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| Web URL(s): | https://scisoc.confex.com/scisoc/2018am/meetingapp.cgi/Paper/112641
Last checked: 11/14/2018
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): | Pereira, Carlos Henrique;
Kenworthy, Kevin E.;
Quesenberry, Kenneth H.;
Unruh, J. Bryan;
Rodrigues Nunes, Jose Airton;
Rios, Esteban F. |
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| Author Affiliation: | Pereira and Rios: Agronomy, University of Florida, Gainesville, FL; Kenworthy: Agronomy Department, University of Florida, Gainesville, FL; Quesenberry: University of Florida, Gainesville, FL; Unruh: Environmental Horticulture Department, University of Florida West Florida Research & Education Center, Jay, FL; Rodrigues Nunes: Biology, Federal University of Lavras, Lavras, Brazil |
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| Title: | Multi-environmental evaluation of St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] breeding lines for turf performance using mixed models |
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| Section: | C05 turfgrass science
Other records with the "C05 turfgrass science" Section
Turf physiology, molecular biology, and genetics poster (Includes student competiton)
Other records with the "Turf physiology, molecular biology, and genetics poster (Includes student competiton)" 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. 112641. |
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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: Cultivar evaluation; Cultivar improvement; Genotyping; Stenotaphrum secundatum
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| Abstract/Contents: | "St. Augustinegrass is the most extensively used turfgrass for managed landscapes in Florida. In order to decrease genetic vulnerability and to identify new genotypes with broad adaptation, an understanding of the effect of genotype by environment interaction (GEI) it is necessary. The GEI of potential new cultivars is best evaluated in multi-environment trials (MET). The objective of this study was to estimate genetic parameters from MET of St. Augustinegrass genotypes for coverage (CO), turf quality (TQ), turf color (TC) across five locations in Florida (Arcadia, Hague, Citra, Cocoa Beach and Jay) with multiple visual ratings over five years (2011-2016). The assessed genotypes were composed of 26 breeding lines, and the cultivars: 'Floraverde', 'Palmetto', 'Captiva' and 'Floratam'. The trials were arranged as randomized complete block designs with three replications. Linear mixed models with repeated measures (seasons within years) were implemented in ASReml-R to estimate variance components. Moreover, we described the GEI by GGEbiplot analysis using GGEbiplotGUI R package. By the REML LRT test, significant differences were observed among genotypes. The estimates of genotype-mean heritabilities were 0.26 for TQ; 0.13 for TC and 0.18 for CO. The genotypic correlations among years (rB) ranged from 0.35 to 0.83 for TQ; 0.48 to 0.69 for TC and 0.05 to 0.90 for CO, indicating stable genotypic performance for TQ and TC across years within locations. The GGE biplot analysis indicated that genotypes 2 and 3 were superior at Jay and Arcadia for TC and all locations for TQ. Genotypes 20 and 21 were superior at Hague for TC. For CO, most of the genotypes were clustered near each other, while genotypes 11 and 13 indicated less association with locations, e.g. genotypes 9 and 4 at Jay and Arcadia. These results exhibit the importance of evaluating genotypes across multiple locations prior to release." |
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| Language: | English |
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| References: | 0 |
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| Note: | This item is an abstract only!
"233"
"Poster Number: 1292" |
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| ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Pereira, C. H., K. E. Kenworthy, K. H. Quesenberry, J. B. Unruh, J. A. Rodrigues Nunes, and E. F. Rios. 2018. Multi-environmental evaluation of St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] breeding lines for turf performance using mixed models. Agron. Abr. p. 112641. |
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Last checked: 11/14/2018
Requires: JavaScript |
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