Shrimp Aquaculture

Important variables related to the survival outcome were identified using the Boruta algorithm. Boruta is a feature selection algorithm based on the random forest algorithm, which determines important features based on statistical significance.

In a nutshell, it works by comparing the calculated Z-score of each variable using the original values in a model versus the maximum Z-score of each variable using a randomised set of values. It then eliminates variables with Z-scores that are not higher than the maximum Z-score of the random ones. Variables with the higher Z-scores were then interpreted as the important variables.

Additional correlation analysis using Person correlation was then carried out on these resulting variables to explore the relationship between any two pairs. This revealed that feed products had a linear relationship with each other in terms of improving shrimp survival. The software tool Python was utilised to run the analyses.

From this analysis, it was identified that specific feed and supplement variables were highly associated with a high survival rate (>80%). From the set of physicochemical variables - dissolved oxygen, PH , depth, temperature, and salinity were revealed to be important parameters. From the set of water management input variables, ammonia and magnesium levels were revealed to be significant parameters for shrimp survival. As shown in Table 2, these variables were supported with a mean importance score produced by the Boruta algorithm.