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| Web URL(s): | https://scisoc.confex.com/scisoc/2018am/meetingapp.cgi/Paper/112121
Last checked: 11/12/2018
Requires: JavaScript |
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| Publication Type:
| Report |
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| Content Type: | Abstract or Summary only |
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| Author(s): | Qu, Henry Yuanshuo;
Green, Edwin J.;
Bonos, Stacy A.;
Meyer, William A. |
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| Author Affiliation: | Qu, Bonos, and Meyer: Plant Biology, Rutgers University, New Brunswick, NJ; Green: Ecology, Evolution & Natural Resources, Rutgers University, New Brunswick, NJ |
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| Title: | Application of Bayesian statistics to genotype evaluation and phenotypic selection |
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| Section: | C05 turfgrass science
Other records with the "C05 turfgrass science" Section
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Other records with the "Molecular techniques, genetics and plant breeding II: Abiotic and biotic stress oral (includes student competition)" Section
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| Meeting Info.: | Baltimore, Maryland: November 4-7, 2018 |
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| Source: | ASA, CSSA and SSSA International Annual Meetings. 2018, p. 112121. |
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| Publishing Information: | [Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Canadian Society of Agronomy] |
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| # of Pages: | 1 |
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| Keywords: | TIC Keywords: ANOVA; Festuca arundinacea; Genotypes; Phenotypes; Population genetics
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| Abstract/Contents: | "Population means and variances are important parameters in the study of plant breeding. The estimation and comparison of these parameters is a question that plant breeders are faced with all the time. There are various approaches for estimation and inference for population variances. However, these approaches are either sensitive to violation of assumptions, or involve intensive calculations and, therefore, are not widely adopted by the plant breeding community. A widespread practice for estimation and inference of population mean is analysis of variance (ANOVA). Despite its popularity, this procedure is not necessarily the best approach, and requires certain assumptions that tend to be overlooked. This project briefly discusses the principle of this traditional approach and that of Bayesian statistics, with the intention to introduce the application of a more flexible and realistic model for genotype evaluation and phenotypic selection. The comparison of the two approaches was provided using a sample dataset collected from a rainout shelter study on tall fescue [Schedonorus arundinaceus (Schreb.)]." |
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| Language: | English |
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| References: | 0 |
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| Note: | This item is an abstract only!
"71-3" |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Qu, H. Y., E. J. Green, S. A. Bonos, and W. A. Meyer. 2018. Application of Bayesian statistics to genotype evaluation and phenotypic selection. Agron. Abr. p. 112121. |
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Last checked: 11/12/2018
Requires: JavaScript |
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