This is much more of a statistical modelling question, and the topic of an entire course in linear models. You are treating pl_height1 and an INDEPENDENT variable in your model example, rhather than the dependent variable that you said initially. In using the BY statement, you are not adjusting for the effect of the categorical variables, merely testing the linear relationship within each combination.
You can do this with REG, you do not have to use GLM (GLM would be required with two dependent variables, but with one of each you can use REG). Look at the ODS Statistical graphics, there is one that may do a graph you would find useful (Figure 21.3)
http://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_odsgraph_sec... .
If you want to control for the categorical variables, you are either back to GLM (where you can use a CLASS statement), or you need to recode the categorical variables as a series of binary variables. However, in GLM you lose the R-squared part of the plot. Either way, you now have a host of other modelling issues (which gets to my "entire course" comment).
You can do the approach you described for a first look at your data, but you likely will want to consult with a statistician before diving too deeply into the modelling area. You may benefit from talking to a statistician who focuses in the agricultural area, as there are some techniques that they use that I (a biostatistician) haven't used since grad school.
Doc Muhlbaier
Duke