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

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

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

Preferential retention of chromosome regions in derived synthetic wheat lines: a source of novel alleles for wheat improvement

Synthetic hexaploid wheats (SHWs) and their synthetic derivative lines (SDLs) are being used as a means of introducing novel genetic variation into bread wheat (BW). Phenotypic information for days to flowering, height, grain weight and grain yield was collected from multiple environments for three SDL families, each with ∼50 lines, and their elite BW parents. In general, the SDLs were earlier flowering and taller with larger grain size, but similar grain yield to the BWs. The three SDL families and their SHW and BW parents were genotyped using mapped DArT (diversity arrays technology) markers. Within each SDL family, SHW-specific DArT markers were used to identify SHW-derived chromosomal regions that appeared to be preferentially retained in the SDL families, as determined by retention at frequencies >0.25, the expected frequency for Mendelian segregation. Regions on chromosomes 2BS and 7BL appeared to be preferentially retained in all three SDL families, while regions on chromosomes 1AL, 1BS, 3BS, 5AS, 5BL, and 7AS were preferentially retained in two of the three SDL families. Other regions were preferentially retained in single families only, including some regions located on the D genome. Single-marker regression analysis was performed using the preferentially retained markers and identified markers and regions that were significantly associated with one or more of the four traits measured. Comparative mapping also indicates that these preferentially retained markers and chromosome regions may co-locate with previously identified QTLs for anthesis, height, grain weight and/or grain yield. Therefore, SHWs may contain novel alleles at these loci in these regions for these traits, which may provide a selective advantage to the SDLs. This approach could provide a useful method for identifying chromosomal regions of interest with potentially novel alleles for introgression for further BW improvement