Improving the monitoring of crop productivity using spaceborne solar‐induced fluorescence

TLDR

Large‑scale monitoring of crop growth and yield is crucial for forecasting food production, prices, and regional food security, and the emerging satellite retrieval of solar‑induced fluorescence (SIF) offers the first direct measurement of plant photosynthetic activity. The authors present a framework linking SIF retrievals to crop yield by incorporating stoichiometry, photosynthetic pathways, and respiration losses. They applied this framework to estimate U.S. crop productivity (2007‑2012) using GOES‑2 SIF retrievals, county‑level yield statistics, and compared the results to traditional monitoring methods.

Abstract

Large-scale monitoring of crop growth and yield has important value for forecasting food production and prices and ensuring regional food security. A newly emerging satellite retrieval, solar-induced fluorescence (SIF) of chlorophyll, provides for the first time a direct measurement related to plant photosynthetic activity (i.e. electron transport rate). Here, we provide a framework to link SIF retrievals and crop yield, accounting for stoichiometry, photosynthetic pathways, and respiration losses. We apply this framework to estimate United States crop productivity for 2007-2012, where we use the spaceborne SIF retrievals from the Global Ozone Monitoring Experiment-2 satellite, benchmarked with county-level crop yield statistics, and compare it with various traditional crop monitoring approaches. We find that a SIF-based approach accounting for photosynthetic pathways (i.e. C3 and C4 crops) provides the best measure of crop productivity among these approaches, despite the fact that SIF sensors are not yet optimized for terrestrial applications. We further show that SIF provides the ability to infer the impacts of environmental stresses on autotrophic respiration and carbon-use-efficiency, with a substantial sensitivity of both to high temperatures. These results indicate new opportunities for improved mechanistic understanding of crop yield responses to climate variability and change.