Cotton Modeling to Assess Climate Change and Crop Management December 2005 V. R. Reddy 1 and K. R....
-
Upload
natalie-tyler -
Category
Documents
-
view
218 -
download
0
Transcript of Cotton Modeling to Assess Climate Change and Crop Management December 2005 V. R. Reddy 1 and K. R....
Cotton Modeling to Assess Climate Cotton Modeling to Assess Climate Change and Crop ManagementChange and Crop Management
December 2005December 2005
V. R. Reddy1 and K. R. Reddy2
1USDA-ARS, Crop Systems and Global Change Laboratory, BARC-West, Beltsville, MD 20705, USA
2Department of Plant and Soil Sciences, Mississippi State University, Mississippi State, MS 39762, USA
Provide quantitative description and understandingof biological problems.
Help pinpoint knowledge gaps.
Design critical experiments.
Synthesize knowledge about different componentsof a system.
Summarize data.
Transfer research results to users.
Why Do We Need Models?
Farm management (e.g. planting, irrigation, fertilization and harvest scheduling).
Resource management (e.g. several Govt. agencies and private comp. use).
Policy analysis.
Production forecasts (e.g. global, regional and local forecasts).
Research and development (e.g. research priorities and guide fund allocations).
Turning information into knowledge (e.g. information overflow in every area including agricultural research).
Demand for Models
Timeline for Information Flow
Identify knowledge void
Conceptualize the experiment
Implementation
Analyze data
Publication
Technology transfer
Farm decisions
Crop model/DSS
Months
Months
Months/Years
Months
Years
Months/Years
Months/Years
Scientists
Ext. Personnel
Industry Reps
Consultants
Farmers
Months/Years
Months
SPAR – Database for Modeling
Temperature and Crop DevelopmentSpecies and Genotypic Variability
Temperature, °C
15 20 25 30 35
Day
s to
Squ
are
15
20
25
30
35
40
45
50
55
60
65
Upland, DES 119
Pima Cotton
Upland, DP 51
SPAR – Database for Modeling
Photosynthesis and Leaf Water Potential
Leaf Water Potential, MPa
-4.0-3.5-3.0-2.5-2.0-1.5-1.0
Ph
otos
ynth
esis
, mg
CO
2 m
-2 s-1
0
2
4
6
8
10
350 µl l-1 CO2
700 µl l-1 CO2
GOSSYM: Model Structure
PMAP
COTPLT
GOSSYM
CLYMAT
SOIL
CHEM
PNET
GROWTH
PLTMAP
OUTPUT
PIX
PREP
RUTGRO
NITRO
MATAL
DATES
TMPSOL
FRTLIZ
ET
UPTAKE
CAPFLO
NITRIF
RIMPED
ABSCISE
FREQ
RAIN
FERT
RUNOFF GRAFLO
For more details on model structure: Hodges et al., 1998
GOSSYM: Model Validation
United States Greece
China
Israel
Continuous evolution of the model by extensive testing across diverse environments, soil conditions and cultural practices.
Information feedback from scientists, farmers and farm managers.
Climate Change Effects
Atmospheric Carbon Dioxide Enrichment - YieldStoneville, MS - Mean of 30 Years
Atmospheric Carbon Dioxide Concentration (µl l-1)
0 200 400 600 800 1000
Lin
t Y
ield
(kg
ha-1
)
800
1000
1200
1400
1600
1800
2000
Climate Change – Cotton YieldExtreme Events - Cotton Yield
Climate Change Scenario
Lin
t Y
ield
(kg
ha
-1)
800
1000
1200
1400
1600
1800
2000
2200Current + Ambient CO2Current + Elevated CO2Future + Elevated CO2
Hot Dry Cold Dry Cold Wet NormalHot Wet
1993
1980
1992
1984
1989
Extreme Years Lint yield
Tillage and Erosion Studies
GOSSYM was used to evaluate the effects of erosion and erosion-related activities on lint yields.
GOSSYM was also used to investigate the effects of simulated tillage and wheel traffic on growth and yield.
Insect Damage Assessment
RbWHIMS: Rule-based Wholistic Insect Management System.
Provides information to the user for determining pesticide management strategies.
Recommendations include: extent of pest control,timing of pesticide application/no application and when to observe the field for future management strategies.
Genetics Improvement Research
GOSSYM – a tool to predict the effect and economic benefit of various genetic combinations.
Photosynthesis was found to be the limiting factor in the okra leaf-type cottons which have more number of bolls/plant and less lint yield than normal leaf-type cottons.
GOSSYM: Educational Applications
As a tool for learning: principles of crop and soil management.
As a classroom teaching tool: graphically presents the changes in plant growth and development.
Educating farm managers to improve their crop productivity.
Assist crop consultants in the decision making process.
22 (15 Ph.D and 7 MS) theses on GOSSYM were accepted since 1979 at MSU.
GOSSYM served as a template to other crop models (melons, soybean, corn, wheat, rice and potato) at USDA.
GOSSYM: Model ApplicationsGOSSYM: Model ApplicationsField Scale
Pre-season and In-season Decisions
Timely decisions can be taken by predictions with GOSSYM.
Helps in decision-making regarding leasing of farms.
Estimations before hand – fertilization and irrigation costs.
GOSSYM – for determining crop termination, nitrogen application, irrigation management.
Growth Regulator Applications
n = 162
Simulated vs Observed Plant Height
Observed Plant Height, cm
0 25 50 75 100 125 150 175
Sim
ulat
ed P
lant
Hei
ght,
cm
0
25
50
75
100
125
150
1751:1
Growth Regulator Applications
n = 371:1
Simulated vs. Observed yield
Observed Yield, t ha-1
0.0 0.5 1.0 1.5 2.0 2.5
Sim
ulat
ed Y
ield
, t h
a-1
0.0
0.5
1.0
1.5
2.0
2.5
GOSSYM: Reap Profits
In another study, GOSSYM plots had a profit of $100 - $350 ha-1 (McKinion et al., 1989).
GOSSYM plots had a profit of $80 ha-1 than farmer plots (Ladewig and Powell, 1992).
GOSSYM Plots Farmer Plots
GOSSYMGOSSYM
Deficiencies and Future Development Needs
Deficiencies and Future Needs
Fiber quality?Nutrients other than
C and N?
Extreme weather, Hail? Winds?
Modern/transgenic cottons?
Damage due to UV-B/pests/herbicides?
GOSSYM
Thank You
Shall We Discuss!