Abstract

Functionally-Enhanced Derivative Spectroscopy (FEDS) is a simple, fast and easy to use deconvolution  method  based  on  the  combination  of  derivative  spectroscopy  and  simple  functional  algorithms.  As  analytical  technique  has  demonstrated  to  be  a  powerful  tool  for analysis of spectral signals of mid-infrared spectra. In specific, FEDS produces the separation  of  overlapped  signals  through  a  transformation  of  the  spectrum  that  consists  of making the signals more acute and intense depending on the signal to noise ratio. The purpose of this review is to provide a theoretical and applied overview of ability of FEDS for the improving spectral analysis of complex samples with importance in materials, food and  biomedical  engineering,  environmental  sciences,  microbiology,  biotechnology  and  biological, chemical and physical science, among others.

Keywords

derivative spectroscopy, functional transformation, mid-infrared spectrum, deconvolution, signal overlap