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최소 단어 이상 선택하여야 합니다.
선택한 단어 수는 30입니다.
최대 10 단어까지만 선택 가능합니다.
최대 10 단어까지만 선택 가능합니다.
제안 방법
- p data-page="1">Objectives : The objectives of this study were to determine the applicability of an NIR spectrocomputer system for protein and oil analysis in soybean seed and to provide the mass screening technique for high quality soybean breeding.
데이터처리
- In the NIRS equation of protein, the most accurate equation condition was obtained at 2, 8, 6, l(2nd derivative, 8nm 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 condition 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.
이론/모형
- Results : A total of 189 soybean calibration samples and 103 soybean NIRS validation samples were used for NIRS equation development and validation, respectively. In the NIRS equation of protein, the most accurate equation condition was obtained at 2, 8, 6, l(2nd derivative, 8nm 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 condition was obtained at 1, 4, 4, 1 condition with SNV-D scatter correction method and near infrared( 1100—2500nm) region by using MPLS regression.
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