Bibliographic citations
Javier, R., (2021). Validación de la metodología para la determinación de Lignina celulosa y Hemicelulosa por espectroscopia infrarroja en árboles [Universidad Nacional Agraria La Molina]. https://hdl.handle.net/20.500.12996/5176
Javier, R., Validación de la metodología para la determinación de Lignina celulosa y Hemicelulosa por espectroscopia infrarroja en árboles []. PE: Universidad Nacional Agraria La Molina; 2021. https://hdl.handle.net/20.500.12996/5176
@misc{renati/244093,
title = "Validación de la metodología para la determinación de Lignina celulosa y Hemicelulosa por espectroscopia infrarroja en árboles",
author = "Javier Astete, Rosario Elyzabeth",
publisher = "Universidad Nacional Agraria La Molina",
year = "2021"
}
The Amazonian trees, Capirona (Callycophilum spruceanum) and Bolaina (Guazuma crinita), have a great economic importance because of fast-growing cycle and a variety enduse of their wood. The development of competitive and efficient tress with forest breeding programs requires technological tools to select vegetal material based on wood chemical composition. The aim of this study was to identify chemical differences between upper and lower stem of Capirona and Bolaina as well as to develop models for predicting the chemical composition of these two species from Fourier transform infrared spectra (FTIR). FTIR spectra were obtained from 150 samples for each specie that were 1.8 year-old. The results showed significant differences between the upper and lower stem for each species in terms of cellulose, hemicellulose, holocellulose and lignin. This variability was useful to build the PLS (partial least squares) models from the FTIR spectra and they were evaluated by root mean squared error of predictions (RMSEP) and ratio of performance to deviation (RPD). In Capirona, lignin model achieved high efficiency because of RMSEP = 0.48 and RPD > 2. On the other hand, cellulose, hemicellulose and holocellulose models had RMSEP values of 2.06, 0.68 and 2.07 and RPD values of 1.96, 1.60 and 1.90 respectively, which were sufficient for the prediction of wood properties (RPD > 1.5). In Bolaina, the cellulose model had excellent predictive capacity (RPD = 6.14). Likewise, the lignin, hemicellulose and holocellulose models showed good predictive capacity (RPD > 2.0). To conclude, both species showed significant differences between upper and lower wood chemical composition, and that FTIR-ATR together with PLS is a reliable method to determine the wood chemical composition in juvenile trees of Capirona and Bolaina.
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