Quantification and prediction of the concentration of different dilutions of Lambda Cyhalothrin through colorimetry and neural networks

The Lambda Cyhalothrin is an insecticide of broad spectrum used in agriculture, to reduce the loss in crops, due to the attack of some pests. This compound has the presence of the radicals chlorine, fluorine and cyano, which can cause serious effects on human health when are ingested. Because of this, exist the need of develop non - destructive methods, capable of determining the concentration of the pesticide in farming, for eradicate the presence of this substance on the fruit used as food. To achieve this, commercial Lambda Cyhalothrin and distilled water were used, to obtain the recommended dilutions for the treatment of various pests in agriculture. The samples were analyzed through colorimetry, obtaining the characteristic color spaces for the pesticide, with a correlation of 0.92 for the parameters "a" and "b", and 0.98 for the parameter "L". The Cab chroma and Hue angle were determined in 9.72 and 275° respectively for the pure compound. in the dilution, the value of Hue angle decreases until 220°. Through neural networks in Matlab, the relationship between the reflection spectrum of the dilutions with the concentration thereof was established. Estimating a prediction in the accuracy higher than 0.98 in the coefficient of determination