TDS in TimeSens as a Panel Leader Date: 18 - 19 September 2014 Time: 9 am - 5.30 pm Venue: Singapore Polytechnic 500 Dover Road Singapore 139651 Cost: $1,200 (excluding GST) What is TimeSens? TimeSens is a new software dedicated to both sensory data acquisition and analysis. TimeSens features classical sensory data acquisition protocols (profile tests, hedonic tests and TDS). Statistical analysis includes standard and innovative ones. Objective of the Course 1. To gain in-depth knowledge of TDS both on data collection and analysis 2. To organise TimeSens as a panel leader 3. To design, customise, deploy and monitor TimeSens sessions. Those sessions could be: TDS, QDA, hedonic test, PSP and soon (CATA, sorting, napping, difference and similitude testing …) Who should attend this course? • Anyone having a need to collect and/or analyse sensory data, specifically but not exclusively, TDS data • Panel leader wanting to get more out of their TDS or QDA data • No prior statistical knowledge requested Key Speaker: Mr. Pascal Schlich Pascal Schlich is a Director of Research with the INRA (National Institute for Agronomical Research) in Dijon, France. He is currently the head of the ChemoSens platform which gathers the facilities in both sensory and physicochemical analyses of the Center for Taste and Feeding (CSGA) in Dijon. Dr. Schlich is a statistician by trade who specialized in sensometrics. He has 25 years of methodological research on difference testing, panellist performances, descriptive analysis, preference mapping and new sensory data collection techniques such as the Temporal Dominance of Sensations (TDS). Dr Schlich also teaches statistics for sensory analysis at the University of Dijon and in several other universities and high schools in France. He is a well-sought after speaker for conferences related to sensory science and sensometrics. Organised By: PROGRAM DAY 1 1. Introduction to TDS (45 m) • Origin • Principle of data acquisition • Data coding (dominance rate) and basic representation (TDS curves, Duration and Score parameter) 2. Doing a TDS session prepared in advance as panelist (45 m) * • Participants will TDS-profile in TimeSens on their own devices (laptop, tablet or smartphone with large screen) some food samples in order to generate TDS data as panelist themselves 3. Analysis of data collected at step 2 with sufficient introduction to the techniques used (90 m)* • Band-plots (at individual and group levels) • Indicators of individual behaviors (latency, duration, number of citations) • TDS curves and TDS curves of differences between two products or two groups of products • CVA or PCA of duration parameter • PCA of product trajectories • Correspondence analyses of numbers of citations by product/attribute and subject/attribute Lunch Break4. Philosophy and structure of TimeSens (15 m) • TimeSens architecture • TimeSens server • TimeSens for Panelist • TimeSens for Panel Leader 5. In-depth description of the “TimeSens as a Panel Leader” components (90 m) • Protocol: choosing panelists, products, descriptors and experimental designs • Scenario: building the sequence of screens seen by the panelist • Deployment: making the session available through the internet • Monitoring: the panelist responses • Data: checking, filtering and sorting the collected data • Analysis: ordering graphics and statistical analysis of the data to the TimeSens server • Output: receiving outputs (tables and graphics) from the TimeSens server 6. In depth description of the chocolate TimeSens session (30 m) • This step will be conducted in parallel to step 5 component by component 7. Practical 1: designing your own TDS session (45 m) • Each participant designs his/her own TDS session with the help of the trainer 8. Summing up of the first day (30 m) • Additional questions on practical 1 • General discussion End of Day 1 Session DAY 2 9. Advanced topic in TDS (1H30) • Panel performances : Pineau et al (2014) method, CRI and current research • Multi-bite TDS • Temporal Drivers of Liking (TDL) : mixing liking scales with TDS 10. Advanced functions and uses of TimeSens (1H30) • Blocks and individualized experimental designs • Advanced scenarios using the conditional visibility feature • Describing the full list of control types • Using timers, chronometers and feed-back to panelists • Using the local mode for collecting data when no internet available 11. Understanding the structure of some TDL sessions (30 m) • Alternated Temporal Drivers of Liking (A-TDL) • Simultaneous Temporal Drivers of Liking (S-TDL) Lunch Break 12. Practical 2: designing an advanced session featuring several tasks (1H30) • This could eventually be done in groups of participants (for instance by company) on specific needs they may have 13. Panorama of the specific statistical analysis available in TimeSens for QDA data (1H00)** • This could eventually be done in groups of participants 14. Summing-up & discussion (30 m) 15. Evaluation (15 m) * Could be conducted on existing data if participants already did it in a previous workshop ** Optional. Upon interest of participants and depending on time left Registration: Please email your name, company, designation, and contact number to [email protected].
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