Crop models are essential tools for assessing the threat of climate change to local and global food production 1 . Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature 2 . Here we systematically tested 30 di erent wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 • C to 32 • C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each • C of further temperature increase and become more variable over space and time.Understanding how different climate factors interact and impact food production 3 is essential when reaching decisions on how to adapt to the effects of climate change. To implement such strategies the contribution of various climate variables on crop yields need to be separated and quantified. For instance, a change in temperature will require a different adaptation strategy than a change in rainfall 4 . Temperature changes alone are reported to have potentially large negative impacts on crop production 5 , and hotspots-locations where plants suffer from high temperature stress-have been identified across the globe 6,7 . Crop simulation models are useful tools in climate impact studies as they deal with multiple climate factors and how they interact with various crop growth and yield formation processes that are sensitive to climate. These models have been applied in many studies, including the assessment of temperature impacts on crop production 1,8 . However, none of the crop models have been tested systematically against experiments at different temperatures in field conditions. Although many glasshouse and controlled-environment temperature experiments have been described, they are often not suitable for model testing as the heating of root systems in pots 9 and effects on micro-climate differ greatly from field conditions 10 . Detailed information on field experiments with a wide range of sowing dates and infrared heating recently became available for wheat 11,12 . Such experiments are well suited for testing the ability of crop models to quantify temperature responses under field conditions. Testing the temperature responses of crop models is particularly important for assessing the impact of climate change on wheat production, because the largest uncertainty in simulated impacts on yield arises from increasing temperatures 2 .In a 'Hot Serial Cereal' (HSC) well-irrigated and fertilized experiment with a single cultivar, the observed days after sowing (DAS) to maturity declined...

Domesticated crops experience strong human-mediated selection aimed at developing high-yielding varieties adapted to local conditions. To detect regions of the wheat genome subject to selection during improvement, we developed a high-throughput array to interrogate 9,000 gene-associated single-nucleotide polymorphisms (SNP) in a worldwide sample of 2,994 accessions of hexaploid wheat including landraces and modern cultivars. Using a SNP-based diversity map we characterized the impact of crop improvement on genomic and geographic patterns of genetic diversity. We found evidence of a small population bottleneck and extensive use of ancestral variation often traceable to founders of cultivars from diverse geographic regions. Analyzing genetic differentiation among populations and the extent of haplotype sharing, we identified allelic variants subjected to selection during improvement. Selective sweeps were found around genes involved in the regulation of flowering time and phenology. An introgression of a wild relative-derived gene conferring resistance to a fungal pathogen was detected by haplotype-based analysis. Comparing selective sweeps identified in different populations, we show that selection likely acts on distinct targets or multiple functionally equivalent alleles in different portions of the geographic range of wheat. The majority of the selected alleles were present at low frequency in local populations, suggesting either weak selection pressure or temporal variation in the targets of directional selection during breeding probably associated with changing agricultural practices or environmental conditions. The developed SNP chip and map of genetic variation provide a resource for advancing wheat breeding and supporting future population genomic and genomewide association studies in wheat.SNP genotyping | polyploid wheat | selection scans | wheat improvement | breeding history

Drought is the main abiotic constraint on cereal yield. Analysing physiological determinants of yield responses to water may help in breeding for higher yield and stability under drought conditions. The traits to select (either for stress escape, avoidance or tolerance) and the framework where breeding for drought stress is addressed will depend on the level and timing of stress in the targeted area. If the stress is severe, breeding under stress-free conditions may be unsuccessful and traits that confer survival may become a priority. However, selecting for yield itself under stress-alleviated conditions appears to produce superior cultivars, not only for optimum environments, but also for those characterized by frequent mild and moderate stress conditions. This implies that broad avoidance/tolerance to mild-moderate stresses is given by constitutive traits also expressed under stress-free conditions. In this paper, we focus on physiological traits that contribute to improved productivity under mild-moderate drought. Increased crop performance may be achieved through improvements in water use, water-use efficiency and harvest index. The first factor is relevant when soil water remains available at maturity or when deep-rooted genotypes access water in the soil profile that is not normally available; the two latter conditions become more important when all available water is exhausted by the end of the crop cycle. Independent of the mechanism operating, a canopy able to use more water than another would have more open stomata and therefore higher canopy temperature depression, and 13C discrimination (delta13C) in plant matter. The same traits would also seem to be relevant when breeding for hot, irrigated environments. Where additional water is not available to the crop, higher water-use efficiency (WUE) appears to be an alternative strategy to improve crop performance. In this context delta13C constitutes a simple but reliable measure of WUE. However, in contrast to lines performing better because of increased access to water, lines producing greater biomass due to superior WUE will have lower delta13C values. WUE may be modified not only through a decrease in stomatal conductance, but also through an increase in photosynthetic capacity. Harvest index is strongly reduced by terminal drought (i.e. drought during grain filling). Thus, phenological traits increasing the relative amount of water used during grain filling, or adjusting the crop cycle to the seasonal pattern of rainfall may be useful. Augmenting the contribution of carbohydrate reserves accumulated during vegetative growth to grain filling may also be worthwhile in harsh environmcnts. Alternatively, extending the duration of stem elongation without changing the timing of anthesis would increase the number of grains per spike and the harvest index without changing the amount of water utilized by the crop.

Wheat is fundamental to human civilization and has played an outstanding role in feeding a hungry world and improving global food security. The crop contributes about 20 % of the total dietary calories and proteins worldwide. Food demand in the developing regions is growing by 1 % annually and varies from 170 kg in Central Asia to 27 kg in East and South Africa. The developing regions (including China and Central Asia) account for roughly 53 % of the total harvested area and 50 % of the production. Unprecedented productivity growth from the Green Revolution (GR) since the 1960s dramatically transformed world wheat production, benefitting both producers and consumers through low production costs and low food prices. Modern wheat varieties were adopted more rapidly than any other technological innovation in the history of agriculture, recently reaching about 90 % of the area in developing regions. One of the key challenges today is to replace these varieties with new ones for better sustainability. While the GR "spared" essential ecosystems from conversion to agriculture, it also generated its own environmental problems. Also productivity increase is now slow or static. Achieving the productivity gains needed to ensure food security will therefore require more than a repeat performance of the GR of the past. Future demand will need to be achieved through sustainable intensification that combines better crop resistance to diseases and pests, adaptation to warmer climates, and reduced use of water, fertilizer, labor and fuel. Meeting these challenges will require concerted efforts in research and innovation to develop and deploy viable solutions. Substantive investment will be required to realize sustainable productivity growth through better technologies and policy and institutional innovations that facilitate farmer adoption and adaptation. The enduring lessons from the GR and the recent efforts for sustainable intensification of cereal systems in South Asia and other regions provide useful insights for the future.

A restricted range in height and phenology of the elite Seri/Babax recombinant inbred line (RIL) population makes it ideal for physiological and genetic studies. Previous research has shown differential expression for yield under water deficit associated with canopy temperature (CT). In the current study, 167 RILs plus parents were phenotyped under drought (DRT), hot irrigated (HOT), and temperate irrigated (IRR) environments to identify the genomic regions associated with stress-adaptive traits. In total, 104 QTL were identified across a combination of 115 traits × 3 environments × 2 years, of which 14, 16, and 10 QTL were associated exclusively with DRT, HOT, and IRR, respectively. Six genomic regions were related to a large number of traits, namely 1B-a, 2B-a, 3B-b, 4A-a, 4A-b, and 5A-a. A yield QTL located on 4A-a explained 27 and 17% of variation under drought and heat stress, respectively. At the same location, a QTL explained 28% of the variation in CT under heat, while 14% of CT variation under drought was explained by a QTL on 3B-b. The T1BL.1RS (rye) translocation donated by the Seri parent was associated with decreased yield in this population. There was no co-location of consistent yield and phenology or height-related QTL, highlighting the utility of using a population with a restricted range in anthesis to facilitate QTL studies. Common QTL for drought and heat stress traits were identified on 1B-a, 2B-a, 3B-b, 4A-a, 4B-b, and 7A-a confirming their generic value across stresses. Yield QTL were shown to be associated with components of other traits, supporting the prospects for dissecting crop performance into its physiological and genetic components in order to facilitate a more strategic approach to breeding.Electronic supplementary materialThe online version of this article (doi:10.1007/s00122-010-1351-4) contains supplementary material, which is available to authorized users.

Past increases in yield potential of wheat have largely resulted from improvements in harvest index rather than increased biomass. Further large increases in harvest index are unlikely, but an opportunity exists for increasing productive biomass and harvestable grain. Photosynthetic capacity and efficiency are bottlenecks to raising productivity and there is strong evidence that increasing photosynthesis will increase crop yields provided that other constraints do not become limiting. Even small increases in the rate of net photosynthesis can translate into large increases in biomass and hence yield, since carbon assimilation is integrated over the entire growing season and crop canopy. This review discusses the strategies to increase photosynthesis that are being proposed by the wheat yield consortium in order to increase wheat yields. These include: selection for photosynthetic capacity and efficiency, increasing ear photosynthesis, optimizing canopy photosynthesis, introducing chloroplast CO(2) pumps, increasing RuBP regeneration, improving the thermal stability of Rubisco activase, and replacing wheat Rubisco with that from other species with different kinetic properties.

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots.

A substantial increase in grain yield potential is required, along with better use of water and fertilizer, to ensure food security and environmental protection in future decades. For improvements in photosynthetic capacity to result in additional wheat yield, extra assimilates must be partitioned to developing spikes and grains and/or potential grain weight increased to accommodate the extra assimilates. At the same time, improvement in dry matter partitioning to spikes should ensure that it does not increase stem or root lodging. It is therefore crucial that improvements in structural and reproductive aspects of growth accompany increases in photosynthesis to enhance the net agronomic benefits of genetic modifications. In this article, six complementary approaches are proposed, namely: (i) optimizing developmental pattern to maximize spike fertility and grain number, (ii) optimizing spike growth to maximize grain number and dry matter harvest index, (iii) improving spike fertility through desensitizing floret abortion to environmental cues, (iv) improving potential grain size and grain filling, and (v) improving lodging resistance. Since many of the traits tackled in these approaches interact strongly, an integrative modelling approach is also proposed, to (vi) identify any trade-offs between key traits, hence to define target ideotypes in quantitative terms. The potential for genetic dissection of key traits via quantitative trait loci analysis is discussed for the efficient deployment of existing variation in breeding programmes. These proposals should maximize returns in food production from investments in increased crop biomass by increasing spike fertility, grain number per unit area and harvest index whilst optimizing the trade-offs with potential grain weight and lodging resistance.