• 제목/요약/키워드: Near-infrared (NIR) spectroscopy

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휴대용 분광분석기를 이용한 알코올 중에 함유되어 있는 물의 측정 (Determination of water content in alcohol by portable near infrared (NIR) system)

  • 안지원;우영아;김효진
    • 분석과학
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    • 제16권2호
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    • pp.95-101
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    • 2003
  • 본 연구에서는 근적외선 분광분석법 (NIR)을 이용하여 메탄올과 에탄올 혼합액 중의 물의 함량을 비파괴적으로 측정하였다. Photo-diode array 방식의 휴대용 NIR system과 scanning 방식의 NIR spectrometer를 이용하여 두 기기 사이의 calibration 결과를 비교하였다. 알코올 혼합액 중의 물의 함량을 정량분석 하기 위해 부분최소자승회귀분석법 (PLSR : partial least squares regression)을 사용하였다. 그 결과 SEP (standard error of prediction)가 photo-diode array 방식을 사용하였을 때는 0.10%, scanning 방식을 사용하였을 때는 0.12%였다. Calibration 모델의 안정성을 확인하기 위하여 6일 동안 2%의 메탄올을 함유하고 있는 에탄올 용액 중의 물의 함량이 3%, 5% 및 7% 되도록 시료를 조제하여 측정하였다. 두 가지 방식의 NIR 모두 3%이내의 변동계수 (CV : coefficient of variation)로 좋은 결과를 나타내었다. 이번 연구를 통해서 메탄올과 에탄올 혼합액 중의 물의 함량 측정이 근적외선 분광분석법을 이용하여 성공적으로 수행되었고 photo-diode array 방식의 휴대용 NIR 시스템을 이용해서 scanning 방식의 NIR spectrometer를 이용한 결과와 유사한 결과를 얻을 수 있었다.

DETERMINATION OF MOISTURE AND NITROGEN ON UNDRIED FORAGES BY NEAR INFRARED REFLECTANCE SPECTROSCOPY(NIRS)

  • Cozzolino, D.;Labandera, M.;Inia La Estanzuela
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1620-1620
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    • 2001
  • Forages, both grazed and conserved, provide the basis of ruminant production systems throughout the world. More than 90 per cent of the feed energy consumed by herbivorous animals world - wide were provided by forages. With such world - wide dependence on forages, the economic and nutritional necessity of been able to characterize them in a meaningful way is vital. The characterization of forages for productive animals is becoming important for several reasons. Relative to conventional laboratory procedures, Near Infrared Reflectance Spectroscopy (NIRS) offers advantages of simplicity, speed, reduced chemical waste, and more cost-effective prediction of product functionality. NIR spectroscopy represents a radical departure from conventional analytical methods, in that entire sample of forage is characterized in terms of its absorption properties in the near infrared region, rather than separate subsamples being treated with various chemicals to isolate specific components. This forces the analyst to abandon his/her traditional narrow focus on the sample (one analyte at a time) and to take a broader view of the relationship between components within the sample and between the sample and the population from which it comes. forage is usually analysed by NIRS in dry and ground presentation. Initial success of NIRS analysis of coarse forages suggest a need to better understand the potential for analysis of minimally processed samples. Preparation costs and possible compositional alterations could be reduced by samples presented to the instrument in undried and unground conditions. NIRS has gained widespread acceptance for the analysis of forage quality constituents on dry material, however little attention has been given to the use of NIRS for chemical determinations on undried and unground forages. Relatively few works reported the use of NIRS to determine quality parameters on undried materials, most of them on both grass and corn silage. Only two works have been found on the determination of quality parameters on fresh forages. The objectives of this paper were (1) to evaluate the use of NIRS for determination of nitrogen and moisture on undried and unground forage samples and (2) to explore two mathematical treatments and two NIR regions to predict chemical parameters on fresh forage. Four hundred forage samples (n: 400) were analysed in a NIRS 6500 instrument (NIR Systems, PA, USA) in reflectance mode. Two mathematical treatments were applied: 1,4,4,1 and 2,5,5,2. Predictive equations were developed using modified partial least squares (MPLS) with internal cross - validation. Coefficient of determination in calibration (${R^2}_{CAL}$) and standard error in cross-validation (SECV) for moisture were 0.92 (12.4) and 0.92 (12.4) for 1,4,4,1 and 2,5,5,2 respectively, on g $kg^{-1}$ dry weight. For crude protein NIRS calibration statistics yield a (${R^2}_{CAL}$) and (SECV) of 0.85 (19.8) and 0.85 (19.6) for 1,4,4,1 and 2,5,5,2 respectively, on a dry weight. It was concluded that NIRS is a suitable method to predict moisture and nitrogen on fresh forage without samples preparation.

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NIR - a Tool for Evaluation of Milling Procedure

  • Gergely, Sziveszter;Handzel, Lidia;Zoltan, Andrea;Salgo, Andras
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1125-1125
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    • 2001
  • Micro-scale test methods are producing small-sample size where the conventional physical and chemical tests can not be used (high standard deviation, uncertain sampling conditions, low repeatability). Different small-scale test methods were developed recently for determination of physico-chemical, functional, rheological properties of wheat or wheat dough using miniaturized instruments with sophisticated sample preparation/handling and mechanics (RVA, 2 g mixograph, micro-Z-arm mixer, small-scale noodle maker, micro-baking method etc.). The small-scale methodologies can be used as basic research tools or as technology supported measurements and can be also essential in the early selection for quality traits in breeding programs. The milling as a sample preparation step is essential procedure providing good quality flour or semolina samples from small amount of grain (5-10 g) in a reproducible and reliable way. The aim of present study was to use NIR as quality control tool, and to evaluate the recently developed and manufactured micro-scale lab mill (FQC-2000) produced by Inter-Labor Co. Ltd., Hungary. The milling characteristics of the new instrument were compared to other laboratory mills and the effects of milling action on the chemical composition of fractions were analysed. The fractions were tested with both chemical and near infrared spectroscopic methods. The micro-scale milling resulted significantly different yields, particle size distributions and different fractions from compositional point of view. The near infrared spectra were sensitive enough to distinguish the fractions obtained by different milling procedures. Quantitative NIR calibration equations were developed and tested in order to measure the chemical composition of characteristic milling fractions. Special qualification procedure the PQS (Polar Qualification System) method was used for detecting the differences between fractions obtained by macro and micro-milling procedures. The results and the limitations of PQS method in this application will be discussed.

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닥나무 인피섬유와 한지의 원산지 판별모델 개발을 위한 NIR 및 MIR 스펙트럼 데이터의 PLS-DA 적용 (Discrimination model for cultivation origin of paper mulberry bast fiber and Hanji based on NIR and MIR spectral data combined with PLS-DA)

  • 장경주;정소윤;고인희;정선화
    • 분석과학
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    • 제32권1호
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    • pp.7-16
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    • 2019
  • 본 연구에서는 닥나무 인피섬유와 이를 이용하여 제조한 한지의 FT-NIR및 FT-MIR 스펙트럼 데이터를 각각PLS-DA에 적용하여 닥나무 인피섬유 및 한지의 원산지 판별 모델을 개발하고자 하였다. 본 연구를 위하여 서로 다른 원산지의 국내산 닥나무 인피섬유 10점을 채취하여 한지로 제조하였다. 상기시료의 FT-NIR 및 FT-IR 스펙트럼 데이터는 데이터 전처리 과정을 거쳐 PLS-DA를 수행하였다. 모델링 결과, 닥나무 인피섬유와 한지의 NIR 스펙트럼 데이터가 판별모델의 교차 검증결과 및 성능평가(정확도, 민감도, 특이도)에서 모두 100 %로 MIR 스펙트럼 데이터보다 우수한 판별 성능을 나타냈다. 또한 지역별로 4 개의 그룹을 형성하는 것을 확인 할 수 있었으며, 닥나무 인피섬유와 한지의 원산지 판별 모델 간 score 형태가 유사하게 나타내는 것을 확인하였다.

Improving Accuracy of Soil Property Measurements by NIR Spectroscopy

  • Ryu, Kwan Shig;Cho, Rae Kwang;Park, Woo Churl;Kim, Bok Jin
    • Journal of Applied Biological Chemistry
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    • 제44권4호
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    • pp.177-179
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    • 2001
  • Traditional wet chemical methods for testing of soil properties require extensive time and labor, and cause the discharge of pollutants, making them undesirable for routine soil analyses. This research was conducted to improve the accuracy of soil properties in soil fertility assessments. A total of 140 finely ground soil samples were used to obtain accurate calibrations and validation for estimating soil moisture, OM, and T-N. Finely ground soil samples satisfied the improved accuracy for routine NIR measuring of the field soils. The results indicated that NIR spectroscopy could be used as a routine method for quantitatively determining OM, moisture, and T-N of field soil, although this technique requires many combinations of sample pretreatments and data manipulations to obtain optimal predictions.

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Quality assessment of mushroom (Agricus bisporus) composts during production using Near Infrared spectroscopy

  • Hss, Sharma;Kilpatrick, M;Lyons, G;Murray, J;Mellon, R
    • 한국근적외분광분석학회:학술대회논문집
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    • 한국근적외분광분석학회 2001년도 NIR-2001
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    • pp.1517-1517
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    • 2001
  • Cultural conditions during production of compost, using wheat straw and chicken litter as raw materials, will affect the microbial and biochemical characteristics, leading to a wide variation in mushroom productivity. Over the past 10 years, chemical and instrumental methods, suitable for assessing compost quality have been studied in Northern Ireland. In addition, the use of near subject of investigation over the past 4 years. Previous studies have shown that NIRS can be used fer assessing quality of dried and milled composts. The aim of the current investigation is to develop NIR calibrations for key quality parameters such as dry matter, pH, nitrogen, carbon, ash, microbial population and fibre factions during the two stages of production using spectra of fresh composts. Near infrared reflectance measurements of fresh composts prepared by 6 producers were made during a two-year period. Although the spectra of fresh composts were dominated by two moisture peaks at 1450 nm and 1940 nm, good calibrations for determining moisture content, conductivity, pH, nitrogen, carbon and fibre fractions were developed. The results of quality assessment during commercial production using the calibrations will be presented and discussed.

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The analysis of oat chemical properties using visible-near infrared spectroscopy

  • Jang, Hyeon Jun;Choi, Chang Hyun;Choi, Tae Hyun;Kim, Jong Hun;Kwon, Gi Hyeon;Oh, Seung Il;Kim, Hoon;Kim, Yong Joo
    • 농업과학연구
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    • 제43권5호
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    • pp.715-722
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    • 2016
  • Rapid determination of food quality is important in food distribution. In this study, the chemical properties of oats were analyzed using visible-near infrared (VIS-NIR) spectroscopy. The objective of this study was to develop and validate a predictive model of oat quality by VIS-NIR spectroscopy. A total of 200 oat samples were collected from domestic and import markets. Reflectance spectra, moisture, protein, fat, Fe, and K of oat samples were measured. Reflectance spectra were measured in the wavelength range of 400 - 2,500 nm at 2 nm intervals. The reflectance spectrum of an oat sample was measured after sample cell and reflectance plate spectrum measurement. Preprocessing methods such as normalization and $1^{st}$ and $2^{nd}$ derivations were used to minimize the spectroscopic noise. The partial-least-square (PLS) models were developed to predict chemical properties of oats using a commercial software package, Unscrambler. The PLS models showed the possibility to predict moisture, protein, and fat content of oat samples. The coefficient of determination ($R^2$) of moisture, protein, and fat was greater than 0.89. However, it was hard to predict Fe and K concentrations due to their low concentrations in the oat samples. The coefficient of determinations of Fe and K were 0.57 and 0.77, respectively. In future studies, the stability and practicability of these models should be improved by using a high accuracy spectrophotometer and by performing calibrations with a wider range of oat chemicals.

Comparative Study of NIR-based Prediction Methods for Biomass Weight Loss Profiles

  • Cho, Hyun-Woo;Liu, J. Jay
    • 청정기술
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    • 제18권1호
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    • pp.31-37
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    • 2012
  • 바이오매스가 가진 재생 가능성과 환경적인 장점으로 인해 바이오매스는 바이오에너지와 다른 제품의 주요 원료가 되었다. 바이오매스의 중요 성질을 예측하기 위해 분광학 데이터를 이용하는 연구를 포함한 많은 연구가 수행되었는데 근적외선 분광학은 빠르고 신뢰성 있는 결과를 저비용으로 제공하는 비파괴 방법이기 때문에 널리 사용되었다. 이 연구에서는 서로 다른 여섯가지의 목질계 바이오매스의 근적외선 스펙트럼 데이터를 기반으로 질량 손실 프로파일을 예측하는 다변량 통계기법을 개발하였으며, 상관없는 잡음을 제거하고 근적외선 데이터를 잘 설명하는 파장대역을 선택하기 위해 웨이블릿 분석이 사용되었다. 실제 근적외선 데이터를 가지고 개발된 방법을 예시하였는데 이 때 여러가지 예측모델이 예측 성능을 기준으로 평가되었고 적절한 근적외선 스펙트럼 전처리법의 장점 또한 설명되었다. 웨이블릿으로 압축된 근적외선 스펙트럼을 이용한 부분최소자승법 예측모델이 가장 좋은 성능을 보였으며 개발된 방법은 바이오매스의 빠른 분석에 쉽게 적용될 수 있음 또한 증명되었다.