DRIED GRASS SILAGE ANALYSIS BY NIR REFLECTANCE SPECTROSCOPY-A COMPARISON OF STEPWISE MULTIPLE LINEAR AND PRINCIPAL COMPONENT TECHNIQUES FOR CALIBRATION DEVELOPMENT ON RAW AND TRANSFORMED SPECTRAL DATA |
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引用本文: | GERARD DOWNEY,PAUL ROBERT,DOMINIQUE BERTRAND,MARIE-FRANCOISE DEVAUX. DRIED GRASS SILAGE ANALYSIS BY NIR REFLECTANCE SPECTROSCOPY-A COMPARISON OF STEPWISE MULTIPLE LINEAR AND PRINCIPAL COMPONENT TECHNIQUES FOR CALIBRATION DEVELOPMENT ON RAW AND TRANSFORMED SPECTRAL DATA[J]. 地理学报(英文版), 1989, 0(1) |
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作者姓名: | GERARD DOWNEY PAUL ROBERT DOMINIQUE BERTRAND MARIE-FRANCOISE DEVAUX |
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作者单位: | An Foras Taluntais Department of Food Science and Technology Kinsealy Research Centre Malahide Road Dublin 17 Republic of Ireland,Laboratoire de Technologie des Aliments des Animaux INRA Rue de la Geraudiere 44072 Nantes Cedex France,Laboratoire de Technologie des Aliments des Animaux INRA Rue de la Geraudiere 44072 Nantes Cedex France,Laboratoire de Technologie des Aliments des Animaux INRA Rue de la Geraudiere 44072 Nantes Cedex France |
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摘 要: | Calibrations to predict crude protein (CP) and in vitro dry matter digestibility (IVDMD) in dried grasssilage from reflectance data collected at 19 wavelengths on an InfraAlyzer 400R have been developedusing stepwise multiple linear (SML) and principal component (PC) regression techniques. A directcomparison of the efficacy of each multivariate technique in this application has been possible by usingidentical calibration development and evaluation sample sets. The effect of two data transformation stepsprior to PC regression was also investigated. PC regression of raw reflectance data yielded no significantimprovement in the standard errors of prediction (SEP) for CP and IVDMD over those obtained bySMLR, viz. 0.61 vs 0.63 and 2.9 vs 3.0 respectively. Computation time for development and evaluation ofthe PC regression equation was less than for selection of the best SMLR equation, and PCR equationsmay be more robust. Data transformation to reduce granularity effects prior to PCR did not produce anyimprovement in predictive accuracy for either IVDMD or CP.
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DRIED GRASS SILAGE ANALYSIS BY NIR REFLECTANCE SPECTROSCOPY-A COMPARISON OF STEPWISE MULTIPLE LINEAR AND PRINCIPAL COMPONENT TECHNIQUES FOR CALIBRATION DEVELOPMENT ON RAW AND TRANSFORMED SPECTRAL DATA |
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Abstract: | Calibrations to predict crude protein (CP) and in vitro dry matter digestibility (IVDMD) in dried grass silage from reflectance data collected at 19 wavelengths on an InfraAlyzer 400R have been developed using stepwise multiple linear (SML) and principal component (PC) regression techniques. A direct comparison of the efficacy of each multivariate technique in this application has been possible by using identical calibration development and evaluation sample sets. The effect of two data transformation steps prior to PC regression was also investigated. PC regression of raw reflectance data yielded no significant improvement in the standard errors of prediction (SEP) for CP and IVDMD over those obtained by SMLR, viz. 0.61 vs 0.63 and 2.9 vs 3.0 respectively. Computation time for development and evaluation of the PC regression equation was less than for selection of the best SMLR equation, and PCR equations may be more robust. Data transformation to reduce granularity effects prior to PCR did not produce any improvement in predictive accuracy for either IVDMD or CP. |
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Keywords: | NIR reflectance Multivariate analysis Principal component analysis Stepwise multiple linear regression Silage quality |
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