*** Question regarding CERES Wheat:
 
I have been attempting to simulate a spring variety of wheat (Triticum
aestivum L. cv. Yecora Rojo) planted at a 0.25 m row spacing and grown near
Phoenix, Arizona.  As the specific cultivar parameters are not available, I
have been trying to calibrate the model.   After trying several existing
varieties, playing with numbers and running GenCalc, I am still unable to
obtain acceptable results (I have 3 seasons worth of data).  One of the
biggest problems is obtaining reasonable predictions of both leaf weight and
leaf area index.  If I adjust the parameters to obtain predicted leaf
weights near the observed, LAI is greatly under predicted.  And the reverse
is also true (correctly predict LAI, leaf weight is severely over
predicted).  This leads me to the conclusion that the value used for
specific leaf weight (or equivalent parameter) in the model is not
appropriate for my variety.  I do not see a "species" file for the CERES
model.  Does anyone know where I could change such a parameter?  Or is there
some other action I could try?
 
I would also be interested to hear from anyone who has had success in
applying CERES Wheat in an arid environment.  I am a little concerned in
temperature related responses in the model, as the crop temperature can be
considerable lower than air temperature due to evaporative cooling.
 
 
*** Precision farming, remote sensing and crop models
 
On a somewhat different subject, I would also like to hear from anyone
planning to use remotely sensed data with crop models.  Three major sources
of information that can be  estimated from remotely sensed data are:
 
1. Soil properties - Using images in the red and/or near-infrared (NIR)
portion of the spectrum to spatially interpolate point soil samples and to
identify sampling locations.
 
2. Canopy density - Spectral response in the red and NIR can be used to
derived estimates of LAI using empirical relationships or through canopy
models.
 
3. Evapotranspiration - Application of thermal and reflective data combined
with basic meteorological conditions can be used to obtain instantaneous
estimates of actual ET.
 
I believe all three could be used in applying crop models to precision
farming problems.  We are planning to try some different approaches and I'd
be interested to find out who else is working in this area.
 
Thanks,
 
Ed Barnes
DSSAT class of `96
 
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Edward M. Barnes, Ph.D.             Phone: (602) 379-4356 x 268
Agricultural Engineer                 Fax: (602) 379-4355
USDA, ARS                           email: [log in to unmask]
U.S. Water Conservation Lab
4331 E. Broadway Rd.
Phoenix, AZ 85040
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