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A Single-Time Survey Method to Predict the Daily Weed Density for Weed Control Decision-Making

Published online by Cambridge University Press:  20 January 2017

Roberta Masin ,
Vasileios P. Vasileiadis ,
Donato Loddo ,
Stefan Otto  and
Giuseppe Zanin
Roberta Masin*
Affiliation:
Department of Environmental Agronomy and Crop Science, Padova University, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Vasileios P. Vasileiadis
Affiliation:
National Research Council (CNR) Institute of Agro-Environmental and Forest Biology, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Donato Loddo
Affiliation:
Department of Environmental Agronomy and Crop Science, Padova University, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Stefan Otto
Affiliation:
National Research Council (CNR) Institute of Agro-Environmental and Forest Biology, Viale dell'Università 16, 35020 Legnaro (PD), Italy
Giuseppe Zanin
Affiliation:
Department of Environmental Agronomy and Crop Science, Padova University, Viale dell'Università 16, 35020 Legnaro (PD), Italy
*
Corresponding author's E-mail: roberta.masin@unipd.it
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Abstract

Decision-making processes must indicate if, how, and when weed control should be practiced. So far, Decision Support Systems (DSSs) for weed control to prevent crop yield losses can guide decisions on “if” and “how.” Experience shows that farmers need a DSS that can also guide when to treat, but this can only be done if the actual weed density observed in the field is known during the crop cycle. Emergence models allow the prediction of daily density, but precision depends on the survey date. This study focuses on the estimation of the date of the survey for the best prediction of the daily density throughout the crop cycle. The predicted daily density of each species can be used by DSSs without any further survey, saving time and money and improving the use of the DSSs. Results showed that the best date is when the actual density of each weed reaches or exceeds 50% emergence, and this is earlier than the critical point date, supporting the validity of the date estimation method. The possibility to provide specific advice for farmers considering a proper mortality rate of weed seedlings is then discussed. The ability to optimize the date of sampling can improve the reliability of decision-making tools for integrated weed management, in agreement with the European Union goal of sustainable use of pesticides and more environmentally sustainable cropping systems through the use of integrated pest management.

Keywords

Weed densityweed samplingDecision Support Systemsemergence predictionhydrothermal time
Type
Weed Management
Information
Weed Science , Volume 59 , Issue 2 , June 2011 , pp. 270 - 275
Copyright
Copyright © Weed Science Society of America 

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