This final article in the fertilizer series looks at the innovation and solutions for the negative impacts of synthetic nitrogen fertilizers through the lens of the Right Rate, Right Time, and Right Place in the “Four R” best practices.
The first article in this series, “Fertile Ground for Change,” covered the environmental and social impacts of nitrogen pollution, especially on water quality. The second article, “The Four “Rs” of Addressing the Fertilizer Problem,” reviewed the scale of the nitrogen problem, gaps in nitrogen use efficiency, and the barriers to implementing the current “4R” practices of Right Source, Right Rate, Right Time, Right Place. The third article covered Right Source biofertilizer alternatives that improve nitrogen use efficiency.
Right Rate, Right Time, Right Place
Farmers often base fertilizer application rates on yield goal, an estimation based on historical average yield for a given field plus 10-30%. This estimate can also include crediting for nitrogen-fixing crops in a rotation and residual nitrogen. However, long-term studies indicate that there is little correlation between the yield goal method and actual yield (Raun,2017). Climate, precipitation, the amount of plant-available residual nitrogen in the soil, and the other environmental factors vary year-to-year and directly impact yield and the ideal rate, timing, and area of nutrient application. Soil nutrient needs can also vary across a single field, especially if the field has elevation changes.
Agriculture technology, or ag tech, advances offer a path to realizing the full value of the three Rs of time, place, and rate. These precision agriculture methods include variable rate technologies (VRT), crop and soil sensors, geospatial tools such as precision field mapping for soil and yield and guidance systems that reduce overlapping field passes.
Soil Mapping and enhanced soil Tests
Healthy soils with more biological activity improve the nitrogen use efficiency of fertilizer. In one study with maize, soil biological health accounted for nearly one-fifth of the nitrogen fertilizer effect (Grandy et al., 2022). Thus, regenerative practices that improve soil health and biological activity are one of the keys to reducing the rate of nitrogen fertilizer use.
Ideally, farmers will conduct a soil test annually to determine soil nutrient needs. Yet, because nitrogen is leachable in the soil, the nitrogen levels at the time of the soil test may not be the same when a plant needs the nitrogen. Improvements to soil testing methods offer better insights on the available nitrogen in the soil and include the biological activity, or “life” in the soil. These soil testing solutions can even incorporate genomic sequencing of the soil microbiome.
Soil mapping combines spatial and soil data to generate detailed maps of soil variation in a field. Mapped data includes texture, structure, pH, nutrient levels, and moisture content. Some soil mapping technologies include electromagnetic sensing to map soil composition and in-situ sensors for soil moisture. The detailed soil map is used to guide precision soil tests and the “what, where, and how much” of management decisions.
Yield, Soil, and Plant Monitoring
Yield monitors gather geotagged harvest data on the variations in productivity in a field. The data can be used for traceability to a given field as with Monitoring Measurement Reporting and Verification (MMRV) platforms, or for advanced yield mapping. Plant sensors include in-field instruments to measure the reflectance or the absorbance of green color present in the leaves as a proxy for nitrogen needs. Plant sensors can also be remote technologies via drone, satellite, or aircraft that measure biomass. Soon, soil sensors will monitor not only soil moisture, but soil nitrate levels as well (USGAO, 2024).
Variable Rate Technology
VRT uses soil mapping or data along with machinery equipped with sensors and controls, including automated section control, to target the rate and location of fertilizer applications. By reducing fertilizer use overall and targeting the use where it is needed, VRT reduces nutrient leaching and run-off as well as input costs (McFadden et al., 2023).
Machinery capable of auto guidance also reduces input use by minimizing overlapping of field passes during fertilizer application.
Farm Management
Ideally, all farm data could be aggregated into one platform. These farm management information systems (FMIS) enable farmers to make management decisions by generating application guidance maps, determining timing for fertilization, and helping maximize yield and profitability. FMIS remains challenging, primarily due to the lack of universal standards and interoperability of different equipment and the low adoption of precision ag technology. FMIS technology will also need mature from a platform that aggregates data for farmer analysis to an intelligent tool that informs decision-making (US GAO,2024).
Challenges
Collectively, the adoption rate of one or more precision agriculture technologies is 27% in the US (US GAO, 2024). Automated guidance has the highest adoption rate at about half of commodity crop operations (US GAO, 2024). Despite an uptick in adoption rates since the early 2000s, VRT technology only covers about half of the largest farms (the upper third of acreage per farm) in the US (McFadden et al., 2023). VRT is primarily used by the largest corn and soy producers, covering about 40% of US corn acreage, with lower adoption rates for other commodity crops. Technologies like soil mapping lag VRT in adoption as well. Global adoption rates of VRT are lower with estimated rates between 1-5% for developing regions (Hopkins, 2025; Swinton & Lowenberg-De Boer, 2001).
Barriers to adoption include farm size, high upfront cost, variation in soil attributes and land characteristics, knowledge of technology and support, data privacy concerns, difficulty of use, lack of infrastructure especially broadband, lack of equipment interoperability, and lack of funding for practice transition (McFadden et al., 2023; UNDP, 2021).
Opportunity
According to Global Ag Tech Initiative data, the global market for VRT was USD 7 billion in 2023. The market is projected to soar to USD 25.43 billion by 2033 (Hopkins, 2025). In addition to making these technologies more scalable and affordable, farmers need innovations to address interoperability issues and infrastructure gaps. Innovation is not limited to equipment and software. Farmers will need innovative financing alternatives and services including training to drive adoption. As labor shortages increase, the demand for autonomous equipment will also increase.
The other key opportunity is scaling precision ag technologies like yield and soil maps and VRT for smallholder farms, which represent 90% of global agriculture (UNDP, 2021). Key opportunities at the smallholder scale include robotics and VRT including drone applications and precision ag as a service models (Marston, 2025).
Combined, precision agriculture technologies can reduce usage of synthetic N fertilizer and improve N use efficiency. Doing more with less benefits both farmers and the environment, given the rising cost of inputs. Additionally, these technologies offer a means to reduce pesticide use. Because the technologies maximize farm profits and solve for labor shortages, adoption of precision agriculture presents a path forward for farmer profitability, water quality, soil health, climate, and human health.
References
Grandy, A.S., Daly, A., Bowles, T., Gaudin, A., Jilling, A., Leptin, A., McDaniel, M.D., Wade, J., Waterhouse, H. (2022). The nitrogen gap in soil health concepts and fertility measurements, Soil Biology and Biochemistry, Volume 175, 2022, 108856, ISSN 0038-0717,https://doi.org/10.1016/j.soilbio.2022.108856.
Hopkins, M. (2025, January 6). Variable Rate Technology in Agriculture: An In-Depth Look at the economic benefits and future growth. Global Ag Tech Initiative. https://www.globalagtechinitiative.com/in-field-technologies/variable-rate-technology-in-agriculture-an-in-depth-look-at-economic-benefits-and-future-growth/
Marston, J. (2025, January 14). With a fresh $13m, Niqo Robotics aims to help smallholders ‘lead the innovation curve’ in AI farming. AgFunder News.https://agfundernews.com/with-a-fresh-13m-niqo-robotics-aims-to-help-smallholders-lead-the-innovation-curve-in-ai-farming
McFadden, J., Njuki, E., Griffin, T., & Economic Research Service. (2023). Precision Agriculture in the Digital Era: Recent adoption on U.S. farms. Economic Information Bulletin, 248.https://www.ers.usda.gov/webdocs/publications/105894/eib-248.pdf?v=6882.3
Raun, W., Figueiredo, B., Dhillon, J., Fornah, A., Bushong, J., Zhang, H., & Taylor, R. (2017). Can yield goals be predicted? Agronomy Journal, 109(5), 2389–2395. https://doi.org/10.2134/agronj2017.05.0279
Swinton, Scott & Lowenberg-De Boer, James. (2001). Global adoption of precision agriculture technologies: Who, when and why?. Proceedings of the 3rd European Conference on Precision Agriculture.
United States Government Accountability Office. (2024). TECHNOLOGY ASSESSMENT precision Agriculture Benefits and challenges for technology adoption and use. https://www.gao.gov/assets/d24105962.pdf
United Nations Development Programme, Precision agriculture for smallholder farmers (UNDP Global Centre for Technology, Innovation and Sustainable Development: Singapore, 2021). https://www.undp.org/sites/g/files/zskgke326/files/2021-10/UNDP-Precision-Agriculture-for-Smallholder-Farmers.pdf