An integrated approach for predicting nitrogen status in early cotton and corn
<p>Cotton (<i>Gossypium hirsutum</i> L.) and corn (<i>Zea mays</i> L.) spectral reflectance holds promise for deriving variable rate N (VRN) treatments calibrated with red-edge inflection (REI) type vegetation indices (VIs). The objectives of this study were to define t...
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| Format: | Others |
| Language: | en |
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MSSTATE
2015
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| Online Access: | http://sun.library.msstate.edu/ETD-db/theses/available/etd-03082015-165140/ |
| Summary: | <p>Cotton (<i>Gossypium hirsutum</i> L.) and corn (<i>Zea mays</i> L.) spectral reflectance holds promise for deriving variable rate N (VRN) treatments calibrated with red-edge inflection (REI) type vegetation indices (VIs). The objectives of this study were to define the relationships between two commercially available sensors and the suitable VIs used to predict N status. Field trials were conducted during the 2012-2013 growing seasons using fixed and variable N rates in cotton ranging from 33.6-134.4 kg N ha<sup>-1</sup> and fixed N rates in corn ranging from 0.0 to 268.8 kg N ha<sup>-1</sup>. Leaf N concentration, SPAD chlorophyll and crop yield were analyzed for their relation to fertilizer N treatment. Sensor effects were significant and red-edge VIs most strongly correlated to N status. A theoretical ENDVI index was derived from the research dataset as an improvement and alternative to the Guyots Red Edge Inflection and Simplified Canopy Chlorophyll Content Index (SCCCI). </p> |
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