FTIR spectroscopy was used to quantitatively determine lignin in Eucalyptus globulus wood. A total of 40 wood samples from a 9 year old provenance trial was divided into two independent sets for calibration and validation. Lignin contents, as determined by the acetyl bromide method, ranged from 23 % to 34 % o.d. extractive-free wood. Spectra were recorded with the KBr pellet technique and twelve peaks between 1800cm" 1 to 800cm" 1 used for calibration by linear regression. The best calibration fit (R 2 = 0.98) was obtained with the 1505cm" 1 peak from lignin and the 1157 cm' 1 peak from polysaccharides as a reference. The standard error of calibration (SEC), and the standard error of prediction (SEP) calculated with the validation set, were very low. A linear regression of FTIR measurements proved strong enough to predict lignin content with a very high coefficient of determination. The accuracy of FTIR techniques allows its use in large scale breeding programmes to assess wood lignin content with considerable less effort and shorter time than using wet-lab methods, once a reliable calibration is performed for the species.

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The rapid FTIR (Fourier transform infrared) spectroscopy technique was used to indirectly measure the lignin content of Sitka spruce wood samples. A model was constructed to relate FTIR data to lignin content measured in wood by chemical analysis (i.e. the modified acetyl bromide method), through the application of the principal component regression (PCR) approach to a set of calibration observations. The acetyl bromide method provided lignin determinations ranging from 24% to 34% with a measurement error of 0.6%. A residual standard deviation of 0.8% and an average prediction error of 0.9% were calculated for lignin content when employing the selected PCR model (based on a normalized infrared data set, obtained using the band at 1374 cm -1 as a reference) to indirectly measure this wood property. Furthermore, a large portion of the variability in lignin content was explained by the two principal components retained in the selected calibration model, as indicated by the magnitude (i.e. 0.93) of the coefficient of multiple determination. The model was subsequently employed to predict the lignin content of wood samples collected in a clonal experiment. Two multivariate diagnostic measures were applied to assess the quality of the individual predictions, and the results indicated that the spectral information contained in the new sample vectors was suitable for use with the selected calibration model.

This paper presents results on the research currently being carried out with the objective of developing new electrochemistry-based processes to produce renewable synthetic fuels from liquefied biomass. In the current research line, the gas mixtures obtained from the typical electrolysis are not separated into their components but rather are introduced into a reactor together with liquefied biomass, at atmospheric pressure and different temperatures, under acidified zeolite Y catalyst, to obtain synthesis gas. This gaseous mixture has several applications, like the production of synthetic 2nd generation biofuel (e. g., biomethane, biomethanol, bio-dimethyl ether, formic acid, etc.). The behaviour of operational parameters such as biomass content, temperature and the use of different amounts of acidified zeolite HY catalyst were investigated. In the performed tests, it was found that, in addition to the synthesis gas (hydrogen, oxygen, carbon monoxide and carbon dioxide), methane was also obtained. Therefore, this research is quite promising, and the most favourable results were obtained by carrying out the biomass test at 300 °C, together with 4% of acidified zeolite Y catalyst, which gives a methane volumetric concentration equal to 35%.

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