Verification of interspecific pine hybrids using paternally inherited chloroplast microsatellites

Pollen contamination continues to be a problem for many operational controlled-pollination programs for hybrid trees. In the case of the slash x Caribbean pine hybrid in Queensland, Australia, productivity losses may occur if pure slash is deployed on sites optimal for hybrids. We report a DNA marker assay based on chloroplast microsatellite loci that distinguishes between representatives of slash and Caribbean pine breeding populations. Furthermore, interspecific hybrid Fs were distinguishable from individuals believed to be derived from self fertilisation or outcrossing to other slash pine. The multi-locus assay was optimised for a single-tube PCR reaction and offered an estimated 75% savings in the turnaround time and costs compared with individual PCR amplification of the six loci. Slash pine displayed more variation at these loci than Caribbean pine despite Caribbean pine having been sampled over a more extensive geographical range than the slash pine

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development.

BackgroundIn order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS).ResultsThe PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks.ConclusionEucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks

High-throughput prediction of Acacia and eucalypt lignin syringyl/guaiacyl content using FT-Raman spectroscopy and partial least squares modelling

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

Progress in Myrtacease genetics and genomics: Eucalyptus as the pivotal genus

The status of genomics and genetics research in the Myrtaceae, a large family of dicotyledonous woody plants, is reviewed with Eucalyptus as the focal genus. The family contains over 5,650 species in 130 to 150 genera, predominantly of neo-tropical and Southern Hemisphere distribution. Several genera are well known for their economic importance worldwide. Myrtaceae are typically diploids with small to intermediate genome size. Microsatellites have been developed for several genera while higher throughput marker systems such as diversity arrays technology and single nucleotide polymorphism are available for Eucalyptus. Molecular data have been fundamental to current perspectives on the phylogeny, phylogeography and taxonomy of the Myrtaceae, while numerous studies of genetic diversity have been carried out particularly as it relates to endangered, rare, fragmented, overharvested or economically important species. Large expressed sequence tag collections for species of Eucalyptus have recently become public to support the annotation of the Eucalyptus grandis genome. Transcriptomics in Eucalyptus has advanced by microarrays and next-generation sequencing focusing on wood development. Linkage maps for Eucalyptus display high synteny across species and have been extensively used to map quantitative trait loci for a number of traits including growth, wood quality, disease and insect resistance. Candidate gene-based association genetics have successfully found marker–trait associations for wood and fiber traits. Genomic selection experiments have demonstrated clear potential to improve the efficiency of breeding programs while freeze-tolerant transgenic Eucalyptus trials have recently been initiated. The recently released E. grandis genome, sequenced to an average coverage of 8�, will open up exceptional opportunities to advance Myrtaceae genetics and genomics research