vinyl-1-cyclohexene diepoxide (VCE)/diglycidyl ether of bisphenol-A (DGEBA) epoxy blends with benzylquinoxalinium hexafluoroanti-monate were cured using an electron-beam technique. The effect of DGEBA content to VCE on cure behavior, thermal stabilities, and mechanical properties was investigated. The composition of VCE/DGEBA blend system vaned within 100:0, 80:20, 60:40, 40:60, 20:80, and 0:100 wt%. The cure behavior and thermal stability of the cured specimens was monited by near-infrared spectroscopy and thermogravimetric analysis, respectively. Also, the critical stress intensity factor ($_{4}$) test of the cured specimens was performed to study the mechanical interfacial properties. As a result, the decreases of short side-chain structure and chain scission were observed in NIR measurements as the DGEBA content increases, resulting in varying the hydroxyl and carbonyl groups. And, the initial decomposition temperature (IDT), temperature of maximum weight loss (T$\_$max/), and decomposition activation energy (E$\_$d/) as thermal stability factors were increased with increasing the DGEBA content. These results could be explained by mean of decreasing viscosity, stable aromatic ring structure, and grafted interpenetrating polymer network with increasing of DGEBA content. Also, the maximum $_{4}$ value showed at mixing ratio of 40:60 wt% in this blend system. in this blend system.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.56-56
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• 2010

Single-walled carbon nanotubes (SWCNTs) have attracted much attention as a promising material for transparent conducting films (TCFs), due to their superior electrical conductivity, high mechanical strength, and complete flexibility as well as their one-dimensional morphological features of extremely high length-to-diameter ratios. This study investigated three kinds of SWCNTs with different purities: as-produced SWCNTs (AP-SWCNTs), thermally purified SWCNTs (TH-SWCNTs), thermally and acid purified SWCNTs (TA-SWCNTs). The purity of each SWCNT sample was assessed by considering absorption peaks in the semiconducting ($S_{22}$) and metallic ($M_{11}$) tubes with UV-Vis NIR spectroscopy and a metal content with thermogravimetric analysis (TGA). The purity increased as proceeding the purification stages from the AP-SWCNTs through the thermal purification to the acid purification. The samples containing different contents of SWCNTs were dispersed in water using sodium dodecyl benzensulfate (SDBS). Aqueous suspensions of different purities of SWCNTs were prepared to have similar absorbances in UV-Vis absorption measurements so that one can make the TCFs possess similar optical transmittances irrespective of the SWCNT purity. Transparent conductive SWCNT networks were formed by spraying an SWCNT suspension onto a poly(ethyleneterephthalate) (PET) substrate. As expected, the TCFs fabricated with AP-SWCNTs showed very high sheet resistances. Interestingly, the TH-SWCNTs gave lower sheet resistances to the TFCs than the TA-SWCNTs although the latter was of higher purity in the SWCNT content than the former. The TA-SWCNTs would be shortened in length and be more bundled by the acid purification, relative to the TH-SWCNTs. For both purified (TH, TA) samples, the subsequent nitric acid ($HNO_3$) treatment greatly lowered the sheet resistances of the TCFs, but almost eliminated the difference of sheet resistances between them. This seems to be because the electrical conductivity increased not only due to further removal of surfactants but also due to p-type doping upon the acid treatment. The doping effect was likely to overwhelm the effect of surfactant removal. Although the nitric acid treatment resulted in the similar. electrical properties to the two samples, the TCFs of TH-SWCNTs showed much lower sheet resistances than those of the TA-SWCNTs prior to the acid treatment.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.4
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• pp.515-523
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• 2012

The objective of this study was to investigate the variability in broiler performance, apparent metabolisable energy (AME) and ileal digestible energy (IDE) between five different maize samples fed with and without xylanase at 16,000 U/kg. Various in vitro characterisations were conducted to determine if any could predict performance or AME. Samples of the maize were harvested in five diverse regions and fed individually in a mash diet as follows (g/kg): test maize 608.3; soya bean meal (SBM) 324.1; poultry fat 25.2; salt 4.6; met 2.6; lys 1.6; thr 0.5; limestone 9.7, dical 18.4; vit/min 5.0; CP 210 and ME (kcal/kg) 3,085. The diets were fed to 720 broilers with 6 replicates, each containing 12 birds per treatment, from 0 to 18 d of age. Maize samples were analysed for starch, protein, crude fibre, fat, protein solubility index (PSI) and vitreousness using near infra red reflectance spectroscopy (NIR). They were also assayed using an in vitro starch digestibility method. The results showed that there was no effect of harvest region on the feed intake (FI), body weight gain (BWG) or feed conversion ratio (FCR) of the broilers over the 18 d period (p = 0.959, 0.926, 0.819 respectively). There was an improvement in all parameters with the addition of xylanase (FI p = 0.011; BWG and FCR p<0.001). There was a significant positive effect of xylanase on IDE, AME, IDE Intake (IDEI) and AME intake (AMEI) (p<0.0001 in all cases). Although there was no significant effect of maize source, there was a strong trend towards variability in IDE (p = 0.066) and AME (p = 0.058). There were no significant correlations (p<0.05) between any proximate or physiochemical values and any performance or AME values. This may suggest that none of those selected were suitable predictors for performance or AME. The broilers performed well according to the breed guidelines, with slightly increased FI, increased BWG and similar FCR prior to the addition of xylanase. When FCR and BWG were analysed with FI as a covariate, xylanase addition remained significant suggesting that the improvement in BWG and FCR was driven by an increase in digestibility and nutrient availability.

• Korean Journal of Plant Resources
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• v.23 no.4
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• pp.386-392
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• 2010

This study was done to measure the color and catechins contents in processed teas using the whole bands (400~2500 nm) with near-infrared spectroscopy(NIRS). The powder colors of 109 processed teas were measured with a colorimeter. The a/b ratios in Hunter color scale in processed teas accounted for about 98.9% of the variation in the fermentation degree(FD), indicating that the a/b ratio was a very useful trait for assessing fermentation degree. Also tea powders were scanned in the visible bands used with NIRSystem. The calibration equations for powder colors were developed using the regression method of modified partial least squares(MPLS) with the internal cross validation. The equations had low SECV (standard errors of cross-validation), and high $R^2$ (coefficient of determination in calibration) values with 0.996~1.00, indicating that the visible bands(400~700 nm) with NIRS could be used to rapidly measure the variables related to powder color and fermentation degree. Also another powders of 137 processed teas were scanned at 780~2500 nm bands in the reflectance mode. The calibration equations were developed using the regression method of MPLS with the internal cross validation. The equations had low SECV, and high $R^2$ (0.896~0.983) values, showing that NIRS could be used to rapidly discriminate the contents of EGC($R^2$=0.919), EC(0.896), EGCg(0.978), ECg(0.905) and total catechins(0.983) in processed teas with high precision and ease.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.283-291
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• 2006

To investigate seed non destructive and fast determination technique utilizing near infrared reflectance spectroscopy (NIRs) for screening ultra high oleic (C18:1) and linoleic (C18:2) fatty acid content sesame varieties among genetic resources and lines of pedigree generations of cross and mutation breeding were carried out in National Institute of Crop Science (NICS). 150 among 378 landraces and introduced cultivars were released to analyse fatty acids by NIRs and gas chromatography (GC). Average content of each fatty acid was 9.64% in palmitic acid (C16:0), 4.73% in stearic acid (C18:0), 42.26% in oleic acid and 43.38% in linoleic acid by GC. The content range of each fatty acid was from 7.29 to 12.27% in palmitic, 6.49% from 2.39 to 8.88% in stearic, 12.59% of wider range compared to that of stearic and palmitic from 37.36 to 49.95% in oleic and of the widest from 30.60 to 47.40% in linoleic acid. Spectrums analyzed by NIRs were distributed from 400 to 2,500 nm wavelengths and varietal distribution of fatty acids were appeared as regular distribution. Varietal differences of oleic acid content good for food processing and human health by NIRs was 14.08% of which 1.49% wider range than that of GC from 38.31 to 52.39%. Varietal differences of linoleic acid content by NIRs was 16.41% of which 0.39% narrower range than that of GC from 30.60 to 47.01%. Varietal differences of oleic and linoleic acid content in NIRs analysis were appeared relatively similar inclination compared with those of GC. Partial least square regression (PLSR) among multiple variant regression (MVR) in NIRs calibration statistics was carried out in spectrum characteristics on the wavelength from 700 to 2,500 nm with oleic and linoleic acids. Correlation coefficient of root square (RSQ) in oleic acid content was 0.724 of which 72.4 percent of sample varieties among all distributed in the range of 0.570 percent of standard error when calibrated (SEC) which were considerably acceptable in statistic confidence significantly for analysis between NIRs and GC. Standard error of cross validation (SECV) of oleic acid was 0.725 of which distributed in the range of 0.725 percent standard error among the samples of mother population between analyzed value by NIRs analysis and analyzed value by GC. RSQ of linoleic acid content was 0.735 of which 73.5 percent of sample varieties among all distributed in the range of 0.643 percent of SEC. SECV of linoleic acid was 0.711 of which distributed in the range of 0.711 percent standard error among the samples of mother population between NIRs analysis and GC analysis. Consequently, adoption NIR analysis for fatty acids of oleic and linoleic instead that of GC was recognized statistically significant between NIRs and GC analysis through not only majority of samples distributed in the range of negligible SEC but also SECV. For enlarging and increasing statistic significance of NIRs analysis, wider range of fatty acids contented sesame germplasm should be kept on releasing additionally for increasing correlation coefficient of RSQ and reducing SEC and SECV in the future.