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Defining the ecological condition of cattle ranching systems using fuzzy set theory

Hernández Daumás, Salvador [autor] | Kamplicher, C [autor/a] | Ochoa Gaona, Susana [autora] | Geissen Geissen, Violette [autora] | Huerta Lwanga, Esperanza [autora] | De Jong, Bernardus Hendricus Jozeph [autor].
Tipo de material: Artículo impreso(a) Artículo impreso(a) Tema(s): Sistemas agrícolas integrados | Metodología | Economía agrícola | Cambio climático | Ganadería | Aspectos ambientalesNota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso En: Aspects of Applied Biology. número 93 (2009), páginas 275-280. --ISSN: 0265-1491Número de sistema: 54798Resumen:
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An index based on easy-to-estimate indicators was developed to assess the ecological condition of south Mexican cattle ranching farms. It focuses on the practices for conserving soil productivity and natural vegetation, as these are considered the most sensitive aspects of the local livestock-based agro-ecosystems. The index is the output of a model combining arithmetic algorithms, sets of rules and fuzzy logic, based on quantitative and qualitative data. This paper describes the model components and discusses how it can be used to readily evaluate the ecological state of individual farms, highlighting its weaknesses but showing how decision making can be supported through the use of field indicators that can be estimated at a glance.
Lista(s) en las que aparece este ítem: Susana Ochoa Gaona
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An index based on easy-to-estimate indicators was developed to assess the ecological condition of south Mexican cattle ranching farms. It focuses on the practices for conserving soil productivity and natural vegetation, as these are considered the most sensitive aspects of the local livestock-based agro-ecosystems. The index is the output of a model combining arithmetic algorithms, sets of rules and fuzzy logic, based on quantitative and qualitative data. This paper describes the model components and discusses how it can be used to readily evaluate the ecological state of individual farms, highlighting its weaknesses but showing how decision making can be supported through the use of field indicators that can be estimated at a glance. eng

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