Introduction: Drone intelligence for canola farmers
Increasing yield and productivity is an important challenge for canola farmers. With increased concerns about sustainability and the impact of pesticides on the environment, farmers have to think more carefully about pest and disease control and ensure that they get the best possible return on the pesticides that they use. This is the driving force behind the adoption of precision crop farming.
Based on the Agremo Plant Insights’ user statistics, wheat and corn farmers were among the first to embrace remote sensing in precision farming. It seems that their achievements encouraged others to give agriculture drone technology a shot as well: “So far, Agremo successfully provided insights for more than 100 crop types. And thanks to our avid users, this figure continues to rise”, says Milan, the CEO of Agremo.
A short while ago, Agremo’s agricultural experts determined that there is another crop that could benefit a lot from drone technology: rapeseed and canola. It has been shown that remote sensing can be used for high-throughput phenotyping of canola flowers with confidence. High-throughput phenotyping techniques will potentially improve the throughput and objectivity of detecting flowers in canola and other crops, and contribute to the development of new cultivars in breeding programs and yield estimation in precision agriculture [1]. By combining vegetation indices (VI)s and image classification from UAV-based RGB and multispectral images, we have the potential to estimate flower numbers in canola [2].
What can canola growers do with this data?
Timing is critical in canola production, and Agremo Flowering Estimator estimators can be used to:
- Determine the best time for harvesting and swathing;
- Optimize pest control measures: certain pesticides and fungicides need to be applied during a specific flowering stage to be fully effective;
- Perform yield estimations and estimate biomass.
Farmers know that planting rapeseed or canola — a specific type of rapeseed with a lower level of erucic acid — is both a time and resource-consuming process. What’s more, the individual growth stages of rapeseed and canola have specific and rather inflexible requirements, and missing out on important crop behaviors can result in both financial and harvest loss.
Another challenging point that farmers are facing is that the canola growth cycle lasts almost an entire year, making the cultivation of rapeseed and canola a year-round commitment. Only by monitoring and analyzing crops regularly and in an efficient manner will you be able to draw a positive balance. Constant monitoring is a lot of work and, what’s even worse, it’s a lot of guesswork – far from accurate and reliable insights. Drone technology can solve these kinds of headaches, which is exactly why savvy industry leaders have already started implementing drone solutions. One of them is Canada’s Canola Council: in their annual report for 2016, they describe employing aerial imagery collected by drones for canola performance trials [3].
Precision drone technology is becoming more and more accessible – even small- and mid-scale canola farmers can obtain powerful insights. All it takes are pictures made by a local dronepreneur and a few clicks to run these pictures through a powerful data processing software. Although subject to various constraints in the past, drone technology has managed to become both affordable and applicable thanks to technological advancements. The continuously rising numbers of users and analyzed hectares prove that drone technology is more than a temporary trend — it’s here to stay and will make farmers’ lives easier in the long run.
Agremo’s team of agricultural experts looked at the specific features and conditions of rapeseed and canola and went through the different growth stages to determine when and how agriculture drone technology can help rapeseed and canola growers do better. Their analysis and the following field test of the Agremo mapping team confirmed: making regular aerial footage during the flowering stage of rapeseed and canola and performing a suitable report using a professional agricultural data processing solution (such as Agremo Flowering Estimator) can help optimize rapeseed and canola performances significantly.
In cases of disease outbreaks such as sclerotinia, decisions regarding pest and weed control must be made in a matter of days — and being too late or too early can lead to quite different yield results. As opposed to traditional methods, pictures obtained by precision drone technology can provide actionable and all-round solutions. With drone technology, you can:
- Obtain precise information about your field (with an accuracy of less than an inch);
- Capture high-resolution images of up to 250 acres per hour;
- Enable regular and frequent crop monitoring.
This means no legwork, no guesswork, and no more wasting money on inefficient pest control measures.
Assessing flowering levels of rapeseed and canola for determining the proper time for swathing and harvesting
According to the swathing guidelines published by the Canola Council of Canada, the best time to swath for optimum seed quality and yield is when the seed color change is at about 30 to 40% [4]. It’s recommended to start inspecting the field about one week after the end of the flowering stage, as the proper time to swath is about three to four weeks after it ends. However, determining this stage can be difficult, as the time frames are also quite narrow. What is more, hot and dry weather conditions, for example, can cause seed color to change rapidly.
Why shooting aerial footage of your canola field during the flowering stage is a good idea
One of the many types of information aerial imagery offers is data on the growth stage of a crop. With today’s cameras and data processing software, it’s possible to accurately determine the growth stage of rapeseed and canola. Nine out of ten farmers will confirm that this data is extremely valuable.
Determining the growth stage of canola and rapeseed is required to make important management decisions in terms of pest control measures, for example. By knowing the flowering stage of your crop, you’ll know the optimum time to apply pesticide and fungicide. This is usually easier said than done: the entire flowering stage lasts about 14 to 21 days, and there are very narrow timeframes if you want your pest control measures to work. Flowering analysis can be performed during mid-season tasks to optimize pest control measures and perform yield estimations, and during late-season tasks, if you’d like to determine the optimum time for harvesting and swathing.
There are several benefits that drone-based flowering analysis have as opposed to traditional measures. The drone-based flowering analysis is:
- Fast and help save time and resources
- Able to cover around 500 acres in less than two hours
- Accurate – with error rates lower than 2%
- Proactive and allow effective in-season corrective measures.
What are the benefits of Agremo Flowering analysis?
Agremo Flowering Estimator analysis can be used to determine the best time for harvesting and swathing. They are also beneficial for the optimization of pest control measures because certain pesticides and fungicides need to be applied during a specific flowering stage to be fully effective. Flowering analysis is also used to perform yield estimations and estimate biomass.
Why is the flowering stage important? The timing of disease control is critical in a crop like canola. Take Sclerotinia, for example: depending on the severity of the infection, canola growers can experience an average 10% yield loss or more, as sclerotinia can wreak havoc on growers’ bottom lines [5]. Research has shown that targeting 20 to 30% flowering for fungicide application delivers the best results [6].
Applying fungicide earlier or later than this will either lead to Sclerotinia outbreaks or early petal drop. Bayer Crop Science has confirmed this in the newest guidelines on Proline, a fungicide used for Sclerotinia control. According to them, the optimum timing for applying this type of fungicide is between 20 and 30% bloom, as well [5]. The company claims that a Proline application to canola between the 20 to 50% bloom stage can effectively reduce infection rates by up to 80%.
The 20 to 30% flowering stage is equivalent to about 15 open flowers on the main stem. Up until now, this stage has been determined by walking across the field and counting open flowers on as many plants as possible. Such an approach is not only inaccurate; it’s also exhausting and time-consuming if you have more than a few acres. Scouting only 30% of a 250-acre field means walking almost 4 miles — a distance that makes constant monitoring almost impossible, and even if you make this effort, you still cover only a small part of the field. Agremo Flowering Estimator analysis can be used to:
- Determine the best time for harvesting and swathing;
- Optimize pest control measures: certain pesticides and fungicides need to be applied during a specific flowering stage to be fully effective;
- Perform yield estimations and estimate biomass.
Agremo Flowering Estimator analysis tells you the percentage of plants that have reached the flowering stage. Depending on the plant and crop you are analyzing, you also obtain data on their current flowering stage.
Turning drone-collected pictures into information — How it works
We went on a field trip to find out how this process might look for the average farmer. The rapeseed field we looked at was about 3.5 acres big and a walk through the field led us to believe that the crop was at its absolute best. The mapping was conducted by one of our professional drone operators and our mapping team. The mapping itself was completed within minutes; we uploaded raw data for stitching onto the DroneDeploy platform while we were still on the field. We then chose Agremo Flowering Estimator analysis from the drop-down menu and clicked enter. That was it — the rest was up to the Agremo analysts.
To get conclusive results, it’s important to upload only high-resolution images, so take a look at these tips from a professional drone operator, or read how this successful drone business does it.
By the end of the day, the results were ready: the flowering estimator report revealed that only 68.75% of the field’s crop had reached full flowering levels. What was visible to the naked eye and what looked rich and ample, was far from optimum, which was confirmed in the final flowering report:
If we had simply relied on the visual impression of the crop and the use of ‘mark one’ eyeball, we would have come to the wrong conclusion. Armed with this kind of information, farmers can find out exactly what is happening in their field. And with this kind of technology, it is a matter of minutes, not days.
To sum up
Seasoned farmers know that flowering levels of plants or crops on the same field can vary. Drone data is a great alternative to traditional measures that offer only estimates of a small part of your field. Drone data gives you accurate numbers on the flowering areas on your field.
Sources
[1] S. Sankaran et al., “Detection of canola flowering using proximal and aerial remote sensing techniques,” 2018, doi: 10.1117/12.2304054.
[2] L. Wan et al., “Combining UAV-based vegetation indices and image classificaion to estimate flower number in oilseed rape,” Remote Sens., 2018, doi: 10.3390/rs10091484.
[3] Canadian Canola Council, “An Industry Inspired: 2016 Annual Report,%0 2017. https://www.canolacouncil.org/media/584651/ccc-ar2016_inspired.pdf (accessed Jun. 13, 2020).
[4] Canadian Canola Council, “Canola Swathing Guide,” 2012. [Online]. Available: https://www.canolacouncil.org/media/530966/canola_swathing_guide.pdf.
[5] Bayer, “Does Proline Protect Canola?,” Bayer Crop Science: Canada, 2020. https://www.cropscience.bayer.ca/Products/Fungicides/Proline-canola (accessed Jun. 13, 2020).
[6] B. Barker, “Assessing bloom stage in canola,” Top Crop Manager, 2014. https://www.topcropmanager.com/assessing-bloom-stage-in-canola-15165/ (accessed Jun. 13, 2020).
