The most powerful information every farmer can harbor is the knowledge of his soil, and how they use this knowledge will decide the outcome of the season. Today conducting soil analysis is one way of accomplishing that, but what other options do you have during the growing season to stay proactive. Technology has come a long way, and those that embraces it's power reaps it's benefits.
Supposed you are growing wheat and want to optimize your output then you could use this model by PrecisionHawk
Absolute Sense™ – In Crop Mapping – Nitrogen – Winter Wheat*
A new layer of information to support agronomic decision-making.
- Instant view of nitrogen distribution in your field. Benefits:
- See in-field N variation.
- See best/worst areas for nitrogen uptake.
- Combine with other in-crop nutrient maps and/or soil maps to get a full layered picture of information.
- Supports planning decisions.
- Values in kilograms of nitrogen per hectare. Benefits:
- Additional information to support agronomic decisions for calculating fertilizer applications.
Two color profiles are supported:
- Equal Area uses a dynamic legend, enabling users to see more detail across the field, highlighting where the variation in the field is at one time. This option is best for supporting fertilizer management decisions.
- Equal Spacing visibly useful when comparing against other fields and also previous in-season maps of the same field across growth stages.
What if you wanted to monitor the effectiveness of your irrigation program you could use the model below.
Identify standing water in pre-emergent agriculture fields
Using only high-resolution imagery from your NIR modified sensor, areas of standing water in agriculture fields can be accurately identified and measured. This algorithm was developed to work in pre-emergent agricultural fields and quantify areas that cannot be planted due to standing water. Additional uses could include determining flood damage immediately after an extreme rain event or monitoring water levels of permanent water features.
Users should be aware that outside of pre-emergent agriculture conditions there is potential to misclassify non-water features as standing water. Typically, dark surfaces (shadows, asphalt, etc.) can be confused with water in this algorithm.
What if you wanted to monitor your crops during the growing season then
Soil Adjusted Vegetation Index
SAVI was developed as a modification of the NDVI to correct for the influence of soil brightness. This index is recommended to analyze crops in early or mid growth stages. Early growth stage analysis is recommended when there are clearly separated rows or plants and where soil is very apparent. Mid season growth stage analysis is recommended when plants are not touching, are in separated rows, and where the canopies make a uniform shadow.
So whats the technology behind this? The Drone platform with the right payload to gather the precise data to convert to business insights. If you already are using drones as part of your workflow, then you already have a leg up, if not then hire a company with the capabilities.