Combining a Randomized Block Effect with a Split Plot Design in R

I am having trouble with doing an analysis of variance of a combination of an RCB with a split plot design in R. I understand what the theoretical model looks like, but I'm having trouble writing R code to reflect that, and the output comes out all weird. I found some material, but they either define the block as a fixed effect or use SAS. I was hoping I could get some insight from you guys.

This example involves data from an experiment to compare the response of two plant varieties to increasing amounts of pesticide designed to protect the plants against disease. The experiment was conducted in a greenhouse. Plants were placed on five benches, which were used as blocks to account for local variation in the greenhouse. Each bench was divided into four sections where, for convenience, levels of the pesticide were applied. Each section had two plants, one of each variety. The variable TYPE denotes the variety (S for “susceptible," a genotype susceptible to the disease, and R for “resistant”); the variable DOSE refers to the amount of pesticide, and the variable Y is the plant response. The design is a split plot with the whole plot conducted in randomized complete blocks. DOSE is the whole-plot factor and TYPE is the split-plot factor. Obtain the data and analyze it according to this design.

Here's a link to the dataset if you want to see it. Help would be appreciated on how to construct the code for the ANOVA. Thanks.