• Title, Summary, Keyword: NIRS

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Proton dosimetry intercomparison based on the ICRU protocol

  • Fukumura, Akifumi;Futami, Yasuyuki;Hiraoka, Takeshi;Omata, Kaname;Takeshita, Mitsue;Kawachi, Kiyomitsu;Kanai, Tatsuaki;Miyahara, Nobuyuki;Vatnitsky, Stanislav;Moyers, Michael;Miller, Daniel;Abell, Greg;Pedroni, Eros;Coray, Adolf;mazal, Alejandro;Newhauser, Wayne;Jaekel, Oliver;Heese, Juergen;Verhey, Lynn;daftari, Inder;Grusell, Erik;Molokanov, Alexander;Bloch, Charles
    • Proceedings of the Korean Society of Medical Physics Conference
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    • pp.253-254
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    • 1999
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EMERGING POSSIBILITIES FOR NIRS TO CONTRIBUTO TO ENVIRONMENTAL ANALYSIS

  • Malley, Diane
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • pp.1071-1071
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    • 2001
  • Near-infrared spectroscopy (NIRS) is potentially a powerful and revolutionary technology for environmental analysis. It is supported by a large body of scientific and experiential knowledge. The instrumentation is well-developed, with easy-to-use, highly dependable instruments, but at the same time it is still developing, particularly with the production of more portable and rapid instruments, and more powerful software. NIRS is used globally in numerous industries for commodity analysis. Yet NIRS is largely unknown in the field of environmental chemistry and monitoring, and is not even routinely used in soil analysis, where the research literature on NIRS extends over four decades. Part of the explanation for the poor visibility of NIRS is the fact that NIRS is not routinely taught in Chemistry programs in universities, where most environmental chemists and environmental technicians are trained. This presentation examines the unique capabilities of NIRS, such as rapid, real-time analysis; analysis of whole samples; simultaneous analysis of multiple constituents; cost-effectiveness, and portability, as they match needs for analysis in several environmental areas. Examples of NIRS usage and published and unpublished results will be described for such areas as soil and sediment analysis; water quality monitoring; and nutrient loading in application of manures and sewage sludge (biosolids) to land. Present barriers to the use of NIRS in environmental analysis will be discussed. It is argued that emerging environmental problems and increasing attention to some traditional problems will enhance the application of NIRS in the future.

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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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Non Destructive Fast Determination of Fatty Acid Composition by Near Infrared Reflectance Spectroscopy in Sesame

  • Kang, Churl-Whan;Kim, Dong-Hwi;Lee, Sung-Woo;Kim, Ki-Jong;Cho, Kyu-Chae;Shim, Kang-Bo
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.51 no.spc1
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    • pp.283-291
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    • 2006
  • To investigate seed non destructive and fast determination technique utilizing near infrared reflectance spectroscopy (NIRs) for screening ultra high oleic (C18:1) and linoleic (C18:2) fatty acid content sesame varieties among genetic resources and lines of pedigree generations of cross and mutation breeding were carried out in National Institute of Crop Science (NICS). 150 among 378 landraces and introduced cultivars were released to analyse fatty acids by NIRs and gas chromatography (GC). Average content of each fatty acid was 9.64% in palmitic acid (C16:0), 4.73% in stearic acid (C18:0), 42.26% in oleic acid and 43.38% in linoleic acid by GC. The content range of each fatty acid was from 7.29 to 12.27% in palmitic, 6.49% from 2.39 to 8.88% in stearic, 12.59% of wider range compared to that of stearic and palmitic from 37.36 to 49.95% in oleic and of the widest from 30.60 to 47.40% in linoleic acid. Spectrums analyzed by NIRs were distributed from 400 to 2,500 nm wavelengths and varietal distribution of fatty acids were appeared as regular distribution. Varietal differences of oleic acid content good for food processing and human health by NIRs was 14.08% of which 1.49% wider range than that of GC from 38.31 to 52.39%. Varietal differences of linoleic acid content by NIRs was 16.41% of which 0.39% narrower range than that of GC from 30.60 to 47.01%. Varietal differences of oleic and linoleic acid content in NIRs analysis were appeared relatively similar inclination compared with those of GC. Partial least square regression (PLSR) among multiple variant regression (MVR) in NIRs calibration statistics was carried out in spectrum characteristics on the wavelength from 700 to 2,500 nm with oleic and linoleic acids. Correlation coefficient of root square (RSQ) in oleic acid content was 0.724 of which 72.4 percent of sample varieties among all distributed in the range of 0.570 percent of standard error when calibrated (SEC) which were considerably acceptable in statistic confidence significantly for analysis between NIRs and GC. Standard error of cross validation (SECV) of oleic acid was 0.725 of which distributed in the range of 0.725 percent standard error among the samples of mother population between analyzed value by NIRs analysis and analyzed value by GC. RSQ of linoleic acid content was 0.735 of which 73.5 percent of sample varieties among all distributed in the range of 0.643 percent of SEC. SECV of linoleic acid was 0.711 of which distributed in the range of 0.711 percent standard error among the samples of mother population between NIRs analysis and GC analysis. Consequently, adoption NIR analysis for fatty acids of oleic and linoleic instead that of GC was recognized statistically significant between NIRs and GC analysis through not only majority of samples distributed in the range of negligible SEC but also SECV. For enlarging and increasing statistic significance of NIRs analysis, wider range of fatty acids contented sesame germplasm should be kept on releasing additionally for increasing correlation coefficient of RSQ and reducing SEC and SECV in the future.

Determination of Seed Lipid and Protein Contents in Perilla and Peanut by Near-Infrared Reflectance Spectroscopy

  • Oh, Ki-Won;Choung, Myoung-Gyun;Pae, Suk-Bok;Jung, Chan-Sik;Kim, Byung-Joo;Kwon, Yil-Chan;Kim, Jung-Tae;Kwack, Yong-Ho
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.45 no.5
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    • pp.339-342
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    • 2000
  • Near-infrared reflectance spectroscopy (NIRS) was used to estimate the lipid and protein contents in ground seed samples of perilla (Perilla frutescens Brit.) and peanut (Arachis hypogaea L.). A total of 46 perilla and 80 peanut calibration samples and 23 perilla and 46 pea. nut NIRS validation samples were used for NIRS equation development and validation, respectively. Validation of these NIRS equations showed a range of very low bias (-0.05 to 0.13 %) and standard error of prediction corrected for bias (0.224 to 0.803%) and very high coefficient of determination ($R^2$) (0.962 to 0.985). It was concluded that NIRS could be adapted as a mass screening method for lipid and protein contents in perilla and peanut seed.

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Study on the Fluence and LET Distribution of Projectile Fragments Produced from Heavy Ion Therapeutic Beams

  • Komori, Masataka;Fukumura, Akifumi;Hirai, Masaaki;Kanai, Tatuaki;Kohno, Ryosuke;Kohno, Toshiyuki;Matsufuji, Naruhiro;Nanbu, Syuya;Nishio, Teiji
    • Proceedings of the Korean Society of Medical Physics Conference
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    • pp.216-218
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    • 2002
  • Fluence and LET spectrum for 290,400 MeV/u $\^$12/C and 400 MeV/u $\^$20/Ne beams have been measured by a $\Delta$E-E counter telescope. Total charge-changing cross sections are deduced from measured fluence. The measured cross sections agree with previous measurements, however, they are disagreement with a model calculation. To dose-averaged LETs, the model calculation can reproduce the measured LETs except for peak LETs at Bragg peak region.

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Determination of Seed Protein and Oil Concentration in Kiddny Bean by Near Infrared Spectroscopic Analysis (근적외 분광분석법을 이용한 강낭콩 종실단백질 및 지방의 비파괴 분석)

  • 이한범;최병렬;강창성;김영호;최영진
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.46 no.3
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    • pp.248-252
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    • 2001
  • Near infrared spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. An important merit of the NIRS analytical system is consistent predictions across instruments. However, proper calibration is the most important factor for a NIRS analytical system. Forty samples were obtained from Kyonggi-do Agricultural Research and Extension Services, and used to develop calibrations for crude protein content and crude oil content. Calibrations equations were developed using multiple linear regression (MLR). Accuracy and precision of NIRS predictions were adequate for quality measurement for the two constituents in kidney bean seed. In calibration sample sets (N=30), multiple correlation coefficient between NIR and lab measurements is 0.90 for seed, 0.97 for powder in seed protein concentration and 0.40 for seed and 0.92 for powder in seed oil concentration, respectively. It is concluded that NIRS method is suitable for the determination of seed composition in whole kidney bean.

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