[ANOVA in R] Which ANOVA to run?

#1
Dear forum members,

I have been looking for a solution that fits my analysis both on this forum and the web and have returned empty handed so decided to post my own thread.
For my Master's thesis, we have performed an experiment with 160 plants from 10 different genotypes, divided in 2 treatments (water deficit vs well-watered). So we have 8 individuals per treatment per genotype. We have measured several variables during several weeks but the one I'm interested in is leaf emergence rate (LER). This is simply a measurement of growth, expressed as either cm/day or percentage of total leaf length per day.

The goal: determine whether genotype and treatment have a significant effect on LER. Normally, one would perform a Two-way ANOVA, but since I have measurements of the same plants over the course of several weeks, there will be strong autocorrelations between the observations of the same plant. Everywhere I go, I read I should use Repeated measured ANOVA but if I understand correctly, this method is used to compare the effect of a variable (or in this case, 2 variables) on the output variable before and after, or over the course of a time period. In other words, see whether the output changes over time (hence time is a focal variable).

I have no interest in the evolution of LER over time, I do not expect it to change significantly for the same plant or genotype. I simply want to compare LER between genotypes and treatment, but I need to account for the autocorrelation. One way to do this (which in my opinion is a bit unprofessional) is to run a Two-way ANOVA at each measuring moment. That would work but loses statistical power, complicates interpretation and is just a big hassle honestly.

Could anyone suggest the right analysis method for me, please? I am running this analysis in R, so any suggestions towards packages or functions would also be appreciated.

Thank you for your attention and best regards.