• Title/Summary/Keyword: NIRS (Near-Infrared Reflectance Spectroscopy)

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Analysis on Food Waste Compost by Near Infrared Reflectance Spectroscopy(NIRS) (Near Infrared Reflectance Spectroscopy(NIRS)에 의한 음식물 쓰레기 퇴비 분석에 관한 연구)

  • Lee Hyo-Won;Kil Dong-Yong
    • Korean Journal of Organic Agriculture
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    • v.13 no.3
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    • pp.281-289
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    • 2005
  • In order to find out an alternative way of analysis of food waste compost, the Near Infrared Reflectance Spectroscopy(NIRS) was used for the compost assessment because the technics has been known as non-detructive, cost-effective and rapid method. One hundred thirty six compost samples were collected from Incheon food waste compost factory at Namdong Indurial Complex. The samples were analyzed for nitrogen, organic matter (OM), ash, P, and K using Kjedahl, ignition method, and acid extraction with spectrophotometer, respectively. The samples were scanned using FOSS NIRSystem of Model 6500 scanning mono-chromator with wavelength from $400\~2,400nm$ at 2nm interval. Modified partial Least Squares(MPLS) was applied to develop the most reliable calibration model between NIR spectra and sample components such as nitrogen, ash, OM, P, and K. The regression was validated using validation set(n=30). Multiple correlation coefficient($R^2$) and standard error of prediction(SEP) for nitrogen, ash, organic matter, OM/N ratio, P and K were 0.87, 0.06, 0.72, 1.07, 0.68, 1.05, 0.89, 0.31, 0.77, 0.06, and 0.64, 0.07, respectively. The results of this experiment indicates that NIRS is reliable analytical method to assess some components of feed waste compost, also suggests that feasibility of NIRS can be Justified in case of various sample collection around the year.

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Quality Prediction of Alfalfa Hay by Near Infraced Recfletance Spectroscopy (NIRS) (Near Infraced Recfletance Spectroscopy ( NIRS ) 에 의한 알팔파 건초의 품질 평가)

  • ;N. P. Martin
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.9 no.3
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    • pp.163-167
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    • 1989
  • Near infrared reflectance spectroscopy (NIRS) analysis of commercial farm alfalfa hay for crude prowin (CP), neutral detergent fiber(NDF), and acid detergent fiber(ADF) was compared with wet chemistry results. There were no differences between NIRS and wet chemistry results in CP and ADF content, but there were differences (P <.05) between NIRS and wet chemistry results for sample No.2, 4, 5 in NDF content.

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Applications of Near Infrared Reflectance Spectroscopy(NIRS) in Forage Evaluation (조사료 가치 평가를 위한 근적외선 분광법(NIRS)의 활용)

  • 박형수;이종경;이효원
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.24 no.1
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    • pp.81-90
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    • 2004
  • Farmers need timely information on the nutritional status of their animals and the nutritive value of pastures and supplementary feeds if they are to apply successfully this existing nutritional information. Near infrared reflectance(NIR) spectroscopy has been used over the last forty years to analyse accurately protein, fiber, and other organic components in animal foods. NIR spectroscopy is a rapid, non-destructive, and non-polluting technology. When properly calibrated, NIR spectroscopy is used successfully with both concentrate and forage feeds. NIR methods predict in vitro digestibility accurately and precisely, and can predict in vivo digestibility at least as well as conventional "wet chemistry" methods such as in vivo digestion or the pepsin-cellulase method, and much more rapidly. NIR technology has been applied to the routine monitoring (through analysis of feces samples) of the nutritional status of cattle and other grazing animals. This report reviews the use of near infrared reflectance(NIR) spectroscopy to monitor the nutritive value of animal feeds and the nutritional status of grazing animals.

Determination of Protein Content in Pea by Near Infrared Spectroscopy

  • Lee, Jin-Hwan;Choung, Myoung-Gun
    • Food Science and Biotechnology
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    • v.18 no.1
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    • pp.60-65
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    • 2009
  • Near infrared reflectance spectroscopy (NIRS) was used as a rapid and non-destructive method to determine the protein content in intact and ground seeds of pea (Pisum sativum L.) germplasms grown in Korea. A total of 115 samples were scanned in the reflectance mode of a scanning monochromator at intact seed and flour condition, and the reference values for the protein content was measured by auto-Kjeldahl system. In the developed ground and intact NIRS equations for analysis of protein, the most accurate equation were obtained at 2, 8, 6, 1 math treatment conditions with standard normal variate and detrend scatter correction method and entire spectrum (400-2,500 nm) by using modified partial least squares regression (n=78). External validation (n=34) of these NIRS equations showed significant correlation between reference values and NIRS estimated values based on the standard error of prediction (SEP), $R^2$, and the ratio of standard deviation of reference data to SEP. Therefore, these ground and intact NIRS equations can be applicable and reliable for determination of protein content in pea seeds, and non-destructive NIRS method could be used as a mass analysis technique for selection of high protein pea in breeding program and for quality control in food industry.

Prediction of Chemical Compositions for On-line Quality Measurement of Red Pepper Powder Using Near Infrared Reflectance Spectroscopy (NIRS)

  • Lee, Sun-Mee;Kim, Su-Na;Park, Jae-Bok;Hwang, In-Kyeong
    • Food Science and Biotechnology
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    • v.14 no.2
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    • pp.280-285
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    • 2005
  • Applicability of near infrared reflectance spectroscopy (NIRS) was examined for quality control of red pepper powder in milling factories. Prediction of chemical composition was performed using modified partial least square (MPLS) techniques. Analysis of total 51 and 21 red pepper powder samples by conventional methods for calibration and validation, respectively, revealed standard error of prediction (SEP) and correlation coefficient ($R^2$) of moisture content, ASTA color value, capsaicinoid content, and total sugar content were 0.55 and 0.90, 8.58 and 0.96, 31.60 and 0.65, and 1.82 and 0.86, respectively; SEP and $R^2$ were low and high, respectively, except for capsaicinoid content. The results indicate, with slight improvement, on-line quality measurement of red pepper powder with NIRS could be applied in red pepper milling factories.

Nondestructive Determination of Humic Acids in Soils by Near Infrared Reflectance Spectroscopy

  • Seo, Sang-Hyun;Park, Woo-Churl;Cho, Rae-Kwang;Xiaori Han
    • Near Infrared Analysis
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    • v.1 no.1
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    • pp.31-35
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    • 2000
  • Near-infrared reflectance spectroscopy(NIRS) was used to determine the humic acids in soil samples from the fields of different crops and land-use over Youngnam and Honam regions in Korea. An InfraAlyzer 500 scanning spectrophotometer was obtained near infrared relectance spectra of soil at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid, fulvic acid and its total contents in soils. The raw spectral data(log 1/R) can be used for estimating humic acid, fulvic acid and its total contents in soil by MLR procedure between the content of a given constituent and the spectral response of several bands. In which the predicted results for fulvic acid is the best in the constituents. The new spectral data are converted from the raw spectra by PLSR method such as the first derivative of each spectrum can also be used to predict humic acid and fulvic acid of the soil samples. A low SEC, SEP and a high coefficient of correlation in the calibration and validation stages enable selection of the best manipulation. But a simple calibration and prediction method for determining humic acid and fulvic acid should be selected under similar accuracy and precision of prediction. NIRS technique may be an effective method for rapid and nondestructive determination for humic acid, fulvic acid and its total contents in soils.

Nondestructive determination of humic acid in compost by NIRS

  • Seo, Sang-Hyun;Han, Xiao-Ri;Cho, Rae-Kwang;Park, Woo-Churl
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1623-1623
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    • 2001
  • Composting is a biological method used to transform the organic waste into stable, humified organic amendments. Humification is indicated as the key factor in improving the quality of compost, because of the importance of humic substances to soil ecology, fertility and structure, and their beneficial effects on plant growth The compost constituents vary widely, however, the degree of maturity is very important factor in compost quality. So this experiment carried out to determine the rapid estimation of the quality in cattle, pig, chicken and waste composts using near infrared reflectance spectroscopy(NIRS). Near infrared reflectance spectra of composts was obtained by Infra Alyzer 500 scanning spectrophotometer at 2-nm intervals from 1100 to 2500nm. Multiple linear regression(MLR) or partial least square regression (PLSR) was used to evaluate a NIRS method for the rapid and nondestructive determination of humic acid contents in composts. The results summarized that NIR spectroscopy can be used as a routine testing method to determine quantitatively the humic acid content in the compost samples ondestructively. Especially, we supposed that absorbance around 2300nm is related to humic acid as a factor of compost maturity. However the NIR absorption approach is empirical, it actually requires many combinations of samples and data manipulations to obtain optimal prediction.

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Determination of Protein and Oil Contents in Soybean Seed by Near Infrared Reflectance Spectroscopy

  • Choung, Myoung-Gun;Baek, In-Youl;Kang, Sung-Taeg;Han, Won-Young;Shin, Doo-Chull;Moon, Huhn-Pal;Kang, Kwang-Hee
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.2
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    • pp.106-111
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    • 2001
  • The applicability of near infrared reflectance spectroscopy(NIRS) was tested to determine the protein and oil contents in ground soybean [Glycine max (L.) Merr.] seeds. A total of 189 soybean calibration samples and 103 validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing and 1 point second smoothing) math treatment condition with SNV-D (Standard Normal Variate and Detrend) scatter correction method and entire spectrum by using MPLS (Modified Partial Least Squares) regression. In the case of oil, the best equation was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared (1100-2500nm) region by using MPLS regression. Validation of these NIRS equations showed very low bias (protein:-0.016%, oil : -0.011 %) and standard error of prediction (SEP, protein: 0.437%, oil: 0.377%) and very high coefficient of determination ($R^2$, protein: 0.985, oil : 0.965). Therefore, these NIRS equation seems reliable for determining the protein and oil content, and NIRS method could be used as a mass screening method of soybean seed.

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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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Prediction of the Chemical Composition of Fresh Whole Crop Barley Silages by Near Infrared Spectroscopy

  • Park, Hyung Soo;Lee, Sang Hoon;Lim, Young Cheol;Seo, Sung;Choi, Ki Choon;Kim, Ji Hea;Kim, Jong Geun;Choi, Gi Jun
    • Journal of The Korean Society of Grassland and Forage Science
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    • v.33 no.3
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    • pp.171-176
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    • 2013
  • Near infrared reflectance spectroscopy (NIRS) has become increasingly used as a rapid and accurate method of evaluating some chemical compositions in forages and feedstuff. This study was carried out to explore the accuracy of near infrared spectroscopy (NIRS) for the prediction of chemical parameters of fresh whole crop barley silages. A representative population of 284 fresh whole crop barley silages was used as a database for studying the possibilities of NIRS to predict chemical composition. Samples of silage were scanned at 1 nm intervals over the wavelength range 680~2,500 nm and the optical data were recorded as log 1/Reflectance (log 1/R) and were scanned in fresh condition. NIRS calibrations were developed by means of partial least-squares (PLS) regression. NIRS analysis of fresh whole crop barley silages provided accurate predictions of moisture, acid detergent fiber (ADF), neutral detergent fiber (NDF), crude protein (CP) and pH, as well as lactic acid content with correlation coefficients of cross-validation ($R^2cv$) of 0.96, 0.81, 0.79, 0.84, 0.72 and 0.78, respectively, and standard error of cross-validation (SECV) of 1.26, 2.83, 2.18, 1.19, 0.13 and 0.32% DM, respectively. Results of this experiment showed the possibility of the NIRS method to predict the chemical parameters of fresh whole crop barley silages as a routine analysis method in feeding value evaluation and for farmer advice.