Using leaf optical properties to detect ozone effects on foliar biochemistry

Elizabeth Ainsworth, Shawn P. Serbin, Jeffrey A. Skoneczka, Philip A. Townsend

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)65-76
Number of pages12
JournalPhotosynthesis research
Volume119
Issue number1-2
DOIs
StatePublished - Feb 1 2014

Fingerprint

Biochemistry
Ozone
optical properties
ozone
biochemistry
Optical properties
leaves
reflectance
remote sensing
Soybeans
Remote sensing
phenotype
Least-Squares Analysis
least squares
Crops
methodology
free air carbon dioxide enrichment
soybeans
Throughput
Carboxylation

Keywords

  • Air pollution
  • Photochemical reflectance index
  • Photosynthesis
  • Remote sensing
  • Rubisco
  • Spectroscopy

ASJC Scopus subject areas

  • Biochemistry
  • Plant Science
  • Cell Biology

Cite this

Using leaf optical properties to detect ozone effects on foliar biochemistry. / Ainsworth, Elizabeth; Serbin, Shawn P.; Skoneczka, Jeffrey A.; Townsend, Philip A.

In: Photosynthesis research, Vol. 119, No. 1-2, 01.02.2014, p. 65-76.

Research output: Contribution to journalArticle

Ainsworth, Elizabeth ; Serbin, Shawn P. ; Skoneczka, Jeffrey A. ; Townsend, Philip A. / Using leaf optical properties to detect ozone effects on foliar biochemistry. In: Photosynthesis research. 2014 ; Vol. 119, No. 1-2. pp. 65-76.
@article{2331cef7f1af4c92adcff81525a97606,
title = "Using leaf optical properties to detect ozone effects on foliar biochemistry",
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.",
keywords = "Air pollution, Photochemical reflectance index, Photosynthesis, Remote sensing, Rubisco, Spectroscopy",
author = "Elizabeth Ainsworth and Serbin, {Shawn P.} and Skoneczka, {Jeffrey A.} and Townsend, {Philip A.}",
year = "2014",
month = "2",
day = "1",
doi = "10.1007/s11120-013-9837-y",
language = "English (US)",
volume = "119",
pages = "65--76",
journal = "Photosynthesis Research",
issn = "0166-8595",
publisher = "Springer Netherlands",
number = "1-2",

}

TY - JOUR

T1 - Using leaf optical properties to detect ozone effects on foliar biochemistry

AU - Ainsworth, Elizabeth

AU - Serbin, Shawn P.

AU - Skoneczka, Jeffrey A.

AU - Townsend, Philip A.

PY - 2014/2/1

Y1 - 2014/2/1

N2 - 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.

AB - 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.

KW - Air pollution

KW - Photochemical reflectance index

KW - Photosynthesis

KW - Remote sensing

KW - Rubisco

KW - Spectroscopy

UR - http://www.scopus.com/inward/record.url?scp=84891627620&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84891627620&partnerID=8YFLogxK

U2 - 10.1007/s11120-013-9837-y

DO - 10.1007/s11120-013-9837-y

M3 - Article

C2 - 23657827

AN - SCOPUS:84891627620

VL - 119

SP - 65

EP - 76

JO - Photosynthesis Research

JF - Photosynthesis Research

SN - 0166-8595

IS - 1-2

ER -