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您的检索式：作者名="Christopher P.L.Grof"
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| 1 | C_4 Plants as Biofuel Feedstocks: Optimising Biomass Production and Feedstock Quality from a Lignocellulosic Perspective显示文摘The main feedstocks for bioethanol are sugarcane (Saccharum officinarum) and maize (Zea mays),both of which are C4 grasses,highly efficient at converting solar energy into chemical energy,and both are food crops.As the systems for lignocellulosic bioethanol production become more efficient and cost effective,plant biomass from any source may be used as a feedstock for bioethanol production.Thus,a move away from using food plants to make fuel is possible,and sources of biomass such as wood from forestry and plant waste from cropping may be used.However,the bioethanol industry will need a continuous and reliable supply of biomass that can be produced at a low cost and with minimal use of water,fertilizer and arable land.As many C4 plants have high light,water and nitrogen use efficiency,as compared with C3 species,they are ideal as feedstock crops.We consider the productivity and resource use of a number of candidate plant species,and discuss biomass ‘quality’,that is,the composition of the plant cell wall. | Caitlin S.Byrt Christopher P.L.Grof Robert T.Furbank | 2011 | Journal of Integrative Plant Biology2011，53，2： | 7 |
| 2 | The application of Fourier transform mid-infrared(FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes显示文摘Cell wall composition in monocotyledonous grasses has been identified as a key area of research for developing better feedstocks for forage and biofuel production.Setaria viridis and its close domesticated relative Setaria italica have been chosen as suitable monocotyledonous models for plants possessing the C_4 pathway of photosynthesis including sorghum,maize,sugarcane,switchgrass and Miscanthus×giganteus.Accurate partial least squares regression(PLSR)models to predict S.italica stem composition have been generated,based upon Fourier transform mid-infrared(FTIR)spectra and calibrated with wet chemistry determinations of ground S.italica stem material measured using a modified version of the US National Renewable Energy Laboratory(NREL)acid hydrolysis protocol.The models facilitated a high-throughput screening analysis for glucan,xylan,Klason lignin and acid soluble lignin(ASL)in a collection of 183 natural S.italica variants and clustered them into classes,some possessing unique chemotypes.The predictive models provide a highly efficient screening tool for large scale breeding programs aimed at identifying lines or mutants possessing unique cell wall chemotypes.Genes encoding key catalytic enzymes of the lignin biosynthesis pathway exhibit a high level of conservation with matching expression profiles,measured by RT-q PCR,among accessions of S.italica,which closely mirror profiles observed in the different developmental regions of an elongating internode of S.viridis by RNASeq. | Christopher Brown Antony P.Martin Christopher P.L.Grof | 2017 | Journal of Integrative Agriculture2017，16，6： | 2 |
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