Wheat Growth Monitoring & How to Mitigate Herbicide Resistance

About the project

The project looked at how a farmer can use drones and Agremo reports and analyses throughout the growing season to improve weed and disease management in a wheat crop. The farmer in question was interested in how precision farming could help improve his arable farming technique. The project showed him how drones could help with the management of his spring wheat crop. The project was focused on weed management in particular, and the growing threat of herbicide-resistant weeds.

By using Agremo analysis and a precision agriculture approach to weed management of the growing crop, the farmer was able to save the equivalent of $7.86 per acre on herbicides. This not only improved his profit margin but also reduced the risk of herbicide resistance and improved the environmental sustainability of the operation.

Customer requirements and challenges

Our farmer, Bill, needed timely information to help make crop protection decisions throughout the growing season.

Most herbicide applications should be made before jointing (or Feekes Growth Stage 6), or before the appearance of the first node at the base of the plant (usually 4 to 8 inches tall with 12 or more leaves). Herbicide application during grain ripening may aid harvest operations but will not increase grain yields.

Herbicide resistance is a growing problem for crop farmers in many parts of the world and farmers need to consider strategies to prevent or slow down the development of weeds resistant to commonly used herbicides. Herbicide resistance continues to spread in weed populations, infesting global wheat crops [2].

Field conditions / Existing processes

In the past, Bill conducted crop scouting by walking across his field at various points throughout the season. Although Bill had previously only sprayed when pest or weed infestations had exceeded economic threshold levels, the applications were applied to whole plots or fields.

During the project, weeds had become noticeable before growth stage 30. However, Bill needed to know the extent and severity of the infestation to decide on herbicide applications.

How Agremo approached the project

Agremo is a precision agriculture software that uses AI to analyze aerial imagery. It provides valuable information to growers and Ag professionals about the condition of their crops during the season and helps them to make better-informed decisions. Agremo analysis can be performed on maps gathered with all common sensor/camera types, including RGB, NIR, and Multispectral. The best results are obtained with a resolution of around 0.9 inches per pixel, which can be achieved with almost any commercially-available drone.

It has been shown that a UAV flying at a range of 30 to 100 m altitude and using a moderate number of GCPs can generate ultra-high spatial resolution images with the geo-referencing accuracy that is required to map small weeds in wheat at a very early phenological stage [1].

Agremo recommended that Bill carried out flights at the following BBCH[3] stages of development: Stage 0, 30, 39, and 61.





The process and the solution

Drone flights were carried out at key stages within the development of the crop, and the images were used to generate Agremo reports.

Flight 1 Pre-planting (Stage 00)

Arable Area analysis was performed before sowing to calculate the exact arable area and allow Bill to compare it with planted size. The data allowed him to optimize inputs, and immediately create savings. An elevation map also pointed out places with elevation differences in the field. Such differences need to be spotted to prevent waterlogging, nutrient washing or creating an environment favorable to diseases and weeds.

Flight 2 (Stage 30)

Stand Count checked the germination rate. The plant count report provided information about the difference between the planted and emerged number of plants in the early stage and pointed out zones where plants did not emerge. This helped Bill to decide whether the crop had been successfully established, to replant or not, and provided a check on seed quality, an early indication of yield, and identified low-performing areas.

Weed Detection identified and quantified weed zones in the field. This data helped Bill optimize herbicide applications and achieve savings in areas where spraying was not needed and prevented additional stress and yield loss.             

Flight 3 (Stage 39)

Plant Stress allowed him to check the plant health status after spraying and fertilizing operations in mid-season. Plant Stress analysis detects all the stress in the field and provides field insights about the stress in percentages and the exact location of stress zones.

Flight 4 (Stage 61 – before harvest)

Yield Potential analysis identifies and calculates areas of the field with high yield potential, low-performing areas, and areas with no yield at all, with a special focus on lodging detection. This analysis helped to point out zones with good and poor yield, and enabled a more targeted approach to management.

What happened in the field

The flight carried out at stage 30 revealed a significant weed infestation.

What went as planned

Drone flights were carried out through the growing season as planned and were able to generate a range of Agremo reports that helped Bill make decisions throughout the season. The first report (Eagle Eye) confirmed the exact field size and allowed the correct seed and fertilizer rates to be applied.

What was unplanned

Weed Detection analysis carried out after the second flight indicated that 39% of the field was infested by broad-leaved weeds, mainly henbit and purple dead nettle. The flight was able to provide a map indicating the infested areas which provided Bill with actionable information on weed control. He decided to apply two applications of post-emergence herbicides. In traditional agriculture, the entire area is treated in two treatments, however, armed with the information provided by the drone flight, Bill was able to treat only the affected areas of the field.

Where there any issues

Broadleaf weeds growing in wheat fields can adversely affect crop production in many ways. Weeds compete with wheat for light, water, and minerals, which results in smaller crop yields. Weeds also interfere with crop harvest by raising moisture levels and contaminating the harvested grain.

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What were the decisions informed by Weed Analysis

After the weed analysis, it was decided that herbicide was not required on the whole field since only 39% was infested. The Agremo analysis was able to provide a map of the infested areas and Bill was able to come up with a plan to apply treatment to the affected areas only.

Return on investment

Afterward, Bill sat down and calculated the implications of using the drone. Using a drone with Agremo meant that 35% of the area of the field received herbicide. It should also be noted that although drone scouting costs $4 per acre, in reality, traditional crop scouting would involve walking across the field, and would incur a labor cost.

In this case, opting for a precision agriculture approach saved Bill the equivalent of $7.86 per acre, or $249.63 in total. He reduced production costs, as well as experienced environmental benefits, but reduced the use of herbicides. Also, by leaving some areas of the field untreated, farmers can help minimize the risk of herbicide resistance by reducing the selection pressure for resistant strains of weed. Scouting after herbicide applications can also help to identify herbicide-resistant weed populations.

When compared to the traditional way of doing things, it is evident that precision agriculture offers significant cost savings for wheat producers, and Agremo can provide actionable information to make these savings.


  • D. Gómez-Candón, A. I. De Castro, and F. López-Granados, “Assessing the accuracy of mosaics from unmanned aerial vehicle (UAV) imagery for precision agriculture purposes in wheat,” Precis. Agric., 2014, doi: 10.1007/s11119-013-9335-4.
  • M. J. Walsh and S. B. Powles, “Management of herbicide resistance in wheat cropping systems: Learning from the Australian experience,” Pest Management Science. 2014, doi: 10.1002/ps.3704.
  • Agrifood Canada, “Crop Identification and BBCH Staging Manual: SMAP-12 Field Campaign,” 2011. [Online]. Available: https://smapvex12.espaceweb.usherbrooke.ca/BBCH_STAGING_MANUAL_CEREALS_CORN.pdf.
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