Classical and genomic prediction of hybrid sweet corn performance in organic environments-Reference-Cited by-同舟云学术

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Classical and genomic prediction of hybrid sweet corn performance in organic environments

Published:2021-04-26 Issue:3 Volume:61 Page:1698-1708
ISSN:0011-183X
Container-title:Crop Science
language:en
Short-container-title:Crop Science

Author:

Zystro Jared¹,Peters Tessa²,Miller Kathleen³,Tracy William F.⁴^ORCID

Affiliation:

1. Organic Seed Alliance 1385 8th St., Ste. 125 Arcata CA 95521 USA

2. The Land Institute 2440 E Water Well Rd. Salina KS 67401 USA

3. Syngenta Seeds West Palm Beach FL 33414 USA

4. Department of Agronomy, College of Agricultural and Life Sciences University of Wisconsin–Madison Madison WI 53706 USA

Funder

National Institute of Food and Agriculture

Publisher

Wiley

Subject

Agronomy and Crop Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/csc2.20400

Reference33 articles.

1. Fitting Linear Mixed-Effects Models Usinglme4

2. Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding

3. TASSEL: software for association mapping of complex traits in diverse samples

4. Accuracy of genomic selection to predict maize single-crosses obtained through different mating designs

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1. Advancing water absorption capacity in hard winter wheat using a multivariate genomic prediction approach;Crop Science;2024-08-24

2. Use of simulation to optimize a sweet corn breeding program: implementing genomic selection and doubled haploid technology;G3: Genes, Genomes, Genetics;2024-06-13

3. Utilizing genomic prediction to boost hybrid performance in a sweet corn breeding program;Frontiers in Plant Science;2024-04-25

4. Effects of marker density on genomic prediction for yield traits in sweet corn;Euphytica;2024-03-13

5. Simulation‐based decision‐making and implementation of tools in hybrid crop breeding pipelines;Crop Science;2023-11-21

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