Early season grain yield prediction using remote sensing and site-specific management zones

D. Inman; R. Khosla; M. Lefsky; D.G. Westfall

Early season grain yield prediction using remote sensing and site-specific management zones

In: Precision Agriculture â05

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D. Inman

D. Inman ¹Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523-1170
dinman@colostate.edu

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R. Khosla

R. Khosla ¹Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523-1170

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M. Lefsky

M. Lefsky ²Department of Forestry, Rangeland, and Watershed Stewardship, Colorado State University, Fort Collins, CO 80521-1170

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D.G. Westfall

D.G. Westfall ¹Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523-1170

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Type:: Chapter

Pages:: 835â841

DOI:: https://doi.org/10.3920/978-90-8686-549-9_102

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Remote sensing is a promising tool for characterizing spatial variability of crop grain yield early in the growing season. The objectives of this study were (i) to examine the relationships among spectral vegetation, site-specific management zones and relative maize (Zea Mays L.) yield and, (ii) to determine if site-specific management zones can be used in conjunction with remote sensing imagery to provide early season yield predictions in irrigated maize. Remotely sensed imagery was acquired by aircraft at the six-leaf crop growth stage. Kappa statistics and percent area agreement suggested a moderate area association between NDVI, relative grain yield and management zones (Î = -0.007 to 0.43, % area agreement = 35 to 67 %). Regression models explained 45 and 42 % of the variability in relative grain yield. Inclusion of management zones in the regression models resulted in marginal improvements. Our study indicated that vegetation indices from remotely sensed imagery have the potential to accurately predict grain yield as early as the six-leaf growth stage in irrigated maize.

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Precision Agriculture â05

E-Book ISBN:: 9789086865499

Publisher:: Wageningen Academic

Print Publication Date:: 24 Oct 2005

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Early season grain yield prediction using remote sensing and site-specific management zones

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