Improving N management in processing carrots using drone-based remote sensing for more sustainable production

View the project final report

Commodities

• Vegetables: carrots

Practices

• Crop Production: nutrient management
• Education and Training: on-farm/ranch research

Effective nitrogen management is an area of major concern to all farmers, and its impacts extend far beyond final yield. Excess nitrogen fertilization can cause losses in quality and even yield for a variety of crops, and N leaching is associated with environmental damage and contamination. Still, many farmers tend to over-apply to avoid yield losses. Both the environmental and plant nutrition problems are exacerbated in sandy soils, where leaching can occur rapidly. Processing carrots are grown in such soils in the North Central region, and due to their long season many growers apply three or more topdresses during the summer and fall. The proper timing of these applications is uncertain. Some carrot growers have adopted petiole nitrate sampling as a means of timing these applications, applying N when the sampled nitrate values fall below a threshold. This method is labor intensive, however, and has poor spatial and temporal resolution relative to what is required for decision-making. Further, the thresholds at which fertilization should occur are not well-established. Remote sensing using drones comes with the advantages of being relatively low-cost and rapid to implement, yielding spatially continuous image data which can be collected on-demand.

The approach of this study was to evaluate the impact of topdress application timing on carrot yield, and to compare the accuracy and reliability of drone-based remote sensing methods to petiole nitrate sampling. A two-year on-farm trial (2019-2020) was established with a grower collaborator near Hart, MI to complete this objective. Treatments included a starter-only control (29 kg ha^-1 N) and a ramp of season-total N rates (67, 135, and 202 kg ha^-1 N) applied as starter fertilizer plus topdressed urea, as well as two treatments in which the recommended rate (135 kg ha^-1 N) was applied on a split schedule offset from the other treatments by two weeks (early, late). Three additional treatments had topdresses of 67, 135, and 202 kg ha^-1 N applied entirely at the first topdress date rather than splitting. These treatments allowed analysis of the impact of topdress rate, splitting, and timing on carrot yield and the evolution of petiole nitrate and carrot imagery over the course of the season. Results were communicated to farmers primarily through presentations at scientific conferences, field days, and grower meetings. Planned outcomes included an improved understanding of carrot nutrient management, as well as drone technology and its potential uses for vegetable farmers in the region.

The experiment found that the higher-than-recommended season N rate (202 kg ha^-1) was associated with significantly increased yields in both years, though there were no yield differences between the 67 and 135 kg ha^-1 N rates. In fact, in 2020 there were no differences between any of the lower rates including the starter-only control treatment. Topdress splitting and timing showed no impacts on yield, but split applications and later topdress timings were associated with increased N uptake in a wet year, possibly mitigating the risk of leaching losses. Vegetation indices calculated from both RGB and multispectral drone imagery were found to correlate with final yield across much of the season, and sufficiency indices normalized using a high-N treatment as a healthy reference delivered more conservative recommendations compared to petiole sap nitrate testing.

The main goal of this study was to evaluate how drone-based remote sensing technology can be used for fertilizer application timing decision support in processing carrots. Concomitant with this goal was an evaluation of how application rate, splitting, and timing impact yield. The results of this study can give a realistic picture of the potential of this new technology for carrot nitrogen management, as well as information regarding the importance of timing as a management consideration. The specific outcomes we sought are as follows:

Learning Outcomes

1. Carrot farmers will have a more complete understanding of the importance of nitrogen topdress application timing as a management consideration, and the potential utility of drone-based decision-support relative to current practices (petiole sampling).
2. Vegetable farmers and researchers will have both an improved awareness and greater understanding of drone technology and its strengths and limitations.
3. Farmers and agricultural researchers will be better equipped to critically evaluate scientific or sales publications regarding the use of drones in agriculture.

Action Outcomes

1. Carrot farmers will improve their nitrogen management practices through more robust decision support relative to current practices.
2. Some carrot farmers will be able to integrate drones into their scouting and monitoring programs for nitrogen management.
3. Carrot farmers and researchers will be better able to experiment with drone-based remote sensing for different applications more specific to their needs.