Citrus farmers are using drone technology to spot early signs of citrus greening disease and other threats to their crop, and take steps to protect their yield. Of all the maladies impacting orchards, diseases like citrus greening have long been the primary threat. For decades, citrus groves have steadily declined in Florida, as an outbreak of citrus greening, known as Huanglongbing, or HLB, caused citrus output to decrease by up to 70 percent. Huanglongbing is incurable, making it one of the most destructive citrus plant diseases in the world. Recent extreme weather has cost orchardists millions in profits, compounding matters for Florida-based citrus growers.
WIth the help of drone-based analytics, orchardists can detect diseases early enough to mitigate the risk of damage to surrounding crops. By applying analytics to aerial imagery, orchardists may count and size trees in a given zone or field, and catch near-infrared changes in crop vigor. By catching early signs of disease or nutrient deficiency, farmers can quarantine infected zones and manage nutrient input for trees. Following a storm, they can also use drones to collect imagery of the damage to ensure accurate crop insurance payouts.
Regardless of whether or not a grower has implemented precision agriculture on their farm, there are many ways they can use drone-based aerial intelligence when managing citrus trees. Drone-based crop scouting and precision management are supplanting time-intensive and error-prone traditional methods such as ground-based sampling and satellite imagery for:
- Crop scouting: drones enable farmers to save time by flying overhead and scouting in minutes what would take a day or more for ground-based inspection.
- Counting: drone-based data can be used by farmers to quickly and precisely count trees and capture greater detail on individual trees than satellites, with a near-instant turnaround.
- Sizing: aerial imagery and analytics enable farmers to precisely track tree size across the season and growth years to determine tree age, vigor, and the location of newly planted trees.
- Managing inputs: monitor tree health, vigor, and look for early signs of stressors such as yellowing or browning, damp or dehydrated soil, or shrunken fruit, using vegetative indices.
- Zonal and plot statistics: create management zones in your field to better isolate HLB-infected trees and manage nutrient inputs for uninfected zones
- Maintain documentation: track and store records of seasonal production and yield health in the cloud to easily reference in case of an insurance or food safety audit.
Ultimately, farmers maximize their profitability by using this information in making more efficient and effective input and inventory decisions. While extreme weather is unpredictable, growers can still use drone-based data collection and analytics to develop an efficient response plan that aims to minimize losses. Read on to learn how PrecisionHawk is helping citrus orchardists make more informed management decisions and improve the health of their trees.
Collect High-Quality Citrus Tree Data
At PrecisionHawk, our goal is to help farmers accelerate and streamline the work of data collection, analysis and reporting. Because citrus orchards are often grown on a scale of hundreds to thousands of acres, farmers can optimize their data collection by gathering more imagery in fewer flights. Mature citrus trees can be captured at altitudes as high as 80 meters, enabling users to cover more terrain in less time, while still getting highly accurate data. If a farmer spots an issue on the map, they can collect high-resolution photos of individual trees to investigate it further.
For tree count and inventory, farmers can start with multirotor DJI Phantom 4 or DJI Mavic drones outfitted with RGB sensors. Those seeking more precise health indicators in their groves can use a multispectral sensor, such as the DJI M200 drone equipped with a MicaSense RedEdge-MX or MicaSense Altum sensors to capture thermal or near-infrared imagery. MicaSense’s sensors are purpose-built for precision agriculture. By capturing very narrow spectral bands, between 10-40 nanometers wide, they’re able to detect subtle deviation in leaf color throughout the growing season. They can easily identify leaf browning, a common symptom of stress or lack of nutrition. That means these sensors can help orchardists detect even more nuanced information about nutritional inputs, stressors, and potential disease affecting their trees.
The entire process of data collection and analysis is cloud-based, enabling a smooth transition from capturing data in-field, to analyzing and actioning results. Using PrecisionAnalytics, farmers can upload information about different farms, name different fields, and even import their GPS coordinates to geolocate themselves in relativity to the field.
Process & Analyze Aerial Orchard Imagery and Data
PrecisionAnalytics Agriculture is a complete aerial mapping, modeling, and agronomy platform based on 10 years of agriculture analytics experience and millions of acres of orchard data. The system automatically processes, organizes, and annotates geospatial data. It also applies machine vision to automatically produce rich data visualizations, as well as machine learning to surface trends and patterns in orchards.
In PrecisionAnalytics Agriculture, a farmer can monitor tree health, verify inventory, and run a myriad of other analytic reports within minutes:
- Crops at a glance: Review the overall health of orchards to surface issues related to aging, weather damage, flooding or dehydration, or disease.
- Detailed views: View full-resolution imagery and zoom in on health details of a single tree.
- Geolocation: Quickly identify where an area of concern is relative to your position.
- Instant inventory and canopy sizing: Define an area and then quantify the number and size of trees within it. See the distribution of the age of trees across a field or zone.
- Vegetative Indices: Use indices like NDVI, GLI, and VARI to identify early indicators of and trends in tree stress. Use thermal indices to track soil moisture and heat stress.
- Zonal and plot statistics: Isolate problematic parts of the orchards, such as those showing signs of disease, by defining quarantine zones or creating automatic and custom-defined plots. Or compare the performance of different crop varieties.
- Elevation view: After a storm, identify areas of tree damage and loss, expressed as variations in canopy size, and use the measurement tool to calculate the acreage impacted.
- Comparison view: View multiple datasets at a time to analyze trends in tree growth over time.
- Multi-farm and -field management: Navigate all properties and associated data in a single, streamlined portal.
Plant Count and Canopy Sizing
Users of PrecisionAnalytics Agriculture can apply the Plant Counting and Sizing tool over an area of interest to analyze tree growth, segment trees by canopy size, and track plant development from budding in spring, to harvest and leaf-fall. With this tool, a dot will appear over every tree counted, resulting in a highly accurate count of the number of trees per acre. In cases where trees appear as a dense hedge, the count tool also shows the distance between each tree, regardless of canopy size. Each dot is colorized to indicate one of three sizes (small, medium, large) relative to the entire grove. Users draw perimeters to isolate counts in a given area of the field, or establish zones to compare multiple parts of the field.
Using the plant count and sizing tool, orchardists can inventory their year-over-year number of trees and assess inventory accuracy. Growers can see how many trees died during a season, and where, and identify potential reasons why. They can combine the plant count tool with zonal and plot statistics to compare how various rows of new trees or replants are performing during a season. If trees are underdeveloped for their age or exhibiting yellowing leaves, growers can monitor their performance and section out zones in which to manage nutrients such as pesticides, fertilizer, or irrigation. They can then track the progress of these efforts. As a result, orchardists will better be able to inventory and predict their overall yield.
Considering that Citrus Greening, or HLB, is incurable, citrus orchardists must take measures to minimize the spread of the disease from tree to tree, and protect the health of their yield. Citrus greening affects most types of citrus, including: lemons, limes, oranges, grapefruit, pomelo, tangerine, and others. Symptoms of HLB include yellowing of the leaves and green, misshapen fruit. Unlike yellowing from nutritional deficiencies, HLB yellowing is asymmetrical, usually only affecting one side of the leaf. Farmers can thus identify areas that are yellowing, and make more informed decisions about identifying the source of the yellowing, quarantining and protecting nearby trees.
If using an RGB or multispectral sensor to collect the data, users can then apply a vegetative index, such as VARI or GLI, and instantly see a green versus red overlay of their imagery. The green areas indicate the strongest vegetative vigor, with grades of orange, yellow, and red indicating diminishing vigor, and potential disease or damage. In the case of citrus greening, users can compare the greenness of one tree to a row, field, or entire orchard, and identify where yellowing is occurring. These gradations can be adjusted to clarify tree canopies from grass and weeds, as well as plants that are healthy versus those that are not.
This enables farmers to detect early indicators of stress stemming from crop diseases, most notably yellowing of leaves and greening of fruit. Stressed plants identified by a vegetative index might also indicate issues with pressure from weeds, sucking nutrients away from the trees. Once a user identifies where citrus greening is likely, they can ground-truth and verify it. If HLB is found, farmers can use PrecisionAnalytics’ zonal and plot tools to quarantine an infected area for special treatment. Likewise, farmers can identify and remove the weeds that are leaching nutrients away from the trees, or create zones and determine lb/acre herbicide inputs. As a result, they can take steps to minimize damage, ensure a healthier-looking yield, and maximize profits.
Custom Zones and Comparison View
In cases of citrus greening, orchardists can combine the zonal and plot tools with vegetative indices to build custom management zones within a row, field or orchard. These zonal tools enable farmers to determine tree count and canopy size, and specific areas of stress for that zone, and treat it separately. By building management zones, orchardists can subdivide their field into smaller zones (for instance, a group of 10 rows, or 100 acres), and number those zones. As a result, they can give equal attention and distribution of nutrients to all trees at different stages of growth, or different levels of health, within a field.
With PrecisionAnalytics, citrus growers affected by a hurricane can fly a drone over the field after the weather event, and collect data on damaged trees and flooded areas. They can then use the Elevation tool to identify discrepancies in canopy height that might indicate fallen trees, and designate custom management zones for flooded areas, or zones that need to be harvested quickly to prevent fruit dropping into muddy water and rotting. They can get an accurate count of the number of trees lost, and identify safe zones to replant new trees. Ultimately, knowing exactly where the damage occurred and managing inputs for different zones can help speed yield recovery after a hurricane, and minimize the extent of loss.
Plant Count and Canopy Sizing for Crop Insurance
Orchardists will want to monitor the trees’ growth for inventory and insurance audits. By flying drones over the field for aerial mapping and data collection twice a season, or before harvest, growers can gain a wealth of information with which to track their inventory. They can record the size of trees and correlate canopy sizes for each row, analyze what the yield was per row, and use these metrics to track their performance throughout the season. Ultimately, this can make the seasonal crop insurance audit more efficient, and minimize costly errors.
With PrecisionAnalytics, farmers/crop insurance inspectors can:
- Get a precise count on trees in a field every season, and view year-over-year comparisons
- Use sophisticated sizing estimates to age trees relative to the rest of the field
- Use custom plot statistics to define plots and compare counts from plot-to-plot
- Quickly identify and track trees that died and trees that were planted in a given season
- Track treatment differences (such as fertilizer or herbicide input, irrigation, and quarantines) across plots
- Quantitatively and objectively evaluate differences in treatment across plots to determine success upon yield
Sometimes, farmers may have different insurers or insurance policies on different varieties of trees. Our custom zone tool can also help farmers create and track zones based on insurance provider or policy to simplify record-keeping. They can further subdivide zones based on where the harvested fruit is sold to, or whether it’s left for paying customers to pick--essential information for insurance auditors. Additionally, they’ll be able to pull up data such as count, size, age, and the loss of trees in those zones over the course of the season, streamlining insurance reporting and reducing the potential for human error or miscounting.
With average acre of citrus more than $2,500, the trees should produce healthy looking yields consistently for several years in order to maximize profits. Despite consistent threats from disease and weather damage, orchardists can use precision agriculture drones to be better informed about the health of their plants, and make faster, more efficient decisions to protect their yield. At PrecisionHawk, we’ve optimized our cloud to turnaround high-resolution imagery and analytics in near real-time, and our robust yet flexible machine learning-based algorithms are designed for counting and sizing tree canopies, and identifying changes in leaf vigor.
With years of experience collecting data over orchards, using aerial mapping to scout trees, our data scientists and engineers have developed some of the best-trained machine learning models in the industry. That means our algorithms and indices, including our count tool, are better able to detect individual crops and deliver precise analytics about count, sizing, and health based on terabytes of data across a wide variety of crops and soil types. Additionally, our years of working with leading agronomists have informed our intuitive framework, built for multi-field and multi-form data management and sharing. As a result, farmers can learn how successful they were in growing trees from season to season.
We’re here to help you adopt smarter and more efficient farming practices. Our agricultural experts will assist in evaluating when, where, and how to incorporate drone-based aerial intelligence into your operations. Our global network of drone operators is ready to execute flights on your behalf. And our engineers are continuously optimizing PrecisionAnalytics Agriculture to better automate and accelerate your analysis.
Contact us today for more information on how you can use drone-based aerial intelligence in your operations.