Relationship between cotton yield and soil electrical conductivity, topography, and Landsat imagery

Relationship between cotton yield and soil electrical conductivity, topography, and Landsat imagery Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this study were to evaluate the spatial and temporal variability in cotton (Gossypium hirsutum L.) yield and determine the relationship between yield and soil ECa, topography, and bare soil brightness at a field level in multiple growing seasons. A 50-ha field grown with cotton from 2000 to 2003 and 2005 on the Southern High Plains of Texas was selected for this study. Yield was negatively correlated with bare soil brightness (−0.47 < r < −0.33 for red band) and positively correlated with ECa (0.08 < r < 0.29 for 30-cm ECa and 0.28 < r < 0.44 for 90-cm ECa). Yield had stronger correlation with relative elevation and slope than with profile curvature and planar curvature. Combined, ECa, topographic attributes, and bare soil brightness explained up to 70.1 % of cotton yield variability. Bare soil brightness and ECa were strongly related to soil texture. Brighter soils with low ECa values had lower clay content. Yield and soil properties had stronger correlation in dry growing seasons than in wet growing seasons. Cotton yield variability pattern was relatively stable across different growing seasons. Soil texture was one of the greatest factors influencing cotton yield variability. Results of this study provide a basis for site-specific management of yield goals and variable rate application of water, fertilizers, seeds, and other inputs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Relationship between cotton yield and soil electrical conductivity, topography, and Landsat imagery

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Publisher
Springer Journals
Copyright
Copyright © 2012 by Springer Science+Business Media, LLC
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-012-9277-2
Publisher site
See Article on Publisher Site

Abstract

Understanding spatial and temporal variability in crop yield is a prerequisite to implementing site-specific management of crop inputs. Apparent soil electrical conductivity (ECa), soil brightness, and topography are easily obtained data that can explain yield variability. The objectives of this study were to evaluate the spatial and temporal variability in cotton (Gossypium hirsutum L.) yield and determine the relationship between yield and soil ECa, topography, and bare soil brightness at a field level in multiple growing seasons. A 50-ha field grown with cotton from 2000 to 2003 and 2005 on the Southern High Plains of Texas was selected for this study. Yield was negatively correlated with bare soil brightness (−0.47 < r < −0.33 for red band) and positively correlated with ECa (0.08 < r < 0.29 for 30-cm ECa and 0.28 < r < 0.44 for 90-cm ECa). Yield had stronger correlation with relative elevation and slope than with profile curvature and planar curvature. Combined, ECa, topographic attributes, and bare soil brightness explained up to 70.1 % of cotton yield variability. Bare soil brightness and ECa were strongly related to soil texture. Brighter soils with low ECa values had lower clay content. Yield and soil properties had stronger correlation in dry growing seasons than in wet growing seasons. Cotton yield variability pattern was relatively stable across different growing seasons. Soil texture was one of the greatest factors influencing cotton yield variability. Results of this study provide a basis for site-specific management of yield goals and variable rate application of water, fertilizers, seeds, and other inputs.

Journal

Precision AgricultureSpringer Journals

Published: Aug 14, 2012

References

  • Apparent electrical conductivity measurement in agriculture
    Corwin, DL; Lesch, SM

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