High-precise plant stand count for corn, sunflower and sugar beet by a drone and AI
This article covers precise plant stand count using an off-the-shelf drone and Proofminder’s trained AI algorithm for accurate yield assessment and the following insights on the field. You will find practical tips on image collection and recommended approach for corn, sugar beet and sunflower, but the information is also useful for other field crops, vegetables and orchards. Keep reading!
Plant stand count is an essential task in yield management. It allows growers to estimate the plant population, density, germination rate, and plant health and make timely decisions that finally affect the yield. Common manual methods of plant stand counting have helped growers for decades. They are based on visual inspection and plant calculation on small pre-defined field areas. However, these methods are laborious and far from accurate. Fragmented plant stand count does not provide the complete picture, and problem areas with uneven emergence or weeds might be overlooked. The lack of information on the field eventually leads to a waste of resources and less profitable decisions.
New technologies like drones and AI leverage the opportunity to make Agri operations smarter and more efficient. With this innovative approach, growers can now receive accurate data, make timely decisions and sustainably maximise the yield. Surprisingly, this is not as complicated or costly as it might seem.
This article covers precise plant stand count using an off-the-shelf drone and Proofminder’s trained AI algorithm for accurate yield assessment and the following insights on the field. You will find practical tips on image collection and recommended approach for corn, sugar beet and sunflower, but the information is also useful for other field crops, vegetables and orchards. If you have a drone or considering buying one to turn a tedious task into an interactive process and get a high-precision result, keep reading. You will find drone requirements, flight tips and common mistakes, and learn how to get a precision stand count report in a few hours with an innovative AI farming platform.
Why and when do you need a precise plant stand count?
There are situations when a low accuracy report is acceptable, but it is absolutely essential to have a precise one if you aim to:
- Check the sowing quality, especially if you are producing seeds;
- Understand zones of varying productivity in the fields;
- Receive accurate data during R&D projects;
- Estimate the yield precisely in the early stages;
- Spot rogues;
- Make timely decisions, i.e., partially replant the field;
- Increase the yield potential to meet the production goals.
When is the best time for plant stand count using a drone and AI?
Estimating the number of plants and their density is crucial for early-season yield management. The accurate information here is a chance to save the yield if something goes wrong and improve the harvest. To gather proper images for further analysis, consider the tips about plants and the weather.
The plant should be big enough to be seen from the air, but the leaves are not yet too close to each other to distinguish plants and estimate the density. As an example, for the precise stand count of corn, the plant should have about 3-7 leaves (V3-V7 vegetation stages). The weather should be stable during the footage, thus the lens can adapt to the conditions whether it is sunny or cloudy. Also, it should not be too windy, note that the wind speed may greatly vary depending on the altitude. Which altitude is right for a stand count? Find below!
Figure 1 – Corn field
Figure 2 – Manual plant stand count of corn
Capturing images by a drone – instructions and tips
The ideal resolution for plant stand count by a drone and intelligent software depends on the plant and the goal. For precise stand calculation of corn, sunflower, sugar beet, and some other field crops and vegetables would be 0.8 cm per pixel or less. What does it imply, and what kind of drone is suitable? The widely available DJI Phantom 4 Pro V.2. can be a good entry-level option for that job, similarly, the DJI Phantom 4 RTK is also a great option if you want a professional drone with high precision positioning. You will need to fly at 18-30 meter altitude to get the indicated resolution. Be aware that some of the Integrated controllers (the Plus versions) limit the flight altitude to 25m above the ground so if you want to count small crops and fly low, you would rather choose the simple controller and instruct the drone from your mobile or tablet. The ideal speed to capture detailed images would be between 3-5 m/s depending on the altitude and the wind conditions. Using this drone, you can proceed at about 25-30 hectares per day if you have enough batteries; mind you: you can charge them on the site. At Proofminder, we are working on novel ways to do this image capturing and foresee the possibility in the near future to capture up to double of this area per day by a Phantom 4 drone.
Figure 3 – Shooting images for plant stand count by DJI Phantom 4
Things to avoid; the Top-10 common mistakes in drone footage:
- Wrong exposure setting, not properly assessing the weather, resulting in over- or underexposure. Overexposure is more of a problem than underexposure, so if you need to choose between cloud and sunny, and you are not sure, you can safely go for sunny.
- Too much wind or unstable weather conditions result in blurry images.
- Not equipped with sufficient memory cards, make sure you have at least a 64 GB card for ~40-50 hectares of land.
- Not enough batteries and/or chargers to fly continuously during the day.
- Shooting after rain may require some recalibrations because the plant on the wet soil may not be visible enough, keep this in mind.
- Not flying with the right amount of front/side overlaps, potentially preventing stitching pictures together and creating an orthomosaic. 75% is a safe value in most cases.
- Flying too fast results in blurry images.
- No right logistics and setup – i.e., make sure you have a suitable car and path to access the field, have a generator available to produce power for all the equipment, battery charger and laptop, have a sun-shaded place to work from, etc.
- No proper preparations in flight planning – e.g., cater for height differences in the field upfront.
- Check the airspace before flying and make sure not to fly beyond visibility to avoid losing your drone.
Figure 4 – The process of drone footage for precise stand count
Figure 5 – The shape-file of the field
Plan stand count report and additional insights on your field
Following the instructions will result in lots of useful data and good images for further analysis and insights about the field and plants. What can you, as a grower, do with the collected images? There are a couple of ways – as an illustration, to analyse it manually, which is again time-consuming and subjective or use Artificial Intelligence, which can do the job quickly and accurately. The AI-powered platform can create an orthomosaic, an automatic plant stand count report and mark issues on the field that are not visible or not humanly possible to discover in traditional methods.
Images below show what your plant stand count can look like on the Proofminder platform.
On the automatic report generated in a system, you can see
- Plant & row density;
- Precise plant stand count;
- Each plant is marked on the field with precise coordinates;
- Plant distinguished by phenotype, in this case – male and female plants of hybrid corn are marked with a different colour;
- Zoom-in feature to analyse specific zones, rows or plants.
Figure 6 – A plant stand count report on the Proofminder platform
Figure 7 – A plant-level view of a stand count report on the Proofminder platform
Additional insights & platform capabilities
- During the corn plant stand count, we discovered that lots of plants on a field were destroyed by wild boars;
- The problem areas can be marked with GPS;
- Downloadable shapefile for further usage e.g., compare it with sowing facts;
- As each plant has precise coordinates, derived metrics such as the distance of plants, density, gaps, row distance, etc. can be provided additionally;
- Actionable insights on a level of leaf or plant.
Automated plant stand count - outcomes and benefits
- The plant stand count accuracy of manual methods is hard to estimate; one thing is clear: it can only be precise on small analysed areas of the field; applying these numbers to the whole plot would not give precise information. Drones and AI technologies are able to provide growers with 90-99% of stand count accuracy and reveal other problems on the plant level.
- Technologies make the plant stand count process way more precise, interactive and insightful.
- Additional insights discovered: lots of plants have been destroyed by wild boars.
- A helpful opportunity to export the stand count report and reuse its data in other farming activities.
- Possibility to get the maximum out of the drone-made images and use this information for data-driven decisions and for growing more with confidence.
