2-way Anova design repeated across an extra factor. Which approach is the best?

Hello to everybody,

I am a student working on a trial experiment to find the best combination of growing media, fertilizer application and container position to grow rooted Sitka spruce cuttings over one season.

Attached is the description of the experimental design and a picture of real-life layout.

In short, I am having a design that works with a 2-way anova, but runs across an extra factor(raised/non raised trays) and I am struggling to figure out how to analyse it. I know 3-way anovas are quite basic version of a general linear model but in this case I wonder if a specific GLM model could be designed to effectively analyse the data I have. In professional stats, GLM's are tailored to be as simple as possible while still explaining the variation of the data, I have a feeling that such procedure might be necessary in the case of my experiment. Hence, I am asking for your help guys.

Another problem is that my data consists of continuous (height of cuttings, root/shoot ratio) and categorical (plug formation quality) variables in which case a separate GLM would need to be tailored for each.

If any experienced people could please comment on the viability of such design and guide me through the application of 3-way Anova(if that is the best option) for this particular case that would be more than appreciated.

Thanks in advance ;)