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This article in CS

  1. Vol. 49 No. 3, p. 937-948
     
    Received: May 25, 2008


    * Corresponding author(s): lucasborras@hotmail.com
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doi:10.2135/cropsci2008.05.0286

Modeling Anthesis to Silking in Maize Using a Plant Biomass Framework

  1. Lucas Borrás *ac,
  2. Juan P. Astiniad,
  3. Mark E. Westgatea and
  4. Alan D. Severinib
  1. a Agronomy Dep., Iowa State Univ., 1301 Agronomy Hall, Ames, IA 50011-1010, U.S
    c Current address: Departamento de Producción Vegetal, Facultad de Ciencias Agrarias, Universidad Nacional de Rosario, S2125ZAA Zavalla, Santa Fe, Argentina
    d Current address: Pioneer Hi-Bred Intl., Rutas 31-191, Salto, CP 2741, Buenos Aires, Argentina
    b Estación Experimental Agropecuaria Pergamino, INTA, Pergamino CP 2700, Buenos Aires, Argentina

Abstract

The capacity to predict time to silking relative to anthesis in maize (Zea mays L.) has important implications for breeding and seed production. We developed a theoretical quantitative framework for simulating the anthesis to silking interval (ASI) based on plant growth and biomass partitioning to the ear. We tested this framework to simulate the progress of silking relative to anthesis in nine inbreds and four hybrids whose plant growth rate (PGR) during flowering was altered by stand density, thinning, or defoliating treatments. Time to 50% anthesis varied with genotype but was not affected by canopy modifications (P < 0.01). The ASI, however, varied with genotype and canopy modifications (P < 0.01). The proportion of plants reaching silking ranged from 12 to 100% across treatments. There were significant (P < 0.001) genotype × treatment interactions for PGR around anthesis and plant-to-plant variability in growth rate. Genotypes differed in biomass partitioning to the ear, the pattern of ear biomass (EB) accumulation, and the EB required to achieve silking. Despite these effects, the plant biomass framework accurately simulated silking dynamics relative to anthesis for the 36 treatment combinations (R 2 = 0.86, RMSE = 16.7%). These results show that coupling the expansion growth process of silking with plant growth around flowering is a useful and robust approach for modeling ASI at the population level.

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