I’m doing a custom DOE and would appreciate any tips or pointers on creating optimal recipes.
Is there a better DOE approach than the one constructed, or other factors to bear in mind?
Responses:
- Maximise different nutritional values
- Minimise quantity of salt
- Reach target of taste and smell score
Factors:
- Categorical –> Texture 2 levels : T1 / T2
- Categorical --> Aroma 3 levels: A1/ A3/ A3
- Mixture
- Ingredients to vary: C1 / C2 / C3 / C34
- Ingredients that are constant (flavoured liquid). I have noted it two different values, even though it will be constant in the model, as JMP only accepts two different values
- Water – this factor will be included when the sum of the constant ingredients and those to be varied equal less than 100 gr.
- Blocking: Difference between days of panel testing (6 recipes to be tested / day)
Defining linear constraints:
- Two lines are added which maintains proportions between the constant ingredients (liquid = 69.6%) and the variable ingredients (C1 /C2 /C3 / C4 =30.4%)
Model:
- 2nd level interactions were also selected. To avoid a model singularity one of the ingredients in the ‘model’ parameters must be arbitrarily removed.
- Water and Flavoured liquid were removed. 2nd level interactions involving either water or base were also removed (to decrease number of run and also as we are more interested in effets of the main ingredients)
- Alias – all second level interactions
- Maximum number of runs possible = 50 and with the above model the recommended number = 48 (so all good).
Example of runs:
Questions:
- How is it best to determine the number of central and repeated runs ?
- How do I interpret aliasing and the diagnostics ?
Is there a better DOE approach than the one constructed, or other factors to bear in mind?
Many thanks for any help or insight for my first DOE !!
