- From planting maps, to stand counts and tassel counts, aerial images can help us track in-season field conditions to avoid surprises at harvest.
- Aerial imagery can help us identify weed escapes, insect damage, disease symptoms, nutritional deficiencies and other issues throughout the season, so that we can address them in a timely manner.
- In addition to helping to make decisions to implement corrective measures, field maps can help us build the field’s history and identify problem spots before harvest.
The wonderful aspect of yield monitors is their ability to give us in-cab, real-time yield results. But when yields are lower - or higher - than expected, we naturally want to know the causes and avoid those less-than expected yields next year or for the better, repeat a happy success.
Identifying potential causes of late-season yield-drags can be challenging, and sometimes impossible. Technology focused on improving agriculture production, has made it easier to identify and track field problem areas during the growing season. Advances in image resolution and frequency of data capture makes aerial imagery a valuable scouting tool. Aerial imagery can help identify weed escapes, insect damage, disease symptoms, nutritional deficiencies and weather-related issues, helping farmers address potential problems before they negatively impact yield. Other rising and noteworthy uses of game-changing ag technology include:
- Aerial imaging helps farmers keep a closer eye on stand establishment, as well as crop growth and development throughout every stage.
- GIS-referenced planting maps will show if the as-planted population has actually emerged, and help determine if, and where, a replant might be necessary - a technology of particular advantage in a wet-laden and rain-inundated spring.
- Aerial imagery data will supplement planting maps by performing stand counts across every acre.
- Some imagery providers can perform tassel counts late in the season, to more accurately predict the yield potential of a particular field.
- A new tool, currently being tested by FS companies through GROWMARK’s AgValidity trial program, can test corn ear moisture and help estimate bushels per acre.
- Another tool provides pre-harvest population counts by zone, or measures biomass from the aerial images taken.
With all this technology, farmers and their local agronomists will know, in real time, of any field issues that need their attention early – all before they even get the combine out of the shed. By contrast, let’s walk through an example of a field that was not tracked by technology this past growing season, and the causes of yield variances were only revealed late in the growing season.
As this field started to show problem areas, more information was gathered, and at least three potential causes were identified. 1. Manure applied last fall streaked due to rainfall over the winter. 2. Urea applied over-the top and cross way, also showed streaking. 3. Biomass variances showing the split hybrids' different characteristics. We can visualize these causes in the following images:
IMAGE 1 below. This RGB image shows crop biomass and crop color. Some areas of the field had nitrogen loss from the numerous rains and spring weather. The darker areas had late-season urea application (blue arrow) and the angled lines show areas where manure was applied (red arrow). The streaking and the angles of application in both areas are quite clear. (Image taken August 2019)
IMAGE 2 below. This NDVI image taken during the same flight as the RGB image above, shows the crop response to the urea and manure applications. (Green segments show higher crop response) (Image taken August 2019)
IMAGE 3 below. When this harvest data map was layered against the above two images, a yield difference of +32 bu/a was revealed in the areas that received extra applied nitrogen. (Green segments)
This analysis, done late season, does still leave the question: given the unusual weather events of this growing season, could the farmer have taken correct action if this information was available earlier? The only answer is, perhaps. But without knowing a problem existed, this farmer lost the opportunity to estimate ROI or address in part, the highest N-deficient areas of the field. And without complete or accurate post-season data, the farmer could have instead, made assumptions about what caused less-than-expected yields, and perhaps decide upon adjustments for the following season that could not address the true cause.
What seems to be clear is that ag-centric technology continues to innovate, and the data it gathers will expand into every aspect of the farm operation. And when hardware and software of ag technology platform become more accurate, so will farmers’ crop management decisions.