Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants
Dyah Kurniawati Agustika, Ixora Sartika Mercuriani, Chandra Wahyu Purnomo, Sedyo Hartono, Kuwat Trıyana, Doina Daciana Iliescu, Mark S. Leeson
Abstract
) then the discrete wavelet transform (DWT) was used for dimension reduction. The pre-processed data were then used as an input for classification using a multilayer perceptron neural network, a support vector machine, and linear discriminant analysis. The pre-processing method with the highest classification model accuracy was selected for the further use in the processing. It was seen that only the SG 1st derivative method applied to both wavenumber ranges could produce 100% accuracy. This result was supported by principal component analysis clustering. Thus, we have demonstrated that by using the right pre-processing technique, classification success can be increased, and the process simplified by optimization and minimization of the technique used.