Multi-donor × elite-based populations reveal QTL for low-lodging wheat

Low-lodging high-yielding wheat germplasm and SNP-tagged novel alleles for lodging were identified in a process that involved selecting donors through functional phenotyping for underlying traits with a designed phenotypic screen, and a crossing strategy involving multiple-donor × elite populations

Yielding to the image: how phenotyping reproductive growth can assist crop improvement and production

Reproductive organs are the main reason we grow and harvest most plant species as crops, yet they receive less attention from phenotyping due to their complexity and inaccessibility for analysis. This review highlights recent progress towards the quantitative high-throughput phenotyping of reproductive development, focusing on three impactful areas that are pivotal for plant breeding and crop production. First, we look at phenotyping phenology, summarizing the indirect and direct approaches that are available. This is essential for analysis of genotype by environment, and to enable effective management interpretation and agronomy and physiological interventions. Second, we look at pollen development and production, in addition to anther characteristics, these are critical points of vulnerability for yield loss when stress occurs before and during flowering, and are of particular interest for hybrid technology development. Third, we elaborate on phenotyping yield components, indirectly or directly during the season, with a numerical or growth related approach and post-harvest processing. Finally, we summarise the opportunities and challenges ahead for phenotyping reproductive growth and their feasibility and impact, with emphasis on plant breeding applications and targeted yield increases

Leaf photosynthesis and associations with grain yield, biomass and nitrogen-use efficiency in landraces, synthetic-derived lines and cultivars in wheat

Future genetic progress in wheat grain yield will depend on increasing above-ground biomass and this must be achieved without commensurate increases in N fertilizer inputs to minimise environmental impacts. Our objective was to quantify variation in grain yield, above-ground biomass and N-use efficiency (NUE) and associated traits in a panel of diverse hexaploid wheat germplasm comprising: (i) landraces from the AE Watkins collection, (ii) synthetic-derived hexaploid lines in a cv. Paragon spring wheat background and (iii) UK modern cultivars including cv. Paragon under low N and high N conditions. A field experiment was carried out in two seasons examining 15 genotypes (five landraces, five synthetic-derived (SD) hexaploid lines and five UK modern cultivars) under low N and high N conditions at Nottingham University farm, UK. Machine-harvested grain yield, above-ground biomass and NUE were measured. Physiological traits were assessed including flag-leaf light-saturated photosynthetic rate (Amax) and relative chlorophyll content (SPAD) under HN conditions; and flag-leaf senescence duration and rate and Normalized Difference Vegetative Index (NDVI) under LN and HN conditions. Under HN conditions, the modern cultivars overall produced higher grain yield than the SD lines (+9.7%) and the landraces (+60.4%); and the modern cultivars and SD lines also produced higher biomass than the landraces (30.3% and 28.4%, respectively). Under LN conditions, reduction in grain yield and biomass compared to HN conditions was least for the landraces (−1% and −8.6%, respectively), intermediate for the SD lines (−7.4 and −10.2%, respectively) and highest for the modern cultivars (−9.3 and −24.6%, respectively). As a result, the SD lines had higher biomass (+17%) than the modern cultivars under LN conditions. Under HN conditions the synthetic derivatives (23.8 μmol m−2 s−1) and modern cultivars (241.1 μmol m−2 s−1) had higher pre-anthesis Amax than the landraces (19.7 μmol m−2 s−1) (P < 0.001). Pre-anthesis Amax was strongly positively linearly associated with above-ground biomass (R2 = 0.63, P < 0.001) and grain yield (R2 = 0.75, P < 0.001) amongst the 15 genotypes. Flag-leaf Amax was also positively linearly associated with flag-leaf relative chlorophyll content at anthesis (R2 = 0.74; P < 0.001). Comparing the SD lines to the recurrent parent Paragon, under HN conditions one line (SD 22) had higher pre-anthesis flag-leaf Amax than Paragon (P < 0.05). Under LN conditions one line (SD 24, +27%) had higher yield than Paragon (P < 0.05) and two lines (SD 24 and SD 38, +32% and +31%, respectively) had more biomass than Paragon (P < 0.05). Our results indicated that introgressing traits from synthetic-derived wheat and landraces into UK modern wheat germplasm offers scope to raise above-ground biomass and grain yield in moderate-to-low N availability environments

Meeting the Challenges Facing Wheat Production The Strategic Research Agenda of the Global Wheat Initiative

Wheat occupies a special role in global food security since, in addition to providing 20% of our carbohydrates and protein, almost 25% of the global production is traded internationally. The importance of wheat for food security was recognised by the Chief Agricultural Scientists of the G20 group of countries when they endorsed the establishment of the Wheat Initiative in 2011. The Wheat Initiative was tasked with supporting the wheat research community by facilitating col-laboration, information and resource sharing and helping to build the capacity to address chal-lenges facing production in an increasingly variable environment. Many countries invest in wheat research. Innovations in wheat breeding and agronomy have delivered enormous gains over the past few decades, with the average global yield increasing from just over 1 tonne per hectare in the early 1960s to around 3.5 tonnes in the past decade. These gains are threatened by climate change, the rapidly rising financial and environmental costs of fertilizer, and pesticides, combined with declines in water availability for irrigation in many regions. The international wheat research community has worked to identify major opportunities to help ensure that global wheat pro-duction can meet demand. The outcomes of these discussions are presented in this paper

The Coordination of Leaf Photosynthesis Links C and N Fluxes in C3 Plant Species

Photosynthetic capacity is one of the most sensitive parameters in vegetation models and its relationship to leaf nitrogen content links the carbon and nitrogen cycles. Process understanding for reliably predicting photosynthetic capacity is still missing. To advance this understanding we have tested across C3 plant species the coordination hypothesis, which assumes nitrogen allocation to photosynthetic processes such that photosynthesis tends to be co-limited by ribulose-1,5-bisphosphate (RuBP) carboxylation and regeneration. The coordination hypothesis yields an analytical solution to predict photosynthetic capacity and calculate area-based leaf nitrogen content (Na). The resulting model linking leaf photosynthesis, stomata conductance and nitrogen investment provides testable hypotheses about the physiological regulation of these processes. Based on a dataset of 293 observations for 31 species grown under a range of environmental conditions, we confirm the coordination hypothesis: under mean environmental conditions experienced by leaves during the preceding month, RuBP carboxylation equals RuBP regeneration. We identify three key parameters for photosynthetic coordination: specific leaf area and two photosynthetic traits (k3, which modulates N investment and is the ratio of RuBP carboxylation/oxygenation capacity () to leaf photosynthetic N content (Npa); and Jfac, which modulates photosynthesis for a given k3 and is the ratio of RuBP regeneration capacity (Jmax) to). With species-specific parameter values of SLA, k3 and Jfac, our leaf photosynthesis coordination model accounts for 93% of the total variance in Na across species and environmental conditions. A calibration by plant functional type of k3 and Jfac still leads to accurate model prediction of Na, while SLA calibration is essentially required at species level. Observed variations in k3 and Jfac are partly explained by environmental and phylogenetic constraints, while SLA variation is partly explained by phylogeny. These results open a new avenue for predicting photosynthetic capacity and leaf nitrogen content in vegetation models

Meeting the challenges facing wheat production: The strategic research agenda of the Global Wheat Initiative

Wheat occupies a special role in global food security since, in addition to providing 20% of our carbohydrates and protein, almost 25% of the global production is traded internationally. The importance of wheat for food security was recognised by the Chief Agricultural Scientists of the G20 group of countries when they endorsed the establishment of the Wheat Initiative in 2011. The Wheat Initiative was tasked with supporting the wheat research community by facilitating collaboration, information and resource sharing and helping to build the capacity to address challenges facing production in an increasingly variable environment. Many countries invest in wheat research. Innovations in wheat breeding and agronomy have delivered enormous gains over the past few decades, with the average global yield increasing from just over 1 tonne per hectare in the early 1960s to around 3.5 tonnes in the past decade. These gains are threatened by climate change, the rapidly rising financial and environmental costs of fertilizer, and pesticides, combined with declines in water availability for irrigation in many regions. The international wheat research community has worked to identify major opportunities to help ensure that global wheat production can meet demand. The outcomes of these discussions are presented in this paper

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Drought-adaptive traits derived from wheat wild relatives and landraces

Exotic parents are being used to increase allelic diversity in bread wheat breeding through (i) interspecific hybridization of the ancestral genomes to produce so-called synthetic derived (SYN-DER) wheat, and (ii) crossing with landrace accessions, originating in abiotically stressed environments, that have become isolated from mainstream gene pools. Evaluation of the inherent genetic diversity encompassed by drought-adapted landraces compared with checks using DNA fingerprinting confirmed that some landraces were not only distant from checks but also showed significant diversity among each other. Improvement in performance of SYN-DER lines compared with recurrent parents was not associated with a larger overall investment in root dry weight, but rather an increased partitioning of root mass to deeper soil profiles (between 60 cm and 120 cm) and increased ability to extract moisture from those depths. The best Mexican landraces showed superior ability in terms of water extraction from soil depth, as well as increased concentration of soluble carbohydrates in the stem shortly after anthesis. Although it can be argued that inferring theoretical yield gains from the over-expression of any of these traits is questionable, since compensatory mechanisms may be at work, the fact remains that mechanistic or genetic linkages among physiological traits remain largely un-established. In the meantime, trait information is being used to make strategic crosses based on the theoretical combination of useful stress-adaptive traits with the possibility of realizing additive gene action in selected progeny. Candidates for crossing with elite check cultivars include landraces identified that showed relatively high biomass under drought combined with favourable expression of physiological traits such as stem carbohydrates, water extraction characteristics, and transpiration efficiency

Adaptation of wheat, barley, canola, field pea and chickpea to the thermal environments of Australia

Warming trends involve two agronomically relevant aspects: a gradual increase in long-term mean temperature with the primary effect of shifting phenological patterns, and an increasing incidence of heat waves. Depending on timing, intensity and duration, heat can reduce crop growth and disrupt reproduction. Agronomic and breeding adaptations to elevated temperature have been listed but there is an overall lack of frameworks for systematic analysis. This paper provides agronomic and physiological background for the quantitative assessment of spatial patterns of the thermal regimes for wheat, barley, canola, field pea and chickpea. First, we revise the notion that Australian agriculture is ‘European’ and ill-adapted to the local environments. By showing that Australian agriculture in the southern and western regions is rather Levantine, we advance a more accurate and relevant framework to the thermal regimes of winter crops. Second, we outline the direct and indirect effects of temperature on crop traits and highlight the limitations of different approaches to investigate crop responses to temperature. This is important to make explicit the assumptions of studies dealing with crop responses to temperature; for example, indirect effects of temperature on crops mediated by effects on weeds, pathogens or herbivores could be important. Third, we compare the cardinal temperatures (including base, optimal, and critical thresholds) of our target crops. Cardinal temperatures respond to both natural and agronomic selection and are relevant for crop adaptation. Fourth, we develop a conceptual framework to assess thermal effects on crop yield and adaptive practices and traits, based on the notions of yield being a primary function of seed number, the species-specific critical window for the determination of seed number, and two complementary perspectives involving the photothermal quotient and crop growth rate in the critical window. The framework accounts for both aspects of warming: non-stressful elevated temperature and heat stress. Testable propositions are advanced that inform future research on crop adaptation to elevated temperature