Home » Home & Education » Science » Quali-Sense 1.0
( Free Trial | 4.75 MB )
Quali-Sense 1.0
Software package to Qualify your sensory data
- Developer:
- CAMO Software
- License:
- Demo
- OS:
- Windows 98 / ME / 2000 / XP / 2003
- Date added:
- 3/11/2008
- Last Update:
- 12/18/2007
- User Rating:
- Not yet rated.
- Your Rating:
( Free Trial | 4.75 MB ) Quali-Sense 1.0 Publisher's description
A sensory panel is the most effective, most natural tool to describe the complex properties of food that trigger our five senses when consuming a product.
Quali-Sense is the best companion a panel leader can hope for. Using a set of statistical tests, Quali-Sense detects the personal strengths and weaknesses of each assessor in your panel. Discover the panelists'' sensitivity, reproducibility or cross-over issues for each attribute; check the global panel agreement. And use this information to further train and qualify your panel, such that you can keep on developing unique products.
Features:
1) 5 panelist performance tests
2) Plots for direct data and result visualization
3) Color-coded result tables for easy interpretation
4) Auto Generated Summary Report
Benefits:
1) Detect panelists who are not replicating their assessments accurately.
2) Locate panelists who misunderstood the scale.
3) Evaluate the sensitivity performance of each panelist and needs for retraining.
4) Select reliable panelists and attributes.
Quali-Sense is the best companion a panel leader can hope for. Using a set of statistical tests, Quali-Sense detects the personal strengths and weaknesses of each assessor in your panel. Discover the panelists'' sensitivity, reproducibility or cross-over issues for each attribute; check the global panel agreement. And use this information to further train and qualify your panel, such that you can keep on developing unique products.
Features:
1) 5 panelist performance tests
2) Plots for direct data and result visualization
3) Color-coded result tables for easy interpretation
4) Auto Generated Summary Report
Benefits:
1) Detect panelists who are not replicating their assessments accurately.
2) Locate panelists who misunderstood the scale.
3) Evaluate the sensitivity performance of each panelist and needs for retraining.
4) Select reliable panelists and attributes.
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