DSSAT Listserve,

I am working on a project for my advisor involving using the DSSAT CERES-Maize
corn model globally.  I am setting up the model to run on 0.5 degree resolution
pixels (about 28000 globally), automated in Matlab.  I am trying to set up the
minimum requirements to run the model to predict water demand based on yield,
temp and precipitation.

One of the issues I'm running into is some of the variables I need to
generalize, like soil, cultivar, management, and planting/harvest dates.

For soil, I was thinking I could use the WISE soil database designed from DSSAT.

However, I'm running into problems in figuring out how exactly to attribute each
of my raster pixels globally to the corresponding WISE/FAO soil classifications.
 Some sort of global gridded dataset that I could easily derive the majority
soil type for each 0.5 degree pixel is what I have in mind.

(Or alternatively, if there is a good general, build-in or default soil type
that I could use for the model, since we are mainly interested in a quick
analysis.  We understand that doing a global-scale analysis will have it's
share of error and approximation.)

I hope my question is clear.  If anyone has any pointers or info on where I
could look for this data, it would be appreciated.  Thanks for your time.

(If anyone knows of a good general corn cultivar that I could use for my model
as well, it would be helpful.)

Jonathan Resop
Ph.D. Candidate
Biological Systems Engineering
Virginia Tech