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.

A new method to estimate photosynthetic parameters through net assimilation rate-intercellular space CO2 concentration (A-Ci ) curve and chlorophyll fluorescence measurements.

Gas exchange (GE) and chlorophyll fluorescence (CF) measurements are widely used to noninvasively study photosynthetic parameters, for example the rates of maximum Rubisco carboxylation (Vcmax ), electron transport rate (J), daytime respiration (Rd ) and mesophyll conductance (gm ). Existing methods for fitting GE data (net assimilation rate-intercellular space CO2 concentration (A-Ci ) curve) are based on two assumptions: gm is unvaried with CO2 concentration in the intercellular space (Ci ); and light absorption (α) and the proportion of quanta absorbed by photosystem II (ß) are constant in the data set. These may result in significant bias in estimating photosynthetic parameters. To avoid the above-mentioned hypotheses, we present a new method for fitting A-Ci curves and CF data simultaneously. This method was applied to a data set obtained from cucumber (Cucumis sativus) leaves of various leaf ages and grown under eight different light conditions. The new method had significantly lower root mean square error and a lower rate of failures compared with previously published methods (6.72% versus 24.1%, respectively) and the effect of light conditions on Vcmax and J was better observed. Furthermore, the new method allows the estimation of a new parameter, the fraction of incoming irradiance harvested by photosystem II, and the dependence of gm on Ci .

Interspecific variation in leaf traits, photosynthetic light response, and whole-plant productivity in amaranths (Amaranthus spp. L.).

Photosynthetic light response curve parameters help us understand the interspecific variation in photosynthetic traits, leaf acclimation status, carbon uptake, and plant productivity in specific environments. These parameters are also influenced by leaf traits which rely on species and growth environment. In accessions of four amaranth species (Amaranthus. hybridus, A. dubius, A. hypochondriacus, and A. cruentus), we determined variations in the net photosynthetic light response curves and leaf traits, and analysed the relationships between maximum gross photosynthetic rate, leaf traits, and whole-plant productivity. Non-rectangular hyperbolae were used for the net photosynthesis light response curves. Maximum gross photosynthetic rate (Pgmax) was the only variant parameter among the species, ranging from 22.29 to 34.21 µmol m-2 s-1. Interspecific variation existed for all the leaf traits except leaf mass per area and leaf inclination angle. Stomatal conductance, nitrogen, chlorophyll, and carotenoid contents, as well as leaf area correlated with Pgmax. Stomatal conductance and leaf nitrogen explained much of the variation in Pgmax at the leaf level. At the plant level, the slope between absolute growth rate and leaf area showed a strong linear relationship with Pgmax. Overall, A. hybridus and A. cruentus exhibited higher Pgmax at the leaf level and light use efficiency at the whole-plant level than A. dubius, and A. hypochondriacus. Thus, A. hybridus and A. cruentus tended to be more efficient with respect to carbon assimilation. These findings highlight the correlation between leaf photosynthetic characteristics, other leaf traits, and whole plant productivity in amaranths. Future studies may explore more species and accessions of Amaranthus at different locations or light environments.

Physiological and morphological responses of different spring barley genotypes to water deficit and associated QTLs.

Water deficit is one of the major limitations to food production worldwide and most climate change scenarios predict an aggravation of the situation. To face the expected increase in drought stress in the coming years, breeders are working to elucidate the genetic control of barley growth and productivity traits under water deficit. Barley is known as a relatively drought tolerant crop and genetic variability was observed for drought tolerance traits. The objectives of the present study were the quantification of morphological and physiological responses in a collection of 209 spring barley genotypes to drought stress, and the genetic analysis by genome-wide association study to find quantitative trait loci (QTL) and the allele contributions for each of the investigated traits. In six pot experiments, 209 spring barley genotypes were grown under a well-watered and water-limited regime. Stress phases were initiated individually for each genotype at the beginning of tillering and spiking for the vegetative- and the generative stage experiments, respectively, and terminated when the transpiration rates of stress treatments reached 10% of the well-watered control. After the stress phase, a total of 42 productivity related traits such as the dry matter of plant organs, tiller number, leaf length, leaf area, amount of water soluble carbohydrates in the stems, proline content in leaves and osmotic adjustment of corresponding well-watered and stressed plants were analysed, and QTL analyses were performed to find marker-trait associations. Significant water deficit effects were observed for almost all traits and significant genotype x treatment interactions (GxT) were observed for 37 phenotypic traits. Genome-wide association studies (GWAS) revealed 77 significant loci associated with 16 phenotypic traits during the vegetative stage experiment and a total of 85 significant loci associated with 13 phenotypic traits during the generative stage experiment for traits such as leaf area, number of green leaves, grain yield, harvest index and stem length. For traits with significant GxT interactions, genotypic differences for relative values were analysed using one way ANOVA. More than 110 loci for GxT interaction were found for 17 phenotypic traits explaining in many cases more than 50% of the genetic variance.

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.

A Modeling Approach to Quantify the Effects of Stomatal Behavior and Mesophyll Conductance on Leaf Water Use Efficiency.

Water use efficiency (WUE) is considered as a determinant of yield under stress and a component of crop drought resistance. Stomatal behavior regulates both transpiration rate and net assimilation and has been suggested to be crucial for improving crop WUE. In this work, a dynamic model was used to examine the impact of dynamic properties of stomata on WUE. The model includes sub-models of stomatal conductance dynamics, solute accumulation in the mesophyll, mesophyll water content, and water flow to the mesophyll. Using the instantaneous value of stomatal conductance, photosynthesis, and transpiration rate were simulated using a biochemical model and Penman-Monteith equation, respectively. The model was parameterized for a cucumber leaf and model outputs were evaluated using climatic data. Our simulations revealed that WUE was higher on a cloudy than a sunny day. Fast stomatal reaction to light decreased WUE during the period of increasing light (e.g., in the morning) by up to 10.2% and increased WUE during the period of decreasing light (afternoon) by up to 6.25%. Sensitivity of daily WUE to stomatal parameters and mesophyll conductance to CO2 was tested for sunny and cloudy days. Increasing mesophyll conductance to CO2 was more likely to increase WUE for all climatic conditions (up to 5.5% on the sunny day) than modifications of stomatal reaction speed to light and maximum stomatal conductance.

Parameter identification in a tuberculosis model for Cameroon.

A deterministic model of tuberculosis in Cameroon is designed and analyzed with respect to its transmission dynamics. The model includes lack of access to treatment and weak diagnosis capacity as well as both frequency- and density-dependent transmissions. It is shown that the model is mathematically well-posed and epidemiologically reasonable. Solutions are non-negative and bounded whenever the initial values are non-negative. A sensitivity analysis of model parameters is performed and the most sensitive ones are identified by means of a state-of-the-art Gauss-Newton method. In particular, parameters representing the proportion of individuals having access to medical facilities are seen to have a large impact on the dynamics of the disease. The model predicts that a gradual increase of these parameters could significantly reduce the disease burden on the population within the next 15 years.