| Summary: | Summary: The identification of the estimated dose of human exposure to a pesticide is a fundamental aspect of the use of such compound, since this data is the most important and any protection measure established in order to reduce the health risk of an individual or an exposed population will depend on it. In developed countries and in some agroindustrial farms in Latin America, there are some tools for the evaluation of such exposure, but their implementation in small plots in developing countries is problematic due to production costs.
The author has performed a meta-analysis of human exposure results according to theoretical models of contaminant use, and has selected and evaluated each of the most appropriate models for assessing pesticide exposure in agricultural systems in developing countries.
It has classified eight models (i.e. COSHH, DERM, DREAM, EASE, PHED, RISKOFDERM, STOFFENMANAGER and PFAM) according to multiple analysis criteria and as a result of this evaluation, the theoretical and experimental application of five models (i.e. DERM, DREAM, PHED, RISKOFDERM and PFAM) in agricultural systems of potato, flower and long onion crops in Boyacá, Colombia. The results show that the models provide different estimates of human exposure, which are not completely comparable.
However, due to the simplicity of the algorithm and the specificity of the parameters, the DERM, DREAM and PFAM models have been found to be the most appropriate for application in case studies in developing countries.
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