For lycopene extracted, all variables (temperature, pressure and CO2 flow rate) were to be the influential variables, but there is no possible interaction among variables.
The analysis of experimental design for process optimization results demonstrates that temperature and pressure were to be the influential variables on the extraction yield of seed oil.
A partial component analysis of the intervention plan suggested that the presence of preferred staff was the influential antecedent variable.
The gasification temperature was found to be the most influential variable, with high temperatures leading to an increase in all the response variables studied.
In the analysis of the final model of the stepwise multiple linear regression containing 6 independent variables, household income which explained 72% of the variance was found to be the most influential variable followed by respondents' age and gender, access to information on organic vegetables, household member with health problems, and household location (Table 5).
In the analysis using the stepwise multiple linear regression final model with 5 independent variables, household income which explained 66% of the variance, was found to be the most influential variable followed by gender and age of respondents, access to information on organic agriculture, and presence of household member with a health problems (Table 3).
The solid load was found to be the most influential variable on viscosity.
The peak flow total error was estimated at ±31% and water height was found to be the most influential variable on peak flow, followed by Manning's n.
The variables evaluated in the planning were the live steam ratio and the temperature of the live steam in evaporators 1 and 2. The temperature of the live steam entering the second evaporator was shown to be the most influential variable for the output composition, followed by the live steam flow ratio.
The pH of the sample proved to be the most influential variable during sample enrichment on the SPE cartridge.
