A Novel Model for Measuring the Amount of Four Pesticides with Rapid Safety Classification
Main Article Content
Abstract
According to the Food and Agriculture Organization of the United Nations (FAO) reports that approximately 4.5 million tons of pesticides are used worldwide per year, and estimates that pesticide poisoning causes approximately up to 40,000 deaths per year. The author team therefore has a concept to find a novel parametric model for determining the amount of pesticide residues on either vegetables and fruits. This proposed exponential plus constant model will be applied for the portable spectrometer developed by Natthasak and Suchart. The proposed model can accurately predict the maximum spectral power density (MSPD) in [µW/cm²)] of the spectrum signal from the reflected light of the incident light on four test pesticides: carbendazim, cypermethrin, diazinon, and imidacloprid for each of ten different concentrations from 1 [mg/L] to 10 [mg/L]. The proposed model performance indicators provide the best MSPD estimation with the maximum R² value and the minimum RMSE value when compared to that obtained from the quadratic and line models. Moreover, the developed model has perfectly identified classification accuracy of the four test pesticides at the ten different concentrations accuracy with the Accuracy of 1.000 and the HMRS of 1.000, where both the Accuracy and HMRS values are higher than those obtained from the quadratic and line models.
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