Peng Fu

Photosynthesis — the process by which plants convert sunlight, water and carbon dioxide into energy for growth — powers crop growth, productivity and resilience, yet much of this critical process remains invisible to the human eye. Today, advances in sensing technologies are allowing LSU AgCenter researchers to measure photosynthesis in new ways that were not previously possible, from individual leaves in the field to entire agricultural regions observed by satellites. These observations provide new opportunities to improve crop breeding, monitor crop growth and better understand agricultural productivity and water dynamics in Louisiana.

Because photosynthesis drives plant development and regulates water use, measurements associated with photosynthesis can help researchers better understand crop productivity and water consumption. Studies suggest that continued increases in crop productivity may require a better understanding and optimization of photosynthesis, such as improving photosynthetic efficiency through optimized canopy structure, especially as agricultural systems face increasing environmental challenges, including land shortages and degradation.

Direct measurements of photosynthesis collected at the leaf level remain an important foundation for plant science research. Using portable field instruments (Figure 1), researchers can measure how plants respond to environmental conditions such as heat, drought, disease and salinity stress. These measurements provide detailed information about plant function and photosynthetic performance. However, collecting measurements one leaf at a time is time-consuming, requiring more than 30 minutes for a single leaf, and is difficult to scale across large agricultural systems. New sensing technologies are helping researchers extend these observations from individual plants to entire fields and landscapes.

This research pairs leaf-level photosynthesis measurements with hyperspectral observations, which capture how leaves and crop canopies reflect light across hundreds of narrow wavelengths. Healthy plants absorb and reflect light differently depending on chlorophyll content, water status and photosynthetic activity. This work also contributes to the Global Spectra-Trait Initiative, an international effort to compile plant spectral (related to a spectrum of colors or light) and trait measurements from around the world. The database currently contains more than 7,500 paired measurements that help researchers understand how plant traits are expressed in spectral signals. Combined with machine learning and statistical approaches, these observations allow researchers to estimate plant function and photosynthetic performance without physically sampling every plant.

While leaf-level measurements provide detailed physiological information, drones and satellites allow researchers to scale these observations across fields and regions. Drones equipped with thermal, hyperspectral and multispectral cameras can rapidly monitor crop canopies and identify differences in canopy temperature and plant vigor associated with crop performance. Satellites, including NASA’s Landsat and NISAR missions, repeatedly observe Louisiana’s agricultural landscapes throughout the growing season, providing continuous information on crop development and field conditions, such as soil moisture, over time.

One important application of this research is selecting crop cultivars with improved photosynthetic performance. Feeding a growing population will require continued increases in agricultural productivity, and improving photosynthesis is considered one promising pathway to achieving higher crop yields. At the LSU AgCenter, sensing technologies help researchers and breeders evaluate crop performance more efficiently across large breeding programs.

Traditionally, plant breeders relied heavily on manual observations collected throughout the growing season. Today, drones and spectral sensing technologies allow researchers to rapidly measure plant traits related to photosynthesis, canopy development and water use across thousands of breeding plots. These tools help accelerate the identification of promising cultivars with improved productivity and stress tolerance under Louisiana’s environmental conditions.

Another important application involves monitoring crop growth and estimating productivity at the field level. Because photosynthesis is directly linked to plant growth and water use, repeated observations of crop function can help researchers track crop development throughout the growing season and estimate yield before harvest. At the LSU AgCenter, researchers combine drone and satellite observations with crop and ecosystem models to better understand how plant biomass changes throughout the growing season (Figure 2).

Photosynthesis plays a central role in regulating both crop growth and water use, making it an important process to represent accurately in computational crop models. With improved photosynthesis parameterization, these models can act as digital or virtual representations of crop systems (e.g., biomass accumulation over time shown in Figure 2), helping researchers evaluate how crops may perform under different environmental and management scenarios. When updated continuously with real-time observations, such as those from sensor networks or NASA satellites, these systems may eventually function as “digital twins” of agricultural fields — virtual representations that continuously mirror real-world crop conditions. Such virtual representations could help growers monitor crop conditions, estimate yield and evaluate management strategies for better decisions.

The ability to measure photosynthesis from individual leaves to entire agricultural landscapes represents a major advancement for agricultural science. What was once hidden inside plant leaves can now be monitored across fields and regions using modern sensing technologies. For breeders, these tools provide faster ways to identify promising cultivars. For producers, they offer opportunities for improved crop monitoring and management decisions. For researchers, they create new opportunities to better understand how crops grow and respond to changing environmental conditions.

As sensing technologies continue to advance, digital and precision agriculture will play an increasingly important role in Louisiana farming systems. By combining field research, remote sensing and computational modeling, LSU AgCenter researchers are developing tools and knowledge to support productive, resilient and sustainable agriculture in Louisiana.

This research is supported by the U.S. National Science Foundation, NASA and the Louisiana Board of Regents.

Peng Fu is an assistant professor of digital agriculture in the LSU AgCenter School of Plant, Environmental and Soil Sciences.

This article appears in the summer 2026 edition of Louisiana Agriculture.

Figure 1. LSU AgCenter digital agriculture professor Peng Fu works in the fields measuring photosynthesis using a portable photosynthesis system. Photo by Wei Nie

Figure 2. Simulated plant growth under two levels of photosynthetic capacity. Plants with higher photosynthetic capacity (represented by Vcmax, the maximum rate of carbon fixation during photosynthesis) accumulate more biomass in leaves, stems, roots and grain over time, illustrating how improvements in photosynthesis can contribute to increased crop productivity.