The design was composed of factorial multiple measurements and the results were analyzed according to a mixed linear model, (GLIMMIX) SAS 9.2 (SAS Institute, Cary, NC) and R 2.9.1 and ggplot2 software. We set pre-planned (a priori) contrasts, i.e., we set all our comparisons in advance of multiple setting experiments. Significant differences were presumed at a probability value of p < 0.05. The results were graphed using error bars with 95% confidence intervals. Differences in the means were estimated either with asymptotic techniques for normally distributed data or bootstrapping techniques for non-normally distributed data.