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Environmental Risk Indicators for Weed Management: A Case Study of Ecotoxicity Assessment Using Fuzzy Logic

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Decision Support Systems for Weed Management

Abstract

Herbicide use is a key element in the current intensification of agricultural production systems that usually leads to increases in crop yield. However, development of theoretical frameworks and tools is necessary to allow for environmental assessment of herbicides. In this chapter, we present a series of elements that should be considered for designing these types of tools. In addition, we describe the structure of RIPEST, a simple model based on fuzzy logic that evaluates the ecotoxicological hazard of pesticides (herbicides, fungicides and insecticides). RIPEST was run using a time series of pesticide use and actual soybean yields from Argentina. Results from this cropping system assessment allows for discussion of the ecotoxicological risk of herbicide use, in particular, and pesticides, in general.

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Authors and Affiliations

  1. Facultad de Agronomía, Cátedra de Cerealicultura, Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA), UBA-CONICET, Universidad de Buenos Aires (UBA), Buenos Aires, Argentina

    Diego O. Ferraro, Alejandra C. Duarte Vera, Sebastián Pessah & Felipe Ghersa

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  1. Diego O. Ferraro
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  2. Alejandra C. Duarte Vera
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  3. Sebastián Pessah
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  4. Felipe Ghersa
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Corresponding author

Correspondence to Diego O. Ferraro .

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Editors and Affiliations

  1. Departamento de Agronomía, Universidad Nacional del Sur - CERZOS/CONICET, Bahía Blanca, Buenos Aires, Argentina

    Guillermo R. Chantre

  2. Department of Crop Protection, Institute for Sustainable Agriculture, Córdoba, Córdoba, Spain

    José L. González-Andújar

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Ferraro, D.O., Duarte Vera, A.C., Pessah, S., Ghersa, F. (2020). Environmental Risk Indicators for Weed Management: A Case Study of Ecotoxicity Assessment Using Fuzzy Logic. In: Chantre, G., González-Andújar, J. (eds) Decision Support Systems for Weed Management. Springer, Cham. https://doi.org/10.1007/978-3-030-44402-0_9

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