Date post: | 16-Jan-2016 |
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Precision Agriculture: TheRole of Science
Presented by
Dr. Eduardo Segarra
Department of Agricultural and Applied Economics, Texas Tech University
Purpose of presentation
Highlight the relevancy of “science” based research on agriculture, and highlight the
importance of hedonic pricing
The Agricultural Sector in the 21st. century will be called upon to provide an
abundant, diverse, safe, and of high quality supply of food and fiber at reasonable prices for consumers…. and which is globally competitive, profitable
for producers and processors, and minimizes environmental degradation
Traditional agricultural crop production practices have been based
on broad input utilization prescriptions that ignore site-specific characteristics of crop fields within
farms and/or
across regions
Precision agriculture, precision farming, site-specific management,
or also referred to as remote-sensing farming internalizes
unique features of crop fields to tailor precise input utilization
Specifically, What is Precision Agriculture?
Precision agriculture deals with within-crop field disaggregation of inherent and applied factors of production or other characteristics
which have significant impacts on the overall productivity (amount and quality of output produced) and environmental
implications of crop production
SPATIAL issues addressed by Precision Agriculture practices
• Soil fertility
• Soil water holding capacity
• Weed and pest infestations
• Fertilizer use
• Irrigation water use
• Chemical use (herbicides & insecticides)
• Quality of output produced
• Yield potential
Spatial Variability of Soil Properties
Organic Matter pH Nitrogen Phosphorus Depth to caliche Slope & altitude
Hydraulic properties
Nitrogen Lbs/ANitrogen Lbs/A
Nitrogen
GreenbugDamage
Yield
NO3-N Pre-Season Residual Map from 0 to 12 Inches of Soil Depth,
Gaines County, Texas.
Peanut. NO3-N Pre-Season Residual Map from 0 to 12 Inches of Soil Depth, Gaines County, Texas.
Peanut. Optimal Levels of Spatial Nitrogen Application Map for Precision Farming Practices, Gaines County, Texas.
Spatial Peanut Yield Map for Precision Farming Practices, Gaines County, Texas.
Spatial Peanut Yield Map for Whole-Field Farming Practices,Gaines County, Texas.
Peanut. Spatial Net Revenue Above Nitrogen and Water Costs for Precision Farming Practices, Gaines County, Texas.
Peanut. Spatial Net Revenue Above Nitrogen and Water Costs for Whole-Field Farming Practices, Gaines County, Texas.
Probability Density Function for Peanut Net Revenues Above Nitrogen and Water Costs.
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Pro
b
Cumulative Density Function for Peanut Net Revenues Above Nitrogen and Water Costs.
Corn. NO3-N Pre-Season Residual Map from 0 to 24 Inches of Soil Depth, Halfway, Texas.
Corn. Optimal Levels of Spatial Nitrogen Application Map for Precision Farming Practices on a Per-Year Basis for a Ten-Year Planning Horizon, Halfway, Texas.
Spatial Corn Yield Map for Precision Farming Practices, Halfway, Texas.
Spatial Corn Yield Map for Whole-Field Farming Practices, Halfway, Texas.
Corn. Spatial Net Revenue Above Nitrogen and Water Costs for a Ten-Year Optimization Model for Precision Farming Practices, Halfway, Texas.
Corn. Spatial Net Revenue Above Nitrogen and Water Costs for a Ten-YearOptimization Model for Whole-Field Farming Practices, Halfway, Texas.
0.00 1000.00 2000.00 3000.00 4000.00 5000.00 6000.00 7000.00
Probability Density Function for Corn Net Revenues Above Nitrogen and Water Costs.
0
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0 1000 2000 3000 4000 5000 6000 7000
Pro
b
Cumulative Density Function for Corn Net Revenues AboveNitrogen and Water Costs.
Cotton. NO3-N Pre-Season Residual Map from 0 to 12 Inches of Soil Depth, Lamesa, Texas.
Cotton. Optimal Levels of Spatial Nitrogen Application Map for Precision Farming Practices on a Per-Year Basis for a Ten-Year Planning Horizon, Lamesa, Texas.
Cotton. Spatial Net Revenue Above Nitrogen and Water Costs for a Ten-Year Optimization Model for Precision Farming Practices, Lamesa, Texas.
Cotton. Spatial Net Revenue Above Nitrogen and Water Costs for a Ten-Year Optimization Model for Whole-Field Farming Practices, Lamesa, Texas.
0.00 500.00 1000.00 1500.00 2000.00 2500.00 3000.00
Probability Density Function for Cotton Net Revenues Above Nitrogen and Water Costs, Lamesa, Texas.
0
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Pro
b
Cumulative Density Function for Cotton Net Revenues Above Nitrogen and Water Costs, Lamesa, Texas.
Derivation of PA Practices
• Determine plant growth conditions on a per unit land area basis
• Understand the interactions of plant stress and applied inputs on output production AND quality
• Use variable rate technology to apply inputs where AND when needed
• Develop decision aids for improved crop management (yield and quality)
TECHNOLOGY TRANSFER •Irrigation and Fertilizer use - according to Best Management Practices (BMP)
•IPM on a per unit land area basis
•Optimization of profits (amount of output produced and its quality)
•Minimization of environmental damage