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Using leaf optical properties to detect ozone effects on foliar biochemistry

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Abstract

Efficient methods for accurate and meaningful high-throughput plant phenotyping are limiting the development and breeding of stress-tolerant crops. A number of emerging techniques, specifically remote sensing methods, have been identified as promising tools for plant phenotyping. These remote sensing methods can be used to accurately and rapidly relate variations in leaf optical properties with important plant characteristics, such as chemistry, morphology, and photosynthetic properties at the leaf and canopy scales. In this study, we explored the potential to utilize optical (λ = 500–2,400 nm) near-surface remote sensing reflectance spectroscopy to evaluate the effects of ozone pollution on photosynthetic capacity of soybean (Glycine max Merr.). The research was conducted at the Soybean Free Air Concentration Enrichment (SoyFACE) facility where we subjected plants to ambient (44 nL L−1) and elevated ozone (79–82 nL L−1 target) concentrations throughout the growing season. Exposure to elevated ozone resulted in a significant loss of productivity, with the ozone-treated plants displaying a ~30 % average decrease in seed yield. From leaf reflectance data, it was also clear that elevated ozone decreased leaf nitrogen and chlorophyll content as well as the photochemical reflectance index (PRI), an optical indicator of the epoxidation state of xanthophyll cycle pigments and thus physiological status. We assessed the potential to use leaf reflectance properties and partial least-squares regression (PLSR) modeling as an alternative, rapid approach to standard gas exchange for the estimation of the maximum rates of RuBP carboxylation (V c,max), an important parameter describing plant photosynthetic capacity. While we did not find a significant impact of ozone fumigation on V c,max, standardized to a reference temperature of 25 °C, the PLSR approach provided accurate and precise estimates of V c,max across ambient plots and ozone treatments (r 2 = 0.88 and RMSE = 13.4 μmol m−2 s−1) based only on the variation in leaf optical properties and despite significant variability in leaf nutritional status. The results of this study illustrate the potential for combining the phenotyping methods used here with high-throughput genotyping methods as a promising approach for elucidating the basis for ozone tolerance in sensitive crops.

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Notes

  1. http://www.labsphere.com/products/reflectance-standards-and-targets/reflectance-targets/spectralon-targets.aspx.

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Acknowledgments

We thank Chris Montes, Kannan Puthuval, and David Drag for managing SoyFACE, and Donald Ort for facilitating research. Chris Montes, Joe Sullivan, and Amy Betzelberger assisted with measurements of leaf optical properties and gas exchange. This study was supported in part by the Agriculture and Food Research Initiative competitive grant no. 2010-65114-20355 from the USDA National Institute of Food and Agriculture to E.A.A, NASA Earth and Space Science Fellowship NNX08AV07H to S.P.S. and NASA HyspIRI Preparatory Grant NNX10AJ94G to P.A.T.

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  1. Agricultural Research Service, Global Change and Photosynthesis Research Unit, US Department of Agriculture, University of Illinois, Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL, 61801, USA

    Elizabeth A. Ainsworth & Jeffrey A. Skoneczka

  2. Department of Plant Biology, University of Illinois, Urbana-Champaign, 1201 W. Gregory Drive, Urbana, IL, 61801, USA

    Elizabeth A. Ainsworth

  3. Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 226 Russell Labs, 1630 Linden Drive, Madison, WI, 53706, USA

    Shawn P. Serbin & Philip A. Townsend

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  1. Elizabeth A. Ainsworth
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Correspondence to Elizabeth A. Ainsworth.

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Ainsworth, E.A., Serbin, S.P., Skoneczka, J.A. et al. Using leaf optical properties to detect ozone effects on foliar biochemistry. Photosynth Res 119, 65–76 (2014). https://doi.org/10.1007/s11120-013-9837-y

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