Literature DB >> 22159756

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

Christoph Grieder1, Baldev S Dhillon, Wolfgang Schipprack, Albrecht E Melchinger.   

Abstract

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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Year:  2011        PMID: 22159756     DOI: 10.1007/s00122-011-1761-y

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  8 in total

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  8 in total
  8 in total

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

Authors:  Christoph Grieder; Baldev S Dhillon; Wolfgang Schipprack; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2011-12-13       Impact factor: 5.699

2.  Forecasting the accuracy of genomic prediction with different selection targets in the training and prediction set as well as truncation selection.

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Authors:  Katharina V Alheit; Lucas Busemeyer; Wenxin Liu; Hans Peter Maurer; Manje Gowda; Volker Hahn; Sigrid Weissmann; Arno Ruckelshausen; Jochen C Reif; Tobias Würschum
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5.  Optimum breeding strategies using genomic and phenotypic selection for the simultaneous improvement of two traits.

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Journal:  Theor Appl Genet       Date:  2021-10-07       Impact factor: 5.699

6.  Phenotypic variation in biomass and related traits among four generations advanced lines of Cleome (Gynandropsis gynandra L. (Briq.)).

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7.  General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents.

Authors:  A Larièpe; L Moreau; J Laborde; C Bauland; S Mezmouk; L Décousset; T Mary-Huard; J B Fiévet; A Gallais; P Dubreuil; A Charcosset
Journal:  Theor Appl Genet       Date:  2016-12-02       Impact factor: 5.699

8.  Reciprocal Genetics: Identifying QTL for General and Specific Combining Abilities in Hybrids Between Multiparental Populations from Two Maize (Zea mays L.) Heterotic Groups.

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Journal:  Genetics       Date:  2017-09-28       Impact factor: 4.562

  8 in total

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