Analysis of cefalexin with NIR spectrometry coupled to artificial neural networks with modified genetic algorithm for wavelength selection

In this paper, a novel chemometric method was developed for rapid, accurate, and quantitative analysis of cefalexin. The experiment was carried out by using the near-infrared spectrometry coupled to multivariate calibration (partial least squares and artificial neural nets). The wavelength selection through a modified genetic algorithm with fixed number of select variables would enhance the predictive ability when applying artificial neural networks model.