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- W2385998039 abstract "Non-destructive and rapid monitoring methods for leaf nitrogen and seed protein of rice is of great significance in estimating rice nutritional diagnosis and grain quality monitoring,enhancing nitrogen management and use efficiency.In this study,a pot experiment was conducted to determine leaf nitrogen,grain protein content and canopy spectra in rice,and establish model to predict the leaf nitrogen and seed protein.Key spectral bands were selected by principal component analysis(PCA) method,and the predicted models were built by multiple linear regression(MLR),artificial neural network(ANN) and partial least squares regression(PLSR) model.Results showed that significant correlation was found between leaf nitrogen and grain protein content and key spectral bands,and the determined coefficient of predication(R2p) were higher than 0.847,and tested results predicted by PLSR models is the best.Therefore,it is concluded that rice nutrition and grain quality could be estimated by hyper spectral data." @default.
- W2385998039 created "2016-06-24" @default.
- W2385998039 creator A5031546001 @default.
- W2385998039 date "2012-01-01" @default.
- W2385998039 modified "2023-09-25" @default.
- W2385998039 title "ESTIMATING NITROGEN OF RICE LEAF AND PROTEIN OF RICE SEED BASED ON HYPERSPECTRAL DATA" @default.
- W2385998039 hasPublicationYear "2012" @default.
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