2 resultados para Near- and mid-infrared spectroscopy
em eResearch Archive - Queensland Department of Agriculture
Resumo:
High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).
Resumo:
Ten growth or wood-quality traits were assessed in three nearby Corymbia citriodora subsp. variegata (CCV) open-pollinated family-within-provenance trials (18 provenances represented by a total of 374 families) to provide information for the development of a breeding program targeting both pulp and solid-wood products. Growth traits (diameter at breast high over bark [DBH], height and conical volume) were assessed at 3 and 7 years of age. Wood-quality traits (density [DEN], Kraft pulp yield [KPY], modulus of elasticity [MoE] and microfibril angle [MfA]) were predicted using near-infrared spectroscopy on wood samples collected from these trials when aged between 10 and 12 years. The high average KPY, DEN and MoE, and low average MfA observed indicates CCV is very suitable for both pulp and timber products. All traits were under moderate to strong genetic control. In across- trials analyses, high (>0.4) heritability estimates were observed for height, DEN, MoE and MfA, while moderate heritability estimates (0.24 to 0.34) were observed for DBH, volume and KPY. Most traits showed very low levels of genotype × site interaction. Estimated age–age genetic correlations for growth traits were strong at both the family (0.97) and provenance (0.99) levels. Relationships among traits (additive genetic correlation estimates) were favourable, with strong and positive estimates between growth traits (0.84 to 0.98), moderate and positive values between growth and wood-quality traits (0.32 to 0.68), moderate and positive between KPY and MoE (0.64), and high and positive between DEN and MoE (0.82). However, negative (but favourable) correlations were detected between MfA and all other evaluated traits (−0.31 to −0.96). The genetic correlation between the same trait expressed on two different sites, at family level, ranged from 0.24 to 0.42 for growth traits, and from 0.29 to 0.53 for wood traits. Therefore simultaneous genetic improvement of growth and wood property traits in CCV for the target environment in south-east Queensland should be possible, given the moderate to high estimates of heritability and favourable correlations amongst all traits studied, unless genotype × site interactions are greater than was evident. © 2016 NISC (Pty) Ltd