Corn has been the number one grain since 2022, with a 1.2 billion metric tons production expected to grow at a CAGR of 4.2% up to 2027. Corn is the primary protein feed crop for all animal farming. As the population and incomes rise, the demand for meat products and corn also increases. Since land is finite, 50% of growers in the USA, the largest corn producer, currently use precision ag to improve productivity to meet growing demands.
However, corn growers face numerous challenges, such as pests, disease, and unpredictable weather, which can significantly affect their yield and profitability. To address these challenges, growers can leverage advanced technologies such as drones and AI analytics to improve their crop management practices. In this post, we will explore how Agremo, a leading AI analytics platform, can help corn growers boost their production.
Benefits of using drones and AI analytics in corn production
The main differences between foot and drone scouting are perspective, speed and efficiency, detail, and accessibility. On the other hand, drone scouting offers a more efficient, accurate, and cost-effective way to gather information and insights about a location compared to traditional scouting methods. Drone imagery gives detailed objective information on the small-scale heterogeneity in corn performance and health caused by differences in soil type, nutrient status, and weed, pests, or disease stress.
With drone AI analytics they get to know the exact location and the magnitude of the issue. With such a foundation, it is possible to create VRA spraying and fertilizing maps for both machinery and spraying drones. Providing nutrition and treatment only where necessary optimizes crop performance, health, and yield and reduces environmental impact. Savings and improved productivity enable corn growers to increase their ROI.
How drones and AI analytics work in corn production
Corn growers can choose various drone analyses. Agremo, a reliable analytics provider, offers a wide range of analytics for each stage of corn for complete crop monitoring, as shown in the Figure below. These are arable area calculation, stand count, weed detection, plant vigor, plant stress detection, canopy cover, waterlogging detection, lodging detection, green snap detection, and yield maps.
Until software like Agremo appeared, the most popular analytics with corn growers in the USA have been soil maps, yield maps, and variable rate technologies (VRT) for many years.
Steps to implement drones and AI analytics in corn production
To implement drones and AI analytics in corn production, growers need to follow a few simple steps. Firstly, they need to identify their goals and determine the areas of the field that require monitoring.
Secondly, they need to acquire drone images of the field to prepare a map. If they don’t own a drone, corn growers can engage drone service providers or ask Agremo for help to take field pictures. Drone imagery is stitched using Agremo to give a 2D map of the fields. These maps are analyzed by software analytics based on the latest scientific models and use AI, machine learning, and computer vision.
Agremo reports have statistics and the analyzed field map, which is divided into different farm management zones based on plant performance, health, or field conditions. Using the analyzed map, growers can use VRT to reduce input or apply more fertilizers than average, where needed, to optimize yields. For example, in the USA, automated guidance for VRT in 58% of corn acreage has reduced labor costs and increased productivity.
At the end of the season they can use the stack of data layers generated by Agremo to prepare for the next season, but also to analyze and better understand the yields they got from the current one.
Agremo for Corn Production
More examples are explored below to show the benefits of drone analytics for corn growers provided by Agremo.
Missing plant detection – replanting
Agremo AI analysis: Stand Count
Period: After emergence
Data source: Drone
Required resolution: 2cm/pix
Poor germination or unsuitable conditions can reduce corn emergence. Agremo Stand Count counts the exact plant number and compares it with the expected population to calculate the percentage of missing plants.
After the drone analysis, the growers will understand how many plants they are missing and the distribution of emergence zones across the field. Based on that they can decide to replant after considering the original sowing date, any damage to the crop, uniformity of plant stand, and replanting date and costs.
If the stand is uneven within a row, replanting will not increase yield. If over 50% of the crops emerge three weeks after the initial emergence, replanting could increase yield by 10%; if the delay is less than two weeks, replanting improves yield by less than 5%. Also, growers must remember that replanted plants will suffer from a higher pest and weed population later in the crop season.
Early yield estimation – benchmarking for forward contracting decisions and supply planning
Agremo AI analysis: Stand Count
Period: After the emergence
Data source: Drone
Required resolution: 2cm/pix
Agremo Stand Count after emergence can tell a farmer the final population they can expect and use these figures to estimate yield.
There are well-established data to show how the loss of standing plants will decrease corn yield for each region. Here, the planting date is also crucial. Crops planted a month later have a lower maximum potential (69%) than early-planted crops (100%) for the same target of 35,000 plants/acre. Growers can use the yield estimates to make contracting decisions and supply commitments.
Herbicide distribution optimization using VRA or Spot spraying map
Agremo AI analysis: Weed detection
Period: V0 to V10 stages
Data source: Drone
Required resolution: 2cm/pix
Weeds have the most significant impact when corn is emerging. So, the standard practice is to give a pre-emergence spray and another when corn is at the four-six leaves stage as a blanket treatment for the entire field.
However, weeds tend to grow in patches, and the 30-inch space between corn rows makes weed mapping by drones and detection by Agremo Weed Detection Analysis easy.
Using this map, corn growers can create variable prescription maps, which drones use for spot spraying or VRA to apply herbicides in amounts appropriate to infestation intensity. Agremo Weed Analysis has reduced the application area to only 46% of the total crop area.
So, besides effective weed control, the costs of treatments are reduced, and the environment and biodiversity are spared from the ill effects of chemicals.
Seed/hybrid and field zones evaluation for next season’s planting decisions (hybrid selection)
Agremo AI analysis: Canopy Cover
Period: V10-R3
Data source: Drone/Satellite
Required resolution: 2cm/pix
Growers can select the suitable hybrid or seed brand for the next year or review field zones by evaluating crop performance based on the current years’ analyses.
Agremo’s Canopy Cover analysis can estimate the exact percentage of crop canopy cover based on the Leaf Area Index (LAI). The index also gives information on plant productivity and crop health, allowing farmers to compare cultivars for hybrid or seed selection for the next year; growers can also identify poor-performing areas in their farm, and take proactive measures.
In-field yield estimates and checks for forward contracting decisions, supply planning, and equipment & storage capacity scaling
Agremo AI analysis: Stand Count
Period: Before harvest
Data source: Drone/Satellite
Required resolution: 2cm/pix
Agremo Stand Count taken before harvest allows precise yield estimation using an additional tool. The Stand Count gives the exact number of standing corn plants in the field. Opening the Stand count report enables users to access the Corn Yield Calculator. Growers must provide information on average ears per plant, rows count per ear, grains per ear, grain weight, and grain moisture content. Knowing the precise yield allows growers to plan for contracting decisions, supply planning, and scaling capacity for harvest equipment and storage.
Conclusion
The use of precision ag methods in corn production is not new in the USA and Europe. Large farm owners benefit from objective, affordable, and precise field and crop insights to make data-driven decisions that have increased corn productivity. Drones are becoming popular for scouting and as VRT equipment. Agremo analysis provides well-planned, scientifically guided reports to increase drone analysis and use for sustainable corn production.
Agremo’s technology has been shown to deliver significant savings to corn growers. For example, a study conducted by the University of Nebraska-Lincoln found that using drones and AI analytics reduced nitrogen usage by 50% and increased yields by 10-12%. This resulted in a cost saving of up to $40 per acre for nitrogen fertilizer. Another study by the University of Illinois showed that using drones equipped with multispectral cameras and AI algorithms resulted in a yield increase of 10-20% in corn crops. This translated into a potential revenue gain of up to $100 per acre.
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