Prediction of agrochemical residue data on fruit using an informatic system (PARDIS model).
A 'step-by-step' method was used to develop a simplified procedure for calculating pesticide residue levels on fruit at harvest by considering the application of the compound and the relevant routes of loss. The model is applicable to cases where the most important exposure route is by direct spray to the canopy of the crop and where uptake into the plant by the roots can be disregarded. The exposure dose is calculated by considering the proportion of total crop cover represented by the fruits. The loss processes considered are photodegradation, uptake, volatilization and washoff. The outputs of the model were compared with measured residues of pesticides on pear. Analysis of the model fit demonstrates that the model predicted the measured data with a good level of accuracy for four of seven investigated pesticides. The predicted/observed quotients are close to 1, as is the modelling efficiency, and there are no great differences between the predicted and observed values. Taking into account the extreme simplicity of the model and the complexity of the environmental processes considered, these results encourage further research into the modelling of residue behaviour in food commodities. The objectives of this work were to produce a tool to predict pesticide residues in products of plant origin, to complement monitoring of pesticide levels and to be useful in evaluating the effect of government policies on food safety. All predicted values were below the maximum levels fixed for pesticide residues in pear, as amended in Council Directives 86/362/EEC and 90/642/EEC.
Calliera
Maura
M
Università Cattolica del Sacro Cuore, Institute of Environmental and Agricultural Chemistry, Plant Chemistry Section, Via Emilia Parmense 84, 29100 Piacenza, Italy.
Balderacchi
Matteo
M
Capri
Ettore
E
Trevisan
Marco
M
D004784:Environmental Monitoring / Q000379:methods*; D005638:Fruit / Q000737:chemistry* / Q000378:metabolism; D008954:Models, Biological; D008962:Models, Theoretical; D010573:Pesticide Residues / Q000378:metabolism*; D011237:Predictive Value of Tests; D031989:Pyrus / Q000737:chemistry* / Q000378:metabolism; D014835:Volatilization
D010573:Pesticide Residues