The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes

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 poss...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Brown, Christopher [verfasserIn] Martin, Antony P. Grof, Christopher P.L.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017transfer abstract

Schlagwörter:	lignin biosynthesis Fourier transform mid-infrared spectroscopy monocotyledonous C4 grasses Setaria italica

Umfang:	12

Übergeordnetes Werk:	Enthalten in: Product derivation in practice - de Souza, Leandro Oliveira ELSEVIER, 2015transfer abstract, JIA, Beijing
Übergeordnetes Werk:	volume:16 ; year:2017 ; number:6 ; pages:1256-1267 ; extent:12

Links:	Volltext

DOI / URN:	10.1016/S2095-3119(16)61574-5

Katalog-ID:	ELV030490170

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245	1	4	\|a The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes
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520			\|a 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.
520			\|a 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.
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700	1		\|a Grof, Christopher P.L. \|4 oth
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matchkey_str	brownchristophermartinantonypgrofchristo:2017----:hapiainforetasomiifaefisetocptietfvrainnelalo
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publishDate	2017
allfields	10.1016/S2095-3119(16)61574-5 doi GBVA2017011000005.pica (DE-627)ELV030490170 (ELSEVIER)S2095-3119(16)61574-5 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl Brown, Christopher verfasserin aut The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier Martin, Antony P. oth Grof, Christopher P.L. oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:16 year:2017 number:6 pages:1256-1267 extent:12 https://doi.org/10.1016/S2095-3119(16)61574-5 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 16 2017 6 1256-1267 12 045F 630
spelling	10.1016/S2095-3119(16)61574-5 doi GBVA2017011000005.pica (DE-627)ELV030490170 (ELSEVIER)S2095-3119(16)61574-5 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl Brown, Christopher verfasserin aut The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier Martin, Antony P. oth Grof, Christopher P.L. oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:16 year:2017 number:6 pages:1256-1267 extent:12 https://doi.org/10.1016/S2095-3119(16)61574-5 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 16 2017 6 1256-1267 12 045F 630
allfields_unstemmed	10.1016/S2095-3119(16)61574-5 doi GBVA2017011000005.pica (DE-627)ELV030490170 (ELSEVIER)S2095-3119(16)61574-5 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl Brown, Christopher verfasserin aut The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier Martin, Antony P. oth Grof, Christopher P.L. oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:16 year:2017 number:6 pages:1256-1267 extent:12 https://doi.org/10.1016/S2095-3119(16)61574-5 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 16 2017 6 1256-1267 12 045F 630
allfieldsGer	10.1016/S2095-3119(16)61574-5 doi GBVA2017011000005.pica (DE-627)ELV030490170 (ELSEVIER)S2095-3119(16)61574-5 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl Brown, Christopher verfasserin aut The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier Martin, Antony P. oth Grof, Christopher P.L. oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:16 year:2017 number:6 pages:1256-1267 extent:12 https://doi.org/10.1016/S2095-3119(16)61574-5 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 16 2017 6 1256-1267 12 045F 630
allfieldsSound	10.1016/S2095-3119(16)61574-5 doi GBVA2017011000005.pica (DE-627)ELV030490170 (ELSEVIER)S2095-3119(16)61574-5 DE-627 ger DE-627 rakwb eng 630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl Brown, Christopher verfasserin aut The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes 2017transfer abstract 12 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. 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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq. lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier Martin, Antony P. oth Grof, Christopher P.L. oth Enthalten in Elsevier de Souza, Leandro Oliveira ELSEVIER Product derivation in practice 2015transfer abstract JIA Beijing (DE-627)ELV018624588 volume:16 year:2017 number:6 pages:1256-1267 extent:12 https://doi.org/10.1016/S2095-3119(16)61574-5 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_40 GBV_ILN_283 52.43 Kältetechnik VZ 52.52 Thermische Energieerzeugung Wärmetechnik VZ 52.42 Heizungstechnik Lüftungstechnik Klimatechnik VZ 50.38 Technische Thermodynamik VZ AR 16 2017 6 1256-1267 12 045F 630
language	English
source	Enthalten in Product derivation in practice Beijing volume:16 year:2017 number:6 pages:1256-1267 extent:12
sourceStr	Enthalten in Product derivation in practice Beijing volume:16 year:2017 number:6 pages:1256-1267 extent:12
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bklname	Kältetechnik Thermische Energieerzeugung Wärmetechnik Heizungstechnik Lüftungstechnik Klimatechnik Technische Thermodynamik
institution	findex.gbv.de
topic_facet	lignin biosynthesis Fourier transform mid-infrared spectroscopy monocotyledonous C4 grasses Setaria italica
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container_title	Product derivation in practice
authorswithroles_txt_mv	Brown, Christopher @@aut@@ Martin, Antony P. @@oth@@ Grof, Christopher P.L. @@oth@@
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author	Brown, Christopher
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topic_title	630 640 630 DE-600 640 DE-600 330 VZ 004 VZ 690 VZ 52.43 bkl 52.52 bkl 52.42 bkl 50.38 bkl The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica Elsevier
topic	ddc 630 ddc 640 ddc 330 ddc 004 ddc 690 bkl 52.43 bkl 52.52 bkl 52.42 bkl 50.38 Elsevier lignin biosynthesis Elsevier Fourier transform mid-infrared spectroscopy Elsevier monocotyledonous C4 grasses Elsevier Setaria italica
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title	The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes
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title_full	The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes
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title_sort	application of fourier transform mid-infrared (ftir) spectroscopy to identify variation in cell wall composition of setaria italica ecotypes
title_auth	The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes
abstract	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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.
abstractGer	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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.
abstract_unstemmed	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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.
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title_short	The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes
url	https://doi.org/10.1016/S2095-3119(16)61574-5
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up_date	2024-07-06T17:43:00.228Z
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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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">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 C4 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-qPCR, among accessions of S. italica, which closely mirror profiles observed in the different developmental regions of an elongating internode of S. viridis by RNASeq.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">lignin biosynthesis</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Fourier transform mid-infrared spectroscopy</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">monocotyledonous C4 grasses</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Setaria italica</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Martin, Antony P.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Grof, Christopher P.L.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">de Souza, Leandro Oliveira ELSEVIER</subfield><subfield code="t">Product derivation in practice</subfield><subfield code="d">2015transfer abstract</subfield><subfield code="d">JIA</subfield><subfield code="g">Beijing</subfield><subfield code="w">(DE-627)ELV018624588</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:16</subfield><subfield code="g">year:2017</subfield><subfield code="g">number:6</subfield><subfield code="g">pages:1256-1267</subfield><subfield code="g">extent:12</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/S2095-3119(16)61574-5</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_283</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.43</subfield><subfield code="j">Kältetechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.52</subfield><subfield code="j">Thermische Energieerzeugung</subfield><subfield code="j">Wärmetechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">52.42</subfield><subfield code="j">Heizungstechnik</subfield><subfield code="j">Lüftungstechnik</subfield><subfield code="j">Klimatechnik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">50.38</subfield><subfield code="j">Technische Thermodynamik</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">16</subfield><subfield code="j">2017</subfield><subfield code="e">6</subfield><subfield code="h">1256-1267</subfield><subfield code="g">12</subfield></datafield><datafield tag="953" ind1=" " ind2=" "><subfield code="2">045F</subfield><subfield code="a">630</subfield></datafield></record></collection>
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The application of Fourier transform mid-infrared (FTIR) spectroscopy to identify variation in cell wall composition of Setaria italica ecotypes

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