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Use of Multispectral Imagery for Variable Rate “Application-zone” Identification in Cotton Production Tim Sharp Beltwide Cotton Conference January 6-10,

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Presentation on theme: "Use of Multispectral Imagery for Variable Rate “Application-zone” Identification in Cotton Production Tim Sharp Beltwide Cotton Conference January 6-10,"— Presentation transcript:

1 Use of Multispectral Imagery for Variable Rate “Application-zone” Identification in Cotton Production Tim Sharp Beltwide Cotton Conference January 6-10, 2003

2 1. Introduction  Researchers have been trying to identify the correct management zones based mainly on the variability of the crop yield.  Airborne multispectral imaging of cotton can provide important spatial information  Spatial variations in crop vigor can be observed in green, red and near infrared wavebands  Multispectral images can be used to monitor the spatial and temporal changes in the growth of crops

3 Objective The purpose of this study was to investigate the use of multispectral imagery As a tool to map cotton vigor zones Test the hypothesis that imagery from one year would map the zones in subsequent years (Zones are stable in time and space) Could these maps be a tool for variable rate application prescriptions in the following year

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 Field Data Collected Standard Data by productivity zone –Stand –Height –Total Nodes –Total Bolls Yield Map Data Total Final Plant Maps

6 3. Results and Discussion IMAGE x NDVI - Barn - Moose Lodge - Traveler Rest

7 3. Results and Discussion Barn 9 - 2001 Low Medium High Low Medium High

8 NDVI x NDVI – Barn NDVI 2002 NDVI 2001

9 3. Results and Discussion Moose Lodge 2 - 2002 Low Medium HighLow Medium High

10 NDVI x NDVI – Moose Lodge NDVI 2002 NDVI 2001

11 3. Results and Discussion Traveler’s Rest 1 - 2002 Low Medium High Low Medium High

12 NDVI x NDVI – Traveler’s Rest NDVI 2001 NDVI 2002

13 3. Results and Discussion Wildy 4 – 2002 (Irrigated) Low Medium High Low Medium High

14 NDVI x Yield – Wildy (Irrigated) Yield 1998 NDVI 2002

15 3. Results and Discussion Year 2001 vs Year 2002 - Stand - Height - Total Nodes - Total Bolls

16 3. Results and Discussion MOOSE LODGE BARN TRAVELERS REST STAND 2001 vs 2002 Tukey's Studentized Test with alpha at 5% - Means with the same letter are not significantly different.

17 3. Results and Discussion BARN MOOSE LODGE TRAVELERS REST HEIGHT 2001 vs 2002 Tukey's Studentized Test with alpha at 5% - Means with the same letter are not significantly different.

18 3. Results and Discussion BARN MOOSE LODGE TRAVELERS REST TOTAL NODES 2001 vs 2002 Tukey's Studentized Test with alpha at 5% - Means with the same letter are not significantly different.

19 3. Results and Discussion BARN MOOSE LODGE TRAVELERS REST TOTAL BOLLS 2001 vs 2002 Tukey's Studentized Test with alpha at 5% - Means with the same letter are not significantly different.

20 Summary and Conclusions

21 Some researchers have reported in other areas of the country that zones change position. –May be due to wet soil conditions –May not have enough total variability in the field to fully express zone identity In our study the medium zones may or may not be significantly different from either the low or high zone from one year to the next

22 In West Tennessee Zones did not move from year to year. –With over 100 fields studied across three years –Final Plant Map data were collected from each of the five NDVI classed zones in each field –We never found that the low classed NDVI zone or the High Classed NDVI zone were incorrectly identified –Confirmation plots agreed completely with research site data

23 Implications NDVI classed maps obtained after 550 DD 60 NAWF 5 but prior to defoliation –Will accurately map the productivity zones for the following years –Will allow for the opportunity to plan Variable Rate Applications based on those classed maps in subsequent years –Correctly maps and predicts the cotton vigor to be expressed in those areas

24 Acknowledgements National Cotton Council National Science Foundation


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