Discriminability and uncertainty in principal component analysis (PCA) of temporal check-all-that-apply (TCATA) data

John Castura/ August 26, 2021/ Peer-reviewed Paper/ 0 comments

Temporal check-all-that-apply (TCATA) data can be summarized and explored using principal component analysis (PCA). Here we analyze TCATA data on Syrah wines obtained from a trained sensory panel. We evaluate new and existing methods to explore the uncertainty in the PCA scores. To do so, we use the bootstrap procedure to obtain many virtual panels from the real panel’s data.

Temporal ranking for the characterization and better discrimination of protein beverages with different sweeteners

John Castura/ December 9, 2020/ Poster/ 0 comments

This study proposes the application of ranking to temporal product evaluation to differentiate attribute dominances over time. The ability of the proposed method to discriminate sensory differences was compared to temporal check-all-that-apply (TCATA), a discriminating temporal method for capturing the temporal profile of food and beverage products.

Application of TCATA to examine variation in beer perception due to thermal taste status

John Castura/ April 15, 2019/ Peer-reviewed Paper/ 0 comments

Thermal taste status (TTS) describes a phenotype whereby some individuals experience a thermally-induced taste on thermal stimulation of the tongue (thermal tasters; TTs) and some do not (thermal non-tasters; TnTs). TTs experience a range of orosensations elicited by aqueous solutions and some beverages more intensely than TnTs. Whether this extends throughout ingestion duration is unknown, despite the fact that the

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Using contrails and animated sequences to visualize uncertainty in dynamic sensory profiles obtained from temporal check-all-that-apply (TCATA) data

John Castura/ December 23, 2016/ Peer-reviewed Paper/ 0 comments

Approaches for analyzing temporal check-all-that-apply (TCATA) data are further developed and illustrated using data arising from a Syrah wine finish evaluation. Raw and smoothed trajectories are obtained using principal component analysis. Virtual panels are obtained from a partial bootstrap, and the attribute citation proportions are then projected into the solution space to form contrails.