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Title: Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat

Abstract

Improving photosynthesis to raise wheat yield potential has emerged as a major target for wheat physiologists. Photosynthesis-related traits, such as nitrogen per unit leaf area (Narea) and leaf dry mass per area (LMA), require laborious, destructive, laboratory-based methods, while physiological traits underpinning photosynthetic capacity, such as maximum Rubisco activity normalized to 25 °C (Vcmax25) and electron transport rate (J), require time-consuming gas exchange measurements. The aim of this study was to assess whether hyperspectral reflectance (350–2500 nm) can be used to rapidly estimate these traits on intact wheat leaves. Predictive models were constructed using gas exchange and hyperspectral reflectance data from 76 genotypes grown in glasshouses with different nitrogen levels and/or in the field under yield potential conditions. Models were developed using half of the observed data with the remainder used for validation, yielding correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.7 for J, 0.81 for SPAD, 0.89 for LMA, and 0.93 for Narea, with bias <0.7%. The models were tested on elite lines and landraces that had not been used to create the models. The bias varied between -2.3% and -5.5% while relative error of prediction was similar for SPAD but slightly greater for LMA and Narea.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [4]
  1. CSIRO Agriculture, Canberra, ACT (Australia); Australian National Univ., Canberra, ACT (Australia). ARC Centre of Excellence for Translational Photosynthesis. Research School of Biology
  2. International Maize and Wheat Improvement Centre (CIMMYT), Mexico City (Mexico)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States). Environmental and Climate Sciences Dept.
  4. Australian National Univ., Canberra, ACT (Australia). ARC Centre of Excellence for Translational Photosynthesis. Research School of Biology
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States); International Maize and Wheat Improvement Centre (CIMMYT), Mexico City (Mexico); CSIRO Agriculture, Canberra, ACT (Australia); Australian National Univ., Canberra, ACT (Australia)
Sponsoring Org.:
USDOE; Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA) (Mexico); National Council of Science and Technology (CONACYT) (Mexico); Australian Research Council (ARC); Grains Research & Development Corporation (Australia)
OSTI Identifier:
1439796
Report Number(s):
BNL-114530-2017-JAAM
Journal ID: ISSN 0022-0957
Grant/Contract Number:  
SC0012704; 207607; CE140100015; CSP00168
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Experimental Botany
Additional Journal Information:
Journal Volume: 69; Journal Issue: 3; Journal ID: ISSN 0022-0957
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; electron transport rate; hyperspectral reflectance; leaf dry mass per area; leaf nitrogen; partial least squares; photosynthesis; Rubisco; Triticum aestivum; velocity of carboxylation

Citation Formats

Silva-Perez, Viridiana, Molero, Gemma, Serbin, Shawn P., Condon, Anthony G., Reynolds, Matthew P., Furbank, Robert T., and Evans, John R. Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat. United States: N. p., 2017. Web. https://doi.org/10.1093/jxb/erx421.
Silva-Perez, Viridiana, Molero, Gemma, Serbin, Shawn P., Condon, Anthony G., Reynolds, Matthew P., Furbank, Robert T., & Evans, John R. Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat. United States. https://doi.org/10.1093/jxb/erx421
Silva-Perez, Viridiana, Molero, Gemma, Serbin, Shawn P., Condon, Anthony G., Reynolds, Matthew P., Furbank, Robert T., and Evans, John R. Fri . "Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat". United States. https://doi.org/10.1093/jxb/erx421. https://www.osti.gov/servlets/purl/1439796.
@article{osti_1439796,
title = {Hyperspectral reflectance as a tool to measure biochemical and physiological traits in wheat},
author = {Silva-Perez, Viridiana and Molero, Gemma and Serbin, Shawn P. and Condon, Anthony G. and Reynolds, Matthew P. and Furbank, Robert T. and Evans, John R.},
abstractNote = {Improving photosynthesis to raise wheat yield potential has emerged as a major target for wheat physiologists. Photosynthesis-related traits, such as nitrogen per unit leaf area (Narea) and leaf dry mass per area (LMA), require laborious, destructive, laboratory-based methods, while physiological traits underpinning photosynthetic capacity, such as maximum Rubisco activity normalized to 25 °C (Vcmax25) and electron transport rate (J), require time-consuming gas exchange measurements. The aim of this study was to assess whether hyperspectral reflectance (350–2500 nm) can be used to rapidly estimate these traits on intact wheat leaves. Predictive models were constructed using gas exchange and hyperspectral reflectance data from 76 genotypes grown in glasshouses with different nitrogen levels and/or in the field under yield potential conditions. Models were developed using half of the observed data with the remainder used for validation, yielding correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.7 for J, 0.81 for SPAD, 0.89 for LMA, and 0.93 for Narea, with bias <0.7%. The models were tested on elite lines and landraces that had not been used to create the models. The bias varied between -2.3% and -5.5% while relative error of prediction was similar for SPAD but slightly greater for LMA and Narea.},
doi = {10.1093/jxb/erx421},
journal = {Journal of Experimental Botany},
number = 3,
volume = 69,
place = {United States},
year = {2017},
month = {12}
}

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Works referenced in this record:

A simple new equation for the reversible temperature dependence of photosynthetic electron transport: a study on soybean leaf
journal, January 2004

  • June, Tania; Evans, John R.; Farquhar, Graham D.
  • Functional Plant Biology, Vol. 31, Issue 3
  • DOI: 10.1071/FP03250

Evaluation of Six Algorithms to Monitor Wheat Leaf Nitrogen Concentration
journal, November 2015

  • Yao, Xia; Huang, Yu; Shang, Guiyan
  • Remote Sensing, Vol. 7, Issue 11
  • DOI: 10.3390/rs71114939

Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests
journal, June 2016


Assessing leaf nitrogen content and leaf mass per unit area of wheat in the field throughout plant cycle with a portable spectrometer
journal, January 2013


Predicting tropical plant physiology from leaf and canopy spectroscopy
journal, October 2010


Partial least-squares regression: a tutorial
journal, January 1986


Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology
journal, March 2012

  • Lopes, Marta S.; Reynolds, Matthew P.
  • Journal of Experimental Botany, Vol. 63, Issue 10
  • DOI: 10.1093/jxb/ers071

Remotely estimating photosynthetic capacity, and its response to temperature, in vegetation canopies using imaging spectroscopy
journal, September 2015


NDVI as a potential tool for predicting biomass, plant nitrogen content and growth in wheat genotypes subjected to different water and nitrogen conditions
journal, March 2011

  • Cabrera-Bosquet, L.; Molero, G.; Stellacci, A.
  • Cereal Research Communications, Vol. 39, Issue 1
  • DOI: 10.1556/CRC.39.2011.1.15

Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field
journal, January 2009

  • Jones, Hamlyn G.; Serraj, Rachid; Loveys, Brian R.
  • Functional Plant Biology, Vol. 36, Issue 11
  • DOI: 10.1071/FP09123

Photochemical reflectance index (PRI) and remote sensing of plant CO2 uptake: Letters
journal, May 2011


Wheat Yield Progress Associated with Higher Stomatal Conductance and Photosynthetic Rate, and Cooler Canopies
journal, January 1998


Visible and near-infrared reflectance techniques for diagnosing plant physiological status
journal, April 1998


The pls Package: Principal Component and Partial Least Squares Regression in R
journal, January 2007

  • Mevik, Bjørn-Helge; Wehrens, Ron
  • Journal of Statistical Software, Vol. 18, Issue 2
  • DOI: 10.18637/jss.v018.i02

A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency
journal, July 1992


Red and photographic infrared linear combinations for monitoring vegetation
journal, May 1979


Using near-infrared reflectance spectroscopy to predict carbon, nitrogen and phosphorus content in heterogeneous plant material
journal, February 1999

  • Gillon, Dominique; Houssard, Claudie; Joffre, Richard
  • Oecologia, Vol. 118, Issue 2
  • DOI: 10.1007/s004420050716

Biochemical model of C 3 photosynthesis applied to wheat at different temperatures : Wheat parameters for C3 photosynthesis model
journal, June 2017

  • Silva-Pérez, Viridiana; Furbank, Robert T.; Condon, Anthony G.
  • Plant, Cell & Environment, Vol. 40, Issue 8
  • DOI: 10.1111/pce.12953

The rapid A-C i response: photosynthesis in the phenomic era : Rapid
journal, March 2017

  • Stinziano, Joseph R.; Morgan, Patrick B.; Lynch, Douglas J.
  • Plant, Cell & Environment, Vol. 40, Issue 8
  • DOI: 10.1111/pce.12911

Spectral Reflectance to Estimate Genetic Variation for In-Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat
journal, January 2006


Estimation of plant water concentration by the reflectance Water Index WI (R900/R970)
journal, September 1997

  • Penuelas, J.; Pinol, J.; Ogaya, R.
  • International Journal of Remote Sensing, Vol. 18, Issue 13
  • DOI: 10.1080/014311697217396

Assessing Wheat Traits by Spectral Reflectance: Do We Really Need to Focus on Predicted Trait-Values or Directly Identify the Elite Genotypes Group?
journal, March 2017

  • Garriga, Miguel; Romero-Bravo, Sebastián; Estrada, Félix
  • Frontiers in Plant Science, Vol. 8
  • DOI: 10.3389/fpls.2017.00280

North American vegetation patterns observed with the NOAA-7 advanced very high resolution radiometer
journal, December 1985

  • Goward, Samuel N.; Tucker, Compton J.; Dye, Dennis G.
  • Vegetatio, Vol. 64, Issue 1
  • DOI: 10.1007/BF00033449

A test of the ‘one-point method’ for estimating maximum carboxylation capacity from field-measured, light-saturated photosynthesis
journal, December 2015

  • De Kauwe, Martin G.; Lin, Yan-Shih; Wright, Ian J.
  • New Phytologist, Vol. 210, Issue 3
  • DOI: 10.1111/nph.13815

Raising yield potential of wheat. II. Increasing photosynthetic capacity and efficiency
journal, October 2010

  • Parry, M. A. J.; Reynolds, M.; Salvucci, M. E.
  • Journal of Experimental Botany, Vol. 62, Issue 2
  • DOI: 10.1093/jxb/erq304

Dynamics of floret development determining differences in spike fertility in an elite population of wheat
journal, February 2015


Relationships Between NDVI, Canopy Structure, and Photosynthesis in Three Californian Vegetation Types
journal, February 1995

  • Gamon, John A.; Field, Christopher B.; Goulden, Michael L.
  • Ecological Applications, Vol. 5, Issue 1
  • DOI: 10.2307/1942049

Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat
journal, January 2013

  • Rebetzke, Greg J.; Rattey, Allan R.; Farquhar, Graham D.
  • Functional Plant Biology, Vol. 40, Issue 1
  • DOI: 10.1071/FP12184

Canopy Temperature Depression Association with Yield of Irrigated Spring Wheat Cultivars in a Hot Climate
journal, April 1996


A decimal code for the growth stages of cereals
journal, December 1974


High-Throughput Phenotyping of Maize Leaf Physiological and Biochemical Traits Using Hyperspectral Reflectance
journal, November 2016

  • Yendrek, Craig R.; Tomaz, Tiago; Montes, Christopher M.
  • Plant Physiology, Vol. 173, Issue 1
  • DOI: 10.1104/pp.16.01447

New phenotyping methods for screening wheat and barley for beneficial responses to water deficit
journal, July 2010

  • Munns, R.; James, R. A.; Sirault, X. R. R.
  • Journal of Experimental Botany, Vol. 61, Issue 13
  • DOI: 10.1093/jxb/erq199

Using leaf optical properties to detect ozone effects on foliar biochemistry
journal, May 2013

  • Ainsworth, Elizabeth A.; Serbin, Shawn P.; Skoneczka, Jeffrey A.
  • Photosynthesis Research, Vol. 119, Issue 1-2
  • DOI: 10.1007/s11120-013-9837-y

A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography
journal, January 2009

  • Sirault, Xavier R. R.; James, Richard A.; Furbank, Robert T.
  • Functional Plant Biology, Vol. 36, Issue 11
  • DOI: 10.1071/FP09182

Machine Learning Techniques for Predicting Crop Photosynthetic Capacity from Leaf Reflectance Spectra
journal, June 2017


Imaging spectroscopy algorithms for mapping canopy foliar chemical and morphological traits and their uncertainties
journal, December 2015

  • Singh, Aditya; Serbin, Shawn P.; McNeil, Brenden E.
  • Ecological Applications, Vol. 25, Issue 8
  • DOI: 10.1890/14-2098.1

Assessment of rice leaf growth and nitrogen status by hyperspectral canopy reflectance and partial least square regression
journal, May 2006


Wheat and maize monitoring based on ground spectral measurements and multivariate data analysis
journal, January 2007

  • Karnieli, Arnon
  • Journal of Applied Remote Sensing, Vol. 1, Issue 1
  • DOI: 10.1117/1.2784799

In vivo temperature response functions of parameters required to model RuBP-limited photosynthesis
journal, September 2003


Nondestructive Method for Estimating Chlorophyll Content of Leaves
journal, June 1961


A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species
journal, June 1980

  • Farquhar, G. D.; von Caemmerer, S.; Berry, J. A.
  • Planta, Vol. 149, Issue 1
  • DOI: 10.1007/BF00386231

Modelling and genetic dissection of staygreen under heat stress
journal, August 2016

  • Pinto, R. Suzuky; Lopes, Marta S.; Collins, Nicholas C.
  • Theoretical and Applied Genetics, Vol. 129, Issue 11
  • DOI: 10.1007/s00122-016-2757-4

Achieving yield gains in wheat: Achieving yield gains in wheat
journal, August 2012


Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature
journal, October 2011

  • Serbin, Shawn P.; Dillaway, Dylan N.; Kruger, Eric L.
  • Journal of Experimental Botany, Vol. 63, Issue 1
  • DOI: 10.1093/jxb/err294

A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding
journal, August 2016

  • Tattaris, Maria; Reynolds, Matthew P.; Chapman, Scott C.
  • Frontiers in Plant Science, Vol. 7
  • DOI: 10.3389/fpls.2016.01131

    Works referencing / citing this record:

    Hyperspectral assessment of plant responses to multi‐stress environments: Prospects for managing protected agrosystems
    journal, November 2019

    • Cotrozzi, Lorenzo; Couture, John J.
    • PLANTS, PEOPLE, PLANET, Vol. 2, Issue 3
    • DOI: 10.1002/ppp3.10080

    Genetic determination for source capacity to support breeding of high-yielding rice (Oryza sativa)
    journal, February 2020


    Prescreening in large populations as a tool for identifying elevated CO2-responsive genotypes in plants
    journal, January 2019

    • Shimono, Hiroyuki; Farquhar, Graham; Brookhouse, Matthew
    • Functional Plant Biology, Vol. 46, Issue 1
    • DOI: 10.1071/fp18087

    Drying times: plant traits to improve crop water use efficiency and yield
    journal, January 2020


    The nitrogen cost of photosynthesis
    journal, October 2018

    • Evans, John R.; Clarke, Victoria C.
    • Journal of Experimental Botany, Vol. 70, Issue 1
    • DOI: 10.1093/jxb/ery366

    Spectroscopy can predict key leaf traits associated with source–sink balance and carbon–nitrogen status
    journal, February 2019

    • Ely, Kim S.; Burnett, Angela C.; Lieberman-Cribbin, Wil
    • Journal of Experimental Botany, Vol. 70, Issue 6
    • DOI: 10.1093/jxb/erz061

    Genetic variation for photosynthetic capacity and efficiency in spring wheat
    journal, September 2019

    • Silva-Pérez, Viridiana; De Faveri, Joanne; Molero, Gemma
    • Journal of Experimental Botany, Vol. 71, Issue 7
    • DOI: 10.1093/jxb/erz439

    Field crop phenomics: enabling breeding for radiation use efficiency and biomass in cereal crops
    journal, April 2019

    • Furbank, Robert T.; Jimenez‐Berni, Jose A.; George‐Jaeggli, Barbara
    • New Phytologist, Vol. 223, Issue 4
    • DOI: 10.1111/nph.15817

    From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance
    journal, September 2019

    • Serbin, Shawn P.; Wu, Jin; Ely, Kim S.
    • New Phytologist, Vol. 224, Issue 4
    • DOI: 10.1111/nph.16123

    Predicting dark respiration rates of wheat leaves from hyperspectral reflectance
    journal, March 2019

    • Coast, Onoriode; Shah, Shahen; Ivakov, Alexander
    • Plant, Cell & Environment, Vol. 42, Issue 7
    • DOI: 10.1111/pce.13544

    The “one‐point method” for estimating maximum carboxylation capacity of photosynthesis: A cautionary tale
    journal, June 2019

    • Burnett, Angela C.; Davidson, Kenneth J.; Serbin, Shawn P.
    • Plant, Cell & Environment, Vol. 42, Issue 8
    • DOI: 10.1111/pce.13574

    Hyperspectral imaging combined with machine learning as a tool to obtain high‐throughput plant salt‐stress phenotyping
    journal, December 2019

    • Feng, Xuping; Zhan, Yihua; Wang, Qi
    • The Plant Journal, Vol. 101, Issue 6
    • DOI: 10.1111/tpj.14597

    Assessing durum wheat ear and leaf metabolomes in the field through hyperspectral data
    journal, January 2020

    • Vergara‐Diaz, Omar; Vatter, Thomas; Kefauver, Shawn Carlisle
    • The Plant Journal, Vol. 102, Issue 3
    • DOI: 10.1111/tpj.14636

    Spectral characterization of wheat functional trait responses to Hessian fly: Mechanisms for trait-based resistance
    journal, August 2019


    Hyperspectral Leaf Reflectance as Proxy for Photosynthetic Capacities: An Ensemble Approach Based on Multiple Machine Learning Algorithms
    journal, June 2019

    • Fu, Peng; Meacham-Hensold, Katherine; Guan, Kaiyu
    • Frontiers in Plant Science, Vol. 10
    • DOI: 10.3389/fpls.2019.00730

    Advancing Bromegrass Breeding Through Imaging Phenotyping and Genomic Selection: A Review
    journal, January 2020

    • Biswas, Dilip K.; Coulman, Bruce; Biligetu, Bill
    • Frontiers in Plant Science, Vol. 10
    • DOI: 10.3389/fpls.2019.01673

    Spectral Reflectance Modeling by Wavelength Selection: Studying the Scope for Blueberry Physiological Breeding under Contrasting Water Supply and Heat Conditions
    journal, February 2019

    • Lobos, Gustavo; Escobar-Opazo, Alejandro; Estrada, Félix
    • Remote Sensing, Vol. 11, Issue 3
    • DOI: 10.3390/rs11030329

    Evaluation of Hyperspectral Reflectance Parameters to Assess the Leaf Water Content in Soybean
    journal, March 2019

    • Kovar, Marek; Brestic, Marian; Sytar, Oksana
    • Water, Vol. 11, Issue 3
    • DOI: 10.3390/w11030443

    Nondestructive Phenomic Tools for the Prediction of Heat and Drought Tolerance at Anthesis in Brassica Species
    journal, May 2019


    Multiple-nutrient limitation of upland rainfed rice in ferralsols: a greenhouse nutrient-omission trial
    text, January 2019