Predictions of weed emergence can be used by practitioners to schedule POST weed management operations. Common sunflower seed from Kansas was used at six Midwestern U.S. sites to examine the variability that 16 climates had on common sunflower emergence. Nonlinear mixed effects models, using a flexible sigmoidal Weibull function that included thermal time, hydrothermal time, and a modified hydrothermal time (with accumulation starting from January 1 of each year), were developed to describe the emergence data. An iterative method was used to select an optimal base temperature (Tb) and base and ceiling soil matric potentials (ψb and ψc) that resulted in a best-fit regional model. The most parsimonious model, based on Akaike's information criterion (AIC), resulted when Tb = 4.4 C, and ψb = -20000 kPa. Deviations among model fits for individual site years indicated a negative relationship (r = -0.75; P < 0.001) between the duration of seedling emergence and growing degree days (Tb = 10 C) from October (fall planting) to March. Thus, seeds exposed to warmer conditions from fall burial to spring emergence had longer emergence periods.
- Abiotic influences on seed dormancy
- Regional environmental variation
- Seedling recruitment
ASJC Scopus subject areas
- Agronomy and Crop Science
- Plant Science