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Cotton Field Relations Of Plant Height To Biomass Accumulation And N-Uptake On Conventional And Narrow Row Systems
N. . Vilanova Jr., J. P. Molin, C. Portz, L. V. Posada, G. Portz, R. G. Trevisan
University of Sao Paulo
Although studied for decades, cotton field management remains a challenge for growers, especially due to spatial variability of soil conditions and crop growth, which demands the use of variable rate application technology (VRT) for nitrogen and growth regulators to improve yields and quality and/or save inputs. Canopy optical reflectance sensors are being studied as an option to detect infield variability but may have some limitations due to the known effect of signal saturation when used on very dense canopies, as is typical the case at late growth stages when there is still a need for VRT of growth regulators. Based on that, two commercial fields located on the state of Goiás, central part of Brazil, one planted on conventional row system (100 hectares) and other conducted on narrow rows system (116 hectares) were investigated during the 2012/13 growing season, both planted on no till system over high clay content soils and following corn as previous crop. Each field was scanned with an optical reflectance canopy sensor three times during the season based on days after planting (DAP) (47, 66, and 118 DAP on conventional and 51, 81 and 113 DAP on narrow), followed by manual sampling for crop height, biomass its N content on 30 spots inside the area, guided by the field variability shown by the optical canopy sensor. As the canopy sensor signal, the height of the cotton plant showed a high correlation with biomass and nitrogen uptake, and does not suffer saturation problems at late stages on both planting systems. This technology may be used as base for VRT nitrogen and growth regulators applications, or be combined with reflectance canopy sensors to improve accuracy at late split application, where canopy reflectance sensor are susceptible to lose accuracy.
Keyword: cotton, plant height, spatial variability