Dear Mathias,
Thanks for taking time to write to the DSSAT list. What you wrote really
makes sense, and hope all plant scientist would vote for it.
Nevertheless, we also need understand the limitations of
numerical/mathematical models, especially when deal with biological
systems and their complex interactions with abiotic processes as we do
in cropping system models.
        To my understanding, the DSSAT models have mainly three
components, the water, nitrogen and the crop. For modeling the crop, one
need make sure that the first two components works reasonably well for
the system before modeling the third (the crop). I could not see any
efforts in the study to do this or see any results presented. I expect
the least a table showing the crude water balance simulated to prove
that you got the soil water/nitrogen correct.  For that reason, it is
left to anybody's guess what those components were doing! It is also
possible that one do not want to present all the results when we publish
papers in journals that charge for pages.
Notwithstanding, what I see in the study is that the calibration runs
were made turning off the water and nitrogen modules. To my
understanding, it is in the field experiment used for calibration one
should make sure that there were no abiotic stresses but not in the
model!
If one is one hundred percent confident that the field experiments are
free of water, nitrogen, and temperature stresses, simulations
neglecting (turning off) those processes can be a reasonable
approximation. But, in the studies presented I could not see
experimental treatments!  However, I did notice that the optimum N
treatments were defined as treatments with different levels of N and
manure levels. Here also, I do not see anything mentioned about water
levels in the treatment. Did you totally forget about water and nitrogen
interactions? Keeping in view of the heterogeneous behavior of the
various processes and their interactions in the system do you honestly
think these treatments are be free of abiotic stresses for turning off
the switches in the model, unless we stretch our imaginations really
thin?

What I am trying to say is not that the model is or would work
wonderfully well in all the environments and circumstances, as you
pointed out and we all know that there are many unknowns and
uncertainties in the system that we are not able to grasp yet to model
them correctly. But, given the limitation, at the least the models
should be used correctly to point out their limitations, and this would
certainly appreciated by one and all.
Hope you appreciate the errors in your simulations.
Sorry for taking your time and patience.
Best wishes
Sasi


Saseendran S Anapalli,  Ph. D.
Agricultural Systems Research Unit
USDA-ARS
2150 D Center Ave.
Fort Collins, CO-80526


-----Original Message-----
From: DSSAT - Crop Models and Applications
[mailto:[log in to unmask]] On Behalf Of Matthias Langensiepen
Sent: Friday, March 07, 2008 6:13 AM
To: [log in to unmask]
Subject: Re: weakness of CERES-wheat

Dear all

the recent concern of Dr. Andarzian about our
calibration of CERES-Wheat requires a response:

It was not easy to critize a model which has
taken a lot of efforts to construct and
which is still in widespread use as demonstrated
on this list server. I deeply admire the authors
of DSSAT who contributed significantly to modern
crop modelling and provided a wealth of inspirations
for advancing crop research.

Our motivation to carry out this study and the
discussion of its results are described in the
paper which is the reason for not quoting
them again. However, I would like to respond
to the genetic coefficient issue:

Bahram Andarzian is right in a way that the genome
of a plant is fixed. 30 years after the CERES
model was formulated we are able to decipher the
genome of a plant and can potentially get fascinating
insights into its metabolism. Practically, however, this
is like getting a book which we have waited for for a long
time, but are unable to read. Millions combinations
of metabolic pathways are possible and we are still
very far away even from crasping the complexity of plants.

Using only a handful of so-called "genetic parameters"
is a very crude approximation of this complexity which
is necessary to allow for a practical application of
the model. We do not critize this pragmatic approach.

What we do critize, however, is that the majority of
DSSAT-users do not allow for their changes over time.
A farmer who has cultivated a field for 30 years
knows very well that no crop season is like the other
and that plants respond to these fluctuations in flexible
manners. The underlying biological mechanism is differential
gene activity which results in numerous adaptation strategies
which can differ greatly between seasons. The extreme
seasonal differences of weather conditions at
Schleswig-Holstein (ranging between approx. 250
and 1000 mm rainfall per year with no regular
distribution, for example) forced us to calibrate
the model for each season separately. I hope
this clarifies the issue (We strictly
followed the user guidelines by the way.)

Plants are more clever than we often think.
Francis Halle, a well known botanist from France,
quoted the French writer Michel Luneau in this context,
"who knows how to make the tree speak: For us, say the
trees, all is connected so that there is no need for
any particular centralization. Our internal organization
recognizes neither God nor a master. It is a free association
of elements of different and complementary organs.
These obey nobody but themselves and ask of
their followers a simple and essential agreement:
growth. Each organ is free in the means by which it
attains growth. To each according to its
inspiration..." (Halle F. 2002. In Praise of Plants.
Timber Press. Page 99).

Do we need separate crop coefficients for each plant organ
and season ?

Have a nice weekend.

Matthias






Dear my friends DSSAT servers
   Hi
   Please if possible, see the article entitle" validating CERES-wheat
under North-German environmental condition" by M. Langensiepen and
co-authors in Agricultural Systems Journal (article in press). This
article challenges the using and performance of CERES-wheat model to
simulate grain yield and biomass production under different water and
nitrogen conditions.
   In my idea genetic coefficients are cultivar-dependent and should not
be changed over years, but in their calibration procedure, they assume
genetic coefficients are environment-dependent which according to
environmental condition of each year have changed! If so, what is the
mean of the yield variability? In my idea, yield variability is the
yield of a crop over different years or in the other word, running the
model with fixed genetic coefficients over different years.
   Apparently, it seems that they did not calibrate water and nitrogen
modules in their work!
   This case may be a good discussion topic for DSSAT servers and
sharing information about strength and weakness points of the DSSAT
models with each others.

   Best
   Bahram Andarzian
   Ph.D in Crop Eco-physiology
   Agricultural and Natural Resources Research Center of Khuzestan
   Ahvaz-Iran