• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.29-34
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• 2021

Near infrared reflectance spectroscopy (NIRS) is routinely used for the determination of nutrient components of forages. However, little is known about the impact of sample preparation and wavelength on the accuracy of the calibration to predict minerals. This study was conducted to assess the effect of sample preparation and wavelength of near infrared spectrum for the improvement of calibration and prediction accuracy of Calcium (Ca) and Phosphorus (P) in imported hay using NIRS. The samples were scanned in reflectance in a monochromator instrument (680-2,500 nm). Calibration models (n = 126) were developed using partial least squares regression (PLS) based on cross-validation. 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 highest R2 and the lowest SECV were obtained using oven-dry grinded sample preparation and 1,100-2,500 nm wavelength. The calibration (R2) and SECV were 0.99 (SECV: 468.6) for Ca and 0.91 (SECV: 224.7) for P in mg/kg DM on a dry weight, respectively. Results of this experiment showed the possibility of NIRS method to predict mineral (Ca and P) concentration of imported hay in Korea for routine analysis method to evaluate the feed value.

• Journal of the Korean Wood Science and Technology
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• v.38 no.6
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• pp.526-531
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• 2010

For efficient use of wood, it is important to control moisture of wood in processing wood. Near-infrared (NIR) spectroscopy can be used to estimate the physical and chemical properties of materials quickly and nondestructively. In this study, it was intended to measure the moisture contents on the surface of wood using NIR spectroscopy coupled with multivariate analytic statistical techniques. Because NIR spectroscopy is affected by the chemical components of the specimens and contains signal noise, a regression model for detecting moisture content of wood was established after carrying out several numerical pretreatments such as Smoothing, Derivative and Normalization in this study. It shows that the regression model using NIR absorbance in the range of 750~2,500 nm predicts the actual surface moisture content very well. Near-infrared spectroscopy technique developed in this study is expected to improve a technology to control moisture content of wood in using and drying process.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.98-98
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• 2017

대부분의 가정과 요식업체, 식품가공업계에서 이용하고 있는 식용유지는 저장 및 가공과정 중에 산패가 빈번하게 일어나게 된다. 기존에는 유지 산패를 측정하기 위해 산가, 과산화물가 등을 측정하는 이화학적인 적정방법을 이용하였는데 실험자의 숙련도에 따라 결과의 오차가 발생할 수 있고, 반복실험으로 인한 시간과 비용이 많이 소모되는 등 여러 제약사항을 포함하고 있어 식용유지의 산패를 실시간 비파괴적으로 분석할 수 있는 기술의 개발에 많은 관심이 모아지고 있다. 따라서, 본 연구에서는 식용유지의 저장조건에 따른 산패정도를 비파괴적으로 평가하기 위한 근적외선 분광분석과 인공신경망 분석기술을 개발하여 그 실효성을 평가하였다. 식물성 식용유지인 들기름을 특정 온도에서 일정한 시간동안 저장하면서 이화학적 적정방법을 통해 산가와 과산화물가를 측정하였으며 동일한 시료의 근적외선 투과스펙트럼을 획득하였다. 수집된 정보를 이용하여 유지 산패 예측 모델을 개발하기 위해 다변량 분석기법 (주성분 회귀분석, 최소자승 회귀분석과 인공신경망 분석)을 적용하였다. 분석 결과, 인공신경망 분석모델이 산가 ($R^2_{tra}:0.9037$, $R^2_{val}:0.8175$, $R^2_{test}:0.8555$)와 과산화물가 ($R^2_{tra}:0.9210$, $R^2_{val}:0.9341$, $R^2_{test}:0.8286$)의 예측 성능이 가장 우수한 것으로 확인되었다. 본 연구의 결과들은 농산물과 식품의 성분 측정뿐만 아니라 다른 산업분야에서도 유용하게 활용될 수 있을 것으로 기대되어진다.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.spc1
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• pp.42-46
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• 2006

The purpose of this study was to assess whether mechanical sensory score by Toyo Midometer can be substituted by near-infrared spectroscopy (NIRS) method in whole-grain milled rice samples. Toyo values of collected commercial brand rice (n=127) had comparatively wide ranges from 62.9 to 84.2 (Mean=70.5; S.D.=4.0). Calibration equation was developed using 73 samples. Standard error of calibration (SEC) for sensory score equation and $R^2$ were 0.95, and 0.94, respectively, however, percentage of variation in the reference method values (1-VR) which give a true indication of equation performance was slightly lower (1-VR=0.81) than calibration equation. It was demonstrated that, even though NIRS has potential as a rapid tools to predict rice sensory score, the prediction of sensory score in rice by NIRS needs to be further investigation on a large number of sample with different varieties and growing locations.

• Korean Journal of Food Science and Technology
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• v.24 no.5
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• pp.404-407
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• 1992

This study was conducted to determine the effect of the physical and chemical factors on the absorbance when the chemical component of food was rapidly and effectively analyzed with near infrared reflection spectrophotometer. The absorbance was measured within the wavelength range of 1100 and 2500m and at the various sample temperatures. The absorbance was greatly increased with the rising sample temperature. When the grinding time of samples prolonged, the absorbance was decreased. The absorption peaks occurring in the near infrared spectra of meat, meat protein, pork fat and water were attributed to the overtone and combination vibration of C-H, N-H, O-H or C=O bond within the macromolecules of each sample. The absorbance was lower for meat protein than other meat components. Pork fat was characterized by the ${\cdot}CH_2{\cdot}$ absorption peak at the wavelength of 1700 and 2300 nm and water by the relatively high absorption peak at the wavelength of 1450 and 1930 nm. As a result, the absorbance of near infrared reflection spectrum of meat was affected mainly by fat and water in meat.

• Proceedings of the Korean Society of Tobacco Science Conference
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• 1998.05a
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• pp.23-24
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• 1998

• Proceedings of the Korean Society of Tobacco Science Conference
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• 1998.05a
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• pp.25-25
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• 1998

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06a
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• pp.47-52
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• 1996

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.02a
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• pp.479-484
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• 2000

• The Bulletin of The Korean Astronomical Society
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• v.31 no.2
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• pp.61-61
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• 2006