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.

Consumer hedonic studies with incomplete block designs

John Castura/ August 25, 2021/ Workshop/ 0 comments

Castura, J.C. (2021). Consumer hedonic studies with incomplete block designs. In: Workshop: A journey of consumer segmentation. History and a discussion of current “preference” segmentation approaches based on incomplete and complete test designs (Zach, J., Rothman, L., Carr, B.T., Thomas, H., Castura, J.C.). 14th Pangborn Sensory Science Symposium, 9-12 August. Online. (Workshop Oral). DOWNLOAD

Temporal Rate-All-That-Apply (TRATA): A novel temporal method for sensory evaluation

John Castura/ August 8, 2021/ Poster/ 0 comments

This study introduces temporal rate-all-that-apply (TRATA) as a new temporal sensory method. It was inspired by rate-all-that-apply (RATA) and temporal check-all-that-apply (TCATA), but is most similar to multiple-attribute time intensity (MATI) in that the TRATA method allows for simultaneous rating of attribute intensities over time. Only attributes that are perceived are scaled. In this case study, the TRATA method was

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