Benefits of increasing transpiration efficiency in wheat under elevated CO₂ for rainfed regions

Abstract

Higher transpiration efficiency (TE) has been proposed as a mechanism to increase crop yields in dry environments where water availability usually limits yield. The application of a coupled radiation and TE simulation model shows wheat yield advantage of a high-TE cultivar (cv. Drysdale) over its almost identical low-TE parent line (Hartog), from about À7 to 558 kg/ha (mean 187 kg/ha) over the rainfed cropping region in Australia (221-1,351 mm annual rainfall), under the present-day climate. The smallest absolute yield response occurred in the more extreme drier and wetter areas of the wheat belt.However, under elevated CO 2 conditions, the response of Drysdale was much greater overall, ranging from 51 to 886 kg/ha (mean 284 kg/ha) with the greatest response in the higher rainfall areas. Changes in simulated TE under elevated CO 2 conditions are seen across Australia with notable increased areas of higher TE under a drier climate in Western Australia, Queensland and parts of New South Wales and Victoria. This improved efficiency is subtly deceptive, with highest yields not necessarily directly correlated with highest TE. Nevertheless, the advantage of Drysdale over Hartog is clear with the benefit of the trait advantage attributed to TE ranging from 102% to 118% (mean 109%). The potential annual cost-benefits of this increased genetic TE trait across the wheat growing areas of Australia (5 year average of area planted to wheat) totaled AUD 631 MIL (5-year average wheat price of AUD/260 t) with an average of 187 kg/ha under the present climate. The benefit to an individual farmer will depend on location but elevated CO 2 raises this nation-wide benefit to AUD 796 MIL in a 2°C warmer climate, slightly lower (AUD 715 MIL) if rainfall is also reduced by 20%.

Elevated [CO2] effects on crops: Advances in understanding acclimation, nitrogen dynamics and interactions with drought and other organisms

“…Only with better understanding of the CO 2 × water interactions will it become possible to extrapolate potential adaptive strategies, such as water‐saving traits, to larger regions (Christy et al . ).…”

“…), and extrapolation of these results to a larger cropping region confirmed this trend (Christy et al . ). The explanation may be that e[CO 2 ] changes the water use dynamics of the agro‐ecosystems, possibly shifting timing and extent of water use in a way that amplifies the benefit of higher transpiration efficiency during early growth.…”

Comparison of array‐ and sequencing‐based markers for genome‐wide association mapping and genomic prediction in spring wheat

“…To dissect the genetic basis of traits through GWAS, several studies were conducted using array-based platforms (Liu, Pinto, Cossani, Sukumaran, & Reynolds, 2019;Lopes, Dreisigacker, Pena, Sukumaran, & Reynolds, 2015;Sukumaran, Dreisigacker, Lopes, Chavez, & Reynolds, 2015, 2018bValluru, Reynolds, Davies, & Sukumaran, 2017) in spring wheat and sequencing-based platforms (Sukumaran, Reynolds, & Sansaloni, 2018c) in durum wheat (Triticum durum Desf.). Genomic prediction studies were also conducted using the I90K and DArTseq platforms (Christy et al, 2018;Crossa et al, 2014Crossa et al, , 2016aCrossa et al, , 2016bCrossa et al, , 2017Juliana et al, 2018Juliana et al, , 2019Rutkoski et al, 2016;Sukumaran, Crossa, Jarquin, Lopes, & Reynolds, 2017a, 2017b.…”

A reduced‐tillering trait shows small but important yield gains in dryland wheat production

“…The average annual crop yield potential over the 57 year simulation period at each site and sowing time was based on the total yield for each genotype divided by the number of crops sown in 57 years. To have a realistic comparative analysis across the landscape, all forms of postsowing crop failure were included in the calculation of average annual crop yield (Christy et al, 2018).…”

“…Experimental approaches aimed at interpreting the interaction between genotype and environment are time‐consuming, especially where capturing the impact of long‐term climate is needed (Asseng & Turner, 2007; He, Wang, Wang, & Lilley, 2017). Crop simulation modelling is another approach allowing long‐term assessment under different growing conditions, and especially valuable where it is based on robust data from rigorous field experiments (Christy et al, 2018; Zhao, Rebetzke, Zheng, Chapman, & Wang, 2019). In this current paper, we used experimental data from two growing seasons at the Australian Grains Free‐Air CO 2 Enrichment (AGFACE) facility together with other published data and crop simulation modelling to (a) better understand the interaction between genetic and environmental components of the reduced‐tillering trait in wheat; and (b) extrapolate its potential long‐term average benefits across Australia's arable land (i.e.…”