• 농업과학연구
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• 제39권1호
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• Journal of Biosystems Engineering
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• 제33권3호
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• pp.210-215
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• 2008

The objective of this study was to develop models to predict SCC (somatic cell count) in unhomogenized milk by visible and near-infrared (NIR) spectroscopic technique. Total of 100 milk samples were collected from dairy farms and preserved to minimize propagation of bacteria cells during transportation. Reductive reagents such as methyl red, methylene blue, bromcresol purple, phenol red and resazurin were added to milk samples, and then colors of milk were changed based on SCC of milk. For optimal reductive reagents, reaction time was controlled at 3 level of reaction time. A spectrophotometer was used to measure reflectance spectra from milk samples. The partial least square (PLS) models were developed to predict SCC of unhomogenized milk. The PLS results showed that milk samples with reductive reagents had a good correlation between predicted and measured SCC at 5 minutes of reaction time in the visible range. The PLS models with resazurin reagent had the best performance in $400{\sim}600\;nm$. The prediction results of milk samples with resazurin had 0.86 of correlation coefficient and 14,184 cell/mL of SEP.

• Transactions on Electrical and Electronic Materials
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• 제16권5호
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• pp.280-284
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• 2015

Among many the oxynitrides, TiNO and AlCrNO, have diverse applications in different technological fields. We prepared TiNO/AlCrNO/Al thin films on aluminum substrates using the method of dc reactive magnetron sputtering. The reactive gas flow, gas mixture, and target potential were applied as the sputtering conditions during the deposition in order to control the chemical composition. The multi-layer films have been prepared in an Ar and O₂+N₂ gas mixture rate. The surface properties were estimated by performing scanning electron microscopy (SEM). At a wavelength range of 0.3~2.5 μm, the exact composition and optical properties of thin films were measured by Auger electron spectroscopy (AES) and Ultraviolet-visible-near infrared (UV-Vis-NIR) spectrophotometry. The optimal absorptance of multi-layer films was exhibited above 95.5% in the visible region of the electromagnetic spectrum, and the reflectance was achieved below 1.89%.

• Journal of Biosystems Engineering
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• 제23권6호
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• pp.561-570
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• 1998

The MLR(Multiple Linear Regression) models to estimate soluble solids content non-destructively were presented to make a selection of optimal photosensor utilized to measure the soluble solids content of apples. Visible and NIR absorbance in the 400 to 2498 nanometer(nm) wavelength region, soluble solids content(sugar content), hardness, and weight were measured for 400 apples(gala). Spectrophotometer with fiber optic probe was utilized for spectrum measurement and digital refractometer was used for soluble solids content. Correlation between absorbance spectrum and soluble solids content was analyzed to pick out the optimal wavelengths and to develop corresponding prediction model by means of MLR. For the coefficient of determination($R^2$) to be over 0.92, the MLR models out of the original absorbance were built based on 7 wavelengths of 992, 904, 1096, 1032, 880, 824, 1048nm, and the ones of the second derivative absorbance based on 5 wavelengths of 784, 1056, 992, 808, 872nm. The best model of the second derivative absorbance spectrum had $R^2$=0.91, bias= -0.02bx, SEP=0.28bx for unknown samples.

• Current Applied Physics
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• 제18권11호
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• pp.1225-1229
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• 2018

In this paper, we investigated the electronic structures and defect states of $SrLaMgTaO_6$ (SLMTO) double perovskite structures by using resonant inelastic x-ray scattering. Recently, $Eu^{3+}$ doped SLMTO red phosphors have been vigorously investigated due to their higher red emission efficiency compared to commercial white light emitting diodes (W-LED). However, a comprehensive understanding on the electronic structures and defect states of host SLMTO compounds, which are specifically related to the W-LED and photoluminescence (PL), is far from complete. Here, we found that the PL spectra of SLMTO powder compounds sintered at a higher temperature, $1400^{\circ}C$, were weaker in the blue emission regions (at around 400 nm) and became enhanced in near infrared (NIR) regions compared to those sintered at $1200^{\circ}C$. To elucidate the difference of the PL spectra, we performed resonant inelastic x-ray spectroscopy (RIXS) at Ta L-edge. Our RIXS result implies that the microscopic origin of different PL spectra is not relevant to the Ta-related defects and oxygen vacancies.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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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.

• 한국축산시설환경학회지
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• 제13권2호
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• pp.113-120
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• 2007

본 시험은 근적외선분광법을 이용한 돈분뇨 액비의 질소, 인산, 칼리, 수분 및 유기물의 분석 가능성을 구명하고, 이를 활용한 분석기의 개발을 목적으로 수행하였으며, 그 결과는 다음과 같다. 1. 돈분뇨 액비시료는 $400{\sim}2,500nm$ 대역의 근적외선을 시료에 투과하여 측정하였으며, 동일시료에 대한 습식분석 결과, N, $P_2O_5,\;K_2O$, 수분 및 유기물 함량은 각각 1,555mg/l, 302mg/l, 240mg/l, 98.8%, 0.53%로 조사되었다. 2. 근적외선 분광광도법을 이용한 분석에서 N, $P_2O_5,\;K_2O$, 수분 및 유기물에 대한 RSQ ($r^2$, R, Coefficient of determination)는 각각 0.9190, 0.9749, 0.5046, 0.9883 및 0.9777이었고 SEC(Standard Error of Calibration)는 2.1649, 0.5019, 1.9252, 0.1180 및 0.0789였다. 3. 액비에 대한 이화학적 습식분석과 NIR 흡수스펙트럼 측정결과를 비교 분석하여 돈 분뇨 액비에 포함된 질소, 인산, 칼리, 수분 및 유기물 함량을 실시간으로 분석하고 액비 성분량을 자동 계산할 수 있는 알고리즘을 도입한 액비분석 프로그램을 작성하였다. 4. 액비 성분분석 시작기는 근적외선(NIR : Near InfraRed)을 받아들여 실시간으로 액비성분의 흡수율을 측정하는 광검출장치(NIR Spectrometer), 근적외선 Light Source로부터 나오는 빛을 반사시키는 반사경, 액비성분 분석용 시료를 넣어 측정하는 Cell Mount, $400{\sim}2,500nm$ 대역의 가시광선-근적외선을 방출하는 Tungsten halogen lamp, NIR Spectrometer와 Tungsten halogen lamp로 전압을 입력시켜 주는 Power Supply Module 및 전체를 Black Anodizing한 외형으로 구성되었다. 5. 실험결과, 칼리를 제외한 액비내 모든 성분이 광을 흡수하는 강도는 성분의 농도에 비례하였으며 원시 스펙트럼의 중첩 제거 및 빛의 산란보정을 통해 액비의 질소, 인산성분, 수분 및 유기물 함량을 측정하는데 효과적으로 이용할 수 있을 것으로 사료되며, 분광분석법을 이용한 액비성분 분석기 개발이 완료되면 현장에서 신속하고 정확한 분석이 가능할 것으로 판단된다.

• 한국작물학회지
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• 제53권spc호
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• pp.78-83
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• 2008

콩에 함유된 성분 중 가장 많은 양으로 존재하며, 인축의 주요 단백질 공급원으로 이용되고 있는 콩 단백질의 함량을 1립 비파괴 근적외 분광분석법을 이용하여 동일품종의 개체 내에서 콩이 달린 착협 위치에 따라, 또 콩에서 단백질 함량을 분석하기 위해 개체 내에서 분석시료를 취할 때 개체를 대표할 수 있는 최소 양을 실험적으로 검토한 결과를 요약하면 다음과 같다. 1. 선녹콩 개체 내 단백질 함량은 정규분포를 보였으며, 개체 간에 단백질 함량의 차이가 인정되었다. 2. 콩의 착협 위치에 따른 단백질 함량은 지표면에 가까울수록 단백질 함량이 높았고, 콩 식물체의 윗부분으로 갈수록 단백질 함량이 낮아지는 경향을 나타내었다. 3. 콩에 함유된 단백질의 함량을 정량적으로 분석하기 위해 필요한 최소 시료량을 추정한 결과 최소 10립 이상 혹은 개체 내 총 종자량의 20% 이상을 취하면 개체를 대표하는 단백질 함량을 얻을 수 있는 것으로 조사되었다.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• 한국작물학회지
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• 제64권4호
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• pp.353-365
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• 2019

본 연구는 근적외선 분광분석기(NIRS) 예측모델을 설정하여 유전자원 대량분석 체계를 확립하고 그에 따른 국내 외 밀 자원의 단백질 함량에 관한 기초 정보를 제공하고자 하였다. 1. 농업유전자원센터에 보유하고 있는 20,000여 자원 중 1,798자원을 검량 자원으로 선발하였다. 검량자원의 NIR 스펙트럼을 측정하였고, 단백질 함량 습식분석 데이터 입력 등 일련의 통계적 처리 과정을 거쳐 NIRS 예측모델을 설정했다. 검량 자원의 다양성 지수는 0.80이었고, 습식 분석법에 의한 단백질 평균은 13.2%, 함량 구간은 7.0-20.8%였다. 최적화된 NIRS 모델의 R², SEC, Slope은 0.997, 0.132, 1.000이었다. 300자원을 사용하여 외부 검정 과정을 실시하였고 R², SEP, Slope은 0.994, 0.191, 1.013이었다. 최적화된 NIRS 모델과 외부검정 결과의 통계치가 상호 유사하였고, 1에 가까운 R²와 Slope 값, 낮은 SEC와 SEP 값을 볼 때 본 연구에서 설정한 NIRS 모델은 습식 분석법을 대체하여 밀 자원의 단백질 함량 분석에 적용 가능할 것으로 판단되었다. 2. 국내외 수집된 밀 6,794자원의 NIRS 단백질 함량 측정값을 정규분포로 작성하여 특성을 파악했다. 자원의 다양성 지수는 0.79, 단백질 평균은 12.1%, 전체 자원의 임의구간 42.1% 단백질 함량자원 범위는 10-13%이었으며, 68.0%를 차지하는 자원들의 단백질 함량 범위는 9.5-14.7%였다. 3. 전체 6,794자원의 품종 집단 구성은 육성계통 3,128자원, 재래종 2,705자원, 육성품종 961자원이었다. 육성계통 자원의 다양성 지수는 0.80, 단백질 평균은 11.8%, 전체 자원의 68%를 차지하는 자원들의 함량 범위는 9.2-14.5%였다. 재래종 자원의 다양성 지수는 0.76, 단백질 평균은 12.1%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 9.8-14.4%였다. 육성품종 자원의 다양성 지수는 0.80, 단백질 평균은 12.8%, 전체 자원의 68.0%를 차지하는 자원들의 함량 범위는 10.2-15.4%였다. 재래종 자원은 가장 낮은 다양성 지수를 나타냈고, 육성계통과 육성품종은 동일한 다양성 지수를 나타냈다. 육성계통은 가장 낮은 단백질 평균을 나타냈고, 육성품종은 가장 높은 단백질 평균을 나타냈다.