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A Comparison of Reduced Rate and Economic Threshold Approaches to Weed Management in a Corn–Soybean Rotation

Published online by Cambridge University Press:  20 January 2017

Peter Sikkema
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Laura L. Van Eerd
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Richard J. Vyn
Affiliation:
University of Guelph Ridgetown Campus, Ridgetown, ON, N0P 2C0, Canada
Susan Weaver*
Affiliation:
Agriculture and Agri-Food Canada, Greenhouse and Processing Crops Research Centre, Harrow, ON, N0R 1G0, Canada
*
Corresponding author's E-mail: [email protected]

Abstract

A field study was conducted at two sites in southwestern Ontario, Canada, from 2002 to 2005 to assess the cumulative effects of different weed management strategies applied to the same plots over time in a corn–soybean rotation. These strategies included a POST broad-spectrum herbicide applied at recommended or reduced rates and use of a computer decision aid to select the POST herbicide having the greatest net return (economic threshold approach) based on weed populations before treatment or seed-bank estimates. Four years after study initiation, increased weed populations were observed only in the nontreated control. The reduced rate and economic threshold approaches did not lead to increased weed seed banks compared with the recommended rate of a broad-spectrum herbicide. Reductions in herbicide rate were more effective than the use of economic thresholds for reducing the risk of environmental impact in corn and soybeans. Weed populations in this study were generally above threshold levels, and herbicides selected by the computer decision aid tended to be older, less-expensive herbicides with high use rates. Recommendations by the computer decision aid were generally more effective and more profitable when based on weed populations before treatment than when based on seed-bank estimates.

Type
Research
Copyright
Copyright © Weed Science Society of America 

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