Assessing the risk of pesticide environmental impact in several Argentinian cropping systems with a fuzzy expert indicator

BACKGROUND: The introduction of transgenic soybean (Glycine max, L.) varieties resistant to glyphosate (GR soybeans) has rapidly expanded in Argentina, increasing pesticide use where only grasslands were previously cultivated. The authors compared an estimate of environmental risk for different crops and active ingredients using the IPEST index, which is based on a fuzzy-logic expert system. For IPEST calculations, four modules are defined, one reflecting the rate of application, the other three reflecting the risk for groundwater, surface water and air. The input variables are pesticide properties, site-specific conditions and characteristics of the pesticide application. The expert system calculates the value of modules according to the degree of membership of the input variables to the fuzzy subsets F (favourable) and U (unfavourable), and they can be aggregated following sets of decision rules. IPEST integrated values of >= 7 reflect low environmental risk, and values of <7 reflect high risk. RESULTS: Alfalfa, soybean and wheat showed IPEST values over 7 (low risk), while maize had the lowest IPEST values (high risk). Comparing active ingredients applied in annual and perennial crops, atrazine and acetochlor gave the highest risks of environmental contamination, and they are mainly used in maize. Groundwater was the most affected compartment. CONCLUSIONS: Fuzzy logic provided an easy tool combining different environmental components with pesticide properties to give a simple and accessible risk assessment. These findings provide information about active ingredients that should be replaced in order to protect water and air from pesticide contamination. (C) 2010 Society of Chemical Industry