Acclimation of leaf nitrogen to vertical light gradient at anthesis in wheat is a whole-plant process that scales with the size of the canopy

The Dissection of Nitrogen Response Traits Using Drone Phenotyping and Dynamic Phenotypic Analysis to Explore N Responsiveness and Associated Genetic Loci in Wheat

Inefficient nitrogen (N) utilization in agricultural production has led to many negative impacts such as excessive use of N fertilizers, redundant plant growth, greenhouse gases, long-lasting toxicity in ecosystem, and even effect on human health, indicating the importance to optimize N applications in cropping systems. Here, we present a multiseasonal study that focused on measuring phenotypic changes in wheat plants when they were responding to different N treatments under field conditions. Powered by drone-based aerial phenotyping and the AirMeasurer platform, we first quantified 6 N response-related traits as targets using plot-based morphological, spectral, and textural signals collected from 54 winter wheat varieties. Then, we developed dynamic phenotypic analysis using curve fitting to establish profile curves of the traits during the season, which enabled us to compute static phenotypes at key growth stages and dynamic phenotypes (i.e., phenotypic changes) during N response. After that, we combine 12 yield production and N-utilization indices manually measured to produce N efficiency comprehensive scores (NECS), based on which we classified the varieties into 4 N responsiveness (i.e., N-dependent yield increase) groups. The NECS ranking facilitated us to establish a tailored machine learning model for N responsiveness-related varietal classification just using N-response phenotypes with high accuracies. Finally, we employed the Wheat55K SNP Array to map single-nucleotide polymorphisms using N response-related static and dynamic phenotypes, helping us explore genetic components underlying N responsiveness in wheat. In summary, we believe that our work demonstrates valuable advances in N response-related plant research, which could have major implications for improving N sustainability in wheat breeding and production.

Identification of photosynthetic parameters for superior yield of two super hybrid rice varieties: A cross-scale study from leaf to canopy

Enhancing photosynthetic capacity is widely accepted as critical to advancing crop yield. Therefore, identifying photosynthetic parameters positively related to biomass accumulation in elite cultivars is the major focus of current rice research. In this work, we assessed leaf photosynthetic performance, canopy photosynthesis, and yield attributes of super hybrid rice cultivars Y-liangyou 3218 (YLY3218) and Y-liangyou 5867 (YLY5867) at tillering stage and flowering stage, using inbred super rice cultivars Zhendao11(ZD11) and Nanjing 9108 (NJ9108) as control. A diurnal canopy photosynthesis model was applied to estimate the influence of key environmental factors, canopy attributes, and canopy nitrogen status on daily aboveground biomass increment (AM_DAY). Results showed that primarily the light-saturated photosynthetic rate at tillering stage contributed to the advancing yield and biomass of super hybrid rice in comparison to inbred super rice, and the light-saturated photosynthetic rate between them was similar at flowering stage. At tillering stage, the higher CO₂ diffusion capacity, together with higher biochemical capacity (i.e., maximum carboxylation rate of Rubisco, maximum electron transport rate (J _max), and triose phosphate utilization rate) favored leaf photosynthesis of super hybrid rice. Similarly, AM_DAY in super hybrid rice was higher than inbred super rice at tillering stage, and comparable at flowering stage partially due to increased canopy nitrogen concentration (SLN_ave) of inbred super rice. At tillering stage, model simulation revealed that replacement of J _max and g _m in inbred super rice by super hybrid rice always had a positive effect on AM_DAY, and the averaged AM_DAY increment was 5.7% and 3.4%, respectively. Simultaneously, the 20% enhancement of total canopy nitrogen concentration through the improvement of SLN_ave (TNC-SLN_ave) resulted in the highest AM_DAY across cultivars, with an average increase of 11.2%. In conclusion, the advancing yield performance of YLY3218 and YLY5867 was due to the higher J _max and g _m at tillering stage, and TCN-SLN_ave is a promising target for future super rice breeding programs.

Enhancing crop yields through improvements in the efficiency of photosynthesis and respiration

The rate with which crop yields per hectare increase each year is plateauing at the same time that human population growth and other factors increase food demand. Increasing yield potential (Y p ) of crops is vital to address these challenges. In this review, we explore a component ofY p that has yet to be optimised - that being improvements in the efficiency with which light energy is converted into biomass (ε c ) via modifications to CO2 fixed per unit quantum of light (α), efficiency of respiratory ATP production (ε prod ) and efficiency of ATP use (ε use ). For α, targets include changes in photoprotective machinery, ribulose bisphosphate carboxylase/oxygenase kinetics and photorespiratory pathways. There is also potential forε prod to be increased via targeted changes to the expression of the alternative oxidase and mitochondrial uncoupling pathways. Similarly, there are possibilities to improveε use via changes to the ATP costs of phloem loading, nutrient uptake, futile cycles and/or protein/membrane turnover. Recently developed high-throughput measurements of respiration can serve as a proxy for the cumulative energy cost of these processes. There are thus exciting opportunities to use our growing knowledge of factors influencing the efficiency of photosynthesis and respiration to create a step-change in yield potential of globally important crops.

A model-guided holistic review of exploiting natural variation of photosynthesis traits in crop improvement

Breeding for improved leaf photosynthesis is considered as a viable approach to increase crop yield. Whether it should be improved in combination with other traits has not been assessed critically. Based on the quantitative crop model GECROS that interconnects various traits to crop productivity, we review natural variation in relevant traits, from biochemical aspects of leaf photosynthesis to morpho-physiological crop characteristics. While large phenotypic variations (sometimes >2-fold) for leaf photosynthesis and its underlying biochemical parameters were reported, few quantitative trait loci (QTL) were identified, accounting for a small percentage of phenotypic variation. More QTL were reported for sink size (that feeds back on photosynthesis) or morpho-physiological traits (that affect canopy productivity and duration), together explaining a much greater percentage of their phenotypic variation. Traits for both photosynthetic rate and sustaining it during grain filling were strongly related to nitrogen-related traits. Much of the molecular basis of known photosynthesis QTL thus resides in genes controlling photosynthesis indirectly. Simulation using GECROS demonstrated the overwhelming importance of electron transport parameters, compared with the maximum Rubisco activity that largely determines the commonly studied light-saturated photosynthetic rate. Exploiting photosynthetic natural variation might significantly improve crop yield if nitrogen uptake, sink capacity, and other morpho-physiological traits are co-selected synergistically.

Breeding effects on canopy light attenuation in maize: a retrospective and prospective analysis

The light attenuation process within a plant canopy defines energy capture and vertical distribution of light and nitrogen (N). The vertical light distribution can be quantitatively described with the extinction coefficient (k), which associates the fraction of intercepted photosynthetically active radiation (fPARi) with the leaf area index (LAI). Lower values of k correspond to upright leaves and homogeneous vertical light distribution, increasing radiation use efficiency (RUE). Yield gains in maize (Zea mays L.) were accompanied by increases in optimum plant density and leaf erectness. Thus, the yield-driven breeding programs and management changes, such as reduced row spacing, selected a more erect leaf habit under different maize production systems (e.g., China and the USA). In this study, data from Argentina revealed that k decreased at a rate of 1.1% year-1 since 1989, regardless of plant density and in agreement with Chinese reports (1.0% year-1 since 1981). A reliable assessment of changes in k over time is critical for predicting (i) modifications in resource use efficiency (e.g. radiation, water, and N), improving estimations derived from crop simulation models; (ii) differences in productivity caused by management practices; and (iii) limitations to further exploit this trait with breeding.

Mineralisation of catch crop residues and N transfer to the subsequent crop

Catch crops (CC) are widely used to reduce nitrogen leaching from arable cropping systems. However, the mineralisation rate of different catch crop species, and the fate of the mineralised N remain unclear. In this study, we performed an analysis, based on N mineralisation incubation experiments, to test and parameterise a simple mineralisation model (SMM), based on a first order decay, for different catch crops. For brassicas and legumes, the C:N was confirmed to be a good predictor of both, the amount and rate of mineral N release of CC residues. For grasses, the mineralisation rate could not be well predicted by the C:N, which might partly be due to a very limited dataset. The SMM was then linked with the Agricultural Production Simulator (APSIM) and used to predict the N release from CC residues of either brassicas or legumes, and its fate, including N leaching and N uptake by a subsequent spring barley (SB) crop. APSIM simulations were set up for a period of 20 years and for two sites with different temperature and soil conditions in North-West Europe, Foulum in Denmark and Kiel, Germany. Simulated N uptake by the CC was higher in Kiel compared with Foulum, with an average of 14.8 kg/ha for the crucifers and 16.8 kg/ha for the legume in Foulum, and of 33.2 kg/ha for the crucifers and 51.4 kg/ha for the legume in Kiel. CC increased yield of SB on average by 5 to 7%, due to transfer of N. This N transfer resulted in an average reduction in N leaching by 59% (brassica) and by 43% (legume) in Foulum, and by 83% (brassica) and by 43% (legume) in Kiel. N fertilisation of CC is not of any benefit in most of the 20 years of simulation.

A genome‐wide analysis suggests pleiotropic effects of Green Revolution genes on shade avoidance in wheat

A classic example of phenotypic plasticity in plants is the suit of phenotypic responses induced by a change in the ratio of red to far-red light (R∶FR) as a result of shading, also known as the shade avoidance syndrome (SAS). While the adaptive consequences of this syndrome have been extensively discussed in natural ecosystems, how SAS varies within crop populations and how SAS evolved during crop domestication and breeding remain poorly known. In this study, we grew a panel of 180 durum wheat (Triticum turgidum ssp. durum) genotypes spanning diversity from wild, early domesticated, and elite genetic compartments under two light treatments: low R:FR light (shaded treatment) and high R:FR light (unshaded treatment). We first quantified the genetic variability of SAS, here measured as a change in plant height at the seedling stage. We then dissected the genetic basis of this variation through genome-wide association mapping. Genotypes grown in shaded conditions were taller than those grown under unshaded conditions. Interaction between light quality and genotype did not affect plant height. We found six QTLs affecting plant height. Three significantly interacted with light quality among which the well-known Rht1 gene introgressed in elite germplasm during the Green Revolution. Interestingly at three loci, short genotypes systematically expressed reduced SAS, suggesting a positive genetic correlation between plant height and plant height plasticity. Overall, our study sheds light on the evolutionary history of crops and illustrates the relevance of genetic approaches to tackle agricultural challenges.

Effect of Various Mulch Materials on Chemical Properties of Soil, Leaves and Shoot Characteristics in Dendrocalamus Latiflorus Munro Forests

The effectiveness of mulch treatments on soil quality as well as on the yield and growth rates of bamboo are major considerations and require further attention. The present work was aimed at assessing the impacts of three different mulch materials on soil available nutrients, biochemical traits, and growth patterns of Dendrocalamus latiflorus Munro. We found that relative to the control (CK), bamboo leaves (MB) and organic fertilizers (MF) treatments significantly (P < 0.05) increased the number of bamboo shoots (47.5 and 22.7%) and yield (21.4 and 9.1%), respectively. We observed that under MB and MF treatments, the concentrations of soil available nutrients (nitrogen, phosphorus, and potassium) increased and played a key role in the differences in chlorophyll, leaf carbohydrate contents (soluble sugar and starch) and were essential to promote bamboo shoot development. Furthermore, we infer from principal component analysis (PCA), that both MB and MF appear to be a better choice than rice husks (MR) to improve nutrient availability, biochemical traits of the leaves, and increased bamboo shoot productivity. Consequently, we suggest using organic fertilizers and bamboo leaves as mulch materials are effective for soil conservation to attain high-quality bamboo production.

Importance of the description of light interception in crop growth models

Canopy light interception determines the amount of energy captured by a crop, and is thus critical to modeling crop growth and yield, and may substantially contribute to the prediction uncertainty of crop growth models (CGMs). We thus analyzed the canopy light interception models of the 26 wheat (Triticum aestivum) CGMs used by the Agricultural Model Intercomparison and Improvement Project (AgMIP). Twenty-one CGMs assume that the light extinction coefficient (K) is constant, varying from 0.37 to 0.80 depending on the model. The other models take into account the illumination conditions and assume either that all green surfaces in the canopy have the same inclination angle (θ) or that θ distribution follows a spherical distribution. These assumptions have not yet been evaluated due to a lack of experimental data. Therefore, we conducted a field experiment with five cultivars with contrasting leaf stature sown at normal and double row spacing, and analyzed θ distribution in the canopies from three-dimensional canopy reconstructions. In all the canopies, θ distribution was well represented by an ellipsoidal distribution. We thus carried out an intercomparison between the light interception models of the AgMIP-Wheat CGMs ensemble and a physically based K model with ellipsoidal leaf angle distribution and canopy clumping (KellC). Results showed that the KellC model outperformed current approaches under most illumination conditions and that the uncertainty in simulated wheat growth and final grain yield due to light models could be as high as 45%. Therefore, our results call for an overhaul of light interception models in CGMs.

Genetic regulation of the traits contributing to wheat nitrogen use efficiency

High nitrogen application aimed at increasing crop yield is offset by higher production costs and negative environmental consequences. For wheat, only one third of the applied nitrogen is utilized, which indicates there is scope for increasing Nitrogen Use Efficiency (NUE). However, achieving greater NUE is challenged by the complexity of the trait, which comprises processes associated with nitrogen uptake, transport, reduction, assimilation, translocation and remobilization. Thus, knowledge of the genetic regulation of these processes is critical in increasing NUE. Although primary nitrogen uptake and metabolism-related genes have been well studied, the relative influence of each towards NUE is not fully understood. Recent attention has focused on engineering transcription factors and identification of miRNAs acting on expression of specific genes related to NUE. Knowledge obtained from model species needs to be translated into wheat using recently-released whole genome sequences, and by exploring genetic variations of NUE-related traits in wild relatives and ancient germplasm. Recent findings indicate the genetic basis of NUE is complex. Pyramiding various genes will be the most effective approach to achieve a satisfactory level of NUE in the field.

Biochemical and Genetic Approaches Improving Nitrogen Use Efficiency in Cereal Crops: A Review

Nitrogen is an essential nutrient required in large quantities for the proper growth and development of plants. Nitrogen is the most limiting macronutrient for crop production in most of the world's agricultural areas. The dynamic nature of nitrogen and its tendency to lose soil and environment systems create a unique and challenging environment for its proper management. Exploiting genetic diversity, developing nutrient efficient novel varieties with better agronomy and crop management practices combined with improved crop genetics have been significant factors behind increased crop production. In this review, we highlight the various biochemical, genetic factors and the regulatory mechanisms controlling the plant nitrogen economy necessary for reducing fertilizer cost and improving nitrogen use efficiency while maintaining an acceptable grain yield.

Experiments for in silico evaluation of Optimality of Photosynthetic Nitrogen Distribution and Partitioning in the Canopy: an Example Using Greenhouse Cucumber Plants

Acclimation of leaf traits to fluctuating environments is a key mechanism to maximize fitness. One of the most important strategies in acclimation to changing light is to maintain efficient utilization of nitrogen in the photosynthetic apparatus by continuous modifications of between-leaf distribution along the canopy depth and within-leaf partitioning between photosynthetic functions according to local light availability. Between-leaf nitrogen distribution has been intensively studied over the last three decades, where proportional coordination between nitrogen concentration and light gradient was considered optimal in terms of maximizing canopy photosynthesis, without taking other canopy structural and physiological factors into account. We proposed a mechanistic model of protein turnover dynamics in different photosynthetic functions, which can be parameterized using leaves grown under different levels of constant light. By integrating this dynamic model into a multi-layer canopy model, constructed using data collected from a greenhouse experiment, it allowed us to test in silico the degree of optimality in photosynthetic nitrogen use for maximizing canopy carbon assimilation under given light environments.

Genetic and environmental dissection of biomass accumulation in multi-genotype maize canopies

Multi-genotype canopies are frequent in phenotyping experiments and are of increasing interest in agriculture. Radiation interception efficiency (RIE) and radiation use efficiency (RUE) have low heritabilities in such canopies. We propose a revised Monteith equation that identifies environmental and genetic components of RIE and RUE. An environmental term, a component of RIE, characterizes the effect of the presence or absence of neighbours on light interception. The ability of a given plant to compete with its neighbours is then identified, which accounts for the genetic variability of RIE of plants having similar leaf areas. This method was used in three experiments in a phenotyping platform with 765 plants of 255 maize hybrids. As expected, the heritability of the environmental term was near zero, whereas that of the competitiveness term increased with phenological stage, resulting in the identification of quantitative trait loci. In the same way, RUE was dissected as an effect of intercepted light and a genetic term. This approach was used for predicting the behaviour of individual genotypes in virtual multi-genotype canopies. A large effect of competitiveness was observed in multi-genotype but not in single-genotype canopies, resulting in a bias for genotype comparisons in breeding fields.

Environmental triggers for photosynthetic protein turnover determine the optimal nitrogen distribution and partitioning in the canopy

Plants continually adjust the photosynthetic functions in their leaves to fluctuating light, thereby optimizing the use of photosynthetic nitrogen (Nph) at the canopy level. To investigate the complex interplay between external signals during the acclimation processes, a mechanistic model based on the concept of protein turnover (synthesis and degradation) was proposed and parameterized using cucumber grown under nine combinations of nitrogen and light in growth chambers. Integrating this dynamic model into a multi-layer canopy model provided accurate predictions of photosynthetic acclimation of greenhouse cucumber canopies grown under high and low nitrogen supply in combination with day-to-day fluctuations in light at two different levels. This allowed us to quantify the degree of optimality in canopy nitrogen use for maximizing canopy carbon assimilation, which was influenced by Nph distribution along canopy depth or Nph partitioning between functional pools. Our analyses suggest that Nph distribution is close to optimum and Nph reallocation is more important under low nitrogen. Nph partitioning is only optimal under a light level similar to the average light intensity during acclimation, meaning that day-to-day light fluctuations inevitably result in suboptimal Nph partitioning. Our results provide insights into photoacclimation and can be applied to crop model improvement.

Water- and Nitrogen-Use Efficiencies of Hemp (Cannabis sativa L.) Based on Whole-Canopy Measurements and Modeling

Interest in hemp (Cannabis sativa L.) as a crop for the biobased economy is growing worldwide because hemp produces a high and valuable biomass while requiring low inputs. To understand the physiological basis of hemp's resource-use efficiency, canopy gas exchange was assessed using a chamber technique on canopies exposed to a range of nitrogen (N) and water levels. Since canopy transpiration and carbon assimilation were very sensitive to variations in microclimate among canopy chambers, observations were adjusted for microclimatic differences using a physiological canopy model, with leaf-level parameters estimated for hemp from our previous study. Canopy photosynthetic water-use efficiency (PWUEc), defined as the ratio of gross canopy photosynthesis to canopy transpiration, ranged from 4.0 mmol CO2 (mol H2O)-1 to 7.5 mmol CO2 (mol H2O)-1. Canopy photosynthetic nitrogen-use efficiency (PNUEc), the ratio of the gross canopy photosynthesis to canopy leaf-N content, ranged from 0.3 mol CO2 d-1 (g N)-1 to 0.7 mol CO2 d-1 (g N)-1. The effect of N-input levels on PWUEc and PNUEc was largely determined by the N effect on canopy size or leaf area index (LAI), whereas the effect of water-input levels differed between short- and long-term stresses. The effect of short-term water stress was reflected by stomatal regulation. The long-term stress increased leaf senescence, decreased LAI but retained total canopy N content; however, the increased average leaf-N could not compensate for the lost LAI, leading to a decreased PNUEc. Although hemp is known as a resource-use efficient crop, its final biomass yield and nitrogen use efficiency may be restricted by water limitation during growth. Our results also suggest that crop models should take stress-induced senescence into account in addition to stomatal effects if crops experience a prolonged water stress during growth.

Chlorophyll Can Be Reduced in Crop Canopies with Little Penalty to Photosynthesis

The hypothesis that reducing chlorophyll content (Chl) can increase canopy photosynthesis in soybeans was tested using an advanced model of canopy photosynthesis. The relationship among leaf Chl, leaf optical properties, and photosynthetic biochemical capacity was measured in 67 soybean (Glycine max) accessions showing large variation in leaf Chl. These relationships were integrated into a biophysical model of canopy-scale photosynthesis to simulate the intercanopy light environment and carbon assimilation capacity of canopies with wild type, a Chl-deficient mutant (Y11y11), and 67 other mutants spanning the extremes of Chl to quantify the impact of variation in leaf-level Chl on canopy-scale photosynthetic assimilation and identify possible opportunities for improving canopy photosynthesis through Chl reduction. These simulations demonstrate that canopy photosynthesis should not increase with Chl reduction due to increases in leaf reflectance and nonoptimal distribution of canopy nitrogen. However, similar rates of canopy photosynthesis can be maintained with a 9% savings in leaf nitrogen resulting from decreased Chl. Additionally, analysis of these simulations indicate that the inability of Chl reductions to increase photosynthesis arises primarily from the connection between Chl and leaf reflectance and secondarily from the mismatch between the vertical distribution of leaf nitrogen and the light absorption profile. These simulations suggest that future work should explore the possibility of using reduced Chl to improve canopy performance by adapting the distribution of the "saved" nitrogen within the canopy to take greater advantage of the more deeply penetrating light.

Suboptimal Acclimation of Photosynthesis to Light in Wheat Canopies

Photosynthetic acclimation (photoacclimation) is the process whereby leaves alter their morphology and/or biochemistry to optimize photosynthetic efficiency and productivity according to long-term changes in the light environment. The three-dimensional architecture of plant canopies imposes complex light dynamics, but the drivers for photoacclimation in such fluctuating environments are poorly understood. A technique for high-resolution three-dimensional reconstruction was combined with ray tracing to simulate a daily time course of radiation profiles for architecturally contrasting field-grown wheat (Triticum aestivum) canopies. An empirical model of photoacclimation was adapted to predict the optimal distribution of photosynthesis according to the fluctuating light patterns throughout the canopies. While the photoacclimation model output showed good correlation with field-measured gas-exchange data at the top of the canopy, it predicted a lower optimal light-saturated rate of photosynthesis at the base. Leaf Rubisco and protein contents were consistent with the measured optimal light-saturated rate of photosynthesis. We conclude that, although the photosynthetic capacity of leaves is high enough to exploit brief periods of high light within the canopy (particularly toward the base), the frequency and duration of such sunflecks are too small to make acclimation a viable strategy in terms of carbon gain. This suboptimal acclimation renders a large portion of residual photosynthetic capacity unused and reduces photosynthetic nitrogen use efficiency at the canopy level, with further implications for photosynthetic productivity. It is argued that (1) this represents an untapped source of photosynthetic potential and (2) canopy nitrogen could be lowered with no detriment to carbon gain or grain protein content.

A Model of Leaf Coordination to Scale-Up Leaf Expansion from the Organ to the Canopy

Process-based crop growth models are popular tools with which to analyze and understand the impact of crop management, genotype-by-environment interactions, or climate change. The ability to predict leaf area development is critical to predict crop growth, particularly under conditions of limited resources. Here, we aimed at deciphering growth coordination rules between wheat (Triticum aestivum) plant organs (i.e. between leaves within a stem, between laminae and sheaths, and between the mainstem and axillary tillers) to model the dynamics of canopy development. We found a unique relationship between laminae area and leaf rank for the mainstem and its tillers, which was robust across a range of sowing dates and plant densities. Robust relationships between laminae and sheath areas also were found, highlighting the tight control of organ growth within and between phytomers. These relationships identified at the phytomer scale were used to develop a simulation model of leaf area dynamics at the canopy level that was integrated in the wheat model SiriusQuality. The model was then evaluated using several independent experiments. The model accurately predicts leaf area dynamics under different scenarios of nitrogen and water limitations. It accounted for 85%, 64%, and 73% of the variability of the surface area of leaf cohorts, total leaf area index, and total green area index, respectively. The process-based model of the dynamics of leaf area described here is a key element to quantify the value of candidate traits for use in plant breeding and to project the impact of climate change on wheat growth.

The impact of modifying photosystem antenna size on canopy photosynthetic efficiency-Development of a new canopy photosynthesis model scaling from metabolism to canopy level processes

Canopy photosynthesis (Ac ) describes photosynthesis of an entire crop field and the daily and seasonal integrals of Ac positively correlate with daily and seasonal biomass production. Much effort in crop breeding has focused on improving canopy architecture and hence light distribution inside the canopy. Here, we develop a new integrated canopy photosynthesis model including canopy architecture, a ray tracing algorithm, and C3 photosynthetic metabolism to explore the option of manipulating leaf chlorophyll concentration ([Chl]) for greater Ac and nitrogen use efficiency (NUE). Model simulation results show that (a) efficiency of photosystem II increased when [Chl] was decreased by decreasing antenna size and (b) the light received by leaves at the bottom layers increased when [Chl] throughout the canopy was decreased. Furthermore, the modelling revealed a modest ~3% increase in Ac and an ~14% in NUE was accompanied when [Chl] reduced by 60%. However, if the leaf nitrogen conserved by this decrease in leaf [Chl] were to be optimally allocated to other components of photosynthesis, both Ac and NUE can be increased by over 30%. Optimizing [Chl] coupled with strategic reinvestment of conserved nitrogen is shown to have the potential to support substantial increases in Ac , biomass production, and crop yields.

Two-Dimensional Visualization of Nitrogen Distribution in Leaves of Chinese Cabbage (Brassica rapa subsp. chinensis) by the Fourier Transform Infrared Photoacoustic Spectroscopy Technique

Understanding nitrogen (N) status in the leaves of Chinese cabbage (Brassica rapa subsp. chinensis) is of significance to both vegetable growth and quality control. Fourier transform infrared photoacoustic spectroscopy was used to perform rapid qualification of N distribution in leaves; a partial least squares algorithm was used to develop a model for prediction of the N content; and N distribution in individual leaves was mapped on the basis of interpolation analysis, which was found to be variable. A reasonable N input level (13 mmol L^-1 N) showed the largest variance of the N content, benefiting N redistribution and use efficiency, but variance decreased at the old stage. Moreover, the pattern of N distribution within a leaf was irregular even among the replications performed for each treatment, and sunlight was found to be the dominant factor as a result of leaves receiving variable light intensities.

High-throughput estimation of incident light, light interception and radiation-use efficiency of thousands of plants in a phenotyping platform

Light interception and radiation-use efficiency (RUE) are essential components of plant performance. Their genetic dissections require novel high-throughput phenotyping methods. We have developed a suite of methods to evaluate the spatial distribution of incident light, as experienced by hundreds of plants in a glasshouse, by simulating sunbeam trajectories through glasshouse structures every day of the year; the amount of light intercepted by maize (Zea mays) plants via a functional-structural model using three-dimensional (3D) reconstructions of each plant placed in a virtual scene reproducing the canopy in the glasshouse; and RUE, as the ratio of plant biomass to intercepted light. The spatial variation of direct and diffuse incident light in the glasshouse (up to 24%) was correctly predicted at the single-plant scale. Light interception largely varied between maize lines that differed in leaf angles (nearly stable between experiments) and area (highly variable between experiments). Estimated RUEs varied between maize lines, but were similar in two experiments with contrasting incident light. They closely correlated with measured gas exchanges. The methods proposed here identified reproducible traits that might be used in further field studies, thereby opening up the way for large-scale genetic analyses of the components of plant performance.

A meta-analysis of leaf nitrogen distribution within plant canopies

BACKGROUND AND AIMS

Leaf nitrogen distribution in the plant canopy is an important determinant for canopy photosynthesis. Although the gradient of leaf nitrogen is formed along light gradients in the canopy, its quantitative variations among species and environmental responses remain unknown. Here, we conducted a global meta-analysis of leaf nitrogen distribution in plant canopies.

METHODS

We collected data on the nitrogen distribution and environmental variables from 393 plant canopies (100, 241 and 52 canopies for wheat, other herbaceous and woody species, respectively).

KEY RESULTS

The trends were clearly different between wheat and other species; the photosynthetic nitrogen distribution coefficient (Kb) was mainly determined by leaf area index (LAI) in wheat, whereas it was correlated with the light extinction coefficient (KL) and LAI in other species. Some other variables were also found to influence Kb We present the best equations for Kb as a function of environmental variables and canopy characteristics. As a more simple function, Kb = 0·5KL can be used for canopies of species other than wheat. Sensitivity analyses using a terrestrial carbon flux model showed that gross primary production tended to be more sensitive to the Kb value especially when nitrogen content of the uppermost leaf was fixed.

CONCLUSION

Our results reveal that nitrogen distribution is mainly driven by the vertical light gradient but other factors such as LAI also have significant effects. Our equations contribute to an improvement in the projection of plant productivity and cycling of carbon and nitrogen in terrestrial ecosystems.

Optimality of nitrogen distribution among leaves in plant canopies

The vertical gradient of the leaf nitrogen content in a plant canopy is one of the determinants of vegetation productivity. The ecological significance of the nitrogen distribution in plant canopies has been discussed in relation to its optimality; nitrogen distribution in actual plant canopies is close to but always less steep than the optimal distribution that maximizes canopy photosynthesis. In this paper, I review the optimality of nitrogen distribution within canopies focusing on recent advancements. Although the optimal nitrogen distribution has been believed to be proportional to the light gradient in the canopy, this rule holds only when diffuse light is considered; the optimal distribution is steeper when the direct light is considered. A recent meta-analysis has shown that the nitrogen gradient is similar between herbaceous and tree canopies when it is expressed as the function of the light gradient. Various hypotheses have been proposed to explain why nitrogen distribution is suboptimal. However, hypotheses explain patterns observed in some specific stands but not in others; there seems to be no general hypothesis that can explain the nitrogen distributions under different conditions. Therefore, how the nitrogen distribution in canopies is determined remains open for future studies; its understanding should contribute to the correct prediction and improvement of plant productivity under changing environments.

Constraints to the potential efficiency of converting solar radiation into phytoenergy in annual crops: from leaf biochemistry to canopy physiology and crop ecology

A new simple framework was proposed to quantify the efficiency of converting incoming solar radiation into phytoenergy in annual crops. It emphasizes the need to account for (i) efficiency gain when scaling up from the leaf level to the canopy level, and (ii) efficiency loss due to incomplete canopy closure during early and late phases of the crop cycle. Equations are given to estimate losses due to the constraints in various biochemical or physiological steps. For a given amount of daily radiation, a longer daytime was shown to increase energy use efficiency, because of the convex shape of the photosynthetic light response. Due to the higher cyclic electron transport, C4 leaves were found to have a lower energy loss via non-photochemical quenching, compared with C3 leaves. This contributes to the more linear light response in C4 than in C3 photosynthesis. Because of this difference in the curvature of the light response, canopy-to-leaf photosynthesis ratio, benefit from the optimum acclimation of the leaf nitrogen profile in the canopy, and productivity gain from future improvements in leaf photosynthetic parameters and canopy architecture were all shown to be higher in C3 than in C4 species. The indicative efficiency of converting incoming solar radiation into phytoenergy is ~2.2 and 3.0% in present C3 and C4 crops, respectively, when grown under well-managed conditions. An achievable efficiency via future genetic improvement was estimated to be as high as 3.6 and 4.1% for C3 and C4 crops, respectively.

An empirical model that uses light attenuation and plant nitrogen status to predict within-canopy nitrogen distribution and upscale photosynthesis from leaf to whole canopy

Modelling the spatial and temporal distribution of leaf nitrogen (N) is central to specify photosynthetic parameters and simulate canopy photosynthesis. Leaf photosynthetic parameters depend on both local light availability and whole-plant N status. The interaction between these two levels of integration has generally been modelled by assuming optimal canopy functioning, which is not supported by experiments. During this study, we examined how a set of empirical relationships with measurable parameters could be used instead to predict photosynthesis at the leaf and whole-canopy levels. The distribution of leaf N per unit area (Na) within the canopy was related to leaf light irradiance and to the nitrogen nutrition index (NNI), a whole-plant variable accounting for plant N status. Na was then used to determine the photosynthetic parameters of a leaf gas exchange model. The model was assessed on alfalfa canopies under contrasting N nutrition and with N2-fixing and non-fixing plants. Three experiments were carried out to parameterize the relationships between Na, leaf irradiance, NNI and photosynthetic parameters. An additional independent data set was used for model evaluation. The N distribution model showed that it was able to predict leaf N on the set of leaves tested. The Na at the top of the canopy appeared to be related linearly to the NNI, whereas the coefficient accounting for N allocation remained constant. Photosynthetic parameters were related linearly to Na irrespective of N nutrition and the N acquisition mode. Daily patterns of gas exchange were simulated accurately at the leaf scale. When integrated at the whole-canopy scale, the model predicted that raising N availability above an NNI of 1 did not result in increased net photosynthesis. Overall, the model proposed offered a solution for a dynamic coupling of leaf photosynthesis and canopy N distribution without requiring any optimal functioning hypothesis.

In silico system analysis of physiological traits determining grain yield and protein concentration for wheat as influenced by climate and crop management

Genetic improvement of grain yield (GY) and grain protein concentration (GPC) is impeded by large genotype×environment×management interactions and by compensatory effects between traits. Here global uncertainty and sensitivity analyses of the process-based wheat model SiriusQuality2 were conducted with the aim of identifying candidate traits to increase GY and GPC. Three contrasted European sites were selected and simulations were performed using long-term weather data and two nitrogen (N) treatments in order to quantify the effect of parameter uncertainty on GY and GPC under variable environments. The overall influence of all 75 plant parameters of SiriusQuality2 was first analysed using the Morris method. Forty-one influential parameters were identified and their individual (first-order) and total effects on the model outputs were investigated using the extended Fourier amplitude sensitivity test. The overall effect of the parameters was dominated by their interactions with other parameters. Under high N supply, a few influential parameters with respect to GY were identified (e.g. radiation use efficiency, potential duration of grain filling, and phyllochron). However, under low N, >10 parameters showed similar effects on GY and GPC. All parameters had opposite effects on GY and GPC, but leaf and stem N storage capacity appeared as good candidate traits to change the intercept of the negative relationship between GY and GPC. This study provides a system analysis of traits determining GY and GPC under variable environments and delivers valuable information to prioritize model development and experimental work.

Nitrogen stress affects the turnover and size of nitrogen pools supplying leaf growth in a grass

The effect of nitrogen (N) stress on the pool system supplying currently assimilated and (re)mobilized N for leaf growth of a grass was explored by dynamic ¹⁵N labeling, assessment of total and labeled N import into leaf growth zones, and compartmental analysis of the label import data. Perennial ryegrass (Lolium perenne) plants, grown with low or high levels of N fertilization, were labeled with ¹⁵NO₃⁻/¹⁴NO₃⁻ from 2 h to more than 20 d. In both treatments, the tracer time course in N imported into the growth zones fitted a two-pool model (r² > 0.99). This consisted of a "substrate pool," which received N from current uptake and supplied the growth zone, and a recycling/mobilizing "store," which exchanged with the substrate pool. N deficiency halved the leaf elongation rate, decreased N import into the growth zone, lengthened the delay between tracer uptake and its arrival in the growth zone (2.2 h versus 0.9 h), slowed the turnover of the substrate pool (half-life of 3.2 h versus 0.6 h), and increased its size (12.4 μg versus 5.9 μg). The store contained the equivalent of approximately 10 times (low N) and approximately five times (high N) the total daily N import into the growth zone. Its turnover agreed with that of protein turnover. Remarkably, the relative contribution of mobilization to leaf growth was large and similar (approximately 45%) in both treatments. We conclude that turnover and size of the substrate pool are related to the sink strength of the growth zone, whereas the contribution of the store is influenced by partitioning between sinks.