Quality control during spirits production and means of authenticating or verifying sources of spirits in the sub-Saharan region of Africa are limited due to lack of resources and the scientific acumen required to develop methodologies for characterizing spirits. However, the increasing needs to protect consumers from negligence, or willful contamination of spirits in this region underscores the urgency with which growth in this area must happen. In this paper, we describe a multivariate statistical framework upon which characterization, identification and authentication of spirits could be developed. The framework exploits the unique chemical fingerprints of spirits with the goal of accomplishing three functions simultaneously: the detection of class differences, the authentication of spirits and the verification of sources. In a test case using the metal contents of 17 Ugandan spirits, this framework shows (i) that a class of unrecorded spirits known locally as Lira-Lira can be singled out from other spirits by their Cu contents, (ii) that localities from where the Lira-Lira spirits were purchased can be resolved to within 8 km by cluster analysis and principal component analysis, (iii) that cluster analysis loadings and scores, placed side-by-side, can pair spirits and their unique discriminating contaminants directly, (iv) that the most important metals for authenticating 13 spirits, source verification and production methods are Al, Sr, Ba, Mn, Zn and Cu (high concentration variability across samples is the qualifying factor), (v) that common sources of contamination can be detected by Pearson correlation analysis (this study finds that Sn/Cd, Pb/Cr, Tl/Cr, Pb/Ni or Cu/Ag as well as the triad Se/As/Ni in the 13 Ugandan spirits are from similar sources), and (vi) that inconsistency in spirits production can be detected with empirical data. Such rudimentary solutions to characterizing spirits have never been offered to the sub-Saharan countries.

Information about food hygiene and quality in the sub-Saharan African countries remains scarce at a time when many of their citizenry are beginning to acquire the much coveted middle income status. Confounding this are challenges linked to monitoring on a continuous basis the safety of food produced by such lucrative industries as the beef industry. The objective of the current study was to initiate a process of encouraging changes in the status quo, by showing how a first step in that direction might look like. Using heavy metal contents of representative beef samples from butcheries in Soroti, Uganda, typical of a sub-Saharan country, we demonstrate how relationships and common sources of metals in food could be identified in a multivariate space. Beef samples from 40 sites were analyzed by atomic absorption spectrometry for iron (Fe), zinc (Zn), nickel (Ni), chromium (Cr), lead (Pb), copper (Cu), cobalt (Co) and cadmium (Cd). The study showed that all beef samples contained these metals, the extent of which were in the order: Fe > Zn >> Ni, Cr > Pb > Cu, Co > Cd. By correlation analysis, the pairs Ni and Cr, Cd and Co, Ni and Fe or Cr and Fe were found to be most likely coming from similar sources. At least three distinct characteristics of beef consumed in Soroti were also found, a distinction perhaps arising from three major categories of feedlots used to raise donor cattle. The incremental risk of children or adults developing cancer over a lifetime was estimated and found to fall into three categories, two of which are separately explained by the presence of Cr or Ni. The sources of these metals remain a matter of speculation on our part. More studies are needed to determine these sources and to understand the nature of cancer risk in the three categories of beef identified here.