Canopy-scale wavelength and vegetative index sensitivities to cotton growth parameters and nitrogen status

Canopy-scale wavelength and vegetative index sensitivities to cotton growth parameters and... Temporal and spatial variability of plant available N in the humid southeastern region of the United States often results in within-field over- and under- application of this nutrient to cotton. Although ground-based canopy reflectance has the potential to quantify crop N status in real-time and drive variable rate fertilizer N applications, currently utilized vegetation indices often fail to correlate strongly with crop N status. Therefore, the objective of this study was to examine relationships between canopy reflectance across wavelengths and calculated ratios and vegetation indices prior to and at flowering to biomass, leaf tissue N concentration, aboveground total N content and lint yield. Data was collected during the third week of flower bud formation and the first week of flowering during the 2008–2010 growing seasons at Mississippi State, MS, USA. Analysis of wavelength sensitivities indicated reflectance near 670 nm was most highly correlated to plant height, but relatively poorly correlated to lint yield, total plant N content and leaf N concentration. The strongest wavelength correlations with leaf N concentration, lint yield and plant total N content were noted near 700 nm. Subsequent analysis indicated indices utilizing reflectance in the red edge region correlated more strongly to leaf N status and total plant N content when compared to indices relying on reflectance in green or red regions. Comparisons between simple red edge indices and more complex calculations of the red edge inflection point suggested a simplified version of the Canopy Chlorophyll Content Index calculation may provide reasonable reliability for real-time detection of cotton N status. Precision Agriculture Springer Journals

Canopy-scale wavelength and vegetative index sensitivities to cotton growth parameters and nitrogen status

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Springer US
Copyright © 2014 by The Author(s)
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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