Nitrogen fertilization management in white oat using spectral indices - Barbosa, Jose de Arruda [UNESP]; Faria, Rogerio Teixeira de [UNESP]; Coelho, Anderson Prates [UNESP]; Dalri, Alexandre Barcellos [UNESP]; Palaretti, Luiz Fabiano [UNESP] (Univ Federal Goias, 2020)
Remote sensing techniques have been considered a new technology in worldwide agriculture for diagnosing the plant nutritional demand. Fertilizer management efficiency is a goal to be achieved, and modern tools based on remote sensing are promising for monitoring the crop needs. This study aimed to evaluate the agronomic performance and relative economic return of white oat under nitrogen rates, as well as to verify whether the normalized difference vegetation index (NDVI) and leaf chlorophyll index (LCI) could be used for topdressing nitrogen fertilization management, in white oat. Treatments consisted of five topdressing nitrogen fertilization strategies: T1 - 160 kg ha(-1) (reference rate); T2 - 90 kg ha(-1) (recommended rate); T3 - 60 kg ha(-1) (economic rate); T4 - 30 kg ha(-1) (when NDVI < 90 % of T1); and T5 - 30 kg ha(-1) (when LCI < 90 % of T1). The white oat did not respond to the topdressing nitrogen fertilization. Its temporal monitoring using spectral indices allowed dispensing the topdressing nitrogen fertilization without reducing the grain and biomass yields and the leaf nitrogen content, when compared to the recommended management (90 kg ha(-1) of N as topdressing), with no differences between the evaluated spectral indices. Thus, both the NDVI and LCI spectral indices are promising tools for the topdressing nitrogen fertilization management in the white oat crop.
Keywords: Avena sativa L.; leaf chlorophyll index; normalized difference vegetation index; precision agriculture