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a USDA-ARS, Crop Science Research Laboratory, P.O. Box 5367, Mississippi State, MS 39762
b Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762
* Corresponding author (JMcCarty{at}msa-msstate.ars.usda.gov).
Primitive accession derived germplasm of cotton, Gossypium hirsutum L., may provide useful traits for cultivar improvement. The ability to predict advanced generation performance when crossed with commercial cultivars would enhance their utility and encourage their use in breeding programs. Our objective for this study was to predict genetic effects for day-neutral derived lines derived from primitive accessions and crossed to cultivars using a mixed linear model approach. Parents and F2 populations were grown at two field locations in 1998 and 1999 and parents and F3s were grown at two locations in 2000. Lint yield, yield components, and fiber quality traits were evaluated. An additive-dominance additive x additive (ADAA) model was used for genetic analysis. A mixed linear model, minimum norm quadratic unbiased estimation (MINQUE) was used to predict genetic effects and genotype values. Generally, the female cultivar parents had higher additive effects for lint yield and lint percentage; however, these females generally had lower additive effects for fiber strength. Significant AA effects widely existed among parents and F2 populations for lint percentage, boll weight, and fiber strength. The correlation coefficients between observed values and predicted values were mainly high among traits and environments. These data suggest that it is appropriate to use the ADAA genetic model to predict genetic effects and hybrid genotypic values for advanced generations. Our study showed that fiber strength may be significantly improved over that of the female parents, while the lint yield was slightly but not significantly predicted to be less than their female parents. This study suggested that day-neutral primitive germplasm accessions provided a valuable gene resource for selecting high yielding lines with significantly improved fiber strength.
Abbreviations: AA, additive x additive effect AD, additive dominance model ADAA, additive-dominance, additive x additive model MINQUE, minimum norm quadratic unbiased estimation
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