Temporal dynamics of spectral reflectance and vegetation indices during canola crop cycle in southern Brazil

Abstract

The objective of this study was to characterize the variability of spectral reflectance and temporal profiles of vegetation indices associated with nitrogen fertilization, crop cycle periods, and weather conditions of the growing season in canola canopies in southern Brazil. An experiment was carried out during the 2013 and 2014 canola growing seasons at EMBRAPA Trigo, Passo Fundo, state of Rio Grande do Sul, Brazil. The experiment was conducted in a randomized block design with four replications. Five doses of nitrogen top dressing were used as treatments: 10, 20, 40, 80, and 160kg ha-1. Measurements were obtained with the spectroradiometer positioned above the canopy, to construct spectral reflectance curves for canola and establish temporal profiles for several vegetation indices (SR, NDVI, EVI, SAVI, and GNDVI). In addition, data on shoot dry matter were obtained and phenological stages were determined. The spectral reflectance curves of canola were reported to change with canopy growth and development. Temporal profiles of vegetation indices showed two maximum peaks, one before flowering and other after flowering. The indices SR, NDVI, EVI, SAVI, and GNDVI were able to characterize changes in the canola canopy over time, as a function of phenological phases, weather conditions, and nitrogen fertilization, throughout the development cycle. Plant growth and development, variations in crop management, and environmental conditions affect the spectral response of canola.

Normalized difference vegetation index obtained by ground-based remote sensing to characterize vine cycle in Rio Grande do Sul, Brazil

“…Ground-based remote sensing has emerged as an important source of data collected in the field in real time. In Brazil, temporal NDVI profiles, obtained by orbital or ground-based remote sensing, have been widely used to monitor biomes (Kuplich;Moreira;Fontana, 2013, Wagner et al, 2013Junges et al, 2016) and characterize vegetation growth in annual crops Fontana, 2011, Bredemeier et al, 2013Fontana et al, 2015;Klering et al, 2016;Pinto et al, 2016). However, the use of precision agriculture technologies applied to perennial crops is incipient in the country (Bassoi et al, 2014), with few studies published on the monitoring of fruit crop cycle using remote sensing techniques.…”

Production Potential and Crop Evapotranspiration Estimation for Bean, Soybean, and Maize Using the Sebal Algorithm

“…Images collected by remote sensing allow interpretation of spatial crops patterns in large areas, however, spatial resolution incompatible with the temporal resolution may affect the applicability of the images, consequently remote sensing has emerged as an important source of data collected in the field in real time, with that has been used to monitor growth in annual crops (Mazzetto et al, 2010;Pinto et al, 2017;Junges et al, 2017). The use of NDVI among different sensors and platforms it is very important for promoting the effectiveness of NDVI on crop assessment across space and over time (Grant, 2017).…”

Analise comparativa entre índices de vegetação e sua relação com o balanço hídrico em soja

“…A Figura 1 mostra o padrão de variação do NDVI e EVI ao longo da safra da soja para os três anos avaliados. Verifica-se que a evolução temporal dos mesmos mostrou algumas similaridades, o que é típico de culturas anuais (Junges & Fontana, 2009;Risso et al, 2012;Pinto et al, 2017). Em novembro, quando ocorreu a semeadura da soja, os valores dos IVs foram baixos e, posteriormente, mostraram crescimento até atingir o seu máximo nos meses de janeiro e fevereiro.…”