• Title/Summary/Keyword: Near-infrared (NIR) spectroscopy

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

  • Ahn, Jhii-Weon;Woo, Young-Ah;Kim, Hyo-Jin
    • Analytical Science and Technology
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    • v.16 no.2
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    • pp.95-101
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    • 2003
  • In this study, water content in the mixture of methanol and ethanol was nondestructively measured by near infrared (NIR) spectroscopy. Two types of NIR instruments, portable NIR system with a photo-diode array and scanning type NIR spectrometer were used and the calibration results were compared. Partial least squares regression (PLSR) was applied for the calibration and validation for the quantitative analysis. The calibration results from both instruments showed good correlation with actual values. The calibration with the use of PLS model predicted water concentration with a standard error of prediction (SEP) of 0.10% and 0.12% for photo diode array and scanning type, respectively. During 6 days, routine analyses for 3%, 5% and 7% water in ethanol solution with 2% methanol were performed to validate the robustness of the developed calibration model. The routine analyses showed good results with coefficient of variation (CV) of within 3% for both types of NIR spectrometers. This study showed that the rapid determination of water in the mixture of methanol and ethanol was successfully performed by NIR spectroscopy and the performance of the portable NIR system with a photo diode array detector was comparable to that of the scanning type NIR spectrometer.

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

  • Cozzolino, D.;Labandera, M.;Inia La Estanzuela
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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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
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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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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Discrimination model for cultivation origin of paper mulberry bast fiber and Hanji based on NIR and MIR spectral data combined with PLS-DA (닥나무 인피섬유와 한지의 원산지 판별모델 개발을 위한 NIR 및 MIR 스펙트럼 데이터의 PLS-DA 적용)

  • Jang, Kyung-Ju;Jung, So-Yoon;Go, In-Hee;Jeong, Seon-Hwa
    • Analytical Science and Technology
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    • v.32 no.1
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    • pp.7-16
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    • 2019
  • The objective of this study was the development of a discrimination model for the cultivational origin of paper mulberry bast fiber and Hanji using near infrared (NIR) and mid infrared (MIR) spectroscopy combined with partial least squares discriminant analysis (PLS-DA). Paper mulberry bast fiber was purchased in 10 different regions of Korea, and used to make Hanji. PLS-DA was performed using pre-treated FT-NIR and FT-MIR spectral data for paper mulberry bast fiber and Hanji. PLS-DA of paper mulberry bast fiber and Hanji samples, using FT-NIR spectral data, showed 100 % performance in cross validation and the confusion matrix (accuracy, sensitivity, and specificity). The discrimination models showed four regional groups which demonstrated clearer separation and much superior score plots in the NIR spectral data-based model than in the MIR spectral data-based model. Furthermore, the discrimination model based on the NIR spectral data of paper mulberry bast fiber had highly similar score morphology to that of the discrimination model based on the NIR spectral data of Hanji.

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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    • v.44 no.4
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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
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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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
    • Korean Journal of Agricultural Science
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    • v.43 no.5
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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
    • Clean Technology
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    • v.18 no.1
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    • pp.31-37
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    • 2012
  • Biomass has become a major feedstock for bioenergy and other bio-based products because of its renewability and environmental benefits. Various researches have been done in the prediction of crucial characteristics of biomass, including the active utilization of spectroscopy data. Near infrared (NIR) spectroscopy has been widely used because of its attractive features: it's non-destructive and cost-effective producing fast and reliable analysis results. This work developed the multivariate statistical scheme for predicting weight loss profiles based on the utilization of NIR spectra data measured for six lignocellulosic biomass types. Wavelet analysis was used as a compression tool to suppress irrelevant noise and to select features or wavelengths that better explain NIR data. The developed scheme was demonstrated using real NIR data sets, in which different prediction models were evaluated in terms of prediction performance. In addition, the benefits of using right pretreatment of NIR spectra were also given. In our case, it turned out that compression of high-dimensional NIR spectra by wavelet and then PLS modeling yielded more reliable prediction results without handling full set of noisy data. This work showed that the developed scheme can be easily applied for rapid analysis of biomass.