Agremo and DRONTIM enable seasonal tobacco monitoring

In 2018, DRONTIM, a drone professional service provider, who partners with Agremo in Croatia, was approached by a client Agroduhan, to digitize tobacco production monitoring and gain better insights. The additional challenge represented convincing the cooperative farmers that drone technology benefits both the growers and the tobacco supplier.

On this project, DRONTIM joined forces with Agremo – a leader in drone analytics backed by AI, computer vision, and machine learning technologies. Based on the information received from DRONTIM, and the supplier (Agroduhan), Agremo suggested six analyses for this project.

DRONTIM visited the cooperative fields included in the project, collected drone images, and provided Agremo with the GeoTIFF orthomosaic maps for further analysis. Once the reports were ready, DRONTIM shared them with the tobacco supplier for other use.

Agroduhan improved tobacco stand count by 17-20% within three years and convinced farmers to use precision farming methods. Mario Samardzic, Drone flight coordinator, DRONTIM, notes, “The project with Agremo is significant for our company since it helps us showcase the usage and benefits of drone data in tobacco production and agriculture.” 

Customer Requirements and Challenges

DRONTIM offers state-of-the-art solutions using unmanned aerial drone imaging, inspections, and data processing of drone maps for the agriculture industry. In addition, the company works with small and medium-sized farmers who require drone equipment to improve their ag operations.

Until 2018, the cooperative farmers included in the project were not familiar with the benefits of precision farming, as they are unaware of the possibilities resulting from recording their fields with drones and analyzing this data.

Client Needs

DRONTIM had to monitor cooperative tobacco farms so that Agroduhan could improve yield per acre by:

  • Gaining visibility of cooperative farms
  • Estimating farm yield to plan processing capacity
  • Getting early warning of crop stress such as pests, diseases, weeds, and nutrition deficiency to take proactive action
  • Identifying problems with flowering
  • Making less and profitable use of resources

Existing Process/Field Condition

Before drones, the tobacco supplier sent field advisors and controllers to appraise the farms and advise producers on improving crop performance. During on-foot scouting, it was only possible to identify stress after it manifested external symptoms and within reach of the controller’s eyes. Moreover, it was impossible to estimate the extent of the stressed area or count all plants on a farm.

On the other hand, drones and Agremo analytics give in-depth information about crops in every square meter of the field. Therefore, the project was a perfect opportunity for DRONTIM to demonstrate and introduce precision farming benefits to the cooperative farmers while at the same time enabling the supplier with better digital field and crop insights.

How Agremo Approached the Challenge

DRONTIM, being an Agremo partner, leveraged Agremo solutions based on AI, machine learning, and computer vision, backed by recent science and the expertise of agronomists. Agremo’s solution can be adjusted for the needs of both drone professionals and enterprises, so it was a perfect fit.

Agremo suggested the following analyses to take care of DRONTIM’s needs:

  • Stand Count to find the exact number of plants in a specific area compared to expected results.
  • Plant Vigor to show variation in crop growth due to nitrogen deficiency.
  • Plant Stress to identify problem fields suffering from yield-limiting stress.
  • Flowering Estimator shows the precise percentage of flowering plants, allowing prediction of time and quantity of yield and planning for pest control.
  • Weed Detection to estimate the precise extent of weed infestation, helping prepare variable prescription maps.
  • Disease Detection for early detection of plant diseases allowing farmers to take preventive measures to curb its spread.

The Process and the Solution

DRONTIM used a seven-step process while collaborating with Agremo.

  1. Client Interview: Gain deeper insights into the client’s challenges and requirements.
  2. Project Analysis: Analyse the needs, and identify any gaps together with Agremo.
  3. Project Preparation: Prepare all the legal documentation and technical requirements, so the project is seamless for both the tobacco supplier and the farmer cooperatives.
  4. Map the Fields with Drones: DronTim recorded high-resolution 2-D images of fields with drones. 
  5. Prepare Field Maps: DronTim stitched the collected images and created orthomosaic maps in GeoTIFF format.
  6. Use Agremo Analytics: The maps were uploaded, and the relevant six analyses were chosen. The maps were inspected using Agremo specialized algorithms, and the generated reports were ready to be delivered.  
  7. Get Agremo Reports: Reports were generated at different stages of the crop cycle. The report includes a detailed PDF file with relevant information, which can also be exported as a CSV file and SHP files of the results and field borders.

Customers/partners can co-brand the reports and the Agremo app with their logo and easily share maps and insights with their clients. DRONTIM distributed maps and reports directly to farmers through emails and accelerated the process from mapping to displaying the results.

What Were the Decisions Informed by Agremo Analyses?

The project made the most impressive progress through the Stand Count and Plant Vigor Analysis:

  • Stand Count identified the exact number of plants, enabling the company to optimize operations by taking appropriate measures on fields and predicting yield to improve the planning of tobacco processing capacities.
  • Plant Vigor was widely used by farmers. It resulted in target fertilization through irrigation systems to reduce costs by variable rate application in only low yield zones identified in analyzed maps.

 Other important information obtained in the project:

  • Plant Stress showed fields that suffered repetitively from stress, allowing consultants to advise proactive measures for the next season.
  • Flowering Estimator helped field advisors assess and suggest solutions when they spotted the problems early enough.
  • Weed Detection analysis was used only in a few problematic fields.
  • Diseases Detection in a few targeted cases was used to convince skeptical farmers that drone technology could detect diseases.

Summary: Return on Investment (ROI) on Precision Agriculture with Agremo

Tobacco farmers and production areas have been steadily declining worldwide. To solve this problem locally, Agroduhan had to intensify efforts and increase production per unit area. As a result, the two primary goals of the project – increasing the number of plants and beginning the digitalization of production monitoring – were achieved.

  • Between 2018-2021, Agroduhan increased the average number of plants per acre by 17-20%.
  • When the farmers saw the analyzed drone imagery and insights so far unavailable to them, they realized they could save time and input costs while improving yields. So now, they are even adding more of the new precision farming methods to their production cycle.

The turnkey solution offered through the joint efforts of DRONTIM and Agremo enabled Agroduhan to achieve both of these objectives. As a result, the project has entered the 4th straight season of monitoring tobacco production in Croatia.

 

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    What precision agriculture reports do you need?

    • 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
    • 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 Count and Size Analysis

      • Count all plants in the field, such as leafy greens, trees, or orchard tree fruits.
      • Classify them per user-set size parameters, and filter out the counted plants per size.
      • Prepare the harvest operation per yield-ready zones
    • 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
    • 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 Count and Size Analysis

      • Count all plants in the field, such as leafy greens, trees, or orchard tree fruits.
      • Classify them per user-set size parameters, and filter out the counted plants per size.
      • Prepare the harvest operation per yield-ready zones