Whew. Don't accidently proliferate resistant nematodes, parasitic organisms mess with my head.

Well, this is the case of needing to have an analytic protocol before conducting the study. You have so many variables it is hard to count them all. And unfortunately secondary to that problem is that you will have a huge permutation of all possible comparisons, which should require correcting your alpha level due to the risk of familywise errors. Lastly, you have a dinky sample size and a binary outcome, which can be a little less forgiving than a continuous one where you can have big treatment effects, where you just have dead Y/N.

What was your plan on the front side to analyze these data, which will likely require a logistic regression? You can cherry pick a comparison, but would have to disclose your initial intention. In analyses things also get tricky when dealing with multiple version of an intervention. I am not sure how to direct you. You really have a daunting path ahead of you and after making corrections for pairwise comparisons, you will need striking results to maintain significance. I have not ran such an analytic project with some many subgroups, it may need to be addressed using multilevel logistic regression, but Power will be low no matter what you do. I would look to your field's literature to see if you can find a comparable study and what analyses they may have conducted. Though remember, just because it was published doesn't mean someone else's approach was correct either!!! It is easy to find poorly conducted studies in journals.