Characterization of the interactions between architecture and source-sink relationships in winter oilseed rape (Brassica napus) using the GreenLab model.

BACKGROUND AND AIMS: This study aimed to characterize the interaction between architecture and source-sink relationships in winter oilseed rape (WOSR): do the costs of ramification compromise the source-sink ratio during seed filling? The GreenLab model is a good candidate to address this question because it has been already used to describe interactions between source-sink relationships and architecture for other species. However, its adaptation to WOSR is a challenge because of the complexity of its developmental scheme, especially during the reproductive phase. METHODS: Equations were added in GreenLab to compute expansion delays for ramification, flowering of each axis and photosynthesis of pods including the energetic cost of oil synthesis. Experimental field data were used to estimate morphological parameters while source-sink parameters of the model were estimated by adjustment of model outputs to the data. Ecophysiological outputs were used to assess the sources/sink relationships during the whole growth cycle. KEY RESULTS: First results indicated that, at the plant scale, the model correctly simulates the dynamics of organ growth. However, at the organ scale, errors were observed that could be explained either by secondary growth that was not incorporated or by uncertainties in morphological parameters (durations of expansion and life). Ecophysiological outputs highlighted the dramatic negative impact of ramification on the source-sink ratio, as well as the decrease in this ratio during seed filling despite pod envelope photosynthesis that allowed significant biomass production to be maintained. CONCLUSIONS: This work is a promising first step in the construction of a structure-function model for a plant as complex as WOSR. Once tested for other environments and/or genotypes, the model can be used for studies on WOSR architectural plasticity.

To what extent may changes in the root system architecture of Arabidopsis thaliana grown under contrasted homogenous nitrogen regimes be explained by changes in carbon supply? A modelling approach.

Root system architecture adapts to low nitrogen (N) nutrition. Some adaptations may be mediated by modifications of carbon (C) fluxes. The objective of this study was to test the hypothesis that changes in root system architecture under different N regimes may be accounted for by using simple hypotheses of C allocation within the root system of Arabidopsis thaliana. With that purpose, a model during vegetative growth was developed that predicted the main traits of root system architecture (total root length, lateral root number, and specific root length). Different experimental data sets crossing three C levels and two N homogenous nutrition levels were generated. Parameters were estimated from an experiment carried out under medium C and high N conditions. They were then checked under other CxN conditions. It was found that the model was able to simulate correctly C effects on root architecture in both high and low N nutrition conditions, with the same parameter values. It was concluded that C flux modifications explained the major part of root system adaptation to N supply, even if they were not sufficient to simulate some changes, such as specific root length.

Plant response to nitrate starvation is determined by N storage capacity matched by nitrate uptake capacity in two Arabidopsis genotypes.

In a low-input agricultural context, plants facing temporal nutrient deficiencies need to be efficient. By comparing the effects of NO(3)(-)-starvation in two lines of Arabidopsis thaliana (RIL282 and 432 from the Bay-0xShahdara population), this study aimed to screen the physiological mechanisms allowing one genotype to withstand NO(3)(-)-deprivation better than another and to rate the relative importance of processes such as nitrate uptake, storage, and recycling. These two lines, chosen because of their contrasted shoot N contents for identical shoot biomass under N-replete conditions, underwent a 10 d nitrate starvation after 28 d of culture at 5 mM NO(3)(-). It was demonstrated that line 432 coped better with NO(3)(-)-starvation, producing higher shoot and root biomass and sustaining maximal growth for a longer time. However, both lines exhibited similar features under NO(3)(-)-starvation conditions. In particular, the nitrate pool underwent the same drastic and early depletion, whereas the protein pool was increased to a similar extent. Nitrate remobilization rate was identical too. It was proportional to nitrate content in both shoots and roots, but it was higher in roots. One difference emerged: line 432 had a higher nitrate content at the beginning of the starvation phase. This suggests that to overcome NO(3)(-)-starvation, line 432 did not directly rely on the N pool composition, nor on nitrate remobilization efficiency, but on higher nitrate storage capacities prior to NO(3)(-)-starvation. Moreover, the higher resistance of 432 corresponded to a higher nitrate uptake capacity and a 2-9-fold higher expression of AtNRT1.1, AtNRT2.1, and AtNRT2.4 genes, suggesting that the corresponding nitrate transporters may be preferentially involved under fluctuating N supply conditions.

Coupling a 3D virtual wheat (Triticum aestivum) plant model with a Septoria tritici epidemic model (Septo3D): a new approach to investigate plant-pathogen interactions linked to canopy architecture.

This work initiates a modelling approach that allows us to investigate the effects of canopy architecture on foliar epidemics development. It combines a virtual plant model of wheat (Triticum aestivum L.) with an epidemic model of Septoria tritici which is caused by Mycosphaerella graminicola, a hemi-biotrophic, splashed-dispersed fungus. Our model simulates the development of the lesions from the infected lower leaves to the healthy upper leaves in the growing canopy. Epidemics result from the repeated successions of lesion development (during which spores are produced) and spores dispersal. In the model, canopy development influences epidemic development through the amount of tissue available for lesion development and through its effects on rain penetration and droplets interception during spore dispersal. Simulations show that the impact of canopy architecture on epidemic development differs between canopy traits and depends on climate. Phyllochron has the strongest effect, followed by leaf size and stem elongation rate.

Modelling wheat growth and yield losses from late epidemics of foliar diseases using loss of green leaf area per layer and pre-anthesis reserves.

BACKGROUND AND AIMS: Crop protection strategies, based on preventing quantitative crop losses rather than pest outbreaks, are being developed as a promising way to reduce fungicide use. The Bastiaans' model was applied to winter wheat crops (Triticum aestivum) affected by leaf rust (Puccinia triticina) and Septoria tritici blotch (STB; Mycosphaerella graminicola) under a range of crop management conditions. This study examined (a) whether green leaf area per layer accurately accounts for growth loss; and (b) whether from growth loss it is possible to derive yield loss accurately and simply. Methods Over 5 years of field experiments, numerous green leaf area dynamics were analysed during the post-anthesis period on wheat crops using natural aerial epidemics of leaf rust and STB. Key Results When radiation use efficiency (RUE) was derived from bulk green leaf area index (GLAI), RUE(bulk) was hardly accurate and exhibited large variations among diseased wheat crops, thus extending outside the biological range. In contrast, when RUE was derived from GLAI loss per layer, RUE(layer) was a more accurate calculation and fell within the biological range. In one situation out of 13, no significant shift in the RUE(layer) of diseased crops vs. healthy crops was observed. A single linear relationship linked yield to post-anthesis accumulated growth for all treatments. Its slope, not different from 1, suggests that the allocation of post-anthesis photosynthates to grains was not affected by the late occurring diseases under study. The mobilization of pre-anthesis reserves completely accounted for the intercept value. Conclusions The results strongly suggest that a simple model based on green leaf area per layer and pre-anthesis reserves can predict both growth and yield of wheat suffering from late epidemics of foliar diseases over a range of crop practices. It could help in better understanding how crop structure and reserve management contribute to tolerance of wheat genotypes to leaf diseases.

The challenge of improving nitrogen use efficiency in crop plants: towards a more central role for genetic variability and quantitative genetics within integrated approaches.

In this review, recent developments and future prospects of obtaining a better understanding of the regulation of nitrogen use efficiency in the main crop species cultivated in the world are presented. In these crops, an increased knowledge of the regulatory mechanisms controlling plant nitrogen economy is vital for improving nitrogen use efficiency and for reducing excessive input of fertilizers, while maintaining an acceptable yield. Using plants grown under agronomic conditions at low and high nitrogen fertilization regimes, it is now possible to develop whole-plant physiological studies combined with gene, protein, and metabolite profiling to build up a comprehensive picture depicting the different steps of nitrogen uptake, assimilation, and recycling to the final deposition in the seed. A critical overview is provided on how understanding of the physiological and molecular controls of N assimilation under varying environmental conditions in crops has been improved through the use of combined approaches, mainly based on whole-plant physiology, quantitative genetics, and forward and reverse genetics approaches. Current knowledge and prospects for future agronomic development and application for breeding crops adapted to lower fertilizer input are explored, taking into account the world economic and environmental constraints in the next century.

Quantification of the effects of Septoria tritici blotch on wheat leaf gas exchange with respect to lesion age, leaf number, and leaf nitrogen status.

Quantification of the damaging effects of pathogens on diseased plants and inclusion of these damaging functions in crop simulation models is of great importance for a more complete understanding of yield response to diseases. In this study, the effect of Septoria tritici blotch (STB) on net photosynthetic and dark respiration rates of wheat flag leaves was quantified. Bastiaans' model: Y=(1-x)beta was used to characterize the relationship between relative leaf photosynthesis (Y, considering Ynet and Ygross) and STB severity (with x the proportion of the diseased area). The value of beta indicates whether the effect of disease on photosynthesis is larger (beta >1), lower (beta <1), or equal (beta =1) to the proportion of visible diseased area. In the experimental conditions used here, leaf nitrogen content (in a range from 0.18 to 0.24 mg cm(-2)), and leaf number (flag and second leaves) did not significantly influence the effect of STB on leaf gas exchange. By contrast, damage depended strongly on the developmental stages of the STB lesions. STB lesions had no effect on inoculated leaves before visible symptoms appeared. Chlorotic symptoms had less effect on leaf net photosynthetic rate than could be accounted for by the visible diseased area (betanet=0.81). The effect of necrotic lesions on the leaf net photosynthetic capacity was slightly greater than that accounted for by visible symptoms (betanet=1.35). Our results suggest that the effect of the necrotic symptoms on the net photosynthesis expressed by betanet >1 is due to a combination of a decrease in the gross photosynthesis (betagross still >1) and to an increase in the dark respiration rate (betagross

Wheat leaf photosynthesis loss due to leaf rust, with respect to lesion development and leaf nitrogen status.

In wheat (Triticum aestivum cv. Soissons) plants grown under three different fertilisation treatments, we quantified the effect of leaf rust (Puccinia triticina) on flag leaf photosynthesis during the whole sporulation period. Bastiaans' model: Y = (1 - x)beta was used to characterize the relationship between relative leaf photosynthesis (Y) and disease severity (x). The evolution of the different types of symptoms induced by the pathogen (sporulating, chlorotic and necrosed tissues) was evaluated using image analysis. The beta-values varied from 2 to 11, 1.4-2, and 0.8-1 during the sporulation period, when considering the proportion of sporulating, sporulating + necrotic, and total diseased area, respectively. Leaf nitrogen (N) content did not change the effect of the disease on host photosynthesis. We concluded that leaf rust has no global effect on the photosynthesis of the symptomless parts of the leaves and that the large range in the quantification of leaf rust effect on the host, which is found in the literature, can be accounted for by considering the different symptom types. We discuss how our results could improve disease assessments and damage prediction in a wheat crop.

Analysis and modelling of effects of leaf rust and Septoria tritici blotch on wheat growth.

A model to predict Septoria tritici blotch (STB) and leaf rust effects on wheat growth was constructed and evaluated in two steps. At the leaf scale, Bastiaans' approach that predicts the relative photosynthesis of a wheat leaf infected with a single disease, was extended to the case of two diseases, one biotrophic and one necrotrophic by considering the leaf rust-STB complex. A glasshouse experiment with flag leaves inoculated either singly with one disease or with two diseases combined was performed to check the leaf damage model. No interaction of the two diseases on photosynthesis loss was observed when they occurred simultaneously on the same leaf. In a second step, the single-leaf model was extended to the canopy scale to model the effects of the leaf rust-STB complex on the growth of a wheat crop. The model predicts the effects of disease on the growth of an affected crop relative to the growth of a healthy crop. The canopy model accounted for different contributions to photosynthetic activity of leaf layers, derived from their position in the canopy and their natural leaf senescence. Treatments differing in nitrogen fertilization, microclimatic conditions, and wheat cultivars were implemented in a field experiment to evaluate the model. The model accurately estimated the effect of disease on crop growth for each cultivar, with differences from experimental values lower than 10%, which suggests that this model is well suited to aid an understanding of disease effects on plant growth. A reduction in green leaf area was the main effect of disease in these field experiments and STB accounted for more than 70% of the reduction in plant growth. Simulations suggested that the production of rust spores may result in a loss of biomass from diseased crops and that stem photosynthesis may need to be considered in modelling diseased crop growth.

Modeling nitrogen uptake in oilseed rape cv Capitol during a growth cycle using influx kinetics of root nitrate transport systems and field experimental data.

The use of kinetic equations of NO3- transport systems in oilseed rape (Brassica napus), determined by 15NO3- labeling under controlled conditions, combined with experimental field data from the INRA-Châlons rape database were used to model NO3- uptake during the plant growth cycle. The quantitative effects of different factors such as day/night cycle, ontogenetic stages, root temperature, photosynthetically active radiation, and soil nitrate availability on different components of the constitutive high-affinity transport systems, constitutive low-affinity transport systems, inducible low-affinity transport systems, and inducible high-affinity transport systems of nitrate were then determined to improve the model's predictions. Simulated uptake correlated well with measured values of nitrogen (N) uptake under field conditions for all N fertilization rates tested. Model outputs showed that the high-affinity transport system accounted for about 89% of total NO3- uptake (18% and 71% for constitutive high-affinity transport systems and inducible high-affinity transport systems, respectively) when no fertilizer was applied. The low-affinity transport system accounted for a minor proportion of total N uptake, and its activity was restricted to the early phase of the growth cycle. However, N fertilization in spring increased the duration of its contribution to total N uptake. Overall, data show that this mechanistic and environmentally regulated approach is a powerful means to simulate total N uptake in the field with the advantage of taking both physiologically regulated processes at the overall plant level and specific nitrate transport system characteristics into account.