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ARS Home » Midwest Area » Urbana, Illinois » Global Change and Photosynthesis Research » Research » Publications at this Location » Publication #293067
Title: Common sunflower seedling emergence across the U.S. Midwest

Author
item CLAY, SHARON - South Dakota State University
item Davis, Adam
item DILLE, J ANITA - Kansas State University
item LINDQUIST, JOHN - University Of Nebraska
item RAMIREZ, ANALIZA H M - Kansas State University
item SPRAGUE, CHRISTY - Michigan State University
item REICKS, GRAIG - South Dakota State University
item Forcella, Frank

Submitted to: Weed Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/22/2013
Publication Date: 1/1/2014
Citation: Clay, S., Davis, A.S., Dille, J., Lindquist, J., Ramirez, A.H.M., Sprague, C., Reicks, G., Forcella, F. 2014. Common sunflower seedling emergence across the U.S. Midwest. Weed Science. 62:63-70.

Interpretive Summary: Timely management of agricultural weeds can improve the cost-effectiveness of control, and reduce crop yield losses to weeds. In order to achieve this, better information is needed, at a regional spatial scale, on the seedling emergence schedules of important agricultural weeds. We measured seedling emergence of common sunflower in five Midwest U.S. states over a three year period. Using a new statistical modeling approach, we found that we could fit a common model to all site-years of seedling emergence data if soil temperatures for the overwinter seed burial environment were taken into account. Such information will enable farmers to time their weed management operations more effectively. Additional work should be performed to generate unified, regional level, seedling emergence models for other weed species.

Technical Abstract: Predicting weed emergence timing from the seed bank can be used by practitioners to schedule post-emergence weed management operations. This study used common sunflower seed from Kansas in 16 site years across the Midwestern U.S. to examine the variability that climate and year had on common sunflower emergence. Nonlinear mixed effects models, using a flexible sigmoidal function (Weibull equation) that included thermal time, hydrothermal time, and a modified hydrothermal time (with accumulation starting from January 1 of each year), were developed to fit the emergence data. An iterative method was used to select optimal base temperature (Tb) and base and ceiling soil matric potentials (psi-b and psi-c) 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 psi-b = -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 overwintering conditions had longer emergence periods.