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Evaluation of environmental impact indicators using fuzzy logic to assess the mixed cropping systems of the Inland Pampa, Argentina
Ferraro, D.O.; Ghersa, C.M.; Sznaider, G.A. (2003). Evaluation of environmental impact indicators using fuzzy logic to assess the mixed cropping systems of the Inland Pampa, Argentina. Agric. Ecosyst. Environ. 96(1-3): 1-18. https://dx.doi.org/10.1016/s0167-8809(03)00017-3
In: Agriculture, Ecosystems and Environment. Elsevier Science: Amsterdam. ISSN 0167-8809; e-ISSN 1873-2305
Peer reviewed article  

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Author keywords
    Pesticides; Tillage; Sustainability; Fuzzy logic; Argentina; Inland Pampa

Auteurs  Top 
  • Ferraro, D.O.
  • Ghersa, C.M.
  • Sznaider, G.A.

Abstract
    Sustainable agriculture requires an adequate analysis framework. Fuzzy logic-based and field scale indicators were developed to evaluate the effects of pesticides and tillage on agroecosystems. All the assumptions and rules for making inferences reflect the current knowledge and the expert perception and judgment about the potential environmental impact of pesticides and tillage. The proposed indicators require four input variables: (1) number and type of applied pesticides, (2) rate of applied pesticides, (3) number and type of tillage tools, and (4) land capability class of each field. In regards to pesticide impact, the indicators consider the toxicity effects on: (1) mammals and (2) insects, while the tillage impact is evaluated taking into account the effects of different tillage operations on: (1) the retention of crop stubble on the soil surface, and (2) the stability of soil aggregates. Two overall outputs were obtained: (1) pesticide index and (2) tillage index. The developed indicators were used to compare the potential environmental effect of current practices carried out in Inland Pampa (Argentina). Concerning pesticide use, cropping winter wheat did less harm to the agroecosystem than cropping maize and sunflower. The overall values of tillage index were similar within crops. However, large differences in pesticide and tillage effects were found among tillage systems. Soybean showed the highest variability in both indexes. The type of analysis carried out in this study using farm-level variables may help find more sustainable ways to manage agricultural inputs.

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