ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2010
Hybrid maize breeding with doubled haploids: V. Selection strategies for testcross performance with variable sizes of crosses and S(1) families.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Applications of Doubled Haploids in Plant Breeding and Applied Research.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Doubled haploid technology for line development in maize: technical advances and prospects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Review
- Gene stacking strategies with doubled haploids derived from biparental crosses: theory and simulations assuming a finite number of loci.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2011Article
- Best linear unbiased prediction and optimum allocation of test resources in maize breeding with doubled haploids.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2011Article
Corrections and comments
- Erratum issued
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In hybrid maize (Zea mays L.) breeding, doubled haploids (DH) are increasingly replacing inbreds developed by recurrent selfing. Doubled haploids may be developed directly from S(0) plants in the parental cross or via S(1) families. In both these breeding schemes, we examined 2 two-stage selecting strategies, i.e., considering or ignoring cross and family structure while selection among and within parental crosses and S(1) families. We examined the optimum allocation of resources to maximize the selection gain DeltaG and the probability P(q) of identifying the q% best genotypes. Our specific objectives were to (1) determine the optimum number and size of crosses and S(1) families, as well as the optimum number of test environments and (2) identify the superior selection strategy. Selection was based on the evaluation of testcross progenies of (1) DH lines in both stages (DHTC) and (2) S(1) families in the first stage and of DH lines within S(1) families in the second stage (S(1)TC-DHTC) with uniform and variable sizes of crosses and S(1) families. We developed and employed simulation programs for selection with variable sizes of crosses and S(1) families within crosses. The breeding schemes and selection strategies showed similar relative efficiency for both optimization criteria DeltaG and P (0.1%). As compared with DHTC, S(1)TC-DHTC had larger DeltaG and P (0.1%), but a higher standard deviation of DeltaG. The superiority of S(1)TC-DHTC was increased when the selection was done among all DH lines ignoring their cross and family structure and using variable sizes of crosses and S(1) families. In DHTC, the best selection strategy was to ignore cross structures and use uniform size of crosses.
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