Software-based Waterlogging Detection Saves Wheat Crops

About the project

Croplands can suffer from waterlogging due to oversupply, topographic, or soil differences that cause problems as deleterious as water deficiency. One farmer used drone software analysis to identify the areas on his farms that were affected by waterlogging to save wheat yields, as traditional methods were not pragmatic, cost-effective, or accurate.

Otherwise, Tim Barney stood to lose nearly 10% of the wheat crop on 125-acres as a result of waterlogging.

He realized that Agremo’s Waterlogging Detection analysis was an excellent fit for his needs. Moreover, the instructions with links to related services made the whole process simple. High-resolution aerial pictures obtained through remote sensing from a drone were stitched to prepare a 2D map of the entire farm and then uploaded to the Agremo app.

Agremo software, which is based on Artificial Intelligence processes, performed automatic analytics of the aerial imagery using spectral data to identify differences in plant health. Then these areas were classified and quantified, and the insights were provided in a report along with the analyzed map and sent to the farmer within two days.

The report had classified the wheat farm into three zones- waterlogged, wet, and fine. The 16 areas to a tune of 9.33 acres or 7.3% of the total farmland that was waterlogged and wet were demarcated on the map.

The farmer was able to locate the 16 problem spots with the help of the map. He took several remedial measures such as draining excess water and providing extra nitrogen based on insights from the report, to prevent loss of wheat yield. He also used the analyzed map to take preventive agricultural measures to avoid waterlogging in succeeding crop cycles on his farm.

Customer requirements and challenges

Tim had grown wheat on a large area, and his investments were considerable, so swift and timely actions were necessary to avoid the loss of profits.

Tim was aware of the remedial steps required to decrease waterlogging and save crop yields. However, accurate and reliable information on the location and size of waterlogged areas was indispensable. Tim needed this information fast to make necessary changes before it was too late.

When he saw leaves of his crops turning yellow, he identified the problem as waterlogging. He was worried that excess water was clogging soil pores, potentially causing several problems, such as:

Client needs

  • Depletion of soil oxygen which leads to the deficiency of this vital element. When plants cannot absorb nitrogen from the soil, they extract it from older leaves to support the growth of new ones. As a result, leaves turn yellow or develop necrotic spots.
  • Denitrification or nitrogen breakdown, if waterlogging continued for too long. When oxygen essential for healthy root and shoot growth is depleted, it results in a reduction of spikelets formation and the number of grains per spike.
  • Impaired root growth and changes in hormone production that affect the absorption of nutrients.
  • An increase in salinity, soil compaction, and manganese toxicity.
  • Increase in root diseases and some water-loving weeds.
  • Reduction in the formation of chlorophyll, stomatal opening, and photosynthesis, which results in reduced carbon fixation and yield.

Existing process / Field condition

Since Tim’s wheat fields were large, he knew traditional scouting methods were not suitable.

To find the exact location and area of problem spots, Tim would have to dig a hole about 30 cm deep in all areas he found suspicious. In such cases, if water flows into the hole, it indicates that the patch is waterlogged. However, this is a tedious and time-consuming process. Tim knew he would never be able to test the entire farm thoroughly by resorting to this technique. The method was also destructive and would result in the loss of many plants.

Also, areas with mild waterlogging and no visible symptoms would be hard to detect. Hence, with rough estimates from manual scouting, Tim’s prescriptive actions would be inaccurate.

How Agremo approached the challenge

Tim had been hearing a lot about precision farming methods at recent agricultural fairs he had attended. There was also a drone demonstration that had impressed him. Within a few hours, the drone could fly over an entire farm and take pictures that could then be used to predict the state of the crops.

Tim also needed software that could conduct complex analyses, as he had no idea how to use GIS or Geographical Information Systems. Online research took him to Agremo’s website and our waterlogging analysis.

Agremo is a precision agriculture software and application that analyzes remote sensing data gathered in near real-time. The software uses Artificial Intelligence (AI), machine learning and computer vision to perform automated analytics of aerial imagery to provide accurate information about crops and fields.

Agremo software identifies, classifies, and quantifies complex 3D spectral and temporal patterns from image data, providing the most precise results. The analysis goes beyond NDVI estimation, which is based solely on differences in vegetation color.

Excited that he had found exactly what he was looking for, Tim registered and contacted Agremo staff.

Design and Plan

Collect data

Analyze data

Deliver and Apply

The Process and the Solution

Based on the information he found on the Agremo website and that he got from our staff, Tim listed his requirements. He needed a drone to take pictures, to produce the 2D map, and to use Agremo software for analysis.

The first phase - Drone:

Tim explored drones and sensors which were supported by Agremo, and found out that he could use any drone that produced orthophoto maps. The sensors could be RGB, NIR, and multispectral. He obtained many high-resolution photos of his 125-acre farm with a drone.

The second phase- Map:

To prepare a map from the drone imagery, Tim used an online “stitching program” provided by DroneDeploy, which is customized for agricultural fields. All the drone photos were combined to give a seamless 2D map of his entire 125-acre farm.

The third phase- Analysis:

Next, Tim uploaded the 2D map to the Agremo web app and followed the instructions. He selected the area on his field he wanted to analyze, chose “Waterlogging Detection analysis” by clicking on the icon, and specified the crop and its growth stage.

The fourth phase- Results:

There was an analyzed map of the field (JPEG file) depicting three categories of areas:

  • Waterlogged areas
  • Wet zones
  • Fine areas with no waterlogging

The insights from the analysis were in the accompanying document (PDF file). A table included the details on acreage and percentage of land for each of the three categories.Tim could use the figures he got for decision making, as no further calculations were needed on his part.

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What were the decisions informed by Agremo analysis?

Based on the report, Tim had more data than ever before, and was now able to:

  • Note the differences in the crop tolerance to flooding
  • Identify areas where crops were severely or moderately affected
  • Spot waterlogging problems before they affected the plant’s performance since moderately flooded areas were also identified
  • Calculate how much yield and profit he would lose
  • Identify when the flooding occurred
  • Provide only necessary amounts of water to each area on his farm to prevent further flooding

The Agremo waterlogging analysis report showed Tim that he had 16 different areas on his 125-acre field which were affected by waterlogging. A total of 9.33 acres or 7.43% of the field were affected.

By knowing the exact size and location of the problem spots, Tim could decide how to remedy problems in the 16 waterlogged areas for the current and future seasons. To help his current crop, he decided to:

  • Apply nitrogen in those zones to compensate for nitrogen deficiency. It made nitrate readily-available and accelerated plant recovery.
  • Keep the field free of extra weeds to reduce competition for oxygen in the root zone.
  • Undertake light cultivation if bruising occurs after intense rainfall, which would help aerate the saturated soil.

Differences in soil type or topography make some parts of the farm more prone to waterlogging. After ascertaining the cause, Tim decided to preempt the possibility of flooding in problem spots for the next season by:

  • Growing and then incorporating a green manure crop to improve soil organic matter and pore space.
  • Build a drainage system across the field to remove flooded water from problem spots.

Summary: Return on Investment (ROI) on precision agriculture with Agremo

Even though precision agriculture sounded daunting, Tim found the Agremo website was user-friendly and reports were easy-to-understand. The Agremo app is designed for people with no previous experience of remote sensing or AI. Agremo’s AI technology allowed the analysis of large amounts of data and provided actionable insights rapidly.

With the Agremo results and model, Tim:

  • Earned more income by saving resources and as much yield as he could in this growing season.
  • Calculated the precise number of pipes and the directions in which to install them to drain the fields.
  • Saved time by taking advantage of modern technology and AI.

Agremo recommends waterlogging analysis for pre-planting, planting, and growing stages. It can also be used for more than 100 species. Based on several years’ experience, we offer analysis both for annual and tree crops.

The data generated by precision farming is a powerful tool that can help farmers like Tim in making correct decisions based on accurate risk assessment. Precision agriculture can save crops, improve resource use efficiency, and increase profits for the farmers. For society, it guarantees less environmental pollution and greater food security.

*Name has been changed to protect the identity of the client.

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