Measuring the profile of trace metals in food is one approach to discriminating its geographic origin. Analytical tools for trace-metal measurement tend to be laboratory-based with expensive capital equipment.
There has been recent research to develop point-of-use sensors for metal ions using specific chemical binders (often based on the chemistry of human olefaction) with fluorescent markers. This paper (purchase requires) takes the work a significant step forward. Their sensor is based upon the principle that different metal ions induce different degrees of aggregation in perylene diimide derivative based supramolecular nanoaggregates. This enabled the construction of a multi-analyte sensor which they report as having ease of preparation, rapid response, and high sensitivity originating from large specific surface areas. The authors report that they used the sensor to build a successful classification model of geographic origin for both drinking water and apples.