Functionally-enhanced derivative spectroscopy (FEDS): a powerful tool to increase of spectral resolution in the mid-infrared advanced analysis of complex samples–a mini review

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

Quantification of Lactobacillus reuteri ProTectis in MRS Broth Using Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) Spectroscopy and Chemometrics

“…45 SG and derivative transformations removes background noise, enhances peak amplitude, and peak separation and identification. 38,46,47 We generated a PLS model using the PCs of the SG1 signal PCA as predictor variables and log-transformed VPC data as the response variable (i.e., PCA−PLS). This model yielded a low RMSECV in the training set, and a low RMSEP value in the testing set (Table 2, Figure 6a).…”

“…SG1 and first derivative transformations of FTIR spectra have been reported to yield superior results in chemometric analysis . SG and derivative transformations removes background noise, enhances peak amplitude, and peak separation and identification. ,, …”