Dataset for: Resolving NMR signals of short chain fatty acid mixtures using Unsupervised Component Analysis

Nuclear Magnetic Resonance (NMR) is a very powerful instrumental technique suited to identify and characterize organic compounds. NMR has been successfully used in the analysis of complex biological and environmental samples, however these applications are still rather limited. In this work we describe Unsupervised Component Analysis (UCA) as a multivariate unsupervised method suited to identify the number of relevant NMR signal contributions and to deconvolute mixed signals into signal individual sources and respective contributions. Using this approach we were able to advance further in the field of quantification of NMR spectra and this methodology will help in the characterization of complex biological samples.