The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.
Improving the monitoring of crop productivity using spaceborne solar‐induced fluorescence
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. C 3 and C 4 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.
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Citations
Cites
Red and photographic infrared linear combinations for monitoring vegetation
Tucker, C. J. (1979) · Remote Sensing of Environment · doi:10.1016/0034-4257(79)90013-0 · Cited by 11,754
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00096-2 · Cited by 9,869
A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species
Farquhar, G. D., von Caemmerer, S., & Berry, J. A. (1980) · Planta · doi:10.1007/bf00386231 · Cited by 8,796
Self-citationGenty, B., Briantais, J.-M., & Baker, N. R. (1989) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/s0304-4165(89)80016-9 · Cited by 8,644
Farquhar, G., O'Leary, M., & Berry, J. (1982) · Australian Journal of Plant Physiology · doi:10.1071/pp9820121 · Cited by 3,903
Self-citationClimate and the efficiency of crop production in Britain
Monteith, J. L. (1977) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1977.0140 · Cited by 3,484 · cited 1×
“Monteith (1977) proposed a seminal idea of modeling NPP using a LUE approach: NPP ¼ aPAR LUENPP ð2Þ where aPAR is absorbed photosynthetic active radiation (PAR) by plants, and LUENPP refers to the efficiency of plants in converting aPAR to biomass or NPP. aPAR is calculated as a product of incident…”
MethodNonlinear temperature effects indicate severe damages to U.S. crop yields under climate change
Schlenker, W., & Roberts, M. J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906865106 · Cited by 3,420
Terrestrial ecosystem production: A process model based on global satellite and surface data
Potter, C. S., Randerson, J. T., Field, C. B., Matson, P. A., Vitousek, P. M., Mooney, H. A., & Klooster, S. A. (1993) · Global Biogeochemical Cycles · doi:10.1029/93gb02725 · Cited by 2,986
Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009
Zhao, M., & Running, S. W. (2010) · Science · doi:10.1126/science.1192666 · Cited by 2,674
Can improvement in photosynthesis increase crop yields?
LONG, S. P., ZHU, X., NAIDU, S. L., & ORT, D. R. (2006) · Plant, Cell & Environment · doi:10.1111/j.1365-3040.2005.01493.x · Cited by 1,586
Cited by
Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress
Mohammed, G. H., Colombo, R., Middleton, E. M., Rascher, U., van der Tol, C., Nedbal, L., Goulas, Y., Pérez-Priego, O., Damm, A., Meroni, M., et al. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.04.030 · Cited by 747
Self-citationSheffield, J., Wood, E. F., Pan, M., Beck, H., Coccia, G., Serrat‐Capdevila, A., & Verbist, K. (2018) · Water Resources Research · doi:10.1029/2017wr022437 · Cited by 561
Metadata
- Authors
- Guan, K., Berry, J. A., Zhang, Y., Joiner, J., Guanter, L., Badgley, G., & Lobell, D. B.
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2015-11-10
- Volume
- 22
- Issue
- 2
- Pages
- 716-726
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W2167443344
- Cited by
- 334
- References
- 47
- FWCI
- 18.65
- Type
- journal article
- Language
- en
- Open access
- closed
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- Guan, K., Berry, J. A., Zhang, Y., Joiner, J., Guanter, L., Badgley, G., & Lobell, D. B. (2016). Improving the monitoring of crop productivity using spaceborne solar‐induced fluorescence. Global Change Biology. https://doi.org/10.1111/gcb.13136
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