Literature DB >> 22159757

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

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

Abstract

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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Year:  2011        PMID: 22159757     DOI: 10.1007/s00122-011-1762-x

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


  3 in total

1.  Energy and CO2 balance of maize and grass as energy crops for anaerobic digestion.

Authors:  Patrick A Gerin; François Vliegen; Jean-Marc Jossart
Journal:  Bioresour Technol       Date:  2007-06-18       Impact factor: 9.642

2.  The genetic architecture of maize flowering time.

Authors:  Edward S Buckler; James B Holland; Peter J Bradbury; Charlotte B Acharya; Patrick J Brown; Chris Browne; Elhan Ersoz; Sherry Flint-Garcia; Arturo Garcia; Jeffrey C Glaubitz; Major M Goodman; Carlos Harjes; Kate Guill; Dallas E Kroon; Sara Larsson; Nicholas K Lepak; Huihui Li; Sharon E Mitchell; Gael Pressoir; Jason A Peiffer; Marco Oropeza Rosas; Torbert R Rocheford; M Cinta Romay; Susan Romero; Stella Salvo; Hector Sanchez Villeda; H Sofia da Silva; Qi Sun; Feng Tian; Narasimham Upadyayula; Doreen Ware; Heather Yates; Jianming Yu; Zhiwu Zhang; Stephen Kresovich; Michael D McMullen
Journal:  Science       Date:  2009-08-07       Impact factor: 47.728

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

  3 in total
  11 in total

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

Authors:  Pascal Schopp; Christian Riedelsheimer; H Friedrich Utz; Chris-Carolin Schön; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2015-08-01       Impact factor: 5.699

2.  Association between line per se and testcross performance for eight agronomic and quality traits in winter rye.

Authors:  Thomas Miedaner; Diana D Schwegler; Peer Wilde; Jochen C Reif
Journal:  Theor Appl Genet       Date:  2013-09-27       Impact factor: 5.699

3.  Multiple-line cross QTL mapping for biomass yield and plant height in triticale (× Triticosecale Wittmack).

Authors:  Katharina V Alheit; Lucas Busemeyer; Wenxin Liu; Hans Peter Maurer; Manje Gowda; Volker Hahn; Sigrid Weissmann; Arno Ruckelshausen; Jochen C Reif; Tobias Würschum
Journal:  Theor Appl Genet       Date:  2013-10-31       Impact factor: 5.699

4.  Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.

Authors:  Tobias A Schrag; Matthias Westhues; Wolfgang Schipprack; Felix Seifert; Alexander Thiemann; Stefan Scholten; Albrecht E Melchinger
Journal:  Genetics       Date:  2018-01-23       Impact factor: 4.562

5.  Testcross performance of doubled haploid lines from European flint maize landraces is promising for broadening the genetic base of elite germplasm.

Authors:  Pedro C Brauner; Wolfgang Schipprack; H Friedrich Utz; Eva Bauer; Manfred Mayer; Chris-Carolin Schön; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2019-03-15       Impact factor: 5.699

6.  Omics-based hybrid prediction in maize.

Authors:  Matthias Westhues; Tobias A Schrag; Claas Heuer; Georg Thaller; H Friedrich Utz; Wolfgang Schipprack; Alexander Thiemann; Felix Seifert; Anita Ehret; Armin Schlereth; Mark Stitt; Zoran Nikoloski; Lothar Willmitzer; Chris C Schön; Stefan Scholten; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2017-06-24       Impact factor: 5.699

7.  Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems.

Authors:  Astrid Junker; Moses M Muraya; Kathleen Weigelt-Fischer; Fernando Arana-Ceballos; Christian Klukas; Albrecht E Melchinger; Rhonda C Meyer; David Riewe; Thomas Altmann
Journal:  Front Plant Sci       Date:  2015-01-20       Impact factor: 5.753

8.  Comparison of whole-genome prediction models for traits with contrasting genetic architecture in a diversity panel of maize inbred lines.

Authors:  Christian Riedelsheimer; Frank Technow; Albrecht E Melchinger
Journal:  BMC Genomics       Date:  2012-09-04       Impact factor: 3.969

Review 9.  Lignin: characterization of a multifaceted crop component.

Authors:  Michael Frei
Journal:  ScientificWorldJournal       Date:  2013-11-14

10.  Genome-wide association study Identified multiple Genetic Loci on Chilling Resistance During Germination in Maize.

Authors:  Guanghui Hu; Zhao Li; Yuncai Lu; Chunxia Li; Shichen Gong; Shuqin Yan; Guoliang Li; Mingquan Wang; Honglei Ren; Haitao Guan; Zhengwei Zhang; Dongling Qin; Mengzhu Chai; Juping Yu; Yu Li; Deguang Yang; Tianyu Wang; Zhiwu Zhang
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

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