Dissertation/Thesis Abstract

Effectiveness of crop reflectance sensors on detection of cotton (Gossypium hirsutum L.) growth and nitrogen status
by Raper, Tyson Brant, M.S., Mississippi State University, 2011, 287; 1497285
Abstract (Summary)

Cotton (Gossypium hirsutum L.) reflectance has potential to drive variable rate N (VRN) applications, but more precise definitions of relationships between sensor-observed reflectance, plant height, and N status are necessary. The objectives of this study were to define effectiveness and relationships between three commercially available sensors, and examine relationships of wavelengths and indices obtained by a spectrometer to plant height and N status. Field trials were conducted during 2008-2010 growing seasons at Mississippi State, MS. Fertilizer N rates ranged from 0-135 kg N ha-1 to establish growth differences. Sensor effects were significant, but sensors monitoring Normalized Difference Vegetation Index (NDVI) failed to correlate well with early-season N status. Wavelengths and indices utilizing the red-edge correlated most strongly with N status. Both Guyot's Red Edge Index (REI) and Canopy Chlorophyll Content Index (CCCI) correlated consistently with N status independent of biomass status early enough in the growing season to drive VRN.

Indexing (document details)
Advisor: Varco, Jac J.
Commitee: Cox, Michael S., Lawrence, Gary W., Reddy, K. Raja, Roberts, Darrin F.
School: Mississippi State University
Department: Plant and Soil Sciences
School Location: United States -- Mississippi
Source: MAI 50/01M, Masters Abstracts International
Subjects: Agronomy, Remote sensing
Keywords: Canopy chlorophyll content index, Cotton, Nitrogen, Normalized difference vegetation index, Red edge index, Sensor
Publication Number: 1497285
ISBN: 978-1-124-80076-9
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