Key Messages

• On-farm research experimentation allows farmers to test sensing technologies to determine whether they can improve nitrogen use efficiency (NUE) and yields in wheat.
• Efficiency and Sustainability: By aligning N applications timing and rate with crop needs, sensor-based tools have the potential to increase NUE and yields.
• Farmers Resilience: Increased NUE and yields enhance farm sustainability in the face of rising input costs and environmental pressures.

Nitrogen (N) management is a cornerstone of modern winter wheat production, directly influencing yield potential, economic returns and environmental sustainability. Efficient N management is essential to meet crop demands without over-applying fertilizers, which can lead to significant environmental challenges such as nitrate leaching, greenhouse gas emissions and reduced nitrogen use efficiency (NUE). Traditional N management practices often involve flat or fixed application rates that fail to account for variability in soil fertility, weather conditions, and crop requirements across fields. These approaches can result in either over-fertilization, wasting resources and harming the environment, or under-fertilization, restricting yield potential. 

To address these limitations, sensor-based nitrogen management technologies have emerged as a promising alternative, enabling site-specific, real-time adjustments to optimize nitrogen applications. A recent survey in digital agriculture shows that less than 10% of Nebraska farmers use vegetation indices in their operations to manage crop nutrition (Balboa et al, 2023). 

This article highlights key findings from on-farm research trials conducted across Nebraska, where sensor-based variable rate nitrogen (VRN) tools were compared against traditional grower practices. These trials aimed to assess the potential of VRN technologies to improve nitrogen use efficiency, increase profitability and reduce environmental risks while maintaining or enhancing grain yield in wheat. By leveraging on-farm experimentation, this research offers valuable insights into the practical implementation of precision agriculture tools in diverse field conditions, helping producers adopt different technologies for decision-making. 

Over three growing seasons (2020-2023), 15 on-farm trials assessed sensor-based N management systems, including active and passive sensors (Figure 1). Results of each single study can be found in the Nebraska On-Farm Research Network results publications (2020-2023).

How Does the Technology Work?

Sensor-based N tools use crop health data to guide in-season fertilizer applications:

• Active sensors emit their own light to measure crop health or vigor, making them reliable for use any time, regardless of sunlight. Active sensors function under varying weather conditions.
• Passive sensors rely on sunlight or external light sources, working best under stable daylight conditions for assessing plant health. While effective for large-scale monitoring, passive sensors may be hindered by weather conditions such as cloud cover.
• N algorithm: The canopy index data, derived from vegetation indices such as NDVI and NDRE, is used alongside parameters like yield goal and sensing date as inputs into algorithms that determines the N rate to apply. In this research, commercial and land grands university algorithms were evaluated in different fields. For more details, visit the NOFRN website for experiment results. 

Summary of Yields and Nitrogen Use Efficiency 

An integrated analysis of all 15 sites showed that sensor-based nitrogen management tools increased nitrogen use efficiency (NUE) in 65% of the cases, while increase in yield compared to growers’ treatment was observed in 43% of the trials (Figure 3). Active canopy sensor contributed with 33.8% of the cases where yield was increased and 50.7% of the cases where NUE was increased.

Take Home Messages

• Reduced Inputs: Overall, sensor-based systems applied 10% less N compared to grower practices, with statistically significant reductions in seven out of 15 site-years.
• Improved Efficiency: Sensor-based N management increased NUE by 4.7% across all trials, with significant gains in five site-years.
• Comparable Yields: Grain yields were similar between treatments, averaging 65.2 bu/ac (sensor-based) and 64.4 bu/ac (grower), with the sensor-based approach outyielding growers’ treatments in four out of 15 site-years.

Practical Implications for Farmers

• On-farm research experimentation allows farmers to test sensing technologies to determine whether they can improve NUE and yields in wheat, providing field-specific insights.
• Efficiency and Sustainability: By aligning N applications with crop needs, sensor-based tools have the potential to increase NUE and yields.
• Farmers’ Resilience: Increased NUE and yields enhance farm sustainability in the face of rising input costs and environmental pressures.

Challenges and Considerations

While sensor-based tools show promise, several barriers must be addressed:

• Cost and Accessibility: High upfront costs for equipment and training can discourage adoption, particularly for smaller operations.
• Weather Dependence: Passive sensors require clear skies for optimal performance, which may delay applications during critical growth stages.
• Logistical Adjustments: In-season applications may require changes to farm operations, particularly during labor-intensive periods.

Farmers interested in adopting these tools can benefit from participating in the Nebraska On-Farm Research Network to test their efficacy under local conditions.

This research was possible through the funding provided by the Conservation Innovation Grant (CIG – USDA NR203A750013G014). We thank farmer participants who allowed us to conduct this research through the Nebraska On-Farm Research Network. We thank former extension educators Laura J. Thompson and Nathan Mueller for their leadership in this project. 

References

Balboa, G. R., Puntel, L. A., & Thompson, L. (2023) On-Farm Research Network Ecosystem Increased Awareness and Use of Digital Agriculture in Nebraska [Abstract]. ASA, CSSA, SSSA International Annual Meeting, St. Louis, MO. https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/150933 

Cesario Pinto J. 2024. "Evaluation Of Digital Ag Tools For Nitrogen Management In Winter Wheat". Ph.D. dissertation. University of Nebraska–Lincoln. Nebraska, USA.  

Pinto, J. G. C. P., Paccioretti, P., Thompson, L., Mueller, N., Balboa, G., Mieno, T., Puntel, L. 2024. Site-Specific Evaluation of Sensor-Based Winter Wheat Nitrogen Tools

Cesario Pinto J. 2024. "Evaluation Of Digital Ag Tools For Nitrogen Management In Winter Wheat". Ph.D. dissertation. University of Nebraska–Lincoln. Nebraska, USA.  

Pinto, J. G. C. P., Paccioretti, P., Thompson, L., Mueller, N., Balboa, G., Mieno, T., Puntel, L. 2024. Site-Specific Evaluation of Sensor-Based Winter Wheat Nitrogen Tools via On-Farm Research. In: International Conference on Precision Agriculture, Manhattan, KS, (USA). Oral Presentation. July 2024.   

Pinto, J. G. C. P., Paccioretti, P., Thompson, L., Mueller, N., Balboa, G., Mieno, T., Puntel, L. 2024. On-Farm Evaluation of Active and Passive Sensor-based N Management in Winter Wheat. In: ASA CSSA SSSA International Annual Meetings, San Antonio, TX. 2024. Oral Presentation. November 2024.