Determination of Methane Fermentation Yield and its Kinetics by near Infrared Spectroscopy and Chemical Composition in Maize

Grieder, Christoph; Mittweg, Greta; Dhillon, B. S.; Montes, Juan M.; Orsini, Elena; Melchinger, Albrecht E.

doi:10.1255/jnirs.959

Cited by 19 publications

(18 citation statements)

References 21 publications

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“…Plant height (m) and dry matter yield of whole-plant biomass (t/ha) were measured for each field plot at the end of the vegetation period. Lignin (%) was measured in the harvested plant material using calibrated near-infrared spectroscopy as described previously (48).…”

Section: Methodsmentioning

confidence: 99%

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

Riedelsheimer

Lisec

Czedik‐Eysenberg

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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The diversity of metabolites found in plants is by far greater than in most other organisms. Metabolic profiling techniques, which measure many of these compounds simultaneously, enabled investigating the regulation of metabolic networks and proved to be useful for predicting important agronomic traits. However, little is known about the genetic basis of metabolites in crops such as maize. Here, a set of 289 diverse maize inbred lines was genotyped with 56,110 SNPs and assayed for 118 biochemical compounds in the leaves of young plants, as well as for agronomic traits of mature plants in field trials. Metabolite concentrations had on average a repeatability of 0.73 and showed a correlation pattern that largely reflected their functional grouping. Genome-wide association mapping with correction for population structure and cryptic relatedness identified for 26 distinct metabolites strong associations with SNPs, explaining up to 32.0% of the observed genetic variance. On nine chromosomes, we detected 15 distinct SNP-metabolite associations, each of which explained more then 15% of the genetic variance. For lignin precursors, including p-coumaric acid and caffeic acid, we found strong associations (P values 2:7 × 10 −10 to 3:9 × 10 −18 ) with a region on chromosome 9 harboring cinnamoyl-CoA reductase, a key enzyme in monolignol synthesis and a target for improving the quality of lignocellulosic biomass by genetic engineering approaches. Moreover, lignin precursors correlated significantly with lignin content, plant height, and dry matter yield, suggesting that metabolites represent promising connecting links for narrowing the genotypephenotype gap of complex agronomic traits.genetic association | metabolomics | Zea mays

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Section: Methodsmentioning

confidence: 99%

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

Riedelsheimer

Lisec

Czedik‐Eysenberg

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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314

257

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“…For determination of MEC, the reference method of which is described by Boguhn et al (2003), the official NIRS calibration of the German association of agricultural research institutes (VDLUFA) was used. Development of the NIRS calibrations for all other traits was described in detail elsewhere (Grieder et al 2011b); coefficients of determination (R 2 ) obtained with validation were 0.90 for fat and starch, 0.84 for ADF, 0.81 for NDF, 0.76 for ADL, and 0.77 for MFY.…”

Section: Field Experiments and Data Collectionmentioning

confidence: 99%

Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance

et al. 2011

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Biofuels have gained importance recently and the use of maize biomass as substrate in biogas plants for production of methane has increased tremendously in Germany. The objectives of our research were to (1) estimate variance components and heritability for different traits relevant to biogas production in testcrosses (TCs) of maize, (2) study correlations among traits, and (3) discuss strategies to breed maize as a substrate for biogas fermenters. We evaluated 570 TCs of 285 diverse dent maize lines crossed with two flint single-cross testers in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and methane yield (MY), the product of DMY and MFY, as the main target trait. Estimates of variance components showed general combining ability (GCA) to be the major source of variation. Estimates of heritability exceeded 0.67 for all traits and were even much greater in most instances. Methane yield was perfectly correlated with DMY but not with MFY, indicating that variation in MY is primarily determined by DMY. Further, DMY had a larger heritability and coefficient of genetic variation than MFY. Hence, for improving MY, selection should primarily focus on DMY rather than MFY. Further, maize breeding for biogas production may diverge from that for forage production because in the former case, quality traits seem to be of much lower importance.

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“…However, this would require fast methods for their determination as possible through the use of online-NIR spectrometers that can directly analyze harvested material on the chopper (Montes et al 2007). The use of online-NIR spectrometers on choppers for determination of relevant quality traits for biogas maize seems promising based on the successfully developed laboratory NIRS calibrations for MFY and other quality traits (Grieder et al 2011a). If selection is performed for quality parameters that relate to whole plant material like MEC, this might produce hybrids with increased grain or starch content, but poor cell wall digestibility of the stover (Argillier et al 2000).…”

Section: Efficiency Of Pre-selection Among Inbred Linesmentioning

confidence: 99%

Breeding maize as biogas substrate in Central Europe: II. Quantitative-genetic parameters for inbred lines and correlations with testcross performance

et al. 2011

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Breeding maize for use as a biogas substrate (biogas maize) has recently gained considerable importance. To optimize hybrid breeding programs, information about line per se performance (LP) of inbreds and its relation to their general combining ability (GCA) is required. The objectives of our research were to (1) estimate variance components and heritability of LP for agronomic and quality traits relevant to biogas production, (2) study correlations among traits as well as between LP and GCA, and (3) discuss implications for breeding of biogas maize. We evaluated 285 diverse dent maize inbred lines in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and their product, methane yield (MY), as the main target trait. In agreement with observations made for GCA in a companion study, variation in MY was mainly determined by DMY. MFY, which showed moderate correlation with lignin but only weak correlation with starch, revealed only low genotypic variation. Thus, our results favor selection of genotypes with high DMY and less focus on ear proportion for biogas maize. Genotypic correlations between LP and GCA [r (g) (LP, GCA)] were highest (≥0.94) for maturity traits (days to silking, dry matter concentration) and moderate (≥0.65) for DMY and MY. Multistage selection is recommended. Selection for GCA of maturity traits, plant height, and to some extent also quality traits and DMY on the level of LP looks promising.

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Determination of Methane Fermentation Yield and its Kinetics by near Infrared Spectroscopy and Chemical Composition in Maize

Cited by 19 publications

References 21 publications

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize

Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance

Breeding maize as biogas substrate in Central Europe: II. Quantitative-genetic parameters for inbred lines and correlations with testcross performance

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