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Increasing leaf transpiration efficiency (TE) may provide leads for growing rice like dryland cereals such as wheat (Triticum aestivum). To explore avenues for improving TE in rice, variations in stomatal conductance (gs ) and mesophyll conductance (gm ) and their anatomical determinants were evaluated in two cultivars from each of lowland, aerobic, and upland groups of Oryza sativa, one cultivar of O. glaberrima, and two cultivars of T. aestivum, under three water regimes. The TE of upland rice, O. glaberrima, and wheat was more responsive to the gm/gs ratio than that of lowland and aerobic rice. Overall, the explanatory power of the particular anatomical trait varied among species. Low stomatal density mostly explained the low gs in drought-tolerant rice, whereas rice genotypes with smaller stomata generally responded more strongly to drought. Compared with rice, wheat had a higher gm , which was associated with thicker mesophyll tissue, mesophyll and chloroplasts more exposed to intercellular spaces, and thinner cell walls. Upland rice, O. glaberrima, and wheat cultivars minimized the decrease in gm under drought by maintaining high ratios of chloroplasts to exposed mesophyll cell walls. Rice TE could be improved by increasing the gm/gs ratio via modifying anatomical traits.

BackgroundProcess-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2].AnalysisA review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth.ConclusionsThe performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity.

Aims To face the challenge of decreasing freshwater availability for agriculture, it is important to explore avenues for developing rice genotypes that can be grown like dryland cereals. Roots play a key role in plant adaptation to dry environments. Methods We examined anatomical and histochemical root traits that affect water acquisition in rice ( Oryza sativa ) and wheat ( Triticum aestivum ). These traits and root growth were measured at two developmental stages for three rice and two wheat cultivars that were grown in pots under three water regimes. Results Wheat roots had larger xylem sizes than rice roots, which potentially led to a higher axial conductance, especially under water-deficit conditions. Suberization, lignification and thickening of the endodermis in rice roots increased with increasing water deficit, resulting in stronger radial barriers for water flow in rice than in wheat, especially near the root apex. In addition, water deficit strongly impeded root growth and lateral root proliferation in rice, but only slightly in wheat, and cultivars within a species differed little in these responses. The stress sensitivity of rice attributes was slightly more prominent at vegetative than at flowering stages. Conclusions Rice root characteristics, which are essential for growth under inundated conditions, are not conducive to growth under water deficit. Although rice roots show considerable plasticity under different watering regimes, improving root xylem size and reducing the radial barriers would be required if rice is to grow like dryland cereals.

Extra ATP required in C4 photosynthesis for the CO2-concentrating mechanism probably comes from cyclic electron transport (CET). As metabolic ATP : NADPH requirements in mesophyll (M) and bundle-sheath (BS) cells differ among C4 subtypes, the subtypes may differ in the extent to which CET operates in these cells. We present an analytical model for cell-type-specific CET and linear electron transport. Modelled NADPH and ATP production were compared with requirements. For malic-enzyme (ME) subtypes, c. 50% of electron flux is CET, occurring predominantly in BS cells for standard NADP-ME species, but in a ratio of c. 6 : 4 in BS :M cells for NAD-ME species. Some C4 acids follow a secondary decarboxylation route, which is obligatory, in the form of ‘aspartate-malate’, for the NADP-ME subtype, but facultative, in the form of phosphoenolpyruvate-carboxykinase (PEP-CK), for the NAD-ME subtype. The percentage for secondary decarboxylation is c. 25% and that for 3-phosphoglycerate reduction in BS cells is c. 40%; but these values vary with species. The ‘pure’ PEP-CK type is unrealistic because its is impossible to fulfilATP : NADPH requirements in BS cells. The standard PEP-CK subtype requires negligible CET, and thus has the highest intrinsic quantum yields and deserves further studies in the context of improving canopy productivity.

Using the GECROS model, we simulated the effect of improvements in photosynthesis a range of growth parameters, including yield, and on the εc (the conversion efficiency of absorbed solar energy to the chemical energy of biomass) and εi (the efficiency of solar energy interception or absorption by the canopy) parameters of the Monteith crop growth equation, for wheat and potato (which use C3 photosynthesis) and maize (which uses C4 photosynthesis). In the case of the C3 crops, the improvements in photosynthesis were via 20% increases in the parameters Vcmax (carboxylation capacity of Rubisco), Jmax (electron transport capacity), Sc/o (Rubisco specificity), κ2LL (efficiency of converting incident light into electron transport) and gm (mesophyll conductance), while for the C4 crop, it was via 20% increase in Vcmax, Jmax and Sc/o and a 20% decrease in gbs (the conductance that controls the leak of CO2 from the bundle sheath cells in C4 leaves). The changes were applied individually and in combination. The responses were modelled using climate data collected over a 10‐year period from 66 sites around Europe. Improvements in photosynthesis did result in increases in yield but with considerable variation between the parameters that were adjusted. The greatest increases were obtained for increases in Jmax and κ2LL (up to an average 11% increase for total plant biomass), and these increases were found across all Europe. Increases in both these parameters have a predominant effect on the light‐use efficiency for subsaturating irradiances. Improvements in the other parameters produced smaller increases. Using the GECROS model, we simulated the effect of improvements in photosynthesis on a range of growth parameters. The responses were modelled using climate data collected over a 10‐year period (1991–2000) from 66 sites around Europe. Improvements in photosynthesis did result in increases in yield. The greatest increases were obtained for increases in Jmax and κ2LL (up to an average 11% increase for total plant biomass), and these increases were found across all Europe. Increases in both these parameters have a predominant effect on the light‐use efficiency for subsaturating irradiances. Improvements in other parameters produced smaller increases.

Rice grain yield and quality are predicted to be highly vulnerable to global warming. Five genotypes including heat-tolerant and susceptible checks, a heat-tolerant near-isogenic line and two hybrids were exposed to control (31 °C/23 °C, day/night), high night-time temperature (HNT; 31 °C/30 °C), high day-time temperature (HDT; 38 °C/23 °C) and high day- and night-time temperature (HNDT; 38 °C/30 °C) treatments for 20 consecutive days during the grain-filling stage. Grain-filling dynamics, starch metabolism enzymes, temporal starch accumulation patterns and the process of chalk formation were quantified. Compensation between the rate and duration of grain filling minimized the impact of HNT, but irreversible impacts on seed-set, grain filling and ultimately grain weight were recorded with HDT and HNDT. Scanning electron microscopy demonstrated irregular and smaller starch granule formation affecting amyloplast build-up with HDT and HNDT, while a quicker but normal amylopast build-up was recorded with HNT. Our findings revealed temporal variation in the starch metabolism enzymes in all three stress treatments. Changes in the enzymatic activity did not derail starch accumulation under HNT when assimilates were sufficiently available, while both sucrose supply and the conversion of sucrose into starch were affected by HDT and HNDT. The findings indicate differential mechanisms leading to high day and high night temperature stress-induced loss in yield and quality. Additional genetic improvement is needed to sustain rice productivity and quality under future climates.

The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C₃ leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO₂). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (A without). However, differences in predicted photosynthesis integrated over a day or over the growing season from A without depended on the value of the kinetic time constant (τ), suggesting that τ is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.

Water scarcity and the increasing severity of water deficit stress are major challenges to sustaining irrigated rice (Oryza sativa) production. Despite the technologies developed to reduce the water requirement, rice growth is seriously constrained under water deficit stress compared with other dryland cereals such as wheat (Triticum aestivum). We exposed rice cultivars with contrasting responses to water deficit stress and wheat cultivars well adapted to water-limited conditions to the same moisture stress during vegetative growth to unravel the whole-plant (shoot and root morphology) and organ/tissue (root anatomy) responses. Wheat cultivars followed a water-conserving strategy by reducing specific leaf area and developing thicker roots and moderate tillering. In contrast, rice 'IR64' and 'Apo' adopted a rapid water acquisition strategy through thinner roots under water deficit stress. Root diameter, stele and xylem diameter, and xylem number were more responsive and varied with different positions along the nodal root under water deficit stress in wheat, whereas they were relatively conserved in rice cultivars. Increased metaxylem diameter and lower metaxylem number near the root tips and exactly the opposite phenomena at the rootshoot junction facilitated the efficient use of available soil moisture in wheat. Tolerant rice 'Nagina 22' had an advantage in root morphological and anatomical attributes over cultivars IR64 and Apo but lacked plasticity, unlike wheat cultivars exposed to water deficit stress. The key traits determining the adaptation of wheat to dryland conditions have been summarized and discussed.

Elucidating the genetic control of rooting behavior under water-deficit stress is essential to breed climate-robust rice (Oryza sativa) cultivars. Using a diverse panel of 274 indica genotypes grown under control and water-deficit conditions during vegetative growth, we phenotyped 35 traits, mostly related to root morphology and anatomy, involving 45,000 root-scanning images and nearly 25,000 cross sections from the root-shoot junction. The phenotypic plasticity of these traits was quantified as the relative change in trait value under water-deficit compared with control conditions. We then carried out a genome-wide association analysis on these traits and their plasticity, using 45,608 high-quality single-nucleotide polymorphisms. One hundred four significant loci were detected for these traits under control conditions, 106 were detected under water-deficit stress, and 76 were detected for trait plasticity. We predicted 296 (control), 284 (water-deficit stress), and 233 (plasticity) a priori candidate genes within linkage disequilibrium blocks for these loci. We identified key a priori candidate genes regulating root growth and development and relevant alleles that, upon validation, can help improve rice adaptation to water-deficit stress.

Predicting the consequences of manipulating genotype (G) and agronomic management (M) on agricultural ecosystem performances under future environmental (E) conditions remains a challenge. Crop modelling has the potential to enable society to assess the efficacy of G × M technologies to mitigate and adapt crop production systems to climate change. Despite recent achievements, dedicated research to develop and improve modelling capabilities from gene to global scales is needed to provide guidance on designing G × M adaptation strategies with full consideration of their impacts on both crop productivity and ecosystem sustainability under varying climatic conditions. Opportunities to advance the multiscale crop modelling framework include representing crop genetic traits, interfacing crop models with large-scale models, improving the representation of physiological responses to climate change and management practices, closing data gaps and harnessing multisource data to improve model predictability and enable identification of emergent relationships. A fundamental challenge in multiscale prediction is the balance between process details required to assess the intervention and predictability of the system at the scales feasible to measure the impact. An advanced multiscale crop modelling framework will enable a gene-to-farm design of resilient and sustainable crop production systems under a changing climate at regional-to-global scales. Climate change will not only challenge current crop modeling techniques, but require new types of models that can account for and operate at multiple scales to measure adaptation and resilience.