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A New Approach To Determine When to Control Weeds

Published online by Cambridge University Press:  12 June 2017

Antonio Berti ,
Claudio Dunan ,
Maurizio Sattin ,
Giuseppe Zanin  and
Philip Westra
Antonio Berti
Affiliation:
Centro di Studio sulla Biologia ed il Controllo delle Piante Infestanti-C.N.R., AGRIPOLIS, 35020 Legmare (Padova), Italy
Claudio Dunan
Affiliation:
Dep. Plant Pathology and Weed Science, Colorado State University, Fort Collins, CO 80523
Maurizio Sattin
Affiliation:
Centro di Studio sulla Biologia ed il Controllo delle Piante Infestanti-C.N.R., AGRIPOLIS, 35020 Legmare (Padova), Italy
Giuseppe Zanin
Affiliation:
Univ. Padova, AGRIPOLIS, 35020 Legmare (Padova), Italy
Philip Westra
Affiliation:
Dep. Plant Pathology and Weed Science, Colorado State University, Fort Collins, CO 80523
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Abstract

A methodological approach to determine the optimum time to control weeds that integrates aspects of weed biology, weed-crop competition, and economics is presented. The approach is based on the concept of Time Density Equivalent: this is defined as the density of weed plants that germinate with the crop and compete until harvest that causes the same yield loss caused by a group of weeds with a given density, time of emergence, and time of removal. A model was developed that accounts for pattern of weed emergence and permits determination of timing of weed control that minimizes economic loss due to weeds emerging both before and after treatments. The outcomes of the model are presented with two examples: corn in competition with velvetleaf and soybean in competition with Amaranthus cruentus. For both crops, six different weed control strategies involving preemergence, chemical, and mechanical postemergence treatments are considered. The results obtained with the model are compared with the calculation of net margin based on assumptions of simultaneous emergence of crop and weeds and no effect of different times of control. Different control strategies are compared considering not only maximum net margin but also its dependence on time of control, because a strategy with a lower value of maximum net margin, but a flatter net margin curve, allows more flexibility of time of control.

Keywords

Dicamba, 3,6,dichloro-2-methoxybenzoic acidfomesafen, 5-[2-chloro-4-(trifluoromethyl)phenoxy]-N-(methylsulfonyl)-2-nitrobenzamidelinuron, N′-(3,4-dichlorophenyl)-N-methoxy-N-methylureaterbuthylazine, 6-chloro-N-(1,1-dimethylethyl)-N′-ethyl-1,3,5-triazine-2,4-diamineAmaranthus cruentus L. ♯ AMACRvelvetleaf, Abutilon theophrasti Mcdicus, ABUTHcorn, Zea mays L.'Dekalb XL72A'soybean, Glycine max(L.) Merrill ‘Hodgson.’Modelscompetitioneconomic critical periodtime density equivalentweed emergence
Type
Weed Biology and Ecology
Information
Weed Science , Volume 44 , Issue 3 , September 1996 , pp. 496 - 503
Copyright
Copyright © 1996 by the Weed Science Society of America 

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References

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