# The Yeast-Based Robotic Encapsulation Scenario: A Systematic Review and Meta-Analysis
## 3 Results and Discussion
### Study Inclusion
The optimizer sets a goal, which is denoted by “optimal value” and represents the best value that the optimizer can achieve. The vertical red lines in the optimization graph represent the current factor settings, indicating the specific combinations at the time of analysis. Dashed blue lines suggest composite responses or desirability for the current factor level, providing a visual view of the relationships between factor configurations and desired responses. Figure 3: Response optimization: survival percentage—pH and materials. (D) Composite desirability, which evaluates how the configurations optimize a set of responses in general; (d) individual desirability, which evaluates how the settings optimize a single response, and (y) the response variable or the dependent variable. The optimizer sets a goal, which is denoted by “optimal value” and represents the best value that the optimizer can achieve. The vertical red lines in the optimization graph represent the current factor settings, indicating the specific combinations at the time of analysis. composite desirability (D) value of 0.5685. Additionally, it shows an individual desirability (d) value of 0.5685 and a predicted response (y) value of 57.933. There is a red line for pH 1 and a red line for temperature 28. According to the statistical model used, it can be stated that the expected survival percentage, considering the temperature and pH variables, is approximately 57.93%. Therefore, the analysis suggests that, although the optimized configurations have achieved a moderate level of desirability for the general set of three variables involved, there is still room for improvement, especially when considering the variables individually. The predicted response provides an estimate of the expected performance under the optimized conditions, indicating that further adjustments may lead to more favorable results in keywords for percentage survival in encapsulated probiotic yeasts in gastrointestinal simulation tests. The vertical red lines represent the current factor settings. Each vertical red line indicates a specific set of settings for the different factors under analysis. The red lines serve as visual markers to indicate the conditions under which experiments are being conducted or optimized. The horizontal blue line indicates how the composite response or desirability varies in relation to different factor configurations. Figure 2 also depicts the relevant elements that describe the optimal choices given a set of options as outlined in our initial list of variables. As it can be seen, the optimizer establishes a target, which is denoted by \"optimal value\" and represents the best value that the optimizer can achieve. Evidently, attaining such a level indicates either that the empirical conditions are equivalent to the theoretical ones or that no interaction is expected between two or more factors. Therefore, a variable \"y\", which corresponds to the predictor, is given. This variable is our compass in order to validate how the interaction between two factors can induce a survival level that is different from the target. Each combination of optimal elements produces different values for \"y\" and the best combination (highlighted in red) is given by the maximum value that the predictor can yield. The data obtained also show that there is a strong negative correlation between the survival response and the temperature factor, since, in the analysis, a straight line with a negative angular coefficient was obtained (black solid line). On the other hand, the pH factor, according to the collected articles, does not seem to play such a significant role. Initially, one must consider that the articles considered in this review mostly carried out gastric simulation tests with narrower pH ranges (an acidic pH value and a basic pH value). As for temperature, a wider range of conditions can be verified. This fact may justify the lower impact of pH as an individual variable.