Ana Alves

Genetic Variation in the Chemical Components of Eucalyptus globulus Wood

Despite the ecological and economic importance of lignin and other wood chemical components, there are few studies of the natural genetic variation that exists within plant species and its adaptive significance. We used models developed from near infra-red spectroscopy to study natural genetic variation in lignin content and monomer composition (syringyl-to-guaiacyl ratio [S/G]) as well as cellulose and extractives content, using a 16-year-old field trial of an Australian tree species, Eucalyptus globulus. We sampled 2163 progenies of 467 native trees from throughout the native geographic range of the species. The narrow-sense heritability of wood chemical traits (0.25–0.44) was higher than that of growth (0.15), but less than wood density (0.51). All wood chemical traits exhibited significant broad-scale genetic differentiation (QST = 0.34–0.43) across the species range. This differentiation exceeded that detected with putatively neutral microsatellite markers (FST = 0.09), arguing that diversifying selection has shaped population differentiation in wood chemistry. There were significant genetic correlations among these wood chemical traits at the population and additive genetic levels. However, population differentiation in the S/G ratio of lignin in particular was positively correlated with latitude (R2 = 76%), which may be driven by either adaptation to climate or associated biotic factors.

Molecular and phenotypic profiling from the base to the crown in maritime pine wood‐forming tissue

Environmental, developmental and genetic factors affect variation in wood properties at the chemical, anatomical and physical levels. Here, the phenotypic variation observed along the tree stem was explored and the hypothesis tested that this variation could be the result of the differential expression of genes/proteins during wood formation. Differentiating xylem samples of maritime pine (Pinus pinaster) were collected from the top (crown wood, CW) to the bottom (base wood, BW) of adult trees. These samples were characterized by Fourier transform infrared spectroscopy (FTIR) and analytical pyrolysis. Two main groups of samples, corresponding to CW and BW, could be distinguished from cell wall chemical composition. A genomic approach, combining large-scale production of expressed sequence tags (ESTs), gene expression profiling and quantitative proteomics analysis, allowed identification of 262 unigenes (out of 3512) and 231 proteins (out of 1372 spots) that were differentially expressed along the stem. A good relationship was found between functional categories from transcriptomic and proteomic data. A good fit between the molecular mechanisms involved in CW-BW formation and these two types of wood phenotypic differences was also observed. This work provides a list of candidate genes for wood properties that will be tested in forward genetics.

Plasticity of maritime pine (Pinus pinaster) wood‐forming tissues during a growing season

The seasonal effect is the most significant external source of variation affecting vascular cambial activity and the development of newly divided cells, and hence wood properties. Here, the effect of edapho-climatic conditions on the phenotypic and molecular plasticity of differentiating secondary xylem during a growing season was investigated. Wood-forming tissues of maritime pine (Pinus pinaster) were collected from the beginning to the end of the growing season in 2003. Data from examination of fibre morphology, Fourier-transform infrared spectroscopy (FTIR), analytical pyrolysis, and gas chromatography/mass spectrometry (GC/MS) were combined to characterize the samples. Strong variation was observed in response to changes in edapho-climatic conditions. A genomic approach was used to identify genes differentially expressed during this growing season. Out of 3512 studied genes, 19% showed a significant seasonal effect. These genes were clustered into five distinct groups, the largest two representing genes over-expressed in the early- or late-wood-forming tissues, respectively. The other three clusters were characterized by responses to specific edapho-climatic conditions. This work provides new insights into the plasticity of the molecular machinery involved in wood formation, and reveals candidate genes potentially responsible for the phenotypic differences found between early- and late-wood.

NIR PLSR results obtained by calibration with noisy, low-precision reference values : Are the results acceptable?

Abstract Both spectral noise and reference method noise affect the accuracy and the precision NIR predicted values. The reference noise is often neglected, and the few reports dealing with it only consider random noise artificially added to the original sound reference data. A calibration for lignin content of maritime pine (Pinus pinaster Ait.) wood meal was developed, but due to low precision and accuracy in the reference data set, NIR partial least-squares regression (PLSR) yielded a slope of 0.51 and an intercept at 14% Klason lignin. We demonstrate with an independent data set for external validation, obtained with higher precision and accuracy, that the NIR PLSR model based on the noisy reference data led to better results. The slope of the correlation between predicted and reference values was 0.89 and the intercept was 3.9. Thus, the model performed much better than expected from the cross-validation results. The predictability can be explained by the facts that the loadings of the first principal component (PC) of the calibration and test samples are very similar and dominated by lignin-related bands, and that most of the variation in the test set can be explained by the first PC. This only explains why the Klason lignin content could be predicted with the model without giving many spectral outliers, but not the good result of the external validation. We show that the latter can be explained by the inverse calibration used for PLSR and that predicted values can be more accurate and precise than the reference values used for calibration.

Quantitative evaluation by attenuated total reflectance infrared (ATR-FTIR) spectroscopy of the chemical composition of decayed wood preserved in waterlogged conditions.

This paper reports on the assessment of lignin and holocellulose by means of ATR-FTIR analysis and multivariate PLS regression. The analysis was conducted on 59 samples coming from different excavations where wood had been preserved in waterlogged conditions. A range of results from different wood species (Alnus sp.p., Cupressus sempervirens, Larix decidua, Picea abies, Pinus sp.p., Quercus sp.p., Ulmus sp.p.), states of preservation, waterlogged environments, and burial times are presented. A calibration model was selected after comparing different reference data (samples extracted and not-extracted, and ash-rich and ash-free bases of calculation for the calibration values), and two different post-acquisition spectroscopic manipulations (both in terms of normalisation procedures and of spectral ranges used for the calibration). Results showed that the best models were different depending on which considered component (lignin or holocellulose) was measured and to which data set (softwood or hardwood) the samples belonged. It is shown that the predictive ability of the models is affected by high ash content (too contaminated samples had to be excluded in order to attain good results, because of excessive overlapping of bands related to the inorganic fraction) but not by the preliminary extraction of sample. Furthermore, the stability of best models is also demonstrated and a procedure of external validation carried out on an external set of samples confirmed the general validity of the identified models.

Improvement of Pinus pinaster Ait elite trees selection by combining near infrared spectroscopy and genetic tools

Abstract The first and the second generation of improved maritime pine (Pinus pinaster) have produced gains of up to 30% in stem volume, a reduction of final harvesting age by 10 years and a considerable improvement of stem straightness. The third generation will include wood quality traits for different end-uses, including pulp and fibre properties. To facilitate this goal, near infrared spectroscopy (NIRS) was used to estimate chemical composition with regard to lignin, cellulose, hemicelluloses, and extractive content, and lignin quality with regard to 4-hydroxy-phenylpropane/guaiacylpropane ratio. A total of 960 samples were investigated which were collected from a large number of trees (belonging to 80 families obtained by crossing 18 mothers and 20 fathers; there are 12 trees per family). Good calibration data was obtained between NIRS and wet chemistry methods (R2 values higher than 0.9 and good precision of prediction). To complete the NIRS work, kraft cookings in small scale, fibre morphology and microdensitometry investigations were also conducted. Genetic calculations indicated that for a 1% rate of selection on mothers and fathers, genetically induced changes are possible with lignin content (−3.8%), cellulose content (+1.3%), pulp yield (+1.8%), fibre length in pulps (+0.17 mm) and wood density (+50 kg m−3).

Determination of the syringyl/guaiacyl ratio of Eucalyptus globulus wood lignin by near infrared-based partial least squares regression models using analytical pyrolysis as the reference method

High syringly/guaiacyl (S/G) ratios are advantageous for chemical pulp production due to higher delignification rates, higher pulp yields and lower chemical consumption. Near infrared-based partial least-squares regression (PLS-R) models were developed to assess the S/G ratio of Eucalyptus globulus wood using analytical pyrolysis as the reference method. The PLS-R models obtained using the wavenumber range from 6100cm−1 to 5450cm−1 (1639–1835nm) of the preprocessed spectra using first derivative (1stDer) and first derivative in combination with; vector normalisation (1stDerVN), multiplicative scatter correction (1stDerMSC) and straight-line-subtraction (1stDerSLS), and the second derivative (2ndDer), are well qualified for rapid screening the S/G ratio of Eucalyptus globulus wood. Overall, models using 1stDerVN and 1stDerMSC preprocess (78 samples) requiring only three PLS components have the best statistics with coefficient of determination (r2) = 0.97, root mean square error of cross-validation (RMSECV)=0.025 and residual prediction deviation (RPD) = 5.7

Estimation of wood basic density of Acacia melanoxylon (R. Br.) by near infrared spectroscopy

Wood basic density is one of the most important wood quality properties and one of the simplest to assess but it is too time consuming to be really useful for the screening of populations or for improvement programmes where large numbers of samples need to be assessed. Although the usefulness of near infrared (NIR) spectroscopy to assess wood properties, including wood density, is well established only a few of the published models are suitable for screening. The NIR-based partial least squares regression models obtained in this study can be used for screening the basic density of the Portuguese blackwood [Acacia melanoxylon (R. Br.)] population with standard errors of cross-validation of only 11 kg m−3 and values for the residual prediction deviation well above the 2.5 limit. It was also concluded that at least 45 samples for calibration and a further 16 samples for validation are necessary to obtain acceptable models for screening. Even using a very small number of spectra per disc, accurate estimates of wood basic density were obtained.

Determination of Eucalyptus globulus wood extractives content by near infrared-based partial least squares regression models: comparison between extraction procedures

Wood extractives, the non-cell wall components that can be removed by solvents, can play an important role in the protection of the living tree as well as derived wood products. On the other hand they can be detrimental for pulp and paper, paint and varnish films and adhesives. The objective of this work was to develop near infrared-based partial least squares regression models for the prediction of wood extractives. The developed models are well suited for screening of the ethanol and total extractives content of Eucalyptus globulus wood. The models for the prediction of ethanol extractives with residual prediction deviations above 5 are also suited for quality control. It is shown that samples with high extractives content always have a more intense OH combination band than the samples with low extractives content and that near infrared can be used for a rough estimation of the relative performance of the reference methods.

Oil content estimation of individual kernels of Quercus ilex subsp. rotundifolia ((Lam) O. Schwarz) acorns by Fourier transform near infrared spectroscopy and partial least squares regression

The aim of this work was to use Fourier transform near infrared (FT-NIR) spectroscopy and partial least squares regression (PLSR) to estimate the oil content of individual Holm oak (Quercus sp.) acorn kernels from different trees, sites and years that should be used in the future for molecular marker association studies. Sampling of acorns in two consecutive years (2003 and 2004) and from different sites in Portugal provided independent sample sets. A total of 89 samples (acorn kernels) representative of the natural oil content range were extracted. The results of the analyses performed by three people revealed accuracy of the oil extraction procedure (n-hexane) and the precision (repeatability) of this method, assessed during a four-day period, gave a standard deviation of 0.1%. Careful wavenumber selection and several steps of validation of the PLSR models led to a final robust model that allowed the precise prediction of the oil content of individual acorns. By using the wavenumber ranges from 5995 to 5323 cm−1 and from 4478 to 4177 cm−1 of the vector normalised spectra, a PLSR model with a coefficient of determination (r 2 ) of 0.992 and a root mean square error of cross-validation (RMSECV) of 0.37% was achieved. The RPD value of about 10 and a bias of almost zero showed that the developed models are good for process control, development, and applied research. Oil content estimation of individual Quercus sp. acorns by FT-NIR and PLSR was shown to be possible. The varying water content detected in the spectra of the milled kernels after drying in similar conditions, within and especially between years, could be handled.