Improving Soybean Yield with Spot Weed Treatment

Drone Spraying Maps – Validated!

Agriculture could be the most inefficient industry, but still with a trend of an increasing number of innovations. Even though agriculture is described as the most traditional, farmers and other participants in the value chain are willing to adopt innovative solutions that can improve their yields and production processes or lowering costs.

Since weed management is almost mandatory in a farmer’s life, we had a monitored test of weed spot treatment with a spraying drone in the Midwest, USA. On a farm where soybeans are grown in rotation with corn, we applied the automated Agremo Weed Detection analysis to identify the areas and the degree of voluntary weed infestation of corn in the soybean crop. A farmer approaches weed control with a new Variable Drone Spraying app created by Agremo and DJI for spraying drones.

Agremo analytics showed that the 65-acre farm had 3.75 acres infested with individual volunteer corn and six acres with clumped corn.

Deciding to control the volunteer corn prevented a 15% and 60% yield loss from individual and clumped volunteer corn, respectively. Besides this yield increase, the farmer saved money by opting for spot variable treatment with a spraying drone T30 instead of a flat treatment. As a result, he needed to use only 60% of herbicides, and his crops were spared losses due to driving. In the end, the farmer saw a 68% boost in his income by opting for spot treatment over flat treatment.

These results validated the Agremo solution, mapping + AI analyses + spraying, for use with DJI drones.

Growers’ Requirements and Challenges

Corn, followed by soybean, is a standard crop rotation in many parts of the US. However, corn kernels dropped during harvest can germinate in the next season and compete with soybean.

Volunteer corn is problematic as it robs soybean of nutrients, sunlight, and water and can reduce yield. Volunteer corn is more competitive than most other weeds, and increases soybean losses more than some larger plants. One volunteer corn plant per 10 square feet reduces yield by 8% to 9%, and one corn per square foot reduces yield by 71%.

If growers allow volunteer corn to grow large, they require more herbicides to control them. Volunteer corn also attracts rootworms, which can become a problem for the next season’s corn crop. If untreated with additional herbicides, glyphosate-resistant volunteer corn can’t be controlled by Roundup used for soybean weeds, and the chances of resistance buildup can increase.

Individual volunteer corn in the soybean field

Traditional Farmer’s Approach

Most commonly, growers use tractors fitted with sprayers for whole-field post-emergence spraying, swelling the cost of treatment. Moreover, the tractor’s movement caused soil compaction, reducing yield per acre. Since it is necessary to travel in opposite directions to avoid shadows of sprays and improve herbicide application around and on weeds, growers were driving more, resulting in more damage to their crops.

How Agremo & DJI Approached the Challenge

Agremo offered DJI a custom-made solution that included their signature AI analytics of multispectral drone imagery to prepare maps that their drones could use for spraying.

Agremo’s popular Weed Detection analysis can precisely identify the exact location, extent, and degree of weed infestation. Agremo platform prepared an AGRAS drone spraying map, using the crop insights from the analysis, allowing drones to make spot Variable Drone Spraying (VDS) applications of herbicides where the weeds are present instead of the entire farm.

A farmer agreed to try the VDS application to help in validating the new Agremo-DJI technology.

The Agremo AI volunteer corn weed detection result

The DJI Phantom 4 Multispectral drone for field scouting

The Process and Solution – A New Collaborative Service

The farmer went about creating the VDS maps for DJI drones based on Agremo analysis, and the ease of use and accuracy were tested on their field using the following technology workflow:

  • Ground truth process: Field data on weeds’ identity and densities were collected manually from one point in the test farm. A location pin or polygon can mark the plot to integrate it later into digital maps.
  • Mapping & AI analyses: DJI drones P4M collected imagery of the farm, which was stitched to prepare field maps.
  • Agremo analysis: The stitched map was analyzed automatically by Weed Detection analysis based on AI, machine learning, and computer vision, informed by state-of-art vegetative indices for weed analysis.
  • Project report: The analysis result was a report that showed the analyzed data and map depicting three zones with varying intensities of volunteer corn infestation.
  • Spraying maps: Agremo used the analyzed map to prepare a prescriptive VDS map compatible with the AGRAS drone platform.
  • Field spraying: The farmer used a DJI AGRAS T30 drone equipped with the new spraying map prepared by Agremo to spot-treat the specific zones where volunteer corn infestation occurred.

By comparing the AI detection result with ground truth, the Agremo analysis was over 95% accurate.

The DJI T30 AGRAS drone for herbicide spraying 

Farmer’s gains from the Agremo & DJI Service

The DJI Agras drone flew and sprayed only the spots where the farmer had volunteer corn in soybean.

Of the total 65 acres of farmland, the farmer had 3.75 acres of individual corn and six acres of clumped corn, and if the farmer had not controlled the volunteer corn, they would have suffered a loss of 15% and 60% yield, respectively. See Table 1.

Table 1: Weed infestation areas and possible losses if the farmer did not control volunteer corn

The expected farm yield is 50 bushels per acre sold at $15 per bushel. The farmer would have incurred a total loss of $3122, $422 due to individual corn and $2,700 due to clumped corn. That would have been a loss of $48 per acre.

With the new technology from Agremo and DJI, the farmer treated only 9.75 acres instead of treating the entire farm with flat spraying rates, saving considerable money. So the increased yield that the farmer obtained by treating the crop was not the only benefit of the new technology.

Returns on Investment

Using the spot treatment increased the farmers’ ROI in two ways:

  1. Reducing the amount and cost needed for herbicide treatment.
  2. Eliminating crop losses due to driving.

Table 2: Comparison of flat and Agremo-DJI spot treatment costs shows that the prices per acre are lower, and yield and profits are higher. 

The cost of herbicide for flat spraying the entire field at $7 per acre would have cost the farmer $455, and the yield losses due to soil compaction caused by driving would have been $975 (or $15 per acre). So the total cost to the farmer from flat spraying would be $1,430.

AGRAS sprays only those places that Agremo AI identified, so the farmer had to spend only 60% of the herbicides. As a result, the cost of the chemicals was down to only $4.20 per acre or $273 for the entire weed management. Moreover, the yield was higher as there were no crop losses due to driving the sprayer in the field. So their ROI from spot treatment is significantly higher than from flat treatment.

With a savings of $17.80 per acre, the farmer’s ROI from the Agremo-DJI spot treatment was 68.39% higher than the flat treatment! And that is a bottom line hard to beat.

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    Director of Agronomy at Black Gold Farms

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    CIO at Cochranville Ag Service

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    Mapping Expert and President @ Caribe Drones // Puerto Rico

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    Drone Operator and Farmer @ Above All Aerial // MN, USA

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    Agroservice and Product Manager (Maize and Oil Crops), KWS SAAT AG

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    What precision agriculture activities do you need?

    • Plant Stress

      • identify and quantify zones of (potential) stress
      • act timely with the most adequate measures
      • increase yield potential
    • Weed Detection

      • spot weed-infested areas in time
      • take immediate effective in-season corrective measures
      • get precise spraying maps
    • Green Snap Detection

      • identify and classify areas with broken plants in the field
      • locate and quantify the crop damage
    • Lodging Detection

      • detect and classify areas with lodged plants
      • locate and quantify the crop damage
    • Stand Count

      • get the precise number of plants in a specific area
      • evaluate seed quality
      • assess field damages
      • know the zones of potential yield losses
    • VRS Stand Count

      • calculate the percentage under the norm in each zone with the same seeding rate
      • reduce input costs in the low-productivity field areas
      • count plants in the best and the worst zones
    • Plant Vigor

      • get data on the exact location, condition, strength, and lushness of vegetation
      • optimize the usage of inputs, save on them and prevent over-application
    • Waterlogging Detection

      • quickly and accurately locate all potential waterlogged areas in your field
      • reduce the negative effects of waterlogging, regardless of the field size and crop sort
    • Hail Damage

      • analyze the percentage of areas damaged by hail or other bad weather events
      • evaluate different levels of damage in the field
      • assess crop damage precisely
    • Canopy Cover

      • get vital data on vegetation conditions and primary plant productivity
      • get the necessary details regarding the leaf area index (LAI)
      • determine the most optimal LAI for the fruits, vegetables, or cereals

       

    • Plant Stress

      • identify and quantify zones of (potential) stress
      • act timely with the most adequate measures
      • increase yield potential
    • Weed Detection

      • spot weed-infested areas in time
      • take immediate effective in-season corrective measures
      • get precise spraying maps
    • Green Snap Detection

      • identify and classify areas with broken plants in the field
      • locate and quantify the crop damage
    • Lodging Detection

      • detect and classify areas with lodged plants
      • locate and quantify the crop damage
    • Stand Count

      • get the precise number of plants in a specific area
      • evaluate seed quality
      • assess field damages
      • know the zones of potential yield losses
    • VRS Stand Count

      • calculate the percentage under the norm in each zone with the same seeding rate
      • reduce input costs in the low-productivity field areas
      • count plants in the best and the worst zones
    • Plant Vigor

      • get data on the exact location, condition, strength, and lushness of vegetation
      • optimize the usage of inputs, save on them and prevent over-application
    • Waterlogging Detection

      • quickly and accurately locate all potential waterlogged areas in your field
      • reduce the negative effects of waterlogging, regardless of the field size and crop sort
    • Hail Damage

      • analyze the percentage of areas damaged by hail or other bad weather events
      • evaluate different levels of damage in the field
      • assess crop damage precisely
    • Canopy Cover

      • get vital data on vegetation conditions and primary plant productivity
      • get the necessary details regarding the leaf area index (LAI)
      • determine the most optimal LAI for the fruits, vegetables, or cereals