The Challenges in Developing Field-based Technologies

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Think about the wildest imagination you have had – what if the right technology was available to make it possible?

For farmers and plant scientists working long hours in the field, whether under the blazing summer sun or year-round in certain regions of the world, there is no doubt that technology has made field work more efficient. From planters and fertilizer-spreading tractors, to automated irrigation systems and phenotyping devices, technological innovations have reshaped agriculture and plant science research. These innovations have expanded planting and harvesting capabilities, accelerated data collection, and improved overall agricultural productivity and research. Over the past decade, even more advanced tools have emerged. AI-powered drones, Bluetooth-enabled systems, environmental sensors, and autonomous robots are transforming how we collect phenotype data from field-grown crops. These tools increase precision, reduce human error, and help researchers work more efficiently. While these technologies have revolutionized agriculture and plant science, their development and deployment come with real challenges.

A major challenge has been ensuring that field-based technologies perform reliably in the environments where they are used. The materials used to develop these technologies must withstand harsh environmental conditions, such as extreme temperatures, humidity, and soil variability. They also need to be designed with regional climates in mind. For example, solar-powered devices will not be effective in areas with inconsistent sunlight. Developers must consider both durability and environmental compatibility to ensure long-term functionality.

The costs associated with developing and deploying field-based technologies presents another significant challenge, particularly for smallholder farmers and research labs with limited budgets. Developing these technologies often requires substantial investment in research, prototyping, testing, and expert labor. For example, the development of drones and automated farm/field machinery would require the employment of materials scientists, engineers and data scientists, which would ultimately go into the costs of production. Even after development, ongoing maintenance and operational costs can limit their utilization. Further, for many users, especially in developing regions, the financial return on investment may take years to realize, which discourages adoption (Morisse et al., 2022).

There’s also a gap between innovation and real-world application. Many farmers may be hesitant to adopt new technologies due to their familiarity with traditional farming methods or skepticism about the effectiveness of modern solutions. Additionally, new technologies often require training to ensure proper usage. Without sufficient educational programs or accessible training resources, farmers may struggle to understand and interpret data or operate advanced tools effectively (Tesso Huluka et al., 2016).

Logistics also pose a major barrier. Many rural areas, particularly in developing countries, lack reliable internet connectivity. Technologies that rely on cloud-based systems or real-time data transmission may not be efficiently utilized. Even where internet access is available, unstable power supply can limit the use of energy-dependent technologies such as automated irrigation systems, robots, and drones (Rozenstein et al., 2024).

Field-based technologies have redefined agricultural research and crop production. But the journey from lab to field is not seamless. Developers and users face serious challenges ranging from environmental, financial, educational, and infrastructural. Yet, these challenges are not insurmountable. Addressing these challenges would require a multidisciplinary approach and collaboration between developers of technology, farmers, and plant scientists to create tools that are relatively affordable, efficient at doing the task they were developed for, and user-friendly. Only then can we fully unlock the potential of technology to improve field-based plant science research, and farming.

 

References

Morisse, M., Wells, D. M., Millet, E. J., Lillemo, M., Fahrner, S., Cellini, F., Lootens, P., Muller, O., Herrera, J. M., Bentley, A. R., & Janni, M. (2022). A European perspective on opportunities and demands for field-based crop phenotyping. Field Crops Research, 276. https://doi.org/10.1016/j.fcr.2021.108371

Rozenstein, O., Cohen, Y., Alchanatis, V., Behrendt, K., Bonfil, D. J., Eshel, G., Harari, A., Harris, W. E., Klapp, I., Laor, Y., Linker, R., Paz-Kagan, T., Peets, S., Rutter, S. M., Salzer, Y., & Lowenberg-DeBoer, J. (2024). Data-driven agriculture and sustainable farming: friends or foes? Precision Agriculture, 25(1), 520–531. https://doi.org/10.1007/s11119-023-10061-5

Tesso Huluka, A., & Negatu, W. (2016). The Impacts of Farmer Field School Training on Knowledge and Farm Technology Adoption: Evidence from Smallholder Maize Farmers in Oromia, Ethiopia. Journal of Economics and Public Finance, 2(1).

 

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About the Authors

Carlos González Sanz

Carlos is a biotechnologist doing a PhD at Universidad Politécnica de Madrid in Spain, and a 2025 Plantae Fellows.  His research focuses on understanding the effect of high temperatures in plants on fungal microbiota recruitment and searching for new isolates that help tackle this stress. You can find him on X: @carlosgonzsanz.

Irene I. Ikiriko

Irene is a PhD candidate at the University of Delaware, and a 2025 Plantae Fellows.  Her ultimate goal is to link plant mechanics to cellular mechano-perception. Her research is punctuated by work at her foundation (Dauntless Widows Foundation), her love for writing, trying new recipes, and learning about history! You can find her on X: @ireneikiriko.