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Genome-Wide Genetic Diversity among Components Does Not Cause Cultivar Blend Responses

S. J. Helland*,a and J. B. Hollandb

a Dep. of Plant Pathology, 351 Bessey Hall, Iowa State Univ., Ames, IA 50011
b USDA-ARS Plant Sci. Research Unit, Dep. of Crop Sci., Box 7620, North Carolina State Univ., Raleigh, NC 27695-7620



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Fig. 1. Quadratic regression of negative values of Lin and Binns' superiority measure (-Pi) for grain yield on the heading date difference between component pure-line midseason-maturity oat cultivars.

 


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Fig. 2. Regression of negative values of Lin and Binns' superiority measure (-Pi) for test weight on the height difference between component pure-line midseason-maturity oat cultivars.

 


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Fig. 3. Regression of negative values of Lin and Binns' superiority measure (-Pi) for grain yield on the pedigree diversity (1–coefficient of parentage) between component pure-line midseason-maturity oat cultivars.

 


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Fig. 4. Regression of negative values of Lin and Binns' superiority measure (-Pi) for test weight on the pedigree diversity (1-coefficient of parentage) between component pure-line midseason-maturity cultivars.

 


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Fig. 5. Regression of negative values of Lin and Binns' superiority measure (-Pi) for grain yield on the AFLP-based genetic diversity (1–Dice coefficient) between component pure-line midseason-maturity cultivars.

 


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Fig. 6. Quadratic regression of the test weight blend response on the square of the pedigree diversity (1 - coefficient of parentage) between component pure-line early-maturity oat cultivars.

 


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Fig. 7. Regression of the grain yield blend response of 28 soybean cultivar blends on the coefficient of parentage of the cultivars used in the blends (Gizlice et al., 1989).

 


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Fig. 8. Regression of the grain yield blend response of stripe-rust-inoculated wheat cultivar blends on the coefficient of parentage of the cultivars used in the blends (Finckh and Mundt, 1992).

 





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