Raman imaging spectroscopy is a relatively new technique that has raised interest in several areas of knowledge due to the possibility of evaluating the spatial distribution of compounds based on their spectra. This paper presents a brief history of the development of this important technique, a theoretical description of the Raman effect and the preprocessing and processing (both univariate and multivariate) tools for Raman data. We also describe the current state of applications for major areas such as agriculture/biomass, environment, biology, medicine, pharmaceutical, geology, foodstuff, artwork, archaeology, material characterization and forensic.

Design of experiments (DOE) applied to mass spectrometry (MS), mainly focusing on the optimization of ionization techniques, has been applied to optimize experiments in order to provide the highest amount of information with the lowest number of experiments. However, DOE has not been used in petroleomics. For the first time, we applied DOE to optimize the main parameters associated with the crude oil analysis in a petroleomics approach. For the ionization technique, atmospheric pressure photoionization (APPI) has been selected and data were acquired in a high resolution (400,000 at m/z 400) and high mass accuracy (< 1 ppm) Fourier transform ion cyclotron resonance (FT-ICR) MS. Full and fractional two-level factorial designs were applied for the APPI(±) FT-ICR MS data set from two different crude oil samples with distinct physical and chemical characteristics. The standard ionization parameters that affect the MS responses of the crude oil analysis were optimized for both APPI(+)-MS and APPI(–)-MS. Such ionization parameters were then successfully applied to a crude oil and its saturated, aromatics, resin and asphaltene fractions, all with superior features of merit. Thus, the optimized APPI(±)-MS parameters should serve as reference and can be used as a guide for new studies in petroleomics.