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a Dep. of Plant Pathology, Iowa State Univ., Ames, IA 50011
b USDA-ARS Plant Science Research Unit, Dep. of Crop Science, Box 7620, North Carolina State Univ., Raleigh, NC 27695-7620
* Corresponding author (sarathom{at}iastate.edu)
Genetic diversity in cropping systems can provide buffering against varying environmental conditions. Therefore, cultivar blends may have greater and more stable yields than their pure-line components. Optimization of cultivar blend development requires knowledge of the relative importance of pure-line yield potential, blend response, and cultivar interactions to blend yield. Grain yield and volume weight of oat (Avena sativa L.) pure-line cultivars and cultivar blends were measured in eight Iowa environments in order to compare their productivity and stability and to estimate genetic components of blend yields. In one experiment, five early-maturing cultivars were grown as pure lines and as all possible two- and three-way cultivar blends. In a second experiment, ten midseason-maturing cultivars were grown as pure lines and as all possible two-way blends. Grain yield was 3% greater (P < 0.05) and volume weight was 1% greater (P < 0.05) in blends than in pure lines in the early-maturity experiment; however, pure line and blends did not differ in the midseason-maturity experiment. Blends had more stable (P < 0.05) yields than pure lines in the early-maturity experiment only. Modified diallel analysis was used to partition the variation among two-way blends into general yielding ability (GYA) and true general competitive ability (TGCA) of each component genotype, and specific competing ability (SCA) interaction between blend components. General yielding ability variation was significant, whereas variation for neither TGCA nor SCA was significant. Oat genotype responses to blending were sufficiently consistent across blending partners that superior blends can be selected based on pure-line evaluations of early-maturing cultivars.
Abbreviations: GBA, general blending ability GLM, general linear models GYA, general yielding ability SCA, specific competing ability TGCA, true general competitive ability
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