IFEVA   02662
INSTITUTO DE INVESTIGACIONES FISIOLOGICAS Y ECOLOGICAS VINCULADAS A LA AGRICULTURA
Unidad Ejecutora - UE
artículos
Título:
Fuzzy knowledge-based model for soil condition assessment in Argentinean cropping systems
Autor/es:
FERRARO, DIEGO OMAR
Revista:
Environmental Modelling and Software
Referencias:
Año: 2009 vol. 24 p. 359 - 370
ISSN:
1364-8152
Resumen:
A knowledge-based system (KBS) was designed for assessing soil condition in agroecosystems. KBS was built through expert opinion elicitation and available scientific data using fuzzy logic. The system was structured into three main elements: 1) input variables that represent the physical domain of soil condition assessment and are related to environmental and crop management conditions; 2) primary modules that describe the fuzzy nature of the soil indicators and; 3) secondary modules that represent the elicited knowledge on soil condition assessment from an expert panel. Higher indicator values reflect better soil condition assessment. KBS application on data from crop fields from Inland Pampa (Argentina) indicated that soil nitrogen depletion poses a hazard for soil health as no crop was able to accomplish more than 50% of the sustainability criteria elicited for soil nitrogen extraction from the system. Conversely, soil carbon and physical conditions exhibited values closer to the desirable scenarios elicited by the fuzzy if-then rules, with values of 0.84, 0.71 and 0.74 for maize, soybean and wheat, respectively. No significant differences were observed in the overall soil degradation module between crops, with values of 0.64 for maize and wheat and 0.67 for soybean. The KBS developed in this work provided an alternative modeling tool for assessing agroecosystem condition when knowledge regarding long-term assessment is imprecise and uncertain.