Predicting pesticide residues to reduce crop contamination.
The system of dynamics between pesticides and plants is reviewed, and a conceptual model capable of reflecting the necessary qualitative and structural peculiarities is proposed as a means of predicting residue levels. The degradation processes of various chemical classes of pesticides in plants under different conditions of use are analyzed. Formulas are developed that enable recognition and estimation of residue levels and duration of retention for "new" pesticides and "old" substances under varying treatment conditions. Estimated data are verified to provide positive assessments of the accuracy of the predictions. Mathematical modeling as a means of perception is stressed. With this method, the outlet value can be controlled by changing such inlet parameters as application rate, frequency of treatments, types of plants, and so on. Residue levels are predicted for different combinations of use conditions in various climatic-geographical regions. The method of estimation also enables the development of important standards such as post-treatment waiting intervals. A more flexible technique can be employed, in which specific periods are established for different plants under various treatment conditions. Thus, both unjustified shortened waiting intervals or unnecessarily elongated intervals periods can be avoided. The greatest value of the modeling approach is that information can be obtained on the degree of potential food contamination and major standards can be developed without the need for extensive experimental use of pesticides under actual conditions. This technique fully considers optimal use conditions for agrochemicals in terms of human requirements and protection of plants. Mathematical modeling protects the environment while enabling the speedy selection of safe parameters for pesticide use conditions nd realization of significant savings in manpower and time. Overall, this estimation method appears to be an efficient link in the broad system of preventing environmental pesticide contamination and protecting human health.
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Spynu
D006801:Humans; D008962:Models, Theoretical; D010573:Pesticide Residues / Q000009:adverse effects / Q000032:analysis; D010945:Plants, Edible / Q000032:analysis
D010573:Pesticide Residues