Team:UC Davis/Signal Oil

With a working model, it was time for the real test: olive oil.

Nine samples of Extra Virgin Olive Oil were obtained and prepared for assay where three of the samples were rancid and six of the samples were fresh. The velocities were recorded with each enzyme for a total of 27 data points. We used the best catalytic matrix from our previous model and again inverted the matrix and multiplied by the observed velocity. The results are below:

We noticed two outliers based on the unsaturated aldehyde prediction, but the picture wasn't clear yet. We plotted the data in three dimensions to mimic an approach taken by geneticists to better visualize patterns in predictive models.

Color and size above indicate the total aldehyde concentration measured. By plotting the predicted concentrations in three dimensions, we saw two obvious outliers. We deemed these two samples rancid based on their demarcation from the rest of the group, but also the high levels of both unsaturated and medium saturated aldehydes...

We got them both right!. The remaining rancid oil was sample number 9, which had the third largest predicted unsaturated aldehyde concentration. In three dimensions, however, there seemed to be no obvious reason to consider this sample rancid. That being said, we got two of the three correct, and we believe this model can only get better. By adding more enzymes to our system, and recording the velocity in combinatorial fashion, anyone can create a multiplexed biosensor capable of determining distinct concentrations in complex mixtures.