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.
Highlights
Global population is predicted to reach 9.7 billion by 2050 (UN Department of Economic and Social Affairs, 2015)
The bias varied between −2.3% and −5.5% while relative error of prediction was similar for SPAD but slightly greater for leaf dry mass per area (LMA) and nitrogen per unit leaf area (Narea)
Two predictions are shown for the Rubisco-related trait Vcmax: (i) Vcmax without leaf temperature correction and (ii) Vcmax25 corrected to a common leaf temperature of 25 °C using in vivo Rubisco kinetics derived for wheat (Silva-Pérez et al, 2017)
Summary
Global population is predicted to reach 9.7 billion by 2050 (UN Department of Economic and Social Affairs, 2015). To satisfy projected demand for cereal grain, wheat yields need to increase at rates far exceeding the current annual genetic gains being made in most parts of the world by plant breeders (Reynolds et al, 2012). Further improvements in yield require increases in biomass, derived from improvements in radiation use efficiency and photosynthetic traits (Parry et al, 2011; Reynolds et al, 2012). Selection based on physiological and biochemical characteristics of wheat genotypes in a breeding programme is uncommon due to cost and the time required for testing at a breeding scale.
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