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Announcing the

UFIS - WWW Pages

Access to the UFIS database is now possible via WWW and telnet. UFIS
is an information system on ecological models and (later on) data. At
this stage UFIS is able to provide detailed model documentations,
searchable in various ways. Work on the expansion of the database
to a large number of models is ongoing.
Later on UFIS will also provide information on data relevant to models
(watch the UFIS-pages).
A description of UFIS is also available via WWW.

Access to UFIS-pages:

http://www.gsf.de/UFIS/ufis

Access to the database via terminal:
telnet cony.gsf.de (146.107.1.2)
login: ufis
password: ufis95

Comments are welcome, send e-mail to: ufis@gsf.de

==============================================================
Michael Knorrenschild
GSF Research Centre for Environment and Health /PUC
P. O. Box 1129 Phone: +49-89-3187-2953
85758 Oberschleissheim FAX: +49-89-3187-3369
Germany e-mail: knorren@gsf.de

This is the last reminder for the Farm Animal Computing Technologies
Conference (FACTs 95) conference in Orlando, Florida March 7-9, 1995.

Room reservations must be made by Feb. 7 so that you can take advantage
of the block reserved at the conference site. Details and a copy of the
program are below. See you there.

Mark Varner
varner@umd5.umd.edu
=====================

Program and Registration

FACTs 95

March 7,8,9 1995
Orlando Florida

Farm Animal Computer Technologies
Conference

Tuesday, March 7

3:00- 6:00 p.m. Internet Demonstration Room
Mark Varner, Moderator

6:00 p.m. Banquet
Gary Weber, Master of Ceremonies

7:30 p.m. Keynote Address

Wednesday, March 8

General Session: Perspectives on Computer
Technologies
Henry Tyrrell, Chair

8:00- 8:35 am Producer Perspective of Information Technology
Sam Cnosson, Wendell, ID

8:35- 9:05 am Agri-Business Perspective of Information
Technology
Paul Johnson DVM, Enterprise, AL

9:05- 9:40 am Possibilities for AI Applications in Animal
Agriculture: A researcher!s perspective
Jon Sticklen, Michigan State University

Developer I: Integrated Systems
Nick Stone, Chair

10:15-10:40 am Dairy Management Information Systems.
Ed Schmisseur, Oregon State University

10:40-11:05 am S.P.E.C.I.A.L. - Simulation Model to Support
Decision Making in Pork Production
Dewey Harris, USDA-MARC

11:05-11:30 am An Integrated Agricultural Planning Model
for the Texas Department of Criminal Justice.
Houshmand Ziari, Texas A & M University
11:30-11:55 am Whole farm planning for crop/livestock farms.
Nick Stone, Virginia Tech

User I: Accessing Information for Decision Support
Systems
Mark Varner, Chair

10:15-10:55 am Development of software that accesses
multiple sources: Lessons learned.
Mike Tomaszewski, Texas A&M

10:55-11:15 am Range Cow Culling and the Value of
Pregnancy Testing: A Decision Support
System via the World Wide Web.
Russell Tronstad, University of Arizona

11:15-11:35 am Forage Information System (FIS) World
Wide Web (WWW).
David Hannaway, Oregon State University

11:35-11:55 am Outreach: A Computer Based, Document
Management System for Extending
Information.
Abbas Ahmadi, University of California

12:00-3:00 p.m. Poster Session
Lawrence Jones, Chair

Developer II: Technologies for Practical Problems
Jim Oltjen, Chair

3:15- 3:40 p.m. Dairy Decision Support System: Dynamic
Simulation Model for Culling Management of
Dairy Cows in Large Dairy Herds.
Terry Lehenbauer, University of California

3:40- 4:05 p.m. Fuzzy Decision Making in Dairy Cattle
Management
Rene Lacroix, McGill University

4:05- 4:30 p.m. The Application of Markov Decision
Processes as a Framework for Decision
Support in Animal Production .
Anders Kristensen, Royal Veterinary and
Agricultural University, Denmark

4:30- 4:55 p.m. Data Preprocessing for Neural Network
Classifiers.
Rene Lacroix, McGill University

User II: Use of Modeling for Practical Decision
Support

3:15- 3:55 p.m. The Florida Dairy Management Project: The
practical application of advanced modeling
techniques to aid decision making.
Mike Delorenzo, University of Florida

3:55- 4:15 p.m. Model for Financial Evaluation of Alternative
Production Strategies for Michigan Dairy
Farms.
Stephen Harsh, Michigan State University

4:15- 4:35 p.m. Implementing an Energy Utilization Model
for Prediction of Cattle Growth and
Composition.
Jim Oltjen, University of California

4:35- 4:55 p.m. The Beef Grazing Model GRAZE:
Availability, Documentation and Case
Studies.
Otto Loewer, University of Florida

Thursday, March 9

Developer III
Larry Jones, Chair

8:00- 8:40 am A Case Study in Generic Task Problem
Solving: Helping to Grow Wheat in Egypt.
Jon Sticklen, Michigan State University

8:40- 9:00 am Utilizing object-oriented analysis, design, and
programming techniques to develop a dairy
herd simulation computer program.
Andy Skidmore, Michigan State University

9:00- 9:20 am Use of single-chip microcontrollers in farm
data collection systems.
Robert Sherlock, Dairy Research Corporation,
New Zealand

9:20-10:00 am An Object Oriented Simulation Model of a
Pig Herd with Emphasis on Information
Flow.
Erik Jorgensen, National Institute of Animal
Science, Denmark

User III: Use of Knowledge-Based Systems in
Practical Decision Support and Training
Basil Eastwood, Chair

8:00- 8:40 am Implementing expert systems: real
knowledge from the school of hard knocks.
Dick Plant, University of California, Davis

8:40- 9:00 am Knowledge and Expert Based Decision
Support Systems for Professional
Agriculturists .
Earl Fuller, University of Minnesota

9:00- 9:20 am Benefits and Characteristics of Computer-
Based Training in Higher Agricultural
Education.
Wolfgang Heuwieser, Fu Berlin

9:20- 9:40 am Use of Decision Support Systems in the
Assessment of Current and Alternative
Livestock Enterprises in Northern Chiapas,
Mexico.
Jerry Stuth, Texas A&M University

General Session: Issues Regarding Transfer and
Widespread Adoption of Technology
Dewayne Dill, Chair

10:00- 10:25 am Considerations for Transfer of Publicly
Developed Computer Technology to
agribusiness.
Shade Sangosina, Monsanto Co., Innovations
Group

10:25- 10:50 am Building Ties with Agribusiness -
Experiences with PigChamp.
Linda Klemmer, Pig Champ Business
Manager, University of Minnesota

10:50- 11:15 am Challenges Marketing and Supporting
Decision Aids in the Public Sector
Roy Black, Michigan State University

11:15- 11:40 am Funding Opportunities and Limitations
through the NRI Ag Systems Program
Jim Cook, USDA/NRICGP

11:40-12:00 Overview of the FACTs95 conference and
concluding remarks.
Larry Huggins, Purdue University

Workshops

#1) Physiological Modeling of Swine Growth and Response to
Nutrition and Environment ( 3 hours)
Larry Turner1, Tom Bridges1, James Usry2, and Rich Gates1
1University of Kentucky
2Heartland Lysine, Inc.

The NCPIG model developed at Kentucky as part of the North
Central Region Project NC-204, will be used to demonstrate the
concepts of physiological modeling of swine for simulating growth
of 20-100 kg pigs. Applications described will include 1) use of
misting systems, 2) nitrogen and phosphorous waste production
prediction for diets supplemented with amino acids and phytase,
3) neural-net development based upon model predictions, and 4)
base growth and nutrition calibration studies. A !hands-on!
session is included, and each participant will receive an executable
version of the model with documentation.

#2) Software Engineering: What is it and What can it do for
You? (3 hours)
Rod Korthals and Sam Alessi, United States Department of
Agriculture

Do you have computer outputs of unknown data, software that
no one can understand, let alone maintain, or problems
finishing programming projects (and the documentation) on
time or within budget? In addition to open discussions and
lessons learned presentations, Mark Borger from the Software
Engineering Institute (SEI), a Federally Funded Research
Center sponsored by the DoD, will discuss some of their
experiences in helping organizations improve their own
software development and maintenance practices.

#3) Delivering Extension Information via WWW (2 hours)
Russell Gum and Russell Tronstad, University of Arizona

This workshop is intended to demonstrate 1) the use of the world-
wide web for delivery of livestock marketing and management
information, and 2) how to build a WWW server.

#4) Fuzzy Expert Systems (2 hours)
Russell Gum and Russell Tronstad, University of Arizona

A hands-on workshop of fuzzy logic and expert systems presented
at a laymen!s level. This will be informative to participants
interested in the practical applications of this technology to the
livestock industry. The workshop will give participants a basic
understanding of what fuzzy expert systems are and an
introduction on how to apply them to real world problems
involving decision support systems.

#5) Joining the Information Superhighway. (2 hours)
Mark Varner, University of Maryland

This workshop will discuss and give experience in joining the
Internet. It will include a years subscription to an email host on
the Internet and telecommunication software.

Conference Committee

Lawrence Jones, Cornell University, Co-Chair
Jim Oltjen, University of California, Co-Chair

Henry Tyrrell, CSRS-USDA
Basil Eastwood, ES-USDA
Nick Stone, Virginia Tech
Dewayne Dill, Cenex/Land O'Lakes
Mark Varner, University of Maryland
Danny Simms, Kansas State University
John Carey, Texas A&M University
Larry Huggins, Purdue University
Rob King, University of Minnesota
Aalt Dhykhuizen, Wageningen Agricultural University

Posters

Use of an Integrated Computerized Record Keeping System and Electronic
Transponders to Manage Beef Cattle Health and Production Records.
Kristin Allen, University of Missouri

Design of a Decision Support System to Evaluate Mastitis Control.
Heather Allore, Cornell University

An Interactive Computer-Based Program to Teach Body Condition Scoring
in Dairy Cattle.
Wolfgang Heuwieser, Fu Berlin

NCPIG: Physiological Model of Swine Growth and Response to Nutrition
and Environment .
Larry Turner, University of Kentucky

Constructing Crop Enterprise Budgets.
Gary Frank, University of Wisconsin

Evaluation of Waste Management Models for Decision Support Systems.
Roger Eigenberg, United States Department of Agriculture

Manure Management: An Example of the National Dairy Database
providing tools for Making Farm-Level Decisions.
Deanne Morse, University of California

Current use of Computer Technology by South Dakota Sheep Producers.
Mike Adelaine, South Dakota State University

Decision making under uncertainty: Application of stochastic dominance to
dairy capital budgeting.
Craig Thomas, University of Florida

A Short-Run Production Planning Model for the Texas Department of
Criminal Justice Michael Packing Plant.
Allen Sturdivant, Texas A&M University

Teaching Animal and Veterinary Science Seniors Using File Transfer
Protocol for Classroom Assignments.
John Miller and Donald Miller, University of Idaho

General Information

Hotel

A block of rooms has been held at the Orlando Marriott, 8001
International Drive, Orlando FL 32819 until February 7, 1995.
Guarantee your reservations with a major credit card by calling 407-351-
2420. Identify yourself with the FACTs Conference to obtain room rates
of $80 single/double. These rates apply three (3) days prior to and three
(3) days after the conference.

Airline Information

USAir is the official airline. Travel must take place between March 3 and
13, 1995; round-trip to and from Orlando; subject to availability; Globe
Travel Service is handling reservations and may be contacted at 800-724-
6191.

Registration

The attached registration form should be returned by February 8, 1995.
The registration fee of $150 includes admission, one proceedings, 1
banquet, 2 lunches and refreshment breaks. Registration received after
February 8 will be $175. Only checks drawn on US banks or international
money orders will be accepted. Make checks payable to Cornell
University and send to: Mrs. Dee Brothers, Cornell University, 272
Morrison Hall, Ithaca NY 14853-4801.

Sponsored in part by:
USDA - Cooperative State Research, Education and Extension Service
NCR 171 Regional Research Project
American Association of Computing Companies

Return registration form to:
Mrs. Dee Brothers, Cornell University,
272 Morrison Hall, Ithaca NY 14853-4801

Registration Information

First name (for badge) _______________________________

Last name _________________________________________

Company/Univ _____________________________________

Address ___________________________________________

____________________________________________

City/State___ _____________________ Zip______________

Email address _______________________________________

Phone (_____)_______________________________________

Registration
rec!d before 2/8/94 $150 ______
rec!d after 2/8/94 $175 ______
student $100 ______

Workshops
#1 $125 ______
#2 $25 ______
#3 $25 ______
#4 $25 ______
#5 $50 ______

Total enclosed $ ______

Dave Gustafson, on behalf of EMWG, raises the following issues:
>
> 1 - Which soil/water partition coefficients should be used in the modeling of
>pesticide movement through soils, those associated with the adsorption step,
>or those associated with desorption? Or is it necessary to use models in which
> sorption hysteresis and/or non-equilibrium is explicitly considered?

It appears that hysteresis of the sorption isotherm cannot in itself
explain the nonideal behavior of breakthrough curves obtained from laboratory
cores of undisturbed soil (Van Genuchten and Cleary, 1979). I would therefore
not expect the use of Kd, instead of Ka (or Ks), to yield substantially better
predictions of pesticide transport in soils.
Also, it is generally thought that rate-limited sorption plays only a
minor role in the sorption of hydrophobic organics to soils, as well as
when the sorption process is of a physical (Van der Waals) nature (Brusseau
and Rao, 1989). Thus, chemical nonequilibrium models, although successful
in representing the shape of BTCs, are not successful in identifying the
process responsible for nonideal behavior.
It is currently believed that one of the most important factors influencing
the transport of pesticides in soils, is the presence of preferential flow
pathways. This is shown by the successes of two-region models over the CDE, in
the simulation of solute BTCs for sorbed and non-sorbed chemicals (Nkeddi-Kizza
et.al., 1984). The effects of preferential pathways on solute transport are
also well illustrated by dye tracing studies (eg. Ghodrati and Jury, 1992).
The use of non-preferential flow oriented models (eg. CDE) in modeling pesticide
transport in soils will yield severe underestimates of penetration depth,
and of time of arrival of the contaminants at a given location (cf discussion
of experimental results in Kladivko et.al., 1991).
Thus, in my view, exposure modeling must include the effects of preferential
transport, maybe even before it worries about Ka vs Kd, or the kinetic aspects
of the sorption process (actually, both avenues should be followed in tandem).

REFS:

Brusseau, M.L., and P.S.C. Rao, 1989. Sorption Nonideality During Organic
Contaminant Transport in Porous Media. Crit. Rev. Env. Cont., 19(1):33-99.

Ghodrati, M., and W.A. Jury, 1992. A Field Study of the Effects of Soil
Structure and Irrigation Method on Preferential Flow of Pesticides in
Unsaturated Soil. J. contam. Hydrol., 11:101-125

Kladivko, E.J., Van Scoyoc, G.E., Monke, E.J., Oates, K.M., and W. Pask, 1991.
Pesticide and Nutrient Movement into Subsurface Tile Drains on a Silt Loam
Soil in Indiana. J. of Environmental Quality, 20(1):264-270

Nkeddi-Kizza, P., J.W. Biggar, H.M. Selim, M.Th. Van Genuchten, P.J. Wierenga,
J.M. Davidson, and D.R. Nielsen, 1984. On the Equivalence of Two Conceptual
Models for Describing Ion Exchange During Transport Through an Aggregated
Oxisol. Water Resour. Res., 20(8):1123-1130

Van Genuchten, M.Th., and R.W. Cleary, 1979. Movement of Solutes in Soil:
Computer-Simulated and Laboratory Results. In: Soil Chemistry B. Physico-
Chemical Models. G.H.Bolt, ed. Elsevier Pub.Co., Amsterdam.

> 2 - Is anyone aware of recent comparisons of field data results of leaching
> or runoff with the predictions of computer models such as GLEAMS or PRZM2?

Melancon, S.M., J.E. Pollard, and S.C. Hern, 1986. Evaluation of SESOIL,
PRZM and PESTAN in a Laboratory Column Leaching Experiment. Env. Toxic.
Chem., 5:865-878.

Sauer, T.J., K.J. Fermanich, and T.C. Daniel, 1990. Comparison of the
Pesticide Root Zone Model Simulated and Measured Pesticide Mobility
Under Two Tillage Systems. J. Environ. Qual., 19:727-734.

Sichani, S.A., B.A. Engel, E.J. Monke, J.D. Eigel, and E.J. Kladivko, 1991.
Validating GLEAMS with Pesticide Field Data on a Clermont Silt Loam Soil.
T. ASAE, 34(4):1732-1737.

For the most recent developments, from Purdue, (notably about GLEAMS), you
may want to contact S. Mamillapalli at sudhakar@ecn.purdue.edu .

--------------------------------------------------------------------------
Hubert Montas,
PhD Candidate,
(317)-494-9772
AGEN 305W,
Purdue University,
West Lafayette, IN.

Bernardo,

Sorry for the late response to your request for info on
a CSMP update. I recently received the following information
from Tadashi Takakura (takakura@tansei.cc.u-tokyo.ac.jp) who
has used CSMP extensively.

1) Micro-CSMP
California Scientific Software
10141 Evening Star dr. #6
Grass Valley, Calfornia 95945-9051
Tel. (916)477-7481
FAX (916)477-8656
2) PSCMP
Department of Theoretical Production Ecology
Agricultural University
P.O. Box 430, 6700 AK Wageningen, The Netherlands
Tel. 31 83 708 2141
3) SYSL
E2 consulting
P.O.Box 1182
Poway, Calfornia 92064
Tel. (619)578-4057
4) ACSL
Mitchell and Gauthier Associates
73 Junction Square Drive
Concord, Massachusetts 01742
Tel. (617) 369-5115

Larry Stikeleather (larry_stikeleather@ncsu.edu) may also
have infromation on CSMP or a substitute for unix platforms.

Robert
****************************************************************

Robert K. Pollock

rpolloc@eng.clemson.edu 803/ 656-4078
Greenhouse Engineering Research lab: 656-4092
Agricultural and Biological Engineering fax: 656-0338
204 McAdams Hall, Clemson University (messages)
Clemson, South Carolina 29634-0357 Vici 656-4045

****************************************************************

Hello Dave !

I am a PhD student at the Ag. Engineering Dept. at Purdue Uninversity.

I am currently working on ground water quality modeling using GIS for

pesticide screening. I am using the DRASTIC and SEEPAGE indexes for Indiana

and eventually the midwest.

1. Do you know of anyone that may have the souce code to the

PATRIOT model. I need to link the STATSGO soils database into the model

instead of the soils5 database.

2. Where can I get valid water table depth information ?

Thanks,

Brian Cooper

>In order to get subscribers talking, I would like to request that each
>new subscriber introduce themself as far as name, affiliation, areas of
>interest models worked with and one 'burning' issue which could serve
>as a focal point of discussion. This introduction, though helpful, is
>voluntary.

I am a lecturer in the Department of Agricultural Economics and Food
Marketing at the University of Newcastle upon Tyne, United Kingdom (more
details at foot of message).

For the past four years I have been part of a multi-disciplinary team
developing a suite of integrated models for exploring changes in
agricultural land use arising from alternative policy scenarios, and the
subsequent ecological and hydrological impacts. The models fall into three
broad categories: agricultural economics; ecology; hydrology. All rely on
publicly available data and use geographical information systems (GIS) for
data manipulation if not actual modelling. The models operate at the scale
of a river catchment and are integrated through a proprietary computerised
decsion support system.

To date, only two catchments have been studied in any detail. These are
the river Tyne (an upland, predominantly grassland catchment in northern
England) and the river Cam (a lowland, predominantly arable catchment in
eastern England). A good summary to the work is provided by Volume 38 of
the Journal of Environmental Planning and Management (the whole volume is
devoted to the project). Other relevant publications include:

Allanson, P., Moxey, A. & White, B. (1993). Measuring Agricultural
Non-Point Pollution for River Catchment Planning, Journal of Environmental
Management , 38, 219-232.

Moxey, A. & Allanson, P (1994). Areal Interpolation of Spatially Extensive
Variables: A Comparison of Alternative Techniques, International Journal of
Geographical Information Systems 8/5, 479-487.

Moxey, A. & Tiffin, R. (1994). Estimating Linear Production Coefficients
from Farm Business Survey Data: A Note, Journal of Agricultural Economics,
45, 381-385.

Moxey, A. & White, B. (1994). Efficient Compliance with Agricultural
Nitrate Pollution Standards, Journal of Agricultural Economics, 45, 27-37.

Moxey, A., McClean, C. & Allanson, P. (1995). Transforming the spatial
basis of agricultural census cover data, Soil Use and Management, 11, (In
press).

Moxey, A., White, B., Sanderson, R. & Rushton, S. (1995). An approach to
linking an ecological vegetation model to an agricultural economic model,
Journal of Agricultural Economics, 46, (In press).

The agricultural economic model is an aggregate-level linear programming
(LP) model of agricultural production. Land classes are used to split a
catchment into sub-regions, each with different production possibilites and
production relationships. My current bugbear is that the level of
aggregation incurred through this does not fit easily with the models
developed by my ecological and hydrological colleagues. Unfortunately,
the data necessary to disaggregate are not available. So, what I need is
some ad hoc, rule-based way of dissaggregating output from the LP model. I
am intrigued by the work of landscape ecologists (e.g. at the Oak Ridge
National Laboratory, USA) and feel sure that simulation modelling and
satellite data, in conjunction with GIS, offer a way forward. Any
suggestions or comments would be much appreciated.

Andy

-----------------------------------------------------------------------------
Andrew Moxey
Lecturer
Room 212
Dept. Agricultural Economics and Food Marketing
The University
Newcastle upon Tyne
NE1 7RU
UK

Phone +191 222 8607/6900
Fax +191 222 6720
e-mail a.p.moxey@ncl.ac.uk
----------------------------------------------------------------------------

>>In order to get subscribers talking, I would like to request that each
>> new subscriber introduce themself as far as name, affiliation, areas of
>> interest models worked with and one 'burning' issue which could serve
>> as a focal point of discussion. This introduction, though helpful, is
>> voluntary.
>>

I never got around to introducing myself earlier, so here's the rundown.

I am a veterinarian (OVC '89) with an MSc in tropical vet med from
Edinburgh University. I am interested in dairy and development issues.
Currently I am at Cornell university doing graduate work in agricultural
economics. I am modelling a disease control situation (looking at
rinderpest and ECF in cattle in sub-saharan Africa) with the objective of
maximizing NPV profits. Planning horizon and vaccination rates are
variable. State variables are numbers of animals in each cohort
(structured according to level of immunity). Difficulties at this stage
are probably universal - how to realistically build the model without
creating a monster, rationalizing the use of a dynamic herd structure as
opposed to a static herd structure, choosing epidemiologic parameters
essential to the model, etc.

Any contact from researchers involved in similar work would be appreciated!

Regards, David Hall

*****@*****@*****@*****@*****@*****@*****@*****@*****@*****@*****@****
>From the desk of: David C. Hall, Ithaca, NY

dch5@cornell.edu

David C. Hall, DVM, MSc
Dept. Agricultural Economics
411 Warren Hall, Cornell University
Ithaca, NY, U.S.A. 14853 Home phone/fax: (607)256-3248
*****#*****#*****#*****#*****#*****#*****#*****#*****#*****#*****#****

>Contents:
>who is Andrew Moxey (A.P.Moxey@newcastle.ac.uk (Andrew Moxey))
>

Who is Steve Jordan?

I am a farmer in Lompoc, CA. I grow vegetables under furrow and
drip irrigation.

What is a _farmer_ doing here?

Our water is salty (Ec 4.0) and I consider ourselves on the
bleeding edge of farming. I got interest in agmodels when the
local ASCS person wanted to install a Nleap program on my ranch.
He, Don Pitts, was going to monitor nitrogen and water, etc. He
moved back to Florida (more support). I was in a lawsuit with the
upstream urban users and the used models (surface and
groundwaterr) extensively. I guess my curiousity got me.

Burning issues? Proper n application, type and amount, under
drip. How to monitor, control, and vary due to crop conditions.

I am a member of staff at the University of North London and am looking
for information on the the following: agricultural products/outputs/trends
with changing climate/development aid inputs for The Gambia and Senegal.

Any information and/or contact names would be most welcome! Please reply
to the above address.

Many thanks
Dr. Graham Walters

The following is a good contact person in The Gambia:

M.B.S. Canteh
P.O. Box 2722 SEREKUNDA
TEL 220 370360
FAX 220 495413

He has a masters in Integrated Pest Management from North Carolina St.
Univ. in Raleigh, NC USA

--
Jack E Bailey
E-Mail : jbailey@wolf
Internet: jbailey@wolf.ces.ncsu.edu
Phone : (919) 515-6688

Try contacting Dr. David Acker, Office of International
Research & Development, Snell Hall 400, Oregon State
University, Corvallis, OR 97331, USA; e-mail:
ackerd@ccmail.orst.edu; ph: (503) 737-2228.

Shree

Shree Nath
Biosystems Analysis Group
Department of Bioresource Engineering
Oregon State University
Corvallis, OR 97331, U.S.A

>>In order to get subscribers talking, I would like to request that each
>> new subscriber introduce themself as far as name, affiliation, areas of
>> interest models worked with and one 'burning' issue which could serve
>> as a focal point of discussion. This introduction, though helpful, is
>> voluntary.
>>

Hello,

I am Adrian Wadley, and I work within the Environmental Sciences Department
of Zeneca Agrochemicals in the UK. We also have a considerable activity in
the Environmental Sciences area in the US although the majority of our modelling

activity (for EU and US) is based in the UK (group of 5 people). We use a range

of models but have concentrated on PRZM, PRZM2 and EXAMS of the EPA
derived models. We use a range of European models such as PESTLA, PELMO
and expect to be using MACRO. Our work concentrates on contributing to risk
assessment and interpretation of our own studies.

Interests include deriving and obtaining agreed data sources for reliable inputs
to
models hence my current query below,

Does anybody know of a source of cropping dates in the US that is more up to
date than 'Usual Planting and Harvesting Dates', USDA Agricultural Handbook
No. 283, published 1972. I am particularly interested at the moment in
planting and harvest dates for Corn (Maize), but would like details for all
important agricultural crops in the US.

Many Thanks

Adrian Wadley

100561,1525@compuserve.com

>>In order to get subscribers talking, I would like to request that each
>> new subscriber introduce themself as far as name, affiliation, areas of
>> interest models worked with and one 'burning' issue which could serve
>> as a focal point of discussion. This introduction, though helpful, is
>> voluntary.
>>

I'm Eric Fraint. An accountant by training, I do a considerable amount of
work building financial models with Excel. I joined this ag-model group
because of this interest in financial modeling. Therefore, though I have no
experience with ag-models, I am very interested in the types of spreadsheet
based modeling being done in this area.

Obligatory intro:

I'm Bill Capehart, Penn State Meteorology. I do remote sensing and modeling
of soil moisutre. As for for long term soil moisture modeling I need
a means estimating vegetation parameters (plant height, LAI, rootdepth,
frac. veg cover etc) as functions of time and easily obtained meteorological
variables...

Adrian: With respect to cropping dates for crops in the US, I suggest the
following: "Major World Crop Areas and Climatic Profiles", USDA,
Agricultural Handbook 664. It was published last year. Obviously its
scope goes beyond the US and cropping dates. It is available from:
ERS-NASS, 341 Victory Drive, Herndon,VA 22070. It costs $(US)20, add an
additional 25 percent for non-US addresses. In the US and Canada, one
can call toll free 1-800-999-6779 to order copies.
Albert Weiss

ALBERT WEISS, DEPT. OF AGRICULTURAL METEOROLOGY
UNIVERSITY OF NEBRASKA-LINCOLN, LINCOLN,NE 68583-0728
VOICE (402)472-6761, FAX (402)472-6614
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From: ADRIAN WADLEY <100561.1525@compuserve.com>
To: Multiple recipients of list <agmodels-l@unl.edu>
Subject: Usual Planting and Harvesting Dates

>>In order to get subscribers talking, I would like to request that each
>> new subscriber introduce themself as far as name, affiliation, areas of
>> interest models worked with and one 'burning' issue which could serve
>> as a focal point of discussion. This introduction, though helpful, is
>> voluntary.
>>

Hello,

I am Adrian Wadley, and I work within the Environmental Sciences Department
of Zeneca Agrochemicals in the UK. We also have a considerable activity in
the Environmental Sciences area in the US although the majority of our modelling

activity (for EU and US) is based in the UK (group of 5 people). We use a range

of models but have concentrated on PRZM, PRZM2 and EXAMS of the EPA
derived models. We use a range of European models such as PESTLA, PELMO
and expect to be using MACRO. Our work concentrates on contributing to risk
assessment and interpretation of our own studies.

Interests include deriving and obtaining agreed data sources for reliable inputs
to
models hence my current query below,

Does anybody know of a source of cropping dates in the US that is more up to
date than 'Usual Planting and Harvesting Dates', USDA Agricultural Handbook
No. 283, published 1972. I am particularly interested at the moment in
planting and harvest dates for Corn (Maize), but would like details for all
important agricultural crops in the US.

Many Thanks

Adrian Wadley

100561,1525@compuserve.com

Dear all!

Bill Capehart wrote
> As for for long term soil moisture modeling I need
> a means estimating vegetation parameters (plant height, LAI, rootdepth,
> frac. veg cover etc) as functions of time and easily obtained meteorological
> variables...

I think these are very interesting questions - for both directions
- modelling soil moisture from vegetation parameters and
- modelling NPP (and other vegetation variables) from environmental conditions

For crude first steps I could think of

- estimating LAI from AET/PET or ET in general using the approach of Woodward
This should work quite well in water limited areas
- estimate frac. veg cover as exp(-0.5*LAI) or so
- I remember some relation of plant height to maximal soil moisture deficit
expressed as cumulative soil water potential (ref in E. D. Schulze
"Plant life forms and their Carbon, Water and Nutrient relations" to
Balding and Cunningham 1974 -sorry I don't have more info...)

Maybe "Estimating Forest Growth and Efficiency in Relation to Canopy Leaf Area"
by R.H. Waring in Adv. Ecol. Res. 1983 might be helpful too.
Root depth might be the hardest I guess.

Maybe you knew all this already...

However I think it would really be nice if some more poeple would respond to
these questions -at least for me. I find them most important in relation
to ecophysiological based simulations of vegetation properties.

Thanks for your time and interest

Joerg Kaduk *
***
MPI for Meteorology kaduk@dkrz.d400.de *****
Bundesstr. 55 Phone + 40 41173 282 ***
D-20146 Hamburg Fax + 40 41173 298 #
---------------------------------------------------------------------- ###

Do you have more precise information on modelling with excel. What types
of specific modelling do you do with financial records.

There are a plethora of crop growth simulation models more or less
available. These models simulation plant growth based on plant
growth processes' response to soils and atmospheric conditions, and
simulate changes in soil condition based on simulated plant response.

Being more or less mechanistic, they are complex. Some are relatively
easy to use (the complexity is transparent to the user), others are
much more difficult to use. Some are written in a highly modular
programming style so they are relatively easy to link with other models,
most are not.

Unfortunately most are not available on ftp sites. My potato model,
SIMPOTATO is -- ftp.tricity.wsu.edu in pub/SIMPOTATO. Any others?

Tom

Tom Hodges, Cropping Systems Modeler
USDA-ARS email: thodges@beta.tricity.wsu.edu
Rt. 2, Box 2953-A voice: 509-786-9207
Prosser, WA 99350 USA Fax: 509-786-9370
== ## Rent this space ## ==
If this represents anything, it is only my opinion.

On Thu, 23 Feb 1995, J.Kaduk wrote:

> Bill Capehart wrote
> > As for for long term soil moisture modeling I need
> > a means estimating vegetation parameters (plant height, LAI, rootdepth,
> > frac. veg cover etc) as functions of time and easily obtained meteorological
> > variables...
>
> I think these are very interesting questions - for both directions
> - modelling soil moisture from vegetation parameters and
> - modelling NPP (and other vegetation variables) from environmental conditions
>

On Thu, 23 Feb 1995, Hodges wrote:

> There are a plethora of crop growth simulation models more or less
> available. >

Would there be a list of all the crop growth programs that are available
with source code?

> Unfortunately most are not available on ftp sites. My potato model,
> SIMPOTATO is -- ftp.tricity.wsu.edu in pub/SIMPOTATO. Any others?
>
> Tom
>
I have been developing a potato crop growth model and would like to release
it soon. It is far simpler than Tom's but requires less input. I will
post details here when I have it ready and when I can find a ftp site to
put it on. I have tried to make it modular although it is written in
turbo pascal (which nobody else seems to use...). I use pascal because it
is possible to make the code very easy to follow for non/novice programmers.

Graham lewis

My name is Guy Canku. I work as the Natural Resources Planner for the
Sisseton-Wahpeton Sioux Tribe. Our location is in the northeastern corner of
South Dakota and our reservation includes SD, ND and MN. I do some GIS work,
data inventory of natural resources, plan development. I am gearing up for
agricultural development and any suggestions, references, and opinions in
development is appreciated

Howdy,
Cornell has a data base giving the usda summaries of planting
dates and dates of various phenological stages by county for
the US if I remmember correctly. There is also a bunch of other
information on just about every thing you wanted to know about
crop summaries in surrounding dirrectories. The gopher address
is:

gopher://usda.mannlib.cornell.edu:70/1

There is a fair amount of information there so good luck not
getting lost. I am not too sure as to the technique that is
used in obtaining the dates and the data, but if anyone would
want to comment on this it would be much appreciated.

Hope that this can be of some help,

Daniel R. Fuka
Quetzal Computational Associates
dan@quetzalcoatl.com

International Conference

AGRICULTURAL AND BIOLOGICAL ENGINEERING -

NEW HORIZONS AND NEW CHALLENGES

to be held at

University of Newcastle upon Tyne, UK

20 -23 September 1995

Conference Theme

The conference is intended to provide a forum for discussion of the emerging discipline of
biological engineering and its relationship to agricultural engineering. The explosion of
knowledge in the biological sciences and the increasing quantification of biological
phenomena presents a great opportunity for those engineers who already work with
biological materials and systems to make explicit their role as biological engineers and to
expand the range of their activities. The theme of the conference links traditional
agricultural engineering activities with newer biologically based engineering and seeks to
explore the challenges and opportunities arising from this conjunction.

New Horizons
The study of biological systems is becoming more quantitative with an
emphasis on correlating material characteristics and behaviour across
scales. Advances in agricultural biotechnology and genetic engineering are resulting in
the development of new materialsand processing techniques. Modelling of complex environmental
systems is increasing and has highlighted the need for improvements in sensing and measurement
technology.

New Challenges
In developed economies high productivity of many staple agricultural products using high
input production systems is being questioned due to surplus production and environmental
degradation. Equally many developing nations wish to avoid dependence on inappropriate
agricultural technology desiring instead to find ways of achieving sustainable development
of their natural resources. Remediation of past environmental degradation and the design
and management of biosystems for the mutual benefit of mankind and nature is a worldwide
concern.

Conference Organisation
The conference will comprise six formal sessions, a poster session and a workshop session over
three days. Five formal sessions will include a keynote address and five state-of-the-art contributions
followed by discussion. The final session will include two keynote papers on the theme of
"Education & Training", which will provide an introduction to the informal workshop session,
where the topic will be further explored in smaller specialist groups.

Session 1 Environmental Management and Amenity Engineering
Keynote : Prof J R O'Callaghan, UK
Scope : Management of the rural environment for amenity, conservation and productive purposes
demands knowledge of the interactions between environmental and economic systems and calls for
development of decision-support tools.
Topics covered will include :
* clean technology concepts - farming as an engineering process
* identification of sustainable production systems in irrigated regions of Australia
* decision support software for reducing agricultural pollution in France
* land-use strategy and environmental conservation in Japan

Session 2 Biosystems and Ecological Engineering
Keynote : Dr S E Jorgensen, Denmark
Scope : Ecological engineering has been defined as the design and manipulation of biosystems
for the mutual benefit of mankind and nature.
Topics covered will include :
* hydrology and management of wetland habitats
* restoration and rehabilitation of disturbed habitats
* design of a productive biosystem based on land treatment of effluent
* design of a microbial biosystem for remediation of polluted land

Session 3 Bioinstrumentation and Environmental Measurement
Keynote : Prof W F McClure, USA
Scope : The development of systems for sensing and quantifying biomaterial characteristics
and measuring environmental variables is a necessary prerequisite to optimisation and control of biomaterial production and bioprocessing
operations and implementation of many environmental monitoring and management schemes.
Topics covered will include :
* use of machine vision and spectrophotometric techniques for detection of plant disease
and plant/weed discrimination.
* sensors and neural networks for fruit handling process and machinery evaluation
* simulation and monitoring of grapevine infection
* developments and future directions for in situ environmental measurement

Session 4 Biomaterials and Bioprocess Engineering
Keynote : Prof A Ishizaki, Japan
Scope : Cooperation between biochemists, biologists and engineers leading to the
development of new biomaterials and processes for industrial and environmental use and
involves study of chemical/physical property interactions, material behaviour at different
spatial resolutions, bioprocess control and environmental impact.
Topics covered will include :
* treatment of fibre crops for industrial use
* microbial treatment of sewage sludge
* fluid expression during biomaterial compaction
* measurement and visualisation of water transfer dynamics in biomaterials

Session 5 Trends in Agrotechnology
Keynote: Prof J. De Baerdemaeker, Belgium
Scope : The new challenges facing agrotechnology are how to implement
alternative land use, how to improve control of the agricultural systems, enhance the
quality of agricultural products while protecting the environment.
Topics covered will include:
* Precision farming: further developments
* Agrotechnology in sub Saharan Africa
* renewable energy opportunities for agiculture
* mechanisation: managing a changing resource

Session 6 Education and Training for Agricultural / Biological Engineers
Keynote : Prof RE Garrett, USA; Prof G Wall, NZ
Scope : Changes in education are often the most difficult to bring about but they are also
crucial for ensuring effective response to the new opportunities and challenges. We wish to
open the debate in Europe on how to educate the next generation of agricultural/biological engineers.
Topics covered will include:
* new curricula ?
* continuing professional development

Proceedings
Keynote papers and abstracts of oral and poster presentations will be
provided at the Conference. Keynote, selected papers and synposes will be published in book
form and distributed after the Conference.

Offers of contributions to the poster and workshop sessions are invited. Abstracts of not
more than 300 words should be submitted not later than 30 April 1995.

Registration Fee
The delegate registration fee of stlg175 will cover attendance at all Conference sessions, official
receptions, lunches, refreshment breaks, and a full copy of the edited Conference proceedings.

Language
The Conference language is English

Venue
The Conference will be held in the Herschel Building, University of Newcastle, Newcastle upon
Tyne, UK.

Accomodation
Accomodation is in a University Hall of Residence which is situated about 10 min walk from the
University.

Registration
Contact :

Marion Turner Tel : +44 191 222 6891
Conference Secretary Fax: +44 191 222 6720
Agriculture Building
University of Newcastle
Newcastle upon Tyne
NE1 7RU, UK

or

Dr. John F. Favier
Dept Agricultual & Environmental Science
University of Newcastle Tel : +44 191 222 8770
Newcastle upon Tyne Fax : +44 191 222 5228
NE1 7RU, UK e-mail: john.favier@ncl.ac.uk

**************************************************************************

In response to your question, my Excel work is of two basic types: the first
is where the model is to be manipulated by myself; the second is where I'm
developing a turnkey application to be used by one of my clients and members
of their staff.

In either case the financial model consists of a mathematical represenation
of the particular business entity or of a particular business problem.
Examples of business problems lending themselves to this approach are
Economic Order Quantity analysis, manufacturing production scheduling, and an
unlimited variety of management reporting approaches.

I do a great deal of customization, particularly for turnkey applications.
Such customization typically involves menu and toolbar modifications and
programming in Visual Basic.

Hope this helps. May I ask your reason for inquiring?

Eric Fraint
YPTC@aol.com

I am a trade policy analyst with Agriculture Canada working on NAFTA
/GATT and trade policy issues. Apart from EXCEL, I use other software
pakages (TSP & LIMDEP) in the course of my duties. Since EXCEL was
recently introduced to most staff members (6mths), I was somewhat
curious as to its capabilties to provide analyses to trade policy issues.
Regards Richard

Hello,
my name is Helmut Schaefer. I am a chemical engineer, working at Bayer, Germany
in the pesticide environmental fate department. I am generally interested in the
application of simulation models for the prediction of environmental
concentrations of pesticides in the compartments soil, air, ground water and
surface water.
Currently I am concerned with the problem of kinetic adsorptions effects. There
are modells on the market which allow the simulation of these effects (i.e
VARLEACH). But I am not sure about how these models can be parametrized, this is
what is the best experimental setup to gain these model parameters. Has anybody
expierence in this field?
The second problem I am facing is that I am working with a version of the
weather generator WGEN developed by Richardson and Wright from 1988. Probably
there is a newer (better) version available. Can anybody give me a contact
adress?
Thank you.
Best regards.
Helmut Schaefer

In response to Helmut Schaefer's (debay5j9@ibmmail.com) question about
weather generators like WGEN, Richardson sent me the latest version
in Feb. 1993. The same algorithm was being used as in WGEN from 1988.
No plans for any other research were underway at that time. You might
want to contact him directly to find out if his group has updated the
software any more.

The 1993 version is now in BASIC and runs on the PC with a graphical
interface. The user selects the part of the US she wants to model
with a mouse. Then the Richardson parameter file is built for
the closest weather station, and x number of years of daily precipitation
and temperatures (minimum and maximum) are generated, where x is user
defined. The program is called CLIMATE.BAS and has information on
the 48 states of the US only. The model was developed at the US Dept of
Agriculture (USDA).

For Europe and South America, I use the WGENPAR program to generate parameters
based on historical weather, and then WGEN to simulate 100+ years of weather.

The last address I have is:

Clarence Richardson
Laboratory Director
USDA ARS
808 E. Blackland Rd.
Temple, TX 76502-9601
817-770-6500
817-770-6561 (FAX)

-----------------------------------------------------

Background on myself: I am a chemical engineer with training in
modeling and artificial intelligence. I use the simulated weather
patterns for Monte Carlo modeling of leaching and carryover potential
for pesticides in the soil/water environment. Models that I use the
most include CALF (and FLOWREV2), PATRIOT (US EPA), PRZM-II (US EPA),
and internal models.

I would be interested in finding out about any knowledge-based systems
or artificial neural networks that have been successfully applied to
agricultural chemical problems.

Karl Schnelle
DowElanco
Indianapolis, IN USA
kschnelle@dowelanco.com

I am new to the list and would appreciate someone directing me to the FAQ
file. Also, does anyone know of a ftp site for WGEN or similar models?

Thanks in advance

Marshall Taylor
Resources Planning Associates, Inc.
231 Langmuir Bldg. 95 Brown Rd.
Ithaca, NY 14850 (607) 257-4305

Helmut: See Pickering et al. (1994) " WeatherMan: A utility for managing
and generating weather data", Agronomy Journal 86:332-337 for a description
of a user-friendly version of WGEN and SIMMETEO. The latter can use monthly
inputs. The software is available from: Dr. Gordon Tsjui, IBSNAT Project,
University of Hawaii, 2500 Dole St., 22 Krauss Hall, Honolulu, Hawaii 96822.
The cost is $(US) 50. Also see Meinke et al.(1995), " Evaluation of radiation
and temperature data generators in the Australian tropics and sub-tropics
using crop simulation models", Ag and Forest Meteorology 72:295-316. In the
Dept of Theoretical Crop Production Ecology or CABO at the Agricultural
University in Wageningen, Netherlands, they developed SIMWTH which is like
WGEN except it can be used in the tropics. It contains an additional harmonic
to handle bimodal distributions of weather variables.
Albert Weiss

ALBERT WEISS, DEPT. OF AGRICULTURAL METEOROLOGY
UNIVERSITY OF NEBRASKA-LINCOLN, LINCOLN,NE 68583-0728
VOICE (402)472-6761, FAX (402)472-6614
E-MAIL AGME011@UNLVM.UNL.EDU

Helmut:
The return address you gave was not operative, so I am bothering
everyone with this reply.

I was interested in both of your questions. I have a model
for transport of pesticides (with other uses as well), primarily for
agricultural simulation, which looks at pesticides in surface runoff as
well as in the root zone. You may be interested in it. But an option in
my model is to simulate kinetic adsorption process in soil transport. I do
not have an answer as to how to parameterize it, however. I believe that
kinetic rate coefficients are only found in the laboratory, but I think a
well designed field experiment could be conducted to infer appropriate
values for a given compound. If you find any information on kinetic
rate coefficients for any common pesticides, I would be grateful for you
to share it, and I will gladly share my model (Opus) with you for your
evaluation.
There is a newer version of WGEN, in the form of a model written in
BASIC with a User Manual:
Hanson, C.L., K.A. Cumming, D.A. Woolhiser, and C.W.
Richardson, "Microcomputer Program for Daily Weather Simulation in
the Contiguous United States." USDA Agricultural
Research Service, Publication ARS-114, July 1994, 38 pp.
Write to
Clayton Hanson
ARS-USDA
NW Wateshed Res. Center
800 Park Blvd. Plaza IV
Suite 105
Boise ID 83712-7716

He should have a copy to send you free of charge. You are already aware
that you will have to develop the weather parameters for Germany,
since the model parameter maps only cover the US. And, I would be
interested if you have developed such parameters from your weather data,
what they are. I have people using Opus, which has a version of WGEN built
in, in Germany and in Austria.

Gruss Gott...
Roger Smith
Roger E. Smith
roger@lily.aerc.colostate.edu

Mr. Fraint inquired about the use of spreadsheets for developing ag
models. My name is Chris Butts, an agricultural engineer at the USDA,
ARS, National Peanut Research Lab. Our research team consists of several
engineers, microbiologists, and an ag economist. Our ag economist,
Marshall Lamb, has developed a whole-farm planning model using Quattro
pro. the model allows the farmer to input detailed crop/enterprise
budgets and crop rotations for each field and farm that he/she operates.
The model then uses LP to optimize allocation of resources for each
crop/enterprise. the model is in BETA testing, with several of the
farmer/cooperaters using the output as supplements to thier production loans.

for more information contact me or Marshall Lamb at the address below.

************************************************************************
* Chris Butts * cbutts@asrr.arsusda.gov
*
* USDA, ARS *****************************
* National Peanut Research Laboratory * Phone: 912-995-7431 *
* 1011 Forrester Dr., SE *****************************
* Dawson, Georgia 31742 * FAX: 912-995-7416 *
************************************************************************

I am very interested in this area of work. At the present time I am
doing a similar thing by using Excel and Visual Basic to develop a
DSS for agricultural machinery selection. From what I have seen so far I think it
will be a very productive route, due partly to the facilities of
Excel and the integration provided by Visual Basic.

I would most interested to know more about your work. I am on leave
of absence from my university but I come in once a week or so to pick
up mail etc. I would like to here more and perhaps we can exchange a
few ideas.

Regards, Ian.

development) decisions by policy makers

Hello, I am an employee of Agriculture Canada. I have reviewed the
literature on R&D models and observed that researchers have used a
variety of models. Some of these models are econometric (Huffmann et al
at Iowa), while others are optimization models (sort of LP type models).
Has anyone developed customized models that can run on a PC to provide
policy makers with information in terms of how to allocate scarce financial
resources among competiting activities. This model could be applied at a
state/ provincial/ experimetal station level. It could also be user friendly to
allow non-economists to have an appreciation of its utility.

Wanted to make you all aware of yet another spreadsheet-based model that I and
a group of co-workers have prepared, called TA-DA! Copies of the EXCEL-based
program are available free of charge to anyone who is interested. Just send me
a note with your mailing address.

David Gustafson
Monsanto
digust@ccmail.monsanto.com

Here is the abstract of a paper given about the model at the ASAE winter
meeting in Atlanta on December 15, 1994:

TA-DA!: A New Geographically-Based, Probabilistic Exposure Modeling System For
Crop Chemicals in the Environment

T.L. Estes(1), D.I. Gustafson(2), K.A. Olefirowicz(1), and B.J. Smith(2)

(1) Rhne-Poulenc Ag Company, 2 T.W. Alexander Drive, Research Triangle Park,
NC 27709
(2) Monsanto Agricultural Group, 700 Chesterfield Parkway N., St. Louis, MO
63198

TA-DA! is a new, geographically-based probabilistic modeling system for
predicting concentrations of agricultural chemicals in ground and surface
water. This prototype has been produced using MicroSoft Excelt4.0, and
includes data for seven midwestern states (IL, IN, IA, KS, MN, NE, WI).
Subsequent versions of the program using different software tools are in
development for the remainder of the US and for the EU countries.

Introduction

A variety of modeling systems have been proposed for predicting environmental
concentrations of crop chemicals. These have ranged in complexity from simple
screening procedures to full-fledged simulation models requiring hundreds of
input parameters and hourly climatic data. In the regulatory management of
crop chemicals, it has become increasingly important to understand both the
geographic distribution of the potential exposure and the probability that user-
selected exposure levels would be observed, given the temporal variability in
climatic conditions, the uncertainties of the input parameters, and the
intrinsic errors within the models themselves.

TA-DA! is a new model that is being developed to address this regulatory need
by providing an entirely graphically-based, one-screen modeling system for
predicting environmental concentrations of crop chemicals. It provides both
the geographic and probabilistic distribution information now required in
today's more sophisticated approach to managing the use of crop chemicals.

The on-screen elements of TA-DA! include two color-coded maps of seven key
Midwestern states (one each for ground and surface water). Predicted
environmental concentrations for flowing surface water and shallow ground water
are shown as probability exceedence curves. The curves are color-coded to
match the maps. Parameters such as aquifer depth, thickness, and porosity are
entered into a spreadsheet, as are values for both the persistence (DT50) and
soil-mobility (KOC) of the chemical. Default values for these and other
physical properties for commercially-available pesticides are taken from the
USDA/ARS pesticide physical property data base. Soil properties are taken from
the USDA/SCS SOILS5 data base, and cropping information is from the 1987 USDA
Ag Census. Climatic data for the entire country are geographically linked to
soils using the Climatedatat Monthly Summary data base available from
Hydrosphere Data Products.

The primary advantage of TA-DA! is its ability to provide instantaneous on-
screen depiction of both the geographic and probabilistic distributions of
expected environmental concentrations (EEC's) based on the most accurate data
available. This confers a powerful interactive capability to rapidly assess
the possible impact of mitigation measures such as geographic restrictions.
This brief paper describes the underlying theory within TA-DA!, its
probabilistic basis, its data sources, and the techniques used to implement it
within MicroSoft Excelt.

Reply to: RE>Another Spreadsheet-Based Model

Please explain in more detail exactly what TA-DA does does.
Thanks
Ted
------------------------------
Date: 2/28/95 3:15 PM
To: Zobeck, Ted
From: agmodels-l@unl.edu

Received: by lubbock.ars.ag.gov with SMTP;28 Feb 1995 15:14:11 -0600
Received: by crcnis1.unl.edu id AA19061
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-0600
Date: Tue, 28 Feb 1995 15:01:20 -0600
Message-Id: <9501287940.AA794011040@ccmail.monsanto.com>
Originator: agmodels-l@unl.edu
Errors-To: jp@unlinfo.unl.edu
Reply-To: <agmodels-l@unl.edu>
Sender: agmodels-l@unl.edu
Version: 5.5 -- Copyright (c) 1991/92, Anastasios Kotsikonas
From: DIGUST@ccmail.monsanto.com
To: Multiple recipients of list <agmodels-l@unl.edu>
Subject: Another Spreadsheet-Based Model

Wanted to make you all aware of yet another spreadsheet-based model that I
and
a group of co-workers have prepared, called TA-DA! Copies of the EXCEL-based

program are available free of charge to anyone who is interested. Just send
me
a note with your mailing address.

David Gustafson
Monsanto
digust@ccmail.monsanto.com

Here is the abstract of a paper given about the model at the ASAE winter
meeting in Atlanta on December 15, 1994:

TA-DA!: A New Geographically-Based, Probabilistic Exposure Modeling System
For
Crop Chemicals in the Environment

T.L. Estes(1), D.I. Gustafson(2), K.A. Olefirowicz(1), and B.J. Smith(2)

(1) Rh#215#ne-Poulenc Ag Company, 2 T.W. Alexander Drive, Research Triangle
Park,
NC 27709
(2) Monsanto Agricultural Group, 700 Chesterfield Parkway N., St. Louis, MO

63198

TA-DA! is a new, geographically-based probabilistic modeling system for
predicting concentrations of agricultural chemicals in ground and surface
water. This prototype has been produced using MicroSoft Excelt4.0, and
includes data for seven midwestern states (IL, IN, IA, KS, MN, NE, WI).
Subsequent versions of the program using different software tools are in
development for the remainder of the US and for the EU countries.

Introduction

A variety of modeling systems have been proposed for predicting environmental

concentrations of crop chemicals. These have ranged in complexity from
simple
screening procedures to full-fledged simulation models requiring hundreds of
input parameters and hourly climatic data. In the regulatory management of
crop chemicals, it has become increasingly important to understand both the
geographic distribution of the potential exposure and the probability that
user-
selected exposure levels would be observed, given the temporal variability in

climatic conditions, the uncertainties of the input parameters, and the
intrinsic errors within the models themselves.

TA-DA! is a new model that is being developed to address this regulatory need

by providing an entirely graphically-based, one-screen modeling system for
predicting environmental concentrations of crop chemicals. It provides both
the geographic and probabilistic distribution information now required in
today's more sophisticated approach to managing the use of crop chemicals.

The on-screen elements of TA-DA! include two color-coded maps of seven key
Midwestern states (one each for ground and surface water). Predicted
environmental concentrations for flowing surface water and shallow ground
water
are shown as probability exceedence curves. The curves are color-coded to
match the maps. Parameters such as aquifer depth, thickness, and porosity
are
entered into a spreadsheet, as are values for both the persistence (DT50) and

soil-mobility (KOC) of the chemical. Default values for these and other
physical properties for commercially-available pesticides are taken from the
USDA/ARS pesticide physical property data base. Soil properties are taken
from
the USDA/SCS SOILS5 data base, and cropping information is from the 1987 USDA

Ag Census. Climatic data for the entire country are geographically linked to

soils using the Climatedatat Monthly Summary data base available from
Hydrosphere Data Products.

The primary advantage of TA-DA! is its ability to provide instantaneous on-
screen depiction of both the geographic and probabilistic distributions of
expected environmental concentrations (EEC's) based on the most accurate data

available. This confers a powerful interactive capability to rapidly assess
the possible impact of mitigation measures such as geographic restrictions.
This brief paper describes the underlying theory within TA-DA!, its
probabilistic basis, its data sources, and the techniques used to implement
it
within MicroSoft Excelt.

Hello is as good as anyway to begin. I am working on a project where we
are trying to scale-up from leaf gas exchage measurements to canopy conditions.
We need to calculate hourly values of soil heat flux density and albedo.
Does anyone know of "simple" (which is in the eyes of the beholder)
algorithms to calculate these quantities? We have hourly values of
meteorological variables (solar radiation,temperature,RH, wind speed,etc.) from
an automated weather station ,knowledge of soil physical properties, LAI,
and leaf nitrogen data available. We are working with maize.Thanks for your
help.
Albert Weiss

ALBERT WEISS, DEPT. OF AGRICULTURAL METEOROLOGY
UNIVERSITY OF NEBRASKA-LINCOLN, LINCOLN,NE 68583-0728
VOICE (402)472-6761, FAX (402)472-6614
E-MAIL AGME011@UNLVM.UNL.EDU

I have read the discussions of "spreadsheet based models" with some
interest. Am I wrong or is this another case of an emphasis on usability,
presentation, etc, without regard to soundness of soil physics and
chemistry? The sales pitch in a recent message used all the right words,
such as on screen, color coding, "powerful" output, but said absolutely
nothing about how the model figures out pesticide movement in a complex and
heterogeneous soil profile. Let us turn from magic and salesmanship
towards process science, and be more honest investigators and less
salesmen/women.
(I'll bet this comment gets someone worked up...)
Roger E. Smith
roger@lily.aerc.colostate.edu

I agree Roger. And I would go on at some length about those who apply
models willy-nilly without a great deal of thought about why they need to
use a model at all or at even greater length about examples where the
modelling seems to have become an end in itself rather than a research
(or decision support) tool but it is far too early in the morning to
raise my blood pressure that much.

Val Snow
________________________________________________________________________
Val Snow CSIRO Division of Water Resources
vos@adl.dwr.csiro.au Private Mail Bag No. 2
61 08 303 8743 (Phone) Glen Osmond, Adelaide
61 08 303 8750 (FAX) South Australia, 5064

On Tue, 28 Feb 1995, Roger Smith wrote:

> I have read the discussions of "spreadsheet based models" with some
> interest. Am I wrong or is this another case of an emphasis on usability,
> presentation, etc, without regard to soundness of soil physics and
> chemistry? The sales pitch in a recent message used all the right words,
> such as on screen, color coding, "powerful" output, but said absolutely
> nothing about how the model figures out pesticide movement in a complex and
> heterogeneous soil profile. Let us turn from magic and salesmanship
> towards process science, and be more honest investigators and less
> salesmen/women.
> (I'll bet this comment gets someone worked up...)
> Roger E. Smith
> roger@lily.aerc.colostate.edu
>

I have a great deal of sympathy for the comments of Roger Smith below.
However there is a place for ALL kinds of efforts in this business of
making our agricultural practices more sound. But as Roger says,
sound physics and chemistry (add plant physiology and micro-
meteorology as well) are an essential basis for good work.

The most complex research models can provide a basis for vastly
simpler application models, when complex interactions can be
approximated for specific sets of conditions. Spreadsheet models
might be a good way to do that approximation if the underlying
processes are understood.

Tom Hodges

Tom Hodges, Cropping Systems Modeler
USDA-ARS email: thodges@beta.tricity.wsu.edu
Rt. 2, Box 2953-A voice: 509-786-9207
Prosser, WA 99350 USA Fax: 509-786-9370
== ## Rent this space ## ==
If this represents anything, it is only my opinion.

On Tue, 28 Feb 1995, Roger Smith wrote:

> I have read the discussions of "spreadsheet based models" with some
> interest. Am I wrong or is this another case of an emphasis on usability,
> presentation, etc, without regard to soundness of soil physics and
> chemistry? The sales pitch in a recent message used all the right words,
> such as on screen, color coding, "powerful" output, but said absolutely
> nothing about how the model figures out pesticide movement in a complex and
> heterogeneous soil profile. Let us turn from magic and salesmanship
> towards process science, and be more honest investigators and less
> salesmen/women.
> (I'll bet this comment gets someone worked up...)
> Roger E. Smith
> roger@lily.aerc.colostate.edu
>

>Hello,
>my name is Helmut Schaefer. I am a chemical engineer, working at Bayer, Germany
>...(snip)
>Currently I am concerned with the problem of kinetic adsorptions effects. There
>are modells on the market which allow the simulation of these effects (i.e
>VARLEACH). But I am not sure about how these models can be parametrized, this
>is
>what is the best experimental setup to gain these model parameters. Has anybody
>expierence in this field?
>...
I have been measuring the kinetics of sorption of pesticides in soils and the
results have become part of the research model RZWQM. The model allows for
three options (a) instantaneoud equilibrium (b) partial instntaneous approach
to equilibrium (c) kinetic approach throughout using the 2-sequential- i
equilibrium model. I suggest (b) seems to be a good compromise and has
also been successful in column leahing studies. RZWQM also allows for a
slower "binding" step that mimics the often-observed increasingly less-
desorbable behavior of pesticides in soils after weeks to months of residence
time.

This is a hot topic in the pesticide modeling area these days. Would you,
Dr. Schaefer, describe how VARLEACH works in this regard? Also, Dr. Smith,
how about OPUS? The fact is, kinetic studies with real soils and pesticides
indicate that even in well-stirred batch studies the sorption process is
complex. How much of this complexity needs to be incorporated into our
models?
Don Wauchope

Hello !

My name is Brian Cooper and I am a PhD student at Purdue University

in West Lafayette Indiana (Go Boilermakers !!!!). I am currently working

on groundwater vulnerabilty models such as DRASTIC and SEEPAGE. These models

take into account various soil attributes as well as certain hydrgeologic

features which include vadose zone and aquifer media, net aquifer recharge,

hydraulic conductivity, and water table depth. I hope to obtain enough data

to map the entire midwest region. I will then varify these maps with

USGS and DNR well monitoring sites. I will also be using pesticide transport

models such as PATRIOT, GLEAMS, and CMLS. If everything goes well I will be

presenting this information at the ASAE conference in Chicago and the AWRA

conference in Houston.

Later

Cooper

In response to Abert Weiss's question about soil heat flux and albedo, I have
just (this morning!) finished a Visual Basic program for calculating
evapotranspiration flux from automatic weather station (AWS) data on hourly
(or shorter) timesteps. This can be used with an AWS with the same config-
uration as quoted (i.e. solar radiation but not net radiation). I have
estimated net radiation and soil heat flux in the following way:-

1. Longwave radiation is estimated from the longwave radiation flux
for clear skies (from Monteith and Unsworth, 1990) reduced according to the
ratio of actual solar radiation / potential for the time of day, year and
location. This is the method used by Campbell Scientific in their on-line
calculation of ET for their AWS and is described in a Technical Note produced
by them.

2. Net radiation is calculated from solar radiation, the albedo of the surface
and the longwave radiation (above). Albedo is assumed to be constant for the
given land cover. (You wanted something more elegant than this didn't you?).

3. Soil heat flux is taken to be 0.1 * net radiation. This is a major
simplification.

The above appears to work OK during the daytime (when ET is taking
place). It is probably not very good for night-time net radiation
or soil heat flux, but then as the stomata are closed and the canopy
resistance is high, the simplification does not have a major effect on ET
and therefore it suits my purposes!

My program for ET will work with almost all AWS that produce an ASCII data
file, and uses the Penman-Monteith method to calculate ET. Default
resistances and albedos are given for standard land covers, but these can
be changed for other cover types. Further details available on request!

---------------------------------------------------------------------
Tim Hess
Department of Water Management
Silsoe College
Cranfield University
Silsoe Tel (0)1525 863292
Bedford, MK45 4DT Fax (0)1525 863000
UK e-mail t.hess@silsoe.cranfield.ac.uk
----------------------------------------------------------------------

I noted with interest (and suppressed glee) the posted-complaints that
yesterday's brief description of TA-DA! was long on "ease-of-use" and short on
physics. Having written various models with a wide-spectrum of physics-based
complexity, I must say that getting the physics right is only a very small part
of writing a USEFUL model. The physics behind TA-DA! are admittedly simple,
but so is F=m*a, which has held up reasonably well over the past few centuries.

The primary technical advantage of producing a model in a spreadsheet
environment is the tremendous ease of accessing, cutting, and pasting vast
amounts of relevant DATA (please disregard the anagram) into the model. But
there are numerous other features making the model more useful, including the
ability to generate graphs and print-outs in virtually any user-defined format,
the portability between platforms, and the immediate interface to the user's
operating system environment.

Comments from others?

comments in Ground Water Modeling Newsletter made by Adrian Brown, IMHO
apply to modeling ag leaching.

... d) Average conductivities, concentrations, and other parameters
are of little use in the evaluation of solute transport: transport
is dominated by non-average conditions.

If this is true is there any utility to current ag models like
PRZM Gleams?
don fontaine

Is Roger Smith saying, "Let's keep our models & plot results in our
labs, because if we make it easy for a non-scientist to use, this
work might show some benefit." ?? I see the point about making sure
the science is OK, but in extension educational efforts, we are
going beyond the printed publication which is not site-specific &
is usually out of date by the time it gets distributed - and programs
that our clients can use and that we can explain to them in workshops
are very important. Bob Peart, Agr. & Biol. Eng., U. Florida.

>I have read the discussions of "spreadsheet based models" with some
>interest. Am I wrong or is this another case of an emphasis on usability,
>presentation, etc, without regard to soundness of soil physics and
>chemistry? The sales pitch in a recent message used all the right words,
>such as on screen, color coding, "powerful" output, but said absolutely
>nothing about how the model figures out pesticide movement in a complex and
>heterogeneous soil profile. Let us turn from magic and salesmanship
>towards process science, and be more honest investigators and less
>salesmen/women.
>(I'll bet this comment gets someone worked up...)
>Roger E. Smith
>roger@lily.aerc.colostate.edu
>

>From all the postings, I would say you were right about getting poeple
worked up, Roger. The debate about simple vs. complex models has been
ongoing for over 20 years now in crop simulation, and is yet unresolved and
probably never will be. The critical point to make here is that models are
built usually with a purpose in mind. If one is trying to explain complex
relationships involving usually non-linear biological, chemical, and
environmental interactions, then the model better have some non-trivial
treatment of those processes. However, if one is trying only to give
insight and solution to a small subset that solves a problem for the end
user, then a simple model may do the job.

>From our 10 years of experience in delivering the GOSSYM/COMAX System to
cotton growers and consultants across the cotton belt for decision support
in cotton crop management, the user interface and ease of use of the
software system is critical to acceptance and continued application. I
agree totally that there must be substance behind the interface.

Another problem that needs to be addressed in this discussion is that
research scientists in ARS do not get credit in the RPES system for
developing user friendly GUI's. At the same time, our end users demand
them, and they are not trivial exercises and take substantial time and
resources to develop, maintain, and extend. We choose to do the development
and maintenance work and to pay the price at evaluation time.
Dr. James M. McKinion Ph. 601-324-4375
USDA-ARS FAX 601-324-4371
Crop Simulation Research Unit Email mckinion@csrumsu.ars.ag.gov
P. O. BOX 5367
Mississippi State, MS 39762
USA

I have built models within spreadsheets and other programs and they have
their uses, especiallly when developing the model. The built in graphics
and dat manipulation facilities are very useful. However, I soon come up
against the limitations of the application program and have to start
programming the model from scratch.
In addition, I find that whether you are using an application program
like a spreadsheet or a programming language, the tools you use can tend
to direct the way the model developes. This is less so when programming
from scratch.

Graham Lewis

On Wed, 1 Mar 1995 08:12:25 -0600,
Bob Peart <peartr@water.agen.ufl.edu> wrote:

> Is Roger Smith saying, "Let's keep our models & plot results in our
>labs, because if we make it easy for a non-scientist to use, this
>work might show some benefit." ?? I see the point about making sure
>the science is OK, but in extension educational efforts, we are
>going beyond the printed publication which is not site-specific &
>is usually out of date by the time it gets distributed - and programs
>that our clients can use and that we can explain to them in workshops
>are very important. Bob Peart, Agr. & Biol. Eng., U. Florida.

This reply is not untypical but more cynical than usually heard when the
subject of model content is raised. Of course I said nothing of the sort.
Model soundness and model utility are neither inversely related, nor or
they mutually exclusive. But what is done when one realizes that the way
nature works is too complex to make into an "easily used" model? Too often
the soundness of process is abandoned, with a variety of rationalizations,
in favor of ease of use, availablity of "parameters", etc. The "user" is
all in favor of ease of use. It is the scientist who is responsible for
what is behind the colored screen interfaces, but who often fools him or
herself in favor of making the model easy to use.
Roger E. Smith
roger@lily.aerc.colostate.edu

On Wed, 1 Mar 1995 08:01:09 -0600,
DONALD D FONTAINE <dfontaine@dow.com> wrote:

>comments in Ground Water Modeling Newsletter made by Adrian Brown, IMHO
>apply to modeling ag leaching.
>
>... d) Average conductivities, concentrations, and other parameters
>are of little use in the evaluation of solute transport: transport
>is dominated by non-average conditions.
>
>If this is true is there any utility to current ag models like
>PRZM Gleams?

>don fontaine
Don: An excellent point. However, not all cases important to pollutant
movement are dominated by variance. The existence of heterogeneity is
often used to trash or at least discount process-based models as being good
for the laboratory only, and implicitly or explicitly to justify the use of
gross simplifications. But I have never seen a demonstration that
simplifications such as "field capacity" based models do a better job of
simulating the effects of heterogeneities.
Roger E. Smith
roger@lily.aerc.colostate.edu

On Wed, 1 Mar 1995 07:22:11 -0600,
DIGUST@ccmail.monsanto.com <DIGUST@ccmail.monsanto.com> wrote:

>I noted with interest (and suppressed glee) the posted-complaints that
>yesterday's brief description of TA-DA! was long on "ease-of-use" and short on
>physics. Having written various models with a wide-spectrum of physics-based
>complexity, I must say that getting the physics right is only a very small part
>of writing a USEFUL model. The physics behind TA-DA! are admittedly simple,
>but so is F=m*a, which has held up reasonably well over the past few centuries.
>
>The primary technical advantage of producing a model in a spreadsheet
>environment is the tremendous ease of accessing, cutting, and pasting vast
>amounts of relevant DATA (please disregard the anagram) into the model. But
>there are numerous other features making the model more useful, including the
>ability to generate graphs and print-outs in virtually any user-defined format,
>the portability between platforms, and the immediate interface to the user's
>operating system environment.
>
>Comments from others?

Indeed, "geting the physics right" has nothing whatever to do with
"usefulness" as such: they are independent objectives, and you comments
merely prove that the latter objective (a perfectly valid one, as long
as it is kept in balance )is dominant in your efforts, as I obsurved.
Roger E. Smith
roger@lily.aerc.colostate.edu

I agree compeltely. Of course it is important to have the science right,
but I have seen to many models in which the user interface was positively
archaic. This has a direct impact on how much *science* can be done with
the model since wrenching a crummy interface takes *lots* of time. It also
has implications for the scientific soundness of the model because it
affects how quickly one can understand and get at the underlying assumptions
of the model. A spreadsheet model has the admirable advantage of having
its working front and center where the user can see and review them. In
addition the interface speads up the volume of science that can be done.
This is important because in many instances the speed with which the
model can be usefully used is the rate limiting factor on getting meaningful
results.

Jonathan Haskett

On Wed, 1 Mar 1995 DIGUST@ccmail.monsanto.com wrote:

> I noted with interest (and suppressed glee) the posted-complaints that
> yesterday's brief description of TA-DA! was long on "ease-of-use" and short on
> physics. Having written various models with a wide-spectrum of physics-based
> complexity, I must say that getting the physics right is only a very small part
> of writing a USEFUL model. The physics behind TA-DA! are admittedly simple,
> but so is F=m*a, which has held up reasonably well over the past few centuries.
>
> The primary technical advantage of producing a model in a spreadsheet
> environment is the tremendous ease of accessing, cutting, and pasting vast
> amounts of relevant DATA (please disregard the anagram) into the model. But
> there are numerous other features making the model more useful, including the
> ability to generate graphs and print-outs in virtually any user-defined format,
> the portability between platforms, and the immediate interface to the user's
> operating system environment.
>
> Comments from others?
>
>

> Is Roger Smith saying, "Let's keep our models & plot results in our
>labs, because if we make it easy for a non-scientist to use, this
>work might show some benefit." ?? I see the point about making sure
>the science is OK, but in extension educational efforts, we are
>going beyond the printed publication which is not site-specific &
>is usually out of date by the time it gets distributed - and programs
>that our clients can use and that we can explain to them in workshops
>are very important. Bob Peart, Agr. & Biol. Eng., U. Florida.

I would heartily endorse this viewpoint. During the past few years I've
found it necessary to move from model development more and more into the
development of techniques for making this information available to
managers and other non-scientists. We started with spreadsheets and are
moving in the direction of decision support systems based on expert
system techniques.

A strong advantage of spreadsheets in dealing with managers is that they
use a computer language that most managers know.

I've written a couple of papers on this, references follow (some of
these are available on our Web server).

Silvert, William. 1983. Ecological modelling with
electronic spreadsheets. Can. Math. Soc. Appl. Math.
Notes 8:1-8.

Silvert, William. 1984. Teaching ecological modeling with
electronic spreadsheets. Collegiate Microcomputer
2:129-133.

Longhurst, Alan, and William Silvert. 1985. A management
model for the Great Bustard in Iberia. Bustard Studies
2:57-72.

Silvert, WIlliam. 1989. Modelling for managers.
Ecological Modelling 47:53-64.

Silvert, William. 1992. Many risks, many models:
addressing the variety of problems that pollution can
cause. ICES 1992 Mini-Symposium on Ecosystem Modelling
as a Tool to Predict Pollution Associated Risks for the
Marine Environment. Proc. ICES Statutory Meeting, C.M.
1992/Mini:4. 4 p.

Silvert, William. 1992. The Desktop Scientist: Models that
a Manager can Use. Presented at 8th ISEM Int. Conf. on
Ecological Modelling.

Silvert, William. 1994. A decision support system for
regulating finfish aquaculture. Ecological Modelling
75/76:609-615.

Silvert, William. 1994. Decision Support Systems for
Coastal Zone Management. To be presented at Coastal
Zone Canada '94 on 20 September 1994.

Silvert, William. 1994. Putting management models on the
manager's desktop. J. Biol. Systems 2(4):519-527.

Silvert, William. 1994? Decision support systems for
aquaculture licensing. J. Applied Ecology (in press).
Presented at Proc. Workshop on Fish Farm Effluents and
their Control in EC Countries, Hamburg, Germany, Nov.
1992

--
Bill Silvert, Habitat Ecology Div., Bedford Inst. Oceanography
P. O. Box 1006, Dartmouth, Nova Scotia, CANADA B2Y 4A2
Personal InterNet Address: silvert@biome.bio.ns.ca
HED runs a WWW server at URL=http://biome.bio.dfo.ca

>The primary technical advantage of producing a model in a spreadsheet
>environment is the tremendous ease of accessing, cutting, and pasting vast
>amounts of relevant DATA (please disregard the anagram) into the model. But
>there are numerous other features making the model more useful, including the
>ability to generate graphs and print-outs in virtually any user-defined
format,
>the portability between platforms, and the immediate interface to the user's
>operating system environment.

I would agree from a developmental standpoint. In fact, most of the modeling
I've worked on (crop disease models) has actually begun with a spreadsheet.
This type of platform does make it easy to try multiple 'what if' scenerios,
and is an unparalled method of being able to 'visualize' the data before
undertaking a large statistical analysis. Unfortunately, as a DSS or any
kind of an end user management tool, there is simply too much information
displayed. From what I've seen in production agriculture, the majority of
farm managers still see computers as oversized typewriters. With this in
mind, a 'black box' approach with a customized interface and summary
information displays is superiror to several screenfulls of 'raw' data. I
realize that a lot of functionality can be written in to a spreadsheet
application using macros and named ranges, but with today's visual
programming tools and high level languages, implementation as a stand-alone
application is not much more effort than 'programming' the spreadsheet.

On another line of thought, what impact does spreadsheet modeling have on
standardization of data input formats, i.e. weather data, soil data etc. I
know IBSNAT has undertaken an effort to standardize these types of inputs.
IMHO spreadsheets make it easy to design formats and move large blocks of
data, but to import data from a non-standard source, and reformat it is
somewhat time consuming, and definitely error prone. I'd be interested to
hear from others about data standardization.

c 'ya
Woody
/**************************************************************************/
Jeff Woodard Glades Crop Care voice: 407-746-3740
949 Turner Quay fax:
407-746-3775
Jupiter, FL 33458
e-mail: woodard@igc.apc.org
-My opinions are my own-
/**************************************************************************/

At the risk of being somewhat commercialistic, I've got 17 rain guages and
20 temperature probes for which I have no use for. These are the Campbell
Scientific TE-525 switch closure tipping bucket rain guages, and 107-B
thermister temperature probes (including 6 plate gill radiation shields),
some of which have never been out of the box. We obtained this equipment
from an insurance company bankruptcy, and don't have enough weather stations
to use them on.

I'd be interested in selling them (at a lower price than available new), or
trading for some relative humidity or solar radiation probes. I can be
contacted by e-mail at woodard@igc.apc.org.

Thanks
Woody
/**************************************************************************/
Jeff Woodard Glades Crop Care voice: 407-746-3740
949 Turner Quay fax:
407-746-3775
Jupiter, FL 33458
e-mail: woodard@igc.apc.org
-My opinions are my own-
/**************************************************************************/

The spreadsheet models I use to determine input costs are pretty simple.

I copy them from Iowa State University paper-based spreadsheets.

What amazes me is how hard it is to get any modeling at all, good bad or
indifferent, to use in aiding in decision making for the guy who drives
the tractor.

As variable rate technology becomes more avaliable and affordable, it
would seem to me that modelling would help make some kind of sense out of
the many inputs involved in trying to figure out why a certain piece of
ground grew a certain yeild of corn. It sure isn't just fertility, we
have at least figured that out. But admitting the truth of that begs
the more difficult question of what combination of weeds, compaction,
slope, soil, variety, moisture, weather, growing degree days, fertilizer,
cultivation, herbicide, insecticides DID produce the yield.

I'm glad to get all the open models I can.

Since I don't use models to make the decisions, just help me, I figure it
is my responsibility if I use one wrong. My problem is, I can't find
them at all to run on my little 386DX33 with 8MB Ram.

Jim - Farmer - Iowa City, IA,
jnmeade@blue.weeg.uiowa.edu

signoff queiroz@ecn.purdue.edu

Dear ag modellers,

I am working at the International Potato Center CIP's station in Quito,
Ecuador, since 1990 as an associate agronomist, more recently also
doing a PhD at Wageningen on constraints to potato production in
Ecuadorian highlands. Yield-gaps are hoped to serve as a measure of
potential impact of relieving each particular contraint. After some
years of conventional on-farm yield gap trials, I started using
simulation to study the various levels of potential yields that are
relevant on the farmers' fields up here. I am considering the
following levels:

(1) (technologically possible,) defined by intercepted irradiation
(temp sum -{cultivar}-> ground cover -> fraction intercepted)
(2) limited by drought
(3) reduced by late blight
(4) actually harvested by the farmers (with obviously a range of
other constraints not simulated by the model)

We use a modification of LINTUL (Spitters, 1987). We produced a new
version that is based on the physical expansion of the plant, later the
row, finally the closed canopy, supposing a density per volume of leaf
area within the canopy. This was necessary because the distances
between plants and rows vary among the crops. We also made a three-
dimensional hourly sub-model to deal with the varying slope,
orientation, obstruction by the surrounding mountains, etc. site
factors.

Drought affects both light use efficiency and the development of ground
cover, whereas late blight only affects the latter. Going into details
would make this story too long. All the models for the levels 1, 2 and
3 were parameterized (analysis ongoing) using on-station field trials
at two altitudes 3050 and 2700 masl. They are being validated on-farm
in Carchi, a major potato production area, where year-round planting is
possible and we get ample variation in environmental conditions, both
in space and time. We expect/require that the model predict a
considerable part of the variation in the actual yields, and that the
absolute simulated values be slightly above level 4. In the previous
on-farm trials we got five-fold differences in yields, not explained by
differences in production technology. Another "validation" would be if
the model could address part of that variation to topography, weather,
soil and cultivar.

I notice I'm speaking about "we" since the second paragraph. We
include also four Dutch master's thesis students from Wageningen Ag.
Uni, all supervised by Louise Fresco (Prof Agronomy/Tropical Crops), I
myself also co-supervised by Anton Haverkort of AB-DLO, the
Netherlands. Dewi Hartkamp works on (1), Stefanie de Kool and Remco
Roeland on (2), Ingrid Schimmel on (3). Also an Ecuadorian student
belongs to the team; Luis Benavides from Central University of Quito
worked on the "old LINTUL". For email addresses for all of them see
Cc: list.

I prefer modelling in SAS, though I have also tried basic and the FSE
(Wageningen). I find SAS code very informative to non-programmers, and
it's easy to integrate the modelling effort with statistical analysis,
graphics etc.

Any contacts, ideas, questions, etc are welcome.

Best regards,

What is your asking price?

As with Mr. Gustafson, I have also found this spreadsheet controversy
amusing. I've seen this bias, as expressed in some of the recent e-mail, in
other fields as well. It generally takes one or both of two forms.

First, if the tool appears to be simple, then the results produced by the
tool must not be useful. The fallacy in this case is misunderstanding the
capability of the tool. The fact is that there is nothing that can be modeled
in a programming language that can't be modeled in a spreadsheet package such
as Excel 5.0 (in which I happen to do most of my work). When you combine this
capability with a spreadsheet's tremendous flexibility the question should
really be: why is anyone still using anything else?

The second bias is the presumption, as in Mr. Roger Smith's letter (2/28),
that use of a spreadsheet automatically means the abandonment of sound
underlying scientific theory. Why would anyone expect this to be the case?
The same physics and chemistry that goes into Mr. Smith's model can just as
easily (in fact, more easily) go into a spreadsheet model.

Responses, yea or nay, are welcomed.

Eric Fraint
YPTC@aol.com

Eric,

Your analysis seems about right on, and I say again that the result is
that we farmers who need one get neither a simple one nor a complicated
one that we can afford or readily use.

One thing for sure - any model used by the government to regulate us
should be readily available in the public domain, whether we have a
machine capable of running it or not. And if it's too complicated for
some dumb farmer to use, maybe it's too complicated for some dumb farmer
to apply. I refer specifical to RUSLE and similar soil erosion models
that we are expected to comply with by using tillage means, rather than
that we could use for "what-if" analysis on our own to consider the
affect of various practices.

Jim - Farmer - Iowa City, IA,
jnmeade@blue.weeg.uiowa.edu

Someone posted their opinion (as opposed to fact) that putting out
software with a decent User Interface was easy these days because of
the programming tools available.

Really? ;^)

Is this on Mars or Earth? :^)

If that person's opinion were indeed fact, MicroSoft would ship
bug free products on-time! After all, Bill has about $400 Million
after-taxes cash flow, the top 0.1% of the programming talent in
the World and advanced access to its own programming APIs.

Irrespective of progamming tools used, an application hitting 35,000 lines
of source code is not likely to be "easy"-anything. :^) New tools,
even Visual Basic, have *steep* learning curves. They are not
bug free, do not have *all* features desired/needed in a single product,
and make increasing expenditure demands on the end-user machines
(or else it will not run----or will run so slowly as to become shelf-ware).
:^)
--
Steve Modena ab4el@Cybernetics.NET

--------End of Unsent Message

------- Forwarded Message Follows -------

From: "Arkadiusz Salski" <OEKO-PROJEKT/AREK>
Subject: fuzzy-ecology - mailing list

CALL FOR PARTICIPATION
in the fuzzy-ecology mailing list

A mailing list for everybody interested in "fuzzy" topics
in ecology has been established. It is important for our
"fuzzy community" in ecology to keep in touch and have an
opportunity for information exchange and for discussion of
issues regarding fuzzy sets and fuzzy logic applications in
the field of ecology. I would like to invite you to participate
in this new mailing list created for this reason.

If you would like to subscribe to fuzzy-ecology, please send
a message to
maiser@pz-oekosys.uni-kiel.d400.de
with
SUBSCRIBE fuzzy-ecology
in the body of an otherwise empty mail.
I look forward to hearing from you. With kind regards
Arkadiusz Salski
--------------------------
Dr. Arkadiusz Salski
Ecosystem Research Center, University of Kiel
Schauenburgerstr. 112, D-24118 Kiel, Germany
arek@pz-oekosys.uni-kiel.d400.de

>... d) Average conductivities, concentrations, and other parameters
>are of little use in the evaluation of solute transport: transport
>is dominated by non-average conditions.
>
>If this is true is there any utility to current ag models like
>PRZM Gleams?
>don fontaine

Given the season-to-season variability in weather, I have found that
the following approach works best when using the above-mentioned
models to evaluate changes in leaching potential from changing
ag. practices: (1) since model output is given as average annual
values, I use a big weather data set (50-year simulation) and use
the output as a first-tier evaluation. Look at changes between
one scenario versus another; (2) a second-tier evaluation can then
be done to assess probability of a critical event occuring, such as
leaching of an herbicide below the root zone at concentrations considered
unacceptable. This is where some researchers bring in Monte Carlo
or other probabilistic tools. One could also just do model runs
under worst-case scenarios (very high rainfall immediately after
herbicied application, for example). Again, look at relative change
rather than the absolute values of the output. All in all, the models
are quite useful, *if* one approaches their use in this manner.

--
Ruth Shaffer-------------------------- |\ _,,,--,,_ ,) -
"You cannot look at a sleeping cat, /,'.-''' -, ;-;;'
and be tense."-Jane Pauley |,4- ) )-,_ ) /\
(ac698@leo.nmc.edu)-------------------'---''(_/--' (_/-'-----

My 2 cents:
When we talk about developing good models that are both useful and easy
to use, we are talking about *three* different processes: modeling,
decision support, and software engineering. Let's keep them separate, at
least in our discussion, if not in our computer code.

1. Models don't solve problems; they mimic some real phenomenon. Models should
be able to be objectively tested (verified, validated, evaluated...) to see
whether they achieve what they set out to achieve. Whether a model is good
or not is independent of its implementation language.

2. Building a good decision support system involves:
o working with clients (decision makers) to determine their needs;
o identifying decisions that clients need help with;
o determining what information, analyses, and knowledge are needed to make
those decisions well;
o providing either the supporting information or potential decisions
or both to the decision maker.
Models often play important roles in decision support systems because they
provide analysis and information. In DSS, the developer and the clients
need to make choices about what kinds of models are appropriate to the
problem.
Often there are several ways to get some piece of the puzzle: one or more
models at different levels of resolution, precision, and complexity,
heuristics, published defaults, etc.

3. Even a good DSS with appropriate and accurate models can fail to be used
because of its design: poor interface, poor flow, failure to take into
account how/when/where the user works, demanding more time, training, or
equipment than the user reasonably expects.
Many features that make software more readily adopted by users (in general)
are built into spreadsheets, so they are one prominant option for delivery
of systems to users.

Ultimately, we hope to solve problems. All three of these activities (with
a few more like good advertising, promotion, support, etc.) are important
toward that end.
--Nick

-----------------------------------------------------------------
Nicholas D. Stone ISIS Lab
Department of Entomology Phone: (703) 231-6885
202 Price Hall FAX: (703) 231-9131
Virginia Tech Internet: nick@vt.edu
Blacksburg, VA 24060 BITNET: nstone@vtvm1

On the WWW:
http://www.ento.vt.edu/Personnel/Professors/NDSInfo.html
-----------------------------------------------------------------
_ __
\ / __/
o |_||__//_
\_/ |\ / \ "Time flies like an arrow;
(_| | >--< \ ) fruit flies like a banana."
/ \_|/____\_/ --Groucho Marx
o | || \\_
_/ \__ \

Hi -

This is Rick Olson, a Biologist at the Crop Simulation Research Unit,
USDA-ARS, Mississippi State. My research involves simulation modeling and
decision-support systems. Enough intro.

I've also been amused by the spreadsheet controversy. It reminds me of the
old (present?) days and the language controversies in bio modeling. You
know, whether C, then C++, then etc. was any good versus good-old-FORTRAN.
When I moved to OOP languages like C++ or Smalltalk, I listened to all kinds
of folk who told me "Well, I can do that in FORTRAN," to which I would reply
"Yes, but why would you WANT to?"

The point is, choose an implementation medium that is right for the job.
Doing OOP in FORTRAN is silly. Likewise, you can, indeed, do anything you
want in Excel, but why would you want to? I use Excel for testing of
equations in model development, etc., due to its "instant gratification"
aspect of changing equation parameters and seeing them change instantly on
the screen. For building complex, graphical interfaces to equally complex,
large simulation models, it just doesn't cut it (IMHO, of course!). There
are plenty of new GUI-building tools, such as Visual Basic, that allow you
to easily construct an interface and then mate with complex simulation
models in any language (as DLLs or DDEs or OLE objects), along with graphing
DLLs, spreadsheet DLLs, etc., etc.

Rick Olson

First, I regret my rather cynical response to Roger Smith's comments
about the spreadsheet - we should be better natured than that -
but I certainly agree with Eric Fraint's comments about the power of
the spreadsheet in simulation work. Bob Peart, U. Florida.

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TO: Attendees and potential attendees of the the 25th Crop Simulation Workshop

Please find attached a copy of the final program of the Crop Simulation
WOrkshop to be held at the Engineering Research Center, Mississippi Research
and Technology Park, Starkville, MS (Mississippi State) during March
13,14,and 15, 1995. Transportation will be provided from local motels to
and from the ERC. If you have preregistered and have not informed us which
motel/hotel you are staying at and need transportation please advise by
e-mail, phone or fax. If you are going to register on-site, ditto the above.

JAMES

--=====================_794164773==_
Content-Type: text/plain; charset="us-ascii"
Content-Disposition: attachment; filename="BSSG.PRO"

Monday, March 13th

12:00-1:00 p.m. Registration

1:00 p.m. Welcome
J. M. McKinion

Session Moderator - James M. McKinion

1:10 p.m. R. Bruce Curry

25 Years - A Look Back

1:30 p.m. Jack Carlson
Migrating the USDA Field Service Center to a Client-Server
Architecture: Implication for Use of Crop Simulation Models

1:50 p.m. B. M. Jacobson
Combining Crop, Weed, Herbicide, Water Quality, and Economic
Models to Assess Overall Impacts of Management Practices

2:10 p.m. J. R. Barrett
Humanization of Decision Support for Managing U. S. Grain (Corn
and Soybean) Production"

2:30 - 3:00 p.m. Coffee Break

Session Moderator - R. Bruce Curry

3:00 p.m. G. F. Sassenrath-Cole
The Role of Leaf and Canopy Architecture in Determining Canopy
Photon Flux Distribution

3:20 p.m. R. Braddock
Towards a Simple Framework for Modelling Root Growth
Dynamics Under Variable Environmental Conditions

3:40 p.m. Avishay Ben-Porath
Graphical Tracking of Cotton Growth

3:40 p.m. E. Jallas
Graphical Input, Representation, and Biometric Analysis of the
Topology of the Cotton Plant

4:00 p.m. D. C. Akins
C++ Classes for a Generic Population Model

4:20 p.m. G. E. Meyer
Virtual Reality Analysis of Plant Canopies for Evaluating Sensor
Designs for Variable-Rate Application Technology

5:00 p.m. ADJOURN
Transportation to Hotels Available

6:30-7:30 p.m. Reception
(Bar-B-Que Dinner)

Session Moderator - K. J. Boote
7:30-10:00 p.m. Roundtable Discussion

Note: Transportation to Hotels Provided

Tuesday, March 14th

Session Moderator - Harry F. Hodges

8:30 a.m. K. J. Boote
Sensitivity Analyses of CROPGRO Model Response to Climatic
Variables

8:50 a.m. Basil Acock
Testing Crop Simulators as Software: GLYCIM Case Study

9:10 a.m. V. R. Reddy
Estimating Soybean Cultivar-Dependent Parameters for
GLYCIM from Field Data on Crop Growth and Development

9:30 a.m. J. Muhidong
Modelling Cotton Fiber Quality: Importance, History, and
Methods

10:00 a.m. Coffee Break

Session Moderator - K. Raja Reddy

10:30 a.m. R. Gordon
A Cultivar Specific Soil Water Sensitive Model of Potato Leaf
Area Index

10:50 a.m. D. Timlin
2DSPUD, A Modular Two-Dimensional Potato Simulation
Model

11:10 a.m. Hsin-I (Wally) Wu
Use of Fractals in Plant Functional Studies

11:30 a.m. A. Marani
Simulating Nitrogen in the CALGOS Cotton Model

12:00 p.m. Lunch

1:00 - 2:30 p.m. Poster Presentations
& Software Demos

2:30-3:00 p.m. Coffee Break

3:00-4:00 p.m. Poster Presentations
& Software Demos
4:00 p.m. ADJOURN
(Transportation Back to Hotel)

5:30 p.m.-11:30 p.m.
Dinner at Silver Star Casino
(Transportation Provided)

Wednesday, March 15, 1995

Moderator - Jeffrey L. Willers

8:30 a. m. D. S. Fisher
Estimating Variable Rates of Comminution and Passage of Forage
Particles in Models of Ruminant Digestion

8:50 a.m. C. S. Liu
The Effect of Fluometuron Concentration and Temperature on
Transpiration Rates and Some Morphological Characteristics of
Four Weed Species

9:10 a.m. J. A. Landivar
Crop Monitoring System Using a Weather Station Network, Plant
Mapping and Crop Simulation

9:30 a.m. X. N. Wang
The Characteristics of Weather Patterns and Their Regional
Distribution

10:00-10:30 a.m. Coffee Break

Moderator - Michael R. Williams

10:30 a.m. K. R. Reddy

10:50 a. m. S. M. Bridges
Problem-Solving Strategies in a Simulation-Based Expert System

11:10 a. m. R. L. Olson
An Emergent Computational Approach to Ecosystem Modelling

11:30 a.m. Hsin-I (Wally ) Wu
An Integrated Resource Simulation Model for a Semi-Arid
Agroecosystem in the Loess Plateau of Northwestern China

11:50 a.m. ADJOURN

WORKSHOP
ON CROP S IMULATION

Organized by:
Biological Systems Simulation Group
Co-Sponsor ed by:
USDA Agric ulture Research Service
Mississipp i State University
American S ociety of Agricultural Engineers

March 13-1 5, 1995
Mississipp i State, Mississippi
--=====================_794164773==_
Content-Type: text/plain; charset="us-ascii"

Dr. James M. McKinion Ph. 601-324-4375
USDA-ARS FAX 601-324-4371
Crop Simulation Research Unit Email mckinion@csrumsu.ars.ag.gov
P. O. BOX 5367
Mississippi State, MS 39762
USA

--=====================_794164773==_--

>Someone posted their opinion (as opposed to fact) that putting out
>software with a decent User Interface was easy these days because of
>the programming tools available.

Well, Stephen, as the "someone" who posted the opinion, I guess I'll respond
[at least I clearly labeled my post as opinion, while yours was stated as
fact ...]

I feel that software tools used should be appropriate for the problem at hand.
While the learning curve on tools like V. Basic may be steep, they are NOT steep
relative to that for Visual C++, Microsoft's current abortion (even with the
foundation classes). And yes, if you need the complete flexibility offered by
Visual C++, you should use it and bite the bullet as to learning curve. (while
this is still opinion, it is informed opinion, because I've used both
Visuals, and others).

Again IMHO, if you expect to produce state-of-the-art software, you use
state-of-the-art tools. If one can't be bothered to learn them, then fork
over the bucks to hire a programmer who can.

As always, in my humble opinion.

Rick

Steve Modena Says:
>Someone posted their opinion (as opposed to fact) that putting out
>software with a decent User Interface was easy these days because of
>the programming tools available.
>
>Really? ;^)
>
>Is this on Mars or Earth? :^)
>
>If that person's opinion were indeed fact, MicroSoft would ship
>bug free products on-time! After all, Bill has about $400 Million
>after-taxes cash flow, the top 0.1% of the programming talent in
>the World and advanced access to its own programming APIs.

< :^)'s deleted >

I did not mean to imply that programming is easy by my prior post. The point
that I was trying to make was that interface development - either in a
spreadsheet or in a
program - takes some time. Obviously, the nicer the interface, the longer
the time.

Yes, the learning curve is steep for some of the new visual programming
environments (I've been working with Borland's Visual C++), but the user
interface development is greatly simplified. Less than three years ago, if
you wanted to write a 'graphic' user interface (and you didn't work for a
big company that had access to expensive compilers/in-house code) You had to
draw out each individual line, polygon, color, attribute etc etc etc, and
after about a month, you could start making the buttons do something besides
display other buttons. With the package I'm using now, you can construct the
entire basic interface framework -windows application with text editor,
support for multiple documents, file save and retreive, search and replace,
menu system, speed bar, help, fly-by hints, scrollbars, scalable windows -
(admittedly not much application functionality) with two mouse clicks, and
about two minutes of compile time.

Comparing the development of a 'management tool' or model with the
development of operating systems, programming environments, databases, and
desktop publishers by a monolithic software corporation I think is just a
wee bit out of line on the complexity scale. It's kind of like comparing a
fungal spore with an elephant - any likenesses to the actual parties is
purely coincidental -.
/**************************************************************************/
Jeff Woodard Glades Crop Care voice: 407-746-3740
949 Turner Quay fax:
407-746-3775
Jupiter, FL 33458
e-mail: woodard@igc.apc.org
-My opinions are my own-
/**************************************************************************/

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