I have an experiment where I am subjecting 8 different samples to different experimental conditions, but then I need to compare the same variable (e.g. concentration) of every different sample against the standard value of the same control sample. ie If the 10 samples are A, B, C, D, E, F, G, H and the control sample is Z, then I need to compare A vs Z, B vs Z, C vs Z etc.

I obviously have several repeats of each sample, including Z.

Since the repeats consist of normally distributed data points with similar variances, I intend to use the student unpaired t-test (2-tailed) to do this. Since Z is a common variable in all the comparisons, do I need to carry out some sort of pairwise correction such as Tukey or Bonferroni?

Bonferroni corrects by multiplying the p-value by the number of comparisons which would technically work out at 36 for 9 sets (8 experiments and one control). But in reality, I am not interested in every single combination (e.g. I am not interested in A vs B or B vs C etc), and am only interested in the comparisons against control, ie 8 comparisons to the same control.

Can I assume that no post-hoc correction is necessary here?