Limites Críticos De Ndvi Para Estimativa Do Potencial Produtivo Do Milho

Abstract

RESUMO - A estimativa do potencial produtivo da cultura do milho ao longo do ciclo de desenvolvimento é uma das novas práticas agrícolas que vêm sendo utilizadas para qualificar o manejo da cultura. Neste sentido, destaca-se a inserção de sensores de vegetação, com a finalidade de realizar o monitoramento do desenvolvimento e da condição nutricional da cultura ao longo do seu ciclo. O objetivo do presente trabalho foi determinar os limites críticos do Índice de vegetação por diferença normalizada (NDVI) para a determinação de classes de potencial produtivo do milho em diferentes estádios fenológicos, utilizando sensor óptico ativo de vegetação (Greenseeker). O experimento foi conduzido na EEA/UFRGS, durante a safra agrícola 2013/2014. Os tratamentos consistiram de diferentes épocas de dessecação da aveia branca (Avena sativa L.) antes da semeadura da cultura do milho. As avaliações com o sensor óptico ativo foram realizadas nos estádios fenológicos V3, V5, V6, V7 e V8. Os resultados mostraram que o NDVI medido pelo sensor Greenseeker foi eficiente na predição da produtividade de milho em diferentes estádios fenológicos. Os limites críticos de NDVI, os quais correspondem a diferentes classes de potencial produtivo, podem ser identificados de maneira rápida e precisa entre os estádios fenológicos V3 a V8 e esta informação pode ser empregada para a adubação nitrogenada em taxa variável de acordo com o potencial produtivo estimado. Palavras-chave: Greenseeker, índice de vegetação, Zea mays, NDVI. CRITICAL LIMITS OF NDVI FOR YIELD POTENTIAL ESTIMATION IN MAIZE ABSTRACT - The estimation of grain yield potential of maize along the growth cycle is one of new agricultural practices that have been used to qualify crop management. In this sense, the use of vegetation sensors can be highlighted, in order to carry out the monitoring of plant development and nutritional condition throughout its development. The objective of this study was to indicate NDVI critical limits for determining grain yield potential classes of maize in different growth stages using an active optical vegetation sensor (Greenseeker). The experiment was carried out in the 2013/14 growing season, in Eldorado do Sul, State of Rio Grande do Sul, southern Brazil. Treatments consisted of different dissecation timing of oat (Avena sativa L.) before corn sowing. Evaluations with the active optical sensor were done at growth stages V3, V5, V6, V7, and V8. Results showed that NDVI measured by the sensor Greenseeker was efficient in identifying maize grain productivity at different growth stages. NDVI critical limits that correspond to different yield potential levels in maize can be quickly and precisely identified between V3 and V8 growth stages and this information can be used for site-specific nitrogen fertilization according to the estimated yield potential. Keywords: Greenseeker, vegetation index, Zea mays, NDVI.

Nutritional Status of Corn Plants Estimated Through Different Vegetation Indices in the Growth Stages

“…Among the relationships between VIs and the N content absorbed by the plant at the V7 growth stages of the corn crop (Figure 5), V11 (Figure 6) and V12 (Figure 7), the ones that showed the best relationships were those in the V12 stage. For the V7 stage, the indices EVI2 and GNDVI (RPAS platform) showed the best relations, with CARVALHO, L. F. D. et al The use of IVs, in the different platforms is an alternative for real-time assessments of the nutritional status of crops and can be an important tool in determining nitrogen fertilizer doses more consistent with the real need for N by plants (VIAN et al, 2018). Schmidt et al (2011) found a satisfactory relationship between the NDVI readings and the nitrogen fertilizer dose demand for corn.…”

“…The use of the IV tool allows the real-time and in-situ estimation of the nutritional status of the plants in different growth stages and also the productive potential of the corn crop, allowing the nitrogen fertilization to be adjusted and applied according to the development of the crop (LI et al, 2010;VIAN et al, 2018).…”

“…Several studies have reported the efficiency of this tool in crops such as corn and wheat (POVH et al, 2008, AMADO et al, 2017. Optical sensors coupled to aircraft or satellites are a potentially important source of data with sufficient spatial resolution to capture spatial variability (SHANAHAN, 2001;VIAN et al, 2018). From the optical sensors, it is possible to produce several vegetation indexes (VIs).…”

Efeito da chuva de granizo em variedades do café arábica por meio de índices de vegetação

“…Os IVs foram calculados com o auxílio do software geoestatístico em plataforma livre QGIS sendo utilizado a Calculadora Raster, algoritmo com a capacidade de realizar os cálculos referentes às expressões matemáticas de cada índice de vegetação (IV), sendo estes: IV por diferença normalizada (NDVI), Vian et al (2018), Equação (1); IV por diferença normalizada da borda vermelha (NDRE), Fitzgerald et al (2006) Equação (2). NDVI = (Nir -Red) / (Nir+Red) (1) NDRE = (Nir-Red Edge) / (Nir + Red Edge)…”

Multispectral aerial images for the evaluation of maize crops

“…The technological advances of RPAs have been remarkable in recent years, both for applications relating to land use, as in issues inherent in the reduction of environmental damage, reducing the need for inputs and maximizing profits (Honda;Jorge, 2013). An increasingly efficient application of N during the crop cycle is also being pursued, since this nutrient promotes the development of the plant, while a low availability of this nutrient prevents higher yields in maize (Vian et al, 2018).…”