Let’s say I have a data file named DATA1 for a 2-factor experiment with A and B columns as factors, and X column is the measured data. So how should I write the aov code for ANOVA of this experiment, if I use CRD, RCBD or split plot design, respectively?

From my current understanding:

If I use CRD, then my aov code should be:
MODEL <- aov(X ~ A*B, data = DATA1)

If I use RCBD, with say BLOCK is the block (or replicate) column, then my aov code should be:
MODEL <- aov(X ~ BLOCK + A*B, data = DATA1)

If I use split plot design, with A is main plot and B is supplot, BLOCK is the block (or replicate) column, then my aov code should be:
MODEL <- aov(X ~ BLOCK + A*B + Error(BLOCK/A), data = DATA1)

Are these correct? Or am I a complete idiot here?

ADDITIONAL:
In the package “agricolae”, they seem to have a specialized function for split plot design:
MODEL <-with(DATA1, sp.plot(BLOCK,A,B,X))
which on the rdrr.io page for sp.plot (https://rdrr.io/cran/agricolae/man/sp.plot.html), it is stated that it’s equivalent to the aov code for split plot I used above. But I can’t seem to get the same results for these 2 codes. So is one of them incorrect?