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Bill Johnson University of Missouri

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Page 1: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Bill JohnsonUniversity of Missouri

Page 2: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

A Decision Support System for Weed Management

University of Nebraskaand

North-Central Partner States

Page 3: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

ObjectiveObjective• Develop a biology and

economics based weed management decision support tool for crop managers

Page 4: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Development TeamDevelopment Team

• Weed Scientists

• Information systems specialist

• Listening group-Users

Page 5: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

WeedSOFT Partner States

IllinoisIllinois MichiganMichiganIndianaIndiana MissouriMissouriKansasKansas NebraskaNebraska

WisconsinWisconsin

Page 6: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

WeedSOFTWeedSOFT

Bioeconomic DecisionBioeconomic Decision

Groundwater VulnerabilityGroundwater VulnerabilityGroundwater Risk AssessmentGroundwater Risk Assessment

Weed IdentificationWeed Identification

Page 7: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

EnviroFXEnviroFXSite and product specific assessment of groundwater contamination risk

Page 8: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States
Page 9: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

MapVIEWMapVIEWColor coded county maps depicting vulnerability of groundwater to contamination

Page 10: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States
Page 11: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

WeedVIEWWeedVIEWVisual images as an aid in weed identification

Page 12: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States
Page 13: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

AdvisorAdvisorComputes crop yield and dollar loss based

on weed density, weed free yield and

crop price

Page 14: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Weed Management StrategiesWeed Management Strategies

• Cultivation

• Pre herbicide

• Post herbicide

• Combined strategies

Page 15: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Treatment Selection CriteriaTreatment Selection Criteria

• Geographical restrictions• Soil properties• Rotational crop• Ground and surface water

restrictions• Crop and weed growth stage

Page 16: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

ADVISORADVISOREvaluation of pre,

post, pre+post weed management strategies in five crops:

corn, sorghum, soybeans, sugarbeets, wheat

Page 17: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

State Specific Parameters

HerbicidesHerbicides Soil Properties Soil PropertiesHerbicide EfficacyHerbicide Efficacy Rotational Restrictions Rotational RestrictionsApplication Rates Application Rates Geographical Restrictions Geographical Restrictions Weed Species Weed Species Weed Competitive Index Weed Competitive Index

Page 18: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Input application informationInput application information

Page 19: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Input crop informationInput crop information

Page 20: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Input environmental informationInput environmental information

Page 21: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Input weed informationInput weed information

Page 22: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

OutputOutput

• Ranking of strategies based on net return or yield

• Detailed economic and efficacy analysis of treatments

• Change in weed seed bank with each treatment

Page 23: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Treatment Ranking and AnalysisTreatment Ranking and Analysis

Seedbank change

Page 24: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

WeedSOFT as a WeedSOFT as a Teaching ToolTeaching Tool

Page 25: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Biological FactorsBiological Factors• Crop and weed species competitiveness• Influence of crop and weed growth

stage on crop-weed interference• Influence of crop row spacing on crop

competitiveness• Influence of precipitation on herbicide

efficacy and rotational crop risk

Page 26: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

17.2/40 = 43%

Corn, Weed free yield = 150 bu/ACorn, Weed free yield = 150 bu/A

Soybeans, Weed free yield = 40 bu/ASoybeans, Weed free yield = 40 bu/A

17.5/150 = 12%

Crop Species CompetitivenessCrop Species Competitiveness

Page 27: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Corn 0-5” height; weed free yield = 150 bu/ACorn 0-5” height; weed free yield = 150 bu/A

17.5/150 = 12%

8.9/150 = 6%

Weed Species CompetitivenessWeed Species Competitiveness

Common cockleburCommon cocklebur

Redroot pigweedRedroot pigweed

Page 28: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Corn 0-5” height; Weed free yield = 150 bu/ACorn 0-5” height; Weed free yield = 150 bu/A

17.5/150 = 12%

Weed Competitiveness Based on Weed HeightWeed Competitiveness Based on Weed Height

Cocklebur 2-4” heightCocklebur 2-4” height

Cocklebur 4-8” heightCocklebur 4-8” height25.1/150 = 17%

Page 29: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Corn 0-5” heightCorn 0-5” height

17.5/150 = 12%

Weed Competitiveness Based on Crop HeightWeed Competitiveness Based on Crop Height

11.4/150 = 7.6%

Corn 6-12” heightCorn 6-12” height

Corn weed free yield = 150 bu/ACorn weed free yield = 150 bu/A

Page 30: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Soybeans 1st trifoliate; weed free yield = 40 bu/ASoybeans 1st trifoliate; weed free yield = 40 bu/A

Weed Competitiveness Based on Row SpacingWeed Competitiveness Based on Row Spacing

30” Row Spacing30” Row Spacing

7.5” Row Spacing7.5” Row Spacing

12.1/40 = 30%

9.9/40 = 25%

Page 31: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Corn 0-5”; Weed free yield = 150 bu/ACorn 0-5”; Weed free yield = 150 bu/ACocklebur 2-4”Cocklebur 2-4”

Herbicide Efficacy Based on MoistureHerbicide Efficacy Based on Moisture

Moisture StressedMoisture Stressed

Excellent MoistureExcellent Moisture

77.9%77.9%

% Control

100%100%

% Control

Page 32: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Corn 0-5”; weed free yield = 150 bu/ACorn 0-5”; weed free yield = 150 bu/ACocklebur 2-4”Cocklebur 2-4”

Cultivation Efficacy Based on MoistureCultivation Efficacy Based on Moisture

Moisture StressedMoisture Stressed

Excellent MoistureExcellent Moisture

72.4 %72.4 %

54.9 %54.9 %

% Control

% Control

Page 33: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Missouri WeedSOFTMissouri WeedSOFT• Decision Support System• Teaching/Learning Tool• Available in 2002 on CD-Rom

–Initial price $195–Yearly updates will be $35-50

• WeedSOFT website–http://weedsoft.unl.edu

Page 34: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

Missouri WeedSOFTMissouri WeedSOFT• To order:

–Make checks payable to WeedSOFT 2002

–Send to : Bulletins, P.O. Box 830918, Lincoln, NE 68583-0918

Page 35: Bill Johnson University of Missouri. A Decision Support System for Weed Management University of Nebraska and North-Central Partner States

WeedSOFTWeedSOFTA State Specific Decision Support System for Weed

Management