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Relationships Between NDVI and Plant Physical Measurements Beltwide Cotton Conference January 6-10, 2003 Tim Sharp.

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Presentation on theme: "Relationships Between NDVI and Plant Physical Measurements Beltwide Cotton Conference January 6-10, 2003 Tim Sharp."— Presentation transcript:

1 Relationships Between NDVI and Plant Physical Measurements Beltwide Cotton Conference January 6-10, 2003 Tim Sharp

2 1. Introduction Aerial photography remains one of the most reliable and widely used forms of remotely sensed imagery –higher special resolution –relatively low cost –near-real-time availability NDVI images can be used: –map crop variations –determining management zones Ground observations x NDVI

3 Objective The purpose of the present work was the study of the relationships between NDVI (Normalized Vegetation Index) obtained by multispectral aerial images and ground plant physical measurements in three cotton fields managed by conventional and variable rate systems The Big Question: –Is this technology profitable?

4 2. Material & Methods Positioning System –GPS NAVMAN / IPAQ Softwares –COTMAN –Farm Site Mate –ERDAS Image –SSToolbox –SAS Imagery Acquisition –Duncan’s camera (Green, Red, Near Infrared bands) –0.5 to 1.5 meter resolution images were utilized

5 2. Material & Methods - Fields Each field was classed into 3 Productivity Zones via NDVI classing –Low, Medium and High 3 Paired farm fields –One field variable rate managed Three zone VR management missions –One field conventionally managed The field data was collected –8 sample replications per productivity zone per field 10 plant replications each point sample (144 sample reps and 1440 plants)

6 Multispectral Image 08/06/2001 Classed Image Low Medium High Zone Classing

7 Field Data Collected COTMAN Standard Data by productivity zone –Stand Count –First Position Retention –Height –Total Nodes –First Fruiting Branch Elongation of 4th Inter-node Yield Map Data Total Final Plant Maps Grid Sample

8 VR Applications Lime where needed Pre-plant Fertilizer Seeding In-furrow Fungicide In-furrow Insecticide Plant Growth Regulator In-season Insecticides Crop Termination

9 VR Applications

10 3. Results and Discussion NDVI vs. Yield NDVI Zones vs. 1 st Position Boll NDVI Zones vs. Total Bolls NDVI Zones vs. Total Nodes NDVI Zones vs. Height NDVI Zones vs. Stand Tukey’s Studentized Test – 5% –Means with the same letter are not significantly different

11 ImageYieldNDVI NDVI vs Yield

12 BA A A A B AB A NDVI Zones x 1 st Position Boll

13 BA A A A B ABA NDVI Zones x Total Bolls

14 BA A A A B AB A NDVI Zones x Total Nodes

15 B A A A A B ABA NDVI Zones x Height

16 B A A A A CBA NDVI Zones x Stand

17 Conventional vs VR Yield Difference equals 63 lbs average

18 Yield By Zone and Harvest Difference H = 33# M = 73# L = 83#

19 In each comparison Variable Rate Cotton production resulted in improved plant physical properties NDVI Zones v.s. 4. Conclusions 1 st Position Boll Total Bolls Total Nodes Height Stand

20 4. Conclusions The total reduction in crop inputs combined with improved plant parameters associated with likely improved yield would indicate that Variable Rate Cotton Production Systems which utilize multispectral image analysis for crop production zone creation are likely to have wide success in commercial cotton production in the Mid-South. Thanks to The National Cotton Council The National Science Foundation


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