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CORN

Predicting Outcrossing in Maize Hybrid Seed Production

^a Agronomy Dep., Iowa State Univ., 2101 Agronomy Hall, Ames, IA 50011
^b Monsanto Company, 503 S. Maplewood, Williamsburg, IA 52361
^c Dep. of Geography and Meteorology, Valparaiso Univ., 1809 Chapel Dr., Valparaiso, IN 46383-6493
^d Dpto. Produccion Vegetal, Fitotecnia, Univ. Politecnica de Madrid, 28040 Madrid, Spain
^e Syngenta Seeds, Washington, IA 52353

^* Corresponding author (westgate{at}iastate.edu).

Controlling pollination of the female inbred is critical to achieve maximum kernel set and high levels of genetic purity in maize (Zea mays L.) hybrid seed production. Although kernel set associated with inbred flowering dynamics is fairly predictable, it has not been possible to predict the level of outcrossing resulting from adventitious pollen entering the seed field. Our objective was to combine our kernel set model with a new Lagrangian pollen dispersal model to determine whether outcrossing could be simulated from flowering dynamics and estimates of pollen drift. This study was conducted in a commercial seed production field in which male and female planting dates were varied to provide a range of flowering synchronies and risk for outcrossing. Kernel production varied from 13.4 x 10⁶ to 24.5 x 10⁶ kernels ha^–1. Outcrossing at field locations 100 to 170 m from an adventitious pollen source varied from 1.4 to 18% as determined by allelic variation at 13 loci. The kernel set model accurately simulated variation in kernel production (R² = 0.83; RMSE = 0.3 x 10⁶) when silk receptivity was limited to 4 d. Percentage outcrossing due to adventitious pollen also was accurately simulated (R² = 0.78; RMSE = 0.8) for wind conditions and plant development patterns typically encountered in maize hybrid seed production. The combined kernel set and pollen dispersal models provide a novel and robust approach for defining management strategies to optimize kernel production and genetic purity.

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Received for publication October 2, 2007.