• Near Infrared Analysis
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• v.2 no.1
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• pp.59-66
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• 2001

Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.87-87
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• 2017

농산물의 품질 및 성분을 측정하는데 있어 기존의 화학적 분석 방식은 정밀도가 높으나 측정에 소요되는 시간과 비용이 많이 들어, 현장 적용하기에는 한계가 있다. 일반적으로 근적외선 분광 분석(Near Infra Red Spectroscopy, NIRS) 방법은 가공 과정에 따라 빠르게 변화되는 단백질 조성 및 수분함량 측정 등에 이용되고 있다. 분석에 소요 시간이 많이 걸리는 켈달법(Kjeldahi method)에 비해 NIR 분광 분석을 통한 보정으로 연속적인 모니터링이 가능하다. 본 연구에서 사용된 시료를 고정시키기 위한 프레임을 제작한 후 NIR센서와 광원인 LED의 각도를 고정시키고 측정 대상체인 사절된 감자 크기에 따라 시료를 고정시킬 수 있는 프레임을 반사면에 위치시켰다. 확산 반사법을 이용하여 프레임에 씨감자 시료를 고정 시킨 후 백색 LED를 이용하여 감자 표면에 빛을 반사시켜 3일 동안 12시간 마다 해당 시료들(열처리, 비누용액 침지, 생감자)의 스펙트럼을 측정하였다. 해당 시료들은 측정 기간 동안 저온상태($4^{\circ}C$)와 실온상태($20^{\circ}C$)에서 보관되었다. 실험 결과는 파장대 145nm에서 저온상태에서 보관된 생감자는 시간경과에 따른 흡광도의 결정 계수값($r^2$)은 0.98 이었다. 이는 감자가 저온에서 생감자의 상태 변화가 일어나고 있다는 것을 의미하고 파장대 145nm에서 시간에 따른 저온상태에서 보관한 감자의 상태 변화 예측이 가능함을 의미한다. 비누용액에 침지시킨 후 실온에 보관한 감자는 시간이 경과함에 따라 파장이 증가함에 따라 흡광도가 증가하였다. 이는 감자에 들어있는 Polyphenol Oxidase 함량 변화로 갈변 현상이 일어난 것을 알 수 있다. 또한 실온에서 보관한 생감자도 시간 경과에 따라 갈변 현상이 일어났지만 용액에 침지시킨 감자보다는 갈변 현상이 36시간 이후로 발견되었다. 열처리 후 실온에서 보관한 감자의 경우에는 갈변현상이 나타나지 않았다. 저온상태에서 보관한 감자시료들 모두 갈변형상이 나타나지 않았지만, 24시간이 지난 후 용액에 침지시킨 감자는 갈변 현상이 발생되었다. 생감자와 열처리한 감자는 시간 경과에 따른 갈변현상이 일어나지 않았으므로, 감자의 갈변현상은 감자의 표면 처리 방법에 국한되지 않고 온도에 영향을 더 많이 받는다는 것을 나타내고 있다. 본 연구는 향후 감자의 품질 및 성분 측정에서 간편하게 사용될 수 있는 감자의 품질 계측 기술에 기여할 것으로 판단된다.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1247-1247
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• 2001

Constituents of animal biofluids such as milk, blood and urine contain information specifically related to metabolic and health status of the ruminant animals. Some changes in composition of biofluids can be attributed to disease response of the animals. Mastitis is a major problem for the global dairy industry and causes substantial economic losses from decreasing milk production and reducing milk quality. The purpose of this study was to investigate potential of NIRS combined with multivariate analysis for cow's mastitis diagnosis based on NIR spectra of milk, blood and urine. A total of 112 bulk milk, urine and blood samples from 4 Holstein cows were analyzed. The milk samples were collected from morning milking. The urine samples were collected before morning milking and stored at -35$^{\circ}C$ until spectral analysis. The blood samples were collected before morning milking using a catheter inserted into the carotid vein. Heparin was added to blood samples to prevent coagulation. All milk samples were analyzed for somatic cell count (SCC). The SCC content in milk was used as indicator of mastitis and as quantitative parameter for respective urine and blood samples collected at same time. NIR spectra of blood and milk samples were obtained by InfraAlyzer 500 spectrophotometer, using a transflectance mode. NIR spectra of urine samples were obtained by NIR System 6500 spectrophotometer, using 1 mm sample thickness. All samples were divided into calibration set and test set. Class variable was assigned for each sample as follow: healthy (class 1) and mastitic (class 2), based on milk SCC content. SIMCA was implemented to create models of the respective classes based on NIR spectra of milk, blood or urine. For the calibration set of samples, SIMCA models (model for samples from healthy cows and model for samples from mastitic cows), correctly classified from 97.33 to 98.67% of milk samples, from 97.33 to 98.61% of urine samples and from 96.00 to 94.67% of blood samples. From samples in the test set, the percent of correctly classified samples varied from 70.27 to 89.19, depending mainly on spectral data pretreatment. The best results for all data sets were obtained when first derivative spectral data pretreatment was used. The incorrect classified samples were 5 from milk samples,5 and 4 from urine and blood samples, respectively. The analysis of changes in the loading of first PC factor for group of samples from healthy cows and group of samples from mastitic cows showed, that separation between classes was indirect and based on influence of mastitis on the milk, blood and urine components. Results from the present investigation showed that the changes that occur when a cow gets mastitis influence her milk, urine and blood spectra in a specific way. SIMCA allowed extraction of available spectral information from the milk, urine and blood spectra connected with mastitis. The obtained results could be used for development of a new method for mastitis detection.

• Journal of Pharmaceutical Investigation
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• v.39 no.1
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• pp.29-36
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• 2009

Since the quality of final products is significantly affected by the homogeneity of powder mixture, the powder blending process has been regarded as one of the critical pharmaceutical unit processes, especially for solid dosage forms. Accordingly, the monitoring to determine a blending process' end-point based on a faster and more accurate in-line/on-line analysis has attracted enormous attentions recently. Among various analytical tools, NIR (near-infrared) spectroscopy has been extensively studied for PAT (process analytical technology) system due to its many advantages. In this study, NIR spectroscopy was employed with an optical fiber probe for the in-line monitoring of fluid-bed blending process. The position of the probe, the ratio of binary powder mixture, the powder size differential and the back-flush period of the shaking bag were examined as principal process parameters. During the blending process of lactose and mannitol powders, NIR spectra were collected, corrected, calibrated and analyzed using MSC and PLS method, respectively. The probe position was optimized. A reasonable end-point was predicted as 1,500 seconds based on 5% RSD value. As a consequence, it was demonstrated that the blending process using a fluid-bed processor has several advantages over other methods, and the application of NIRS with an optical fiber probe as PAT system for a fluid-bed blending process could be high feasible.

• Analytical Science and Technology
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• v.30 no.5
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• pp.234-239
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• 2017

Identifying the components of residues that are not completely burned at the sites of fires site can provide valuable information for tracing the causes of fires. In order to clarify the types of plastic combustion residues found at the scenes of fires, we studied the residue formed after the combustion of polyethylene (PE) and acrylonitrile butadiene styrene (ABS). Plastic samples were burned at 200, 300, 350, 400, and $500^{\circ}C$ for 3 min using a cone calorimeter, and the changes in weight and combustion products were observed. The powder products obtained by lyophilization and pulverization of the combustion products obtained at each temperature were analyzed by a Fourier transform-near infrared (FT-NIR) spectrometer. When the PE samples were burned, the weight did not change up to $350^{\circ}C$, however a significant change in the weight could be measured above $400^{\circ}C$. The principal component analysis (PCA) of the FT-NIR spectra of the PE and ABS samples obtained at each temperature confirmed that the combustion residues at each temperature were PE and ABS, respectively. Therefore, the types of unburned plastics found at the sites of fires can be confirmed rapidly by near infrared spectroscopy.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1615-1615
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• 2001

During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.

• Journal of Science Education
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• v.46 no.3
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• pp.255-265
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• 2022

The purpose of this study is to analyze and compare brain activation that appears in the self-regulation process of biology major and non-major college students in life science learning. The self-regulation task implemented a life science learning situation with the concept of biological classification. The brain activation of college students was measured and analyzed by fNIRS. In the assimilation process, bilateral FP and left DLPFC show significant activation, and the two groups show a difference in the left OFC activation related to motivation and reward. In the conflict process, the left DLPFC shows significantly lower activation in common, and the two groups show a difference in activation between BA 46, which is related to recent memory, and BA 47, which is related to long-term memory. In the accommodation process, a significantly high activation was found in right DLPFC in common, and the two groups show a difference in activation between right DLPFC and right FP. These areas are in the right frontal lobe area and are related to the understanding of life science knowledge. As a result of this study, it can be seen that the brain activation patterns of biology major and non-major college students are different in the self-regulation process. In addition, we will propose additional neurological studies on self-regulation and present systems and learning strategies that can be constructed in school settings.

• Food Engineering Progress
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• v.15 no.1
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• pp.48-55
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• 2011

In this research, the near-infrared absorption from 1,100-2,300 nm was used to measure the content of capsaicinoids in the red-pepper powder by using the Acousto-optic tunable filters (AOTF) spectrometer with sample plate and sample rotating unit. Non-spicy red-pepper samples from one location (Younggwang-gun. Korea) were mixed with spicy one (var. Chungyang) to make samples separated by particle size (below 0.425 mm, 0.425-0.71 mm, and 0.71- 1.4 mm). The Partial Least Squares Regression (PLSR) model to predict the capsaicinoid content on particle sizes was developed with measured spectra by AOTF spectrometer and used to analyze the amount of capsaicinoids by HPLC. The PLSR Model of red-pepper powder of below 0.425 mm, 0.425-0.71 mm, and 0.71-1.4 mm with cross validation had ${R_V}^2$ = 0.948-0.979 and Standard Error of Prediction (SEP) = 6.56-7.94 mg%. The prediction error of smaller particle size of red-pepper powder was low. The best PLSR model was found in pretreatment of Range Normalization, Standard Normal Variate, and 1st Derivatives of red-pepper powder of below 1.4 mm with cross validation, having ${R_V}^2$ = 0.959 and SEP = 8.82 mg%.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.4
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• pp.257-267
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• 2023

The grassland section of the greenhouse gas inventory has limitations due to a lack of review and verification of biomass compared to organic carbon in soil while grassland is considered one of the carbon storages in terrestrial ecosystems. Considering the situation at internal and external where the calculation of greenhouse gas inventory is being upgraded to a method with higher scientific accuracy, research on standards and methods for calculating carbon accumulation of grassland biomass is required. The purpose of this study was to identify international trends in the calculation method of the grassland biomass sector that meets the Tier 2 method and to conduct a review of variables applicable to the Republic of Korea. Identify the estimation methods and access levels for grassland biomass through the National Inventory Report in the United Nations Framework Convention on Climate Change and type the main implications derived from overseas cases. And, a field survey was conducted on 28 grasslands in the Republic of Korea to analyse the applicability of major issues. Four major international issues regarding grassland biomass were identified. 1) country-specific coefficients by land use; 2) calculations on woody plants; 3) loss and recovery due to wildfire; 4) amount of change by human activities. As a result of field surveys and analysis of activity data available domestically, it was found that there was a significant difference in the amount of carbon in biomass according to use type classification and climate zone-soil type classification. Therefore, in order to create an inventory of grassland biomass at the Tier 2 level, a policy and institutional system for making activity data should develop country-specific coefficients for climate zones and soil types.