• 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.

• YAKHAK HOEJI
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• v.42 no.4
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• pp.359-363
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• 1998

Near infrared reflectance spectroscopy (NIRS) was applied for discrimination according to geographical origin (Korea, China) of herb drugs. Herbal medicine has an important role in clinical therapy in Asian countries such as Korea and China. The objective of this study is to provide a convenient and accurate method to determinate geographical origin (Korea, China) of herbal medicine for quality control whose quality is generally different according to geographical origin. A rapid, nondestructive and accurate discrimination was achieved by NIRS. Second derivative spectra of herb drugs were subjected to discriminant analysis. Herbal medicine drugs such as Cassia Semen, Ganoderma and Smilacis Rhizoma was discriminated accurately according to geographical origin using PLS regression method.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2000.06a
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• pp.53-53
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• 2000

• 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.

• Near Infrared Analysis
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• v.1 no.2
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• pp.35-39
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• 2000

The purpose of this research was to find out suitable soil sample preparation and sample holding tools for NIR reflection radiation for estimating soil components. NIR reflectance was scanned at 2nm intervals from 1,100 to 2,500nm with an InfraAlyzer 500(Bran+Luebbe Co.). Coarse(2.0mm) and fine(0.5mm) soil sample and various sample holding tools were used to obtain mean diffuse reflection of the soil for the calibration and validation of the calibration set in estimating moisture, organic matter and total nitrogen of the soils. Multiple linear regression was used to obtain the best correlation of NIR spectroscopy method. Correlation of NIR spectroscopy method. Correlation of NIR spectra for finely and coarsely sized soil did not show much difference. The standard errors of prediction(SE) using different types of sample holding tools for organic matter, total nitrogen and soil moisture were better than 0.765, 0.041 and 0.63% respectively. From the results it can be concluded that NIR spectroscopy with flow type cell could be used as a fast routine testing method in quantitative determination of organic matter, total nitrogen and soil moisture.

• Near Infrared Analysis
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• v.1 no.2
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• pp.41-44
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• 2000

The objectives of this study are to discriminate the geographical origin and cultivation years of ginseng based on the near-infrared(NIR) reflectance spectroscopic analysis. Korea and China ginseng samples were prepared for discrimination of geographical origin. 4, 5 and 6 years-old ginseng samples from Korea were prepared for discrimination of cultivation years. Used spectrometer were InfraAlyzer 500, InfraAlyzer 400 and Fiber optic. Sample type of ginseng was 3, whole ginseng radix, slide section and powder type. The accuracy was affected by sample types and instruments. The accuracy for discrimination geographical origin was 97% in calibration model using IA 500 and ginseng powder. For discrimination of cultivation years, the model with slide selection using IA500 were relative accurate. The accuracy was 96.7% for 4-year, 91.3% for 5-year and 89.3% for 6-year old ginseng. The study shows that NIR spectroscopic analysis can be used to discriminate the geographical origin and cultivation years of ginseng with acceptable accuracy.

• 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.

• Journal of Biosystems Engineering
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• v.38 no.3
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• pp.199-207
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• 2013

Purpose: Tomatoes, an important agricultural product in fresh-cut markets, are sometimes a source of foodborne illness, mainly Salmonella spp. Growth cracks on tomatoes can be a pathway for bacteria, so its detection prior to consumption is important for public health. In this study, multispectral Visible/Near-Infrared (NIR) reflectance imaging techniques were used to determine optimal wavebands for the classification of defect tomatoes. Methods: Hyperspectral reflectance images were collected from samples of naturally cracked tomatoes. To classify the resulting images, the selected wavelength bands were subjected to two-band permutations, and a supervised classification method was used. Results: The results showed that two optimal wavelengths, 713.8 nm and 718.6 nm, could be used to identify cracked spots on tomato surfaces with a correct classification rate of 91.1%. The result indicates that multispectral reflectance imaging with optimized wavebands from hyperspectral images is an effective technique for the classification of defective tomatoes. Conclusions: Although it can be susceptible to specular interference, the multispectral reflectance imaging is an appropriate method for commercial applications because it is faster and much less expensive than Near-Infrared or fluorescence imaging techniques.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.3111-3111
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• 2001

The implementation of NIR and chemometrics in the Pharmaceutical industries is still in strong progress, both regarding qualitative and quantitative applications and beneficial results are seen. Looking at the development so far, NIR will change the pharmaceutical industry even more in the future. This presentation will address the experiences and progress achieved regarding the application and implementation of quantitative methods for determination of content uniformity and assay of tablets with less than 10% w/w of active, using Near Infrared transmittance spectroscopy in combination with PLS. Also qualitative methods for identification of the same tablets by Near Infrared reflectance spectroscopy will be discussed. Four commercial tablet strengths are formulated and produced from two different compositions by direct compression. Three different strengths are dose proportional, i.e. fixed concentration by varying in size. The aim was to replace the conventional primary methods for analysing content uniformity, assay and identification by NIR. Studies were performed on comparing transmittance versus reflectance spectroscopy for both applications on the dose proportional tablets. The model for determination of content uniformity and assay was developed to cover both coated and uncoated tablets, whereas the qualitative model was developed to identify coated tablets only. The impact of the tablet formulation, tablet size and coating, resulted in individual models far each composition The best calibration was achieved using diffuse reflectance for the identification purposes and diffuse transmittance for the quantitative determination of the active content within the tablets. As NIR in combination with other techniques opens up the possibility of total quality management within the production, the transfer of the above-mentioned models from a laboratory based approach to an at-line approach at H.Lundbeck will be addressed too.

• Korean Journal of Food Science and Technology
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• v.28 no.1
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• pp.40-43
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• 1996

Our objective was to evaluate the potential of near-infrared reflectance spectroscopy to determine the salt content of mayonnaise. The calibration equation for salt developed using partial least square regression was compared with conventional method. 100 samples for calibration set and 40 samples for validation set were used. The multiple correlation coefficient was 0.946 and standard error of prediction was 0.017, when calibration equation was applied to validation set. Near-infrared reflectance spectroscopy method for determining salt content of mayonnaise appears quite satisfactory to evaluate nondestructively.