Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat.

The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates.

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology.

Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM-WGP model introduces environmental information to WGP and genomic relatedness information to the genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM-WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM-WGP framework and compared it with CGM and WGP.

Identification of agro-physiological traits of lentil that reduce risks of drought.

Ideotype breeding is an essential approach for selection of desired combination of plant traits for testing in crop growth model for potential yield gain in specific environments and management practices. Here we parameterized plant traits for untested lentil cultivars for the APSIM-lentil model in phenology, biomass, and seed yield. We then tested these against independent data and applied the model in an extrapolated analysis (i) to assess the impact of drought on productivity across different rainfall environments; (ii) to identify impactful plant traits and (iii) to design new lentil ideotypes with a combination of desirable traits that mitigate the impact of drought, in the context of various agronomic practices across a wide range of production environments.

Using genomic prediction with crop growth models enables the prediction of associated traits in wheat.

Crop growth models (CGM) can predict the performance of a cultivar in untested environments by sampling genotype-specific parameters. As they cannot predict the performance of new cultivars, it has been proposed to integrate CGMs with whole genome prediction (WGP) to combine the benefits of both models. Here, we used a CGM-WGP model to predict the performance of new wheat (Triticum aestivum) genotypes.

Does Elevated [CO] Only Increase Root Growth in the Topsoil? A FACE Study with Lentil in a Semi-Arid Environment.

Atmospheric carbon dioxide concentrations [CO] are increasing steadily. Some reports have shown that root growth in grain crops is mostly stimulated in the topsoil rather than evenly throughout the soil profile by e[CO], which is not optimal for crops grown in semi-arid environments with strong reliance on stored water. An experiment was conducted during the 2014 and 2015 growing seasons with two lentil () genotypes grown under Free Air CO Enrichment (FACE) in which root growth was observed non-destructively with mini-rhizotrons approximately every 2-3 weeks.

Narrowing uncertainties in the effects of elevated CO on crops.

Plant responses to rising atmospheric carbon dioxide (CO) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO concentrations.

Sources of uncertainty for wheat yield projections under future climate are site-specific.

Understanding sources of uncertainty in climate-crop modelling is critical for informing adaptation strategies for cropping systems. An understanding of the major sources of uncertainty in yield change is needed to develop strategies to reduce the total uncertainty. Here, we simulated rain-fed wheat cropping at four representative locations in China and Australia using eight crop models, 32 global climate models (GCMs) and two climate downscaling methods, to investigate sources of uncertainty in yield response to climate change.

Early vigour in wheat: Could it lead to more severe terminal drought stress under elevated atmospheric [CO ] and semi-arid conditions?

Early vigour in wheat is a trait that has received attention for its benefits reducing evaporation from the soil surface early in the season. However, with the growth enhancement common to crops grown under elevated atmospheric CO concentrations (e[CO ]), there is a risk that too much early growth might deplete soil water and lead to more severe terminal drought stress in environments where production relies on stored soil water content. If this is the case, the incorporation of such a trait in wheat breeding programmes might have unintended negative consequences in the future, especially in dry years.

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

Reducing the number of tillers per plant using a tiller inhibition (tin) gene has been considered as an important trait for wheat production in dryland environments. We used a spatial analysis approach with a daily time-step coupled radiation and transpiration efficiency model to simulate the impact of the reduced-tillering trait on wheat yield under different climate change scenarios across Australia's arable land. Our results show a small but consistent yield advantage of the reduced-tillering trait in the most water-limited environments both under current and likely future conditions.

Global wheat production with 1.5 and 2.0°C above pre-industrial warming.

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.

Multimodel ensembles improve predictions of crop-environment-management interactions.

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However, few studies have specifically been concerned with the predictive quality of those ensemble predictors.

Elevated [CO2] mitigates the effect of surface drought by stimulating root growth to access sub-soil water.

Through stimulation of root growth, increasing atmospheric CO2 concentration ([CO2]) may facilitate access of crops to sub-soil water, which could potentially prolong physiological activity in dryland environments, particularly because crops are more water use efficient under elevated [CO2] (e[CO2]). This study investigated the effect of drought in shallow soil versus sub-soil on agronomic and physiological responses of wheat to e[CO2] in a glasshouse experiment. Wheat (Triticum aestivum L.

Water availability moderates N fixation benefit from elevated [CO ]: A 2-year free-air CO enrichment study on lentil (Lens culinaris MEDIK.) in a water limited agroecosystem.

Increased biomass and yield of plants grown under elevated [CO ] often corresponds to decreased grain N concentration ([N]), diminishing nutritional quality of crops. Legumes through their symbiotic N fixation may be better able to maintain biomass [N] and grain [N] under elevated [CO ], provided N fixation is stimulated by elevated [CO ] in line with growth and yield. In Mediterranean-type agroecosystems, N fixation may be impaired by drought, and it is unclear whether elevated [CO ] stimulation of N fixation can overcome this impact in dry years.

Effectiveness of time of sowing and cultivar choice for managing climate change: wheat crop phenology and water use efficiency.

Climate change (CC) presents a challenge for the sustainable development of wheat production systems in Australia. This study aimed to (1) quantify the impact of future CC on wheat grain yield for the period centred on 2030 from the perspectives of wheat phenology, water use and water use efficiency (WUE) and (2) evaluate the effectiveness of changing sowing times and cultivars in response to the expected impacts of future CC on wheat grain yield. The daily outputs of CSIRO Conformal-Cubic Atmospheric Model for baseline and future periods were used by a stochastic weather generator to derive changes in mean climate and in climate variability and to construct local climate scenarios, which were then coupled with a wheat crop model to achieve the two research aims.

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

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 -7 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.

Australian wheat production expected to decrease by the late 21st century.

Climate change threatens global wheat production and food security, including the wheat industry in Australia. Many studies have examined the impacts of changes in local climate on wheat yield per hectare, but there has been no assessment of changes in land area available for production due to changing climate. It is also unclear how total wheat production would change under future climate when autonomous adaptation options are adopted.

The relationship between transpiration and nutrient uptake in wheat changes under elevated atmospheric CO.

The impact of elevated [CO ] (e[CO ]) on crops often includes a decrease in their nutrient concentrations where reduced transpiration-driven mass flow of nutrients has been suggested to play a role. We used two independent approaches, a free-air CO enrichment (FACE) experiment in the South Eastern wheat belt of Australia and a simulation study employing the agricultural production systems simulator (APSIM), to show that transpiration (mm) and nutrient uptake (g m ) of nitrogen (N), potassium (K), sulfur (S), calcium (Ca), magnesium (Mg) and manganese (Mn) in wheat are correlated under e[CO ], but that nutrient uptake per unit water transpired is higher under e[CO ] than under ambient [CO ] (a[CO ]). This result suggests that transpiration-driven mass flow of nutrients contributes to decreases in nutrient concentrations under e[CO ], but cannot solely explain the overall decline.

Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functions.

This corrects the article DOI: 10.1038/nplants.2017.

Erratum: The uncertainty of crop yield projections is reduced by improved temperature response functions.

This corrects the article DOI: 10.1038/nplants.2017.

The uncertainty of crop yield projections is reduced by improved temperature response functions.

Increasing the accuracy of crop productivity estimates is a key element in planning adaptation strategies to ensure global food security under climate change. Process-based crop models are effective means to project climate impact on crop yield, but have large uncertainty in yield simulations. Here, we show that variations in the mathematical functions currently used to simulate temperature responses of physiological processes in 29 wheat models account for >50% of uncertainty in simulated grain yields for mean growing season temperatures from 14 °C to 33 °C.

Elevated atmospheric [CO2 ] can dramatically increase wheat yields in semi-arid environments and buffer against heat waves.

Wheat production will be impacted by increasing concentration of atmospheric CO2 [CO2 ], which is expected to rise from about 400 μmol mol(-1) in 2015 to 550 μmol mol(-1) by 2050. Changes to plant physiology and crop responses from elevated [CO2 ] (e[CO2 ]) are well documented for some environments, but field-level responses in dryland Mediterranean environments with terminal drought and heat waves are scarce. The Australian Grains Free Air CO2 Enrichment facility was established to compare wheat (Triticum aestivum) growth and yield under ambient (~370 μmol(-1) in 2007) and e[CO2 ] (550 μmol(-1) ) in semi-arid environments.

Climate and soil properties limit the positive effects of land use reversion on carbon storage in Eastern Australia.

Australia's "Direct Action" climate change policy relies on purchasing greenhouse gas abatement from projects undertaking approved abatement activities. Management of soil organic carbon (SOC) in agricultural soils is an approved activity, based on the expectation that land use change can deliver significant changes in SOC. However, there are concerns that climate, topography and soil texture will limit changes in SOC stocks.