Nirs tools for prediction of main extractives compounds of teak (Tectona grandis L.) heartwood
2012
Niamké, Bobelé Forence | Kokutse, Adzo Dzifa | Kadio, Adjumane Aimé | Leménager, Nicolas | Baudasse, Christine | Nourissier-Mountou, Sophie | Adima, Augustin Amissa | Amusant, Nadine | Chaix, Gilles
Biochemical and physiological process which occurred during heartwood formation have consequences on wood properties such as colour, natural durability and some mechanical properties. However, it is very time-consuming to take measurements of extractives contents. Teak has been reported to contain 1-hydroxy- 2-methyl-anthraquinone, 2-hydroxy-methyl-anthraquinone, 2-methyl- anthraquinone, lapachol, 1,4-naphthoquinone for the main compounds. In teak, natural durability is ascribed to extractives. Consequently, it's possible to estimate natural durability by measurement of extractives indirectly. For the purposes of selection for the production of improved varieties, the number of samples to be measured rapidly exceeds the capacity of a traditional laboratory. Near-infrared spectroscopy approach, based on spectral data and reference data, is a tool enabling many of the chemical properties of wood to be predicted and the number of laboratory measurements to be reduced exponentially. The issue here is a question of checking the effectiveness of NIRS tool to build models and predict the main extractive compounds of teak wood from Ivory Coast. We try to calibrate these chemical properties with Nirs spectral information measured on grounded wood. The results show the possible use of NIRS to predict total phenol content and some main extractive compounds of teak heartwood as tectoquinone, 2-hydroxymethylanthraquinone,Consequently, after verification on other sets of teak samples, which may or may not be included in the prediction model, NIRS can be used to predict extractive compounds accurately for a large number of samples, making it possible to estimate natural durability indirectly and to include these characteristics in the selection criteria for classifying wood and high throughput phenotyping. (Résumé d'auteur)
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