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Modeling site-specific wild oat (Avena fatua) emergence across a variable landscape

Published online by Cambridge University Press:  20 January 2017

Eric R. Page ,
Robert S. Gallagher ,
Armen R. Kemanian ,
Hao Zhang  and
E. Patrick Fuerst
Robert S. Gallagher
Affiliation:
Department of Crop and Soil Sciences, Pennsylvania State University, University Park, PA 16802
Armen R. Kemanian
Affiliation:
Blackland Research and Extension Center, Texas Agricultural Experiment Station, Temple, TX 76502
Hao Zhang
Affiliation:
Department of Statistics, Washington State University, Pullman, WA 99164-3144
E. Patrick Fuerst
Affiliation:
Department of Crop and Soil Sciences, Washington State University, Pullman, WA 99164-6420
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Abstract

The spatial and temporal pattern of wild oat emergence in eastern Washington is affected by the steep, rolling hills that dominate this landscape. The objective of this study was to assess the impact of landscape position and crop residue on the emergence phenology of wild oat. Emergence of a natural wild oat infestation was characterized over two growing seasons (2003 and 2004), at two wheat residue levels (0 and 500 g m−2), and at five landscape positions differing in slope, aspect, and elevation in a no-till winter wheat field. Wild oat emerged 1 to 2 wk earlier at south-facing landscape positions than at north-facing landscape positions. Crop residue delayed wild oat emergence by 7 to 13 d relative to bare soil at south-facing positions in 2003 and had a reduced effect on emergence at north-facing landscape positions. Therefore, preserving surface residues tended to synchronize emergence across the landscape and may facilitate better timing of weed control where residue is present. Emergence of wild oat was modeled as a function of thermal time adjusted by water potential using a Weibull function. Temperature explained more variation in the model than water potential. This model explained much of the variability in wild oat emergence among landscape positions over these 2 yr and may be useful as a tool to predict the timing of wild oat emergence. Results also indicate that site-specific modeling is a plausible approach to improving prediction of weed seedling emergence.

Keywords

Wild oat, Avena fatua L., AVEFAwinter wheat, Triticum aestivum L.Crop residuemicroclimatesite-specific managementsoil moisturesoil temperature

Information

Type
Research Article
Information
Weed Science , Volume 54 , Issue 5 , October 2006 , pp. 838 - 846
Copyright
Copyright © Weed Science Society of America 

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