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ARS Home » Midwest Area » Urbana, Illinois » Global Change and Photosynthesis Research » Research » Publications at this Location » Publication #289131
Title: Using leaf optical properties to detect ozone effects on foliar biochemistry

Author
item Ainsworth, Elizabeth - Lisa
item SERBIN, S - University Of Wisconsin
item Skoneczka, Jeffrey
item TOWNSEND, P - University Of Wisconsin

Submitted to: Photosynthesis Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/25/2013
Publication Date: 5/9/2013
Citation: Ainsworth, E.A., Serbin, S.P., Skoneczka, J.A., Townsend, P.A. 2013. Using leaf optical properties to detect ozone effects on foliar biochemistry. Photosynthesis Research. DOI:10.1007/s11120-013-9837-y.

Interpretive Summary: Remote-sensing methods can be used to accurately and rapidly relate variations in leaf reflectance properties with important plant characteristics, such as leaf biochemistry, morphology, and photosynthetic properties. In this study, we demonstrated the potential to use remote screening to identify ozone sensitivity in soybean. Eleven soybean genotypes were exposed to ambient and elevated ozone concentrations in field conditions. Elevated ozone decreased seed yield by 30% and also decreased leaf nitrogen and chlorophyll content, estimated from leaf reflectance spectra. We also showed that the maximum activity of Rubisco, an important parameter which describes photosynthetic potential, could be accurately estimated from leaf reflectance spectra. Thus, this study illustrates the potential for combining high phenotyping with remote sensing with genotyping methods to elucidate the genetic basis for ozone tolerance in soybean.

Technical 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, 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 elevated ozone (100 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 also 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 (Vc,max), an important parameter describing plant photosynthetic capacity. While we did not find a significant impact of ozone fumigation on Vc,max, standardized to a reference temperature of 25 °C, the PLSR approach provided accurate and precise estimates of Vc,max across control and ozone treatments (r2 = 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 great potential for combining the phenotyping methods used here with high-throughput genotyping methods as a promising approach for elucidating the genetic basis for ozone tolerance in sensitive crops.