Introduction au plan d'expériences en analyse sensorielle

15 Feb 2013 · 29 min
28:49

The lecture introduces experimental planning for sensory analysis, emphasizing the need for designs that isolate product effects from other sources of variation. It begins by critiquing a naïve monadic sequential plan, highlighting confounding between judge, product, presentation rank, session, and succession effects. The speaker then distinguishes complete designs (all judges evaluate all products) from incomplete designs, focusing on Balanced Incomplete Block Designs (BIB) and their properties (equal replication of products and product pairs). Next, the talk covers Latin square designs for managing rank effects, followed by hybrid Yuden/Gudon squares that combine BIB balance with Latin square structure. The Williams square is presented as the most widely used design, achieving orthogonality among product, rank, and succession effects under specific judge‑product count conditions. When standard designs are infeasible, the lecture explains optimal designs built via exchange algorithms that minimize the variance of product effect estimates, using D‑ and A‑optimality criteria. Finally, practical implementation is demonstrated with the Sensominer R package, showcasing the plan.williams and plan.optimal functions for constructing Williams and optimal designs respectively.

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