Advanced Nitrogen Management in Sugar Beet

Objective

This guide aims to show the steps that must be followed to view the Nitrogen status of the sugar beet plant and make a comparison between different plots.

1. Selección de campos en layers

1.1. selection by planting date

To make decisions, you can filter by planting date to compare, for example, early versus late plantings.

1.2. Selection by plot name

You can also select them if you know the plot names or farmer name

Figure 2. Plot selection by name.

2. Acceso al panel de Evolución Nitrógeno (Dashboard)

Una vez seleccionadas las parcelas, accedemos al panel de Dashboard (botón superior derecho). Una vez dentro, debemos ir a “Season evolution”, último botón del margen izquierdo, para que aparezca el gráfico de evolución de nitrógeno.

2.1. Nitrogen-Week Graph Interpretation

Este gráfico permite comparar parcelas con diferente fecha de plantación al compararse con semanas desde fecha de siembra. El promedio de nitrógeno dentro del 25% de las parcelas con mayor contenido de sacarosa a la semana 12 de haber sido plantadas es de 2.65, pudiéndose considerar el nitrógeno de las parcelas próximas a este valor como adecuado. Entre ellas la parcela “Prado”, y la parcela sin nombre de González del Rey. Por el contrario, encontramos parcelas con niveles elevados de nitrógeno para esa fecha, como es el caso de Blanco Bermejo con 2.93.

Figure 3. Nitrogen evolution by date for the different plots. Note: For unnamed plots, the farmer’s name appears

2.2. Nitrogen graph interpretation - Day.

In this graph, only plots with a similar planting date are comparable since it reflects the nitrogen on each date (satellite pass).

Figure 4. Daily nitrogen evolution for different plots. Note: In unnamed plots, the farmer’s name appears

3. Distribución nitrógeno en la parcela

Once the anomaly has been detected, we will visually compare the plot with high levels against the one with optimal values.

Figure 5. Nitrogen evolution for two plots identified as anomalous and normal

We observe that they are relatively close together and have the same planting date.

Figure 6. Plot visualization (RGB)

When viewing the chlorophyll layer, we can see how the plot on the right has low NDRE values.

Figure 7. Plot visualization (NDRE)

3.1. Export information in PDF format

Figure 8. Tool for exporting the nitrogen distribution in the plot to PDF

A PDF is exported with the area in hectares corresponding to each zone. There are a total of 5 zones plus one for soil and another for clouds.

Figure 9. PDF with nitrogen distribution

3.2. Export information in shapefile format

This map can be exported in Shape format so it can be read by a machine or tractor. To do this, select the layer name, the index to be used, in this case the chlorophyll-nitrogen index (NDRE), and the pixel size with which we want it to be exported. The smaller it is, the higher resolution it will have.

Figure 10. Tool for exporting nitrogen distribution in the plot to shapefile

This file can be read by any GIS program, for example QGIS where it is displayed as follows when classified by colors.

Figure 11. Shapefile with nitrogen distribution