Evidence for 2 rules linking words in Herbal A->B

[npcompl33t]

I agree with Stolfi.
Here's another chart on this topic; as you can see, the pharmaceutical sector aligns very well with A...

Your charts just arent graphing the correct things. Pharma has almost no words that end in -chy, and contains far more -eo- in the middle of words than the other sections. It is very apparent it maps into a different space when looking at the PCA, rene also agrees here in the work he published on his currier expansion, as MarcoP said.

Im working on a webapp to allow people to explore the rules i've created as well as ones they want to create, I have to go out of town tomorrow, but i'm hoping ill be able to share it. 

One of the issues is that -or and -ol cannot all be turned into -edy, there is too much unexplained residual mass left over. Chol and Chor collectively occur at like 2-3x chedy's rate each, so there has to be something else capturing at least a portion of that. The yellow portions of the bars in the chart below represent missing mass when trying to map the chor/chol family into chedy.

   

I think nablator is right and to make all of this work likely requires some sort of contextual merging, maybe like a type of proclitic, particularly involving -or, ol, and possibly the ain/aiin families, either into individual or merged forms with other words. So maybe some of chol / chor gets absorbed as 'or' or 'ol' as standalone words or mapped as prefixes. 

The web-app i'm creating has a 'translate' function that applies rules to a given page, for example, f2r, and tries to 'translate' it into Herbal B, or pharma. 

On reading this, it actually starts to sound quite similar to bio, words that would have had different endings all start to sound similar. See the line below, line 7 from f9r, so maybe something like this is actually occuring, and possibly could explain why bio in particular seems so repetitive.  The -edy ending is taking different word forms, maybe something like qokol, qokchor, etc and turning them into qokedy.

   

While i think it is possible to track how certain masses of words become other words, it seems the rules are a bit more complex than simple bigram replacement and may involve context from adjacent words, which is a known voynich trait anyways with respect to q and y.

actually interpreting why certain words become others, especially when multiple options exist (tense, abbreviations, or any of the other items from Solfi's list) is a more difficult task, that I could definitely use help with.

Here is the current rule set i am experimenting with (which has expanded a bit from the initial 2), applied to the same chart Jorge_Stolfi shared. It may not be perfect yet, there may be certain contextual triggers i haven't identified.