Biological Modeling

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Biological Modeling

• Basic Concepts
• Simple Crop Growth Model
• Example Uses of Crop System Models

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Systems Approach
Biological Research
Engineering
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BIOLOGICAL MODEL EXAMPLES

• Crop Growth
• Soil Organic Matter
• Microbial Growth
• Insect Populations
• Predator-Prey Populations
• Bio Reactors
• Fish Growth and Reproduction
• Heart Function
• Animal Temperature Regulation
• Eutrophication Processes
• Chemical Transport in Soil, Water
• Food Chain
• Livestock growth
• Plant and Animal Genetics

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Predicting soybean maturity and yield using
molecular marker information
Prediction of Performance
DNA Analysis
Satt 496
Planting dates Row spacing Irrigation
Williams 82
Vinton 81
Omaha
Linford
Savoy
Yale
Nile
CROP MODEL
Yield Maturity
351 bp
330 bp
Illinois, 7 Locations 5 years 1995-99
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Gene Based Predictions Soybean in Illinois
Time to Maturity
Yield
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Simulated
R20.75
R20.54
Observed
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Terminology

• System Collection of Components
• Model Mathematical Representation of System
  (Components their Interactions)
• State Variables Measures of System that Change
  over Time
• Simulation Solving a Model, predicting system
  behavior over time

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Simple Tomato ModelReferenceJ.W. Jones and
J.C. Luyten, 1998. Simulation of biological
processes. Pages 19-62 in R.M. Peart and R.B.
Curry (Eds) Agricultural Systems Modeling and
Simulation.
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SIMPLE CROP GROWTH MODEL EXAMPLE
Parameters
Parameters

INPUTS
OUTPUTS
MODEL
I0, Light C, CO2 Concentration T, Temperature
N, Nodes Wc, Canopy Weight Wr, Root Weight W,
Total Weight L, Leaf Area Index
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Rate of Crop Dry Weight Growth

• Photosynthesis minus maintenance respiration

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Canopy Photosynthesis (1)

• Many different models. We used the Acock et al.
  (1978) model.
• Pg is a function of light, CO2, temperature and
  plant size.

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Constant LAI4 T30 ºC
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Constant LAI4 CO2 350
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Respiration (maintenance)

• Loss of CO2 from plants due to breakdown and
  resynthesis of existing tissue

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Constant CO2 350, Light flux 1200 12 hr
days
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Constant CO2 350, 12 hr days day/night temp
30/20 ºC
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DNA could provide information to engineer crops
for specific climates
Optimize management for a specific variety

• Soybean Gene Map

Source C. Messina. 2003
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Soybean Yield, kg/ha
Average Yield for Current Conditions
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Crop Models

• Crop growth and yield models have been developed
  for various purposes, among others
• economic risk analysis
• irrigation management
• nutrient management
• pest management
• plant breeding
• precision agriculture
• crop sequencing
• land use planning
• climate change assessment

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DSSAT

• Field-Scale Crop Model Application Software
• Biophysical Models (Crop, Soil, Weather), 17
  Crops
• Risk Analysis (Biophysical and Economic)
• Data Entry and Manipulation Tools
• Utilities (graphics, data entry, management,)
• Crop Rotation Analyzer
• For Use by Researchers
• GIS Products
• GIS-DSSAT Linkage for Region Impact Assessment
• Precision Agriculture Analyzer (GIS)

Developed by IBSNAT Project of USAID, 1983-1993
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Gainesville, FL 1978
Yield
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Testing model predictions, Soybean in Georgia
(1987-1996)
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Crop Model Evaluation in Argentina
On farm tests in Pampas Region. Magrin et al.
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Precision Agriculture

• The Problem
• Yield varies considerably within fields
• Spatially varying inputs and management may
  increase profits and reduce environmental risks
• However
• Understanding what caused yield variability in a
  specific field
• Determining how to vary management across a field
  to optimize profit and meet other goals

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Genetics
Weather
Crop Models Precision Farming

• Yield
• Soil type
• Images
• Pests
• Elevation
• Drainage
• Fertility

• Causes of Yield Variability
• Develop Prescriptions
• Risk Assessment
• Economics

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With accurate inputs, crop models can accurately
predict yield
Simulated versus observed maize grain yield, two
years, using field-measured spatially varying
soil parameters in Michigan. R. Braga (2000).
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Baker Farm (1994) Transect 1
Soybean
W. D. Batchelor et al., 1999 Iowa State University
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Soybean Crop Yield Variability, Baker Farm (1994)
W. D. Batchelor et al., 1999 Iowa State University
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Simulated Yields After Estimating Soil Properties
RMSE 74.35 kg/ha
1998 Season Rain 700 mm
1996 Season Rain 418 mm
A. Irmak et al., 2000 University of Florida
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A. Irmak et al., 2000 University of Florida
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A. Irmak et al., 2000 University of Florida
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DNA provides information to engineer crops for
specific climates
Optimize variety for climate high yield, low
risk of failure

• Soybean Gene Map

Source C. Messina. 2003
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Traditional Biological Research
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Incorporating Models into Biological Research