Open access alternative
The study analysis was done with Design expert software and can be performed by any alternative or similar open access software like R-studio (R version 3.1.2 with installed rsm Package for surface and contour plots) which is open source and free for non-commercial purposes. Any Windows 7 and 64 bit upward with Windows graphics package can support the running of the Design expert software. RStudio Server version gives access to the RStudio IDE (integrated development environment) from anywhere via a web browser, debugs in an interactive manner and runs on the desktop (Windows, Mac, and Linux) or in a browser connected to RStudio Server with boot, class and cluster as recommended packages. Readers and reviewers can replicate this analysis using a detailed unrestricted access methodology described in Chapter 10 of Wu & Hamada (2009). It is recommended that readers look at YouTube tutorial videos on design and optimization of experiments and practice with existing data in previous studies to verify result with ones in those articles.
The design of the experiment for the formulation of the bioremediation cocktail followed three key steps of screening, characteristisation and optimisation (SCO). The combination of knowledge of subject matter and One Variable at a Time (OVAT) or One Factor at a Time (OFAT), was utilized in the screening and characteristion phases to narrow down to the vital few variables or factors necessary for the development of the bioremediation cocktail. In this case, four key variables were identified or selected as vital ingredients for the cocktail mixture. Consortia of four high through-put hydrocarbonoclastic rhizobacterial, two limiting nutrient sources (N-P) from corn steep liquor and poultry dropping, and a third non limiting but vital nutrient of plantain peels char was screened, selected and characterized to established their minimum and maximum concentration range at laboratory scale.
Optimization phase is the cocktail formulation phase and involves finding the vital factors or variables with their minimum and maximum range in concentration or amount. These pre-optimized variables are keyed into the variable view as given in choice software and the runs become the basis for the formulation of sets of unique cocktail mixtures, which are then applied to the same polluted sample soil size and the response reading for Total Hydrocarbon Content (THC) and Total Petroleum Hydrocarbon (TPH) are collected at certain time interval (days). The collected response or results of THC and TPH are re-input back into the software alongside its designed conditions, and the software generates a unique model, usually a quadratic model, where the response (THC or THP removal) is a function of the inputted variable. These software allow researchers or stakeholders to see the variables or factors that makes the greatest impact or effects on TPH or THC removal, the interaction of variables or factor and their effects on THC or TPH removal, and the power factors effects of the variables or factors on THC or THP removal.