Responsive in-season nitrogen management for cereals

Current nitrogen (N) management strategies for worldwide cereal production systems are characterized by low N use efficiency (NUE), environmental contamination, and considerable ongoing debate regarding what can be done to improve N fertilizer management. Development of innovative strategies that improve NUE and minimize off-field losses is crucial to sustaining cereal-based farming. In this paper, we review the major managerial causes for low NUE, including (1) poor synchrony between fertilizer N and crop demand, (2) uniform field applications to spatially variable landscapes that commonly vary in crop N need, and (3) failure to account for temporally variable influences on crop N needs. Poor synchronization is mainly due to large pre-plant applications of fertilizer N, resulting in high levels of inorganic soil N long before rapid crop uptake occurs. Uniform applications within fields discount the fact that N supplies from the soil, crop N uptake, and crop response are spatially variable. Current N management decisions also overlook year-to-year weather variations and sometimes fail to account for soil N mineralized in warm, wet years, ignoring indigenous N supply. The key to optimizing tradeoffs amongst yield, profit, and environmental protection is to achieve synchrony between N supply and crop demand, while accounting for spatial and temporal variability in soil N. While some have advocated a soil-based management zones (MZ) approach as a means to direct variable N applications and improve NUE, this method disregards yearly variation in weather. Thus, it seems unlikely that the soil-based MZ concept alone will be adequate for variable application of crop N inputs. Alternatively, we propose utilizing emerging computer and electronic technologies that focus on the plant to assess N status and direct in-season spatially variable N applications. Several of these technologies are reviewed and discussed. One technology showing promise is ground-based active-light reflectance measurements converted to NDVI or other similar indices. Preliminary research shows this approach addresses the issue of spatial variability and is accomplished at a time within the growing season so that N inputs are synchronized to match crop N uptake. We suggest this approach may be improved by first delineating a field into MZ using soil or other field properties to modify the decision associated with ground-based reflectance sensing. While additional adaptive research is needed to refine these newer technologies and subsequent N management decisions, preliminary results are encouraging.We expect N use efficiency can be greatly enhanced using this plant-based responsive strategy for N management in cereals

Comportamento do NDVI obtido por sensor ótico ativo em cereais Behavior of NDVI obtained from an active optical sensor in cereals

O objetivo deste trabalho foi avaliar, com um sensor ótico ativo, o comportamento do índice de vegetação por diferença normalizada (NDVI - "normalized difference vegetation index"), nas culturas de trigo, triticale, cevada e milho. Cinco experimentos foram conduzidos no Paraná e São Paulo, com variação de classes de solo, doses e fontes de N, e variedades de trigo. As seguintes variáveis foram avaliadas: NDVI, teor de N foliar, matéria seca e produtividade das culturas. Análises de regressões foram realizadas entre as doses de N aplicadas e NDVI, teor de N foliar, matéria seca e produtividade. Análises de correlação entre as variáveis foram realizadas. O trigo, triticale e cevada apresentaram resposta às aplicações de doses crescentes de N, pelo aumento nas leituras do NDVI, no teor de N foliar e na produtividade. Medido pelo sensor ótico ativo utilizado, o NDVI apresenta alto potencial para manejo do N nas culturas do trigo, triticale e cevada, e baixo potencial para a cultura do milho. Há interferência das variedades de trigo nas leituras do sensor ótico ativo.<br>The objective of this work was to evaluate the behavior of the normalized difference vegetation index (NDVI), with an active optical sensor, in wheat, triticale, barley and corn crops. Experiments were conducted in Paraná and São Paulo, comparing different soil classes, N rates and sources, and wheat varieties. The following variables were determined: NDVI, N foliar content, dry mass and crop yield. Regression analyses were performed between NDVI and applied N rates, N foliar content, dry mass and yield. Correlation analyses among the variables were performed. Wheat, triticale and barley crops showed response to increasing N rates by the increase in the NDVI readings, to N foliar content and to yield. Measured by the used active optical sensor the NDVI shows high potential for N management wheat, triticale and barley crops, and low potential for corn crops. There is interference of wheat varieties in the active optical sensor's readings

Validação de modelo para predição do potencial produtivo de trigo com sensor óptico ativo

O objetivo deste trabalho foi validar um modelo baseado no índice de vegetação por diferença normalizada (NDVI), para a predição da variabilidade espacial da biomassa acumulada na parte aérea e da produtividade de grãos de trigo. Foram realizadas leituras georreferenciadas de NDVI e biomassa, no final do afilhamento, e produtividade. O modelo proposto permitiu relacionar classes de variabilidade espacial do NDVI e da biomassa, com 81% de correspondência entre elas. Entretanto, a relação entre as classes de variabilidade espacial da produtividade e do NDVI foi menor, com 48% de correspondência