• Title/Summary/Keyword: Near infrared spectroscopy(NIRS)

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Studies on pharmaceutical assay method using Near Infrared Spectroscopy (NIRS) (II)

  • Kang, Shin-Jung;Yun, Mi-Ok;Lee, Su-Jung;Choi, Hyun-Chul;Kim, Ho-Jeong;Kim, Ji-Yeon
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.4113-4113
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    • 2001
  • This study developed effective assay method of pharmaceutical quality control was developed by near-infrared spectroscopy (NIRS). The calibration equation model of assay was developed by 2nd deriviative PLS(Partial Least Squares) regression method with NIRS over the wavelength range from 1100 to 1400nm using diazepam tablets (2mg, 5mg). Although diazepam tablets are made by 5-different manufacture, they have similar formulation. When the correlation was compared with values by NIRS and HPLC, the R-2s and standard error of calibration (SEC) for 2mg were 0.9300 and 0.98%, the R-2s and SEC for 5mg were 0.9165 and 0.63%. The validation of the calibration equation model yield that the R-2s and standard error of prediction (SEP) for 2mg were 0.9611 and 0.995%, the R-2s and SEP for 5mg were 0.9114 and 0.842%. The method was validated on assay method for diazepam tablets by the calibration equation.

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Measurement of lipid content of compost fermentation using near-infrared spectroscopy

  • Daisuke Masui;Suehara, Ken-ichiro;Yasuhisa Nakano;Takuo Yano
    • Near Infrared Analysis
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    • v.2 no.1
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    • pp.37-42
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    • 2001
  • Near infrared spectroscopy (NIRS) was applied to determination of the lipid content of the compost during the compost fermentation of tofu (soybean0curd) refuse. The absorption of lipid observed at 5 wavelengths, 1208, 1712, 1772, 2312 and 2352 nm on the second derivative spectra. To formulated a calibration equation, a multiple linear regression analysis was carried out between the near-infrared spectral data and on the lipid content in the calibration sample set (sample number, n=60) obtained using Soxhlet extraction method. The value of the multiple correlation coefficient (R) was 0.975 when using the wavelengths of 1208 and 1712 nm were used in the calibration equation. To validate the calibration equation obtained, the lipid content in the validation sample set (n=35) not used for formulating the calibration equation was calculated using the calibration equation, and compared with the value obtained using the Soxhlet extraction method. Good agreement was observed between the results of the Soxhlet extraction method and those values of the NIRS method. The simple correlation coefficient (r) and standard error of prediction (SEP) were 0.964 and 0.815 %, respectively. suitability of the lipid content as an indicator of the compost fermentation of tofu refuse was also studied. The decrease of the lipid content in the compost corresponded to the decrease of the total dry weight of the compost in the composter. The lipid content was a significant indicator of the compost fermentation. The NIRS method was applied to measure the time course of the lipid content in the compost fermentation and good results were obtained. The study indicates that NIRS is a useful method for process management of the compost fermentation of tofu refuse.

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.

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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EVALUATION OF NIRS FOR ASSESSING PHYSICAL AND CHEMICAL CHARACTERISTICS OF LINEN WEFT YARN

  • Sharma, Hss;Kernaghan, K.;Whiteside, L.
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1091-1091
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    • 2001
  • Previous reports have shown that Near Infrared Spectroscopy (NIRS) can be used to assess physical and chemical properties of flax fibre and fabric quality. Currently, spinners assess yarn quality mainly based on strength and regularity measurements. There two key characteristics are influenced by quality of raw fibres used, especially the degree of rotting and strength. The aim of this investigation was to evaluate the use of NIRS for assessing quality of weft grade yarn available on the commercial market. In order to develop the NIR calibrations, a range of samples representing poor, medium and good quality weft yarn samples was included in the calibration and validation sample sets. The samples were analysed for physical and chemical parameters including caustic weight loss, fibre fractions, lipid, ash and minerals. A detailed protocol for assessing yarn quality has been developed to maximize the accuracy of the reflectance spectra. The development of partial least squares regression models and validation of the calibration equations using blind samples will be presented and discussed.

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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.

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.

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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Near-Infrared Spectroscopy versus Transcranial Doppler-Based Monitoring in Carotid Endarterectomy

  • Cho, Jun Woo;Jang, Jae Seok
    • Journal of Chest Surgery
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    • v.50 no.6
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    • pp.448-452
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    • 2017
  • Background: Proper monitoring of cerebral perfusion during carotid artery surgery is crucial for determining if a shunt is needed. We compared the safety and reliability of near-infrared spectroscopy (NIRS) w ith transcranial Doppler (TCD) for cerebral monitoring. Methods: This single-center, retrospective review was conducted on patients who underwent carotid endarterectomy (CEA) using selective shunt-based TCD or NIRS at Daegu Catholic University Medical Center from November 2009 to June 2016. Postoperative complications were the primary outcome, and the distribution of risk factors between the 2 groups was compared. Results: The medical records of 74 patients (45 TCD, 29 NIRS) were reviewed. The demographic characteristics were similar between the 2 groups. One TCD patient died within the 30-day postoperative period. Postoperative stroke (n=4, p=0.15) and neurologic complications (n=10, p=0.005) were only reported in the TCD group. Shunt usage was 44.4% and 10.3% in the TCD and NIRS groups, respectively (p=0.002). Conclusion: NIRS-based selective shunting during CEA seems to be safe and reliable for monitoring cerebral perfusion in terms of postoperative stroke and neurologic symptoms. It also reduces unnecessary shunt usage.