Using multispecies NIRS calibration for predicting chemical properties of eucalypts wood

Breeding programs in Africa are generally based on growth criteria and rarely on wood chemical properties. Indeed, chemical analysis are often expensive, time-consuming and require several replicates. Then, using NIRS to predict these properties is a relevant solution. The research question focuses on the possibility of using multispecies models to predict properties of different species. This study considers 7 chemical properties (extractives, Klason lignin, acidosoluble lignin ASL, SG ratio, holocellulose, alphacellulose, hemicelluloses) based on 367 samples from 4 countries, belonging to 5 eucalypt species with hybrids (E. robusta, camaldulensis, urophylla, uropellita, urograndis). Established models were validated by cross- and test-set validation. Results shows that all R2CV are greater than 0.73, and all %RMSECV are less than 8.3% except for extractives and ASL. Prediction errors (%RMSEP) are always less than 9.5% except for these 2 properties, with respectively 23.6% and 18.1%. Prediction errors are always less than the double of the error of laboratory (%SEL). This study shows that multispecies NIRS models can be used to predict chemical properties, there is no significant difference between measurement error obtained with standardized method and %RMSEP. This method is particularly well-suited for a rapid wood phenotyping of multiple samples belonging to different species.

Bibliographic Details

Main Authors:	Razafimahatratra, Andriambelo Radonirina, Ramananantoandro, Tahiana, Nourissier, Sophie, Mevanarivo, Zo Elia, Tomazello Filho, Mario, Makouanzi, Garel, Clément-Vidal, Anne, Rodrigues, José, Chaix, Gilles
Format:	conference_item biblioteca
Language:	eng
Published:	CIRAD
Online Access:	http://agritrop.cirad.fr/589463/ http://agritrop.cirad.fr/589463/1/ID589463.pdf
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