Low plant density can reduce sunflower premature ripening caused by Phoma macdonaldii

In France, premature ripening (PR) is a widespread damage of a fungal disease of sunflower caused by Phoma macdonaldii. Previous results indicated that girdling canker at the stem base, caused by P. macdonaldii, was its primary cause. Previous studies have reported the influence of nitrogen and water supply on the incidence and severity of PR but an additional study was required to analyze the effect of plant density on the level of attack for a more comprehensive cultural control of PR. In a 2-year field study (2008 and 2009) in Toulouse (France), a susceptible cultivar (cv. Heliasol) artificially inoculated at star bud stage with P. macdonaldii was grown at three plant densities (4, 6.5 and 9 plants m−2) factorially combined with three N fertilization rates (0, 50/75 and 150 kg N ha−1) and two water regimes (irrigated and rainfed). P. macdonaldii symptoms were scored weekly to calculate the area under disease progress curve (AUDPC) and percentage of PR plants. Microclimatic conditions were monitored using thermo-hygrometers within the crop. The fraction of photosynthetically active radiation intercepted by the canopy (fPARi) and leaf area index (LAI) were measured at anthesis. Plant water status during the disease progression was characterized by crop simulation (SUNFLO) and N status at anthesis was assessed from shoot N content (Nm) analysis and N Nutrition Index (NNI) calculation. Increasing plant density resulted in a greater proportion of PR plants, and this proportion increased further when N was applied at 150 kg ha−1, the highest rate, and the crop was not irrigated. Despite differing canopy development, differences in microclimatic conditions between density levels were too small to explain the PR differences. However plant N concentration and diameter at stem base were closely related to PR incidence. Thin plants (grown at high density) with non-limiting N supply were the most susceptible to premature ripening. This study opens new avenues for the control of PR through crop management and emphasizes the key role of plant morphology in the development of the disease. Stem base diameter is a morphological trait that could be manipulated through crop management (plant density, N fertilization) and probably breeding in the future when developing integrated disease management systems in sunflower

Nitrogen and water management can limit premature ripening of sunflower induced by Phoma macdonaldii

Premature ripening (PR) is one of the most important diseases of sunflower in France since the 90s. Previous results indicated that girdling canker of the stem base, caused by Phoma macdonaldii was its primary cause but elucidation of critical environmental factors involved is crucial for better control of the disease. A field study was conducted in three contrasting cropping seasons (2006–2008) and investigated the effect of N fertilization (0, 75 and 150 kg N ha−1) and water regime (rainfed, irrigated) on two cultivars with artificial inoculation (AI) and natural infection (NI). Disease assessment was recorded weekly to calculate the area under disease progress curve (AUDPC) and the final percentage of PR plants. Data showed that high levels of N fertilization led to significantly (P < 0.05) more PR than non-fertilization. Water deficit conditions were significantly (P < 0.05) involved in disease severity, and AUDPC and PR were increased when dry conditions were associated with high N supply. This was true for two cultivars which differed in their susceptibility to the disease but cv. Heliasol RM was significantly (P < 0.05) more affected than cv. Melody, partially resistant to PR. Despite contrasting weather patterns, these results demonstrated a clear role of crop management and environmental conditions on the incidence and severity of stem base attacks responsible for the PR syndrome. These findings suggest that sunflower crop husbandry should be adapted to minimize premature ripening induced by P. macdonaldii

Prediction of sunflower grain oil concentration as a function ofvariety, crop management and environment using statistical models

Sunflower (Helianthus annuus L.) raises as a competitive oilseed crop in the current environmentallyfriendly context. To help targeting adequate management strategies, we explored statistical models astools to understand and predict sunflower oil concentration. A trials database was built upon experi-ments carried out on a total of 61 varieties over the 2000–2011 period, grown in different locations inFrance under contrasting management conditions (nitrogen fertilization, water regime, plant density).25 literature-based predictors of seed oil concentration were used to build 3 statistical models (multiplelinear regression, generalized additive model (GAM), regression tree (RT)) and compared to the refer-ence simple one of Pereyra-Irujo and Aguirrezábal (2007) based on 3 variables. Performance of modelswas assessed by means of statistical indicators, including root mean squared error of prediction (RMSEP)and model efficiency (EF). GAM-based model performed best (RMSEP = 1.95%; EF = 0.71) while the simplemodel led to poor results in our database (RMSEP = 3.33%; EF = 0.09). We computed hierarchical contribu-tion of predictors in each model by means of R2and concluded to the leading determination of potentialoil concentration (OC), followed by post-flowering canopy functioning indicators (LAD2 and MRUE2),plant nitrogen and water status and high temperatures effect. Diagnosis of error in the 4 statistical mod-els and their domains of applicability are discussed. An improved statistical model (GAM-based) wasproposed for sunflower oil prediction on a large panel of genotypes grown in contrasting environments

Increased genetic diversity improves crop yield stability under climate variability: a computational study on sunflower

A crop can be represented as a biotechnical system in which components are either chosen (cultivar, management) or given (soil, climate) and whose combination generates highly variable stress patterns and yield responses. Here, we used modeling and simulation to predict the crop phenotypic plasticity resulting from the interaction of plant traits (G), climatic variability (E) and management actions (M). We designed two in silico experiments that compared existing and virtual sunflower cultivars (Helianthus annuus L.) in a target population of cropping environments by simulating a range of indicators of crop performance. Optimization methods were then used to search for GEM combinations that matched desired crop specifications. Computational experiments showed that the fit of particular cultivars in specific environments is gradually increasing with the knowledge of pedo-climatic conditions. At the regional scale, tuning the choice of cultivar impacted crop performance the same magnitude as the effect of yearly genetic progress made by breeding. When considering virtual genetic material, designed by recombining plant traits, cultivar choice had a greater positive impact on crop performance and stability. Results suggested that breeding for key traits conferring plant plasticity improved cultivar global adaptation capacity whereas increasing genetic diversity allowed to choose cultivars with distinctive traits that were more adapted to specific conditions. Consequently, breeding genetic material that is both plastic and diverse may improve yield stability of agricultural systems exposed to climatic variability. We argue that process-based modeling could help enhancing spatial management of cultivated genetic diversity and could be integrated in functional breeding approaches

Analyse et modélisation des effets de la conduite de culture sur deux maladies cryptogamiques majeures du tournesol (Phoma macdonaldii et Phomopsis helianthi)

Le phoma (Phoma macdonaldii / Leptosphaeria linquistii) et le phomopsis (Phomopsis / Diaporthe helianthi) sont deux champignons pathogènes majeurs du tournesol. Dans un contexte d objectif de réduction de la lutte chimique, une meilleure compréhension des interactions peuplement-agents pathogènes-environnement-conduite de culture est nécessaire. Des essais menés au champ et en serre à Auzeville en 2010 et 2011 ont permis de décomposer les effets de la conduite de culture du tournesol sur l apparition et le développement des deux maladies. Les variables clés de l architecture des plantes en peuplement et du microclimat, modifiées par la conduite de culture (choix variétal, densité de semis, fertilisation azoté, irrigation) ont été décrites et mises en relation avec les composantes de la maladie. Ainsi, pour le phomopsis, le rôle déterminant du microclimat résultant du niveau de développement de la couverture foliaire lors des phases initiales d infection a été confirmé. La taille des feuilles et le diamètre des tiges sont des caractères déterminants de la progression des dégâts sur feuille et tige. Les conséquences des attaques de phomopsis sur feuille en termes de mécanismes de nuisibilité ont été analysées finement et modélisées. Pour le phoma, le rôle du statut nutritionnel azoté dans la progression des attaques sur tige et collet a été confirmé. La fonction régulatrice du phoma vis-à-vis des attaques de phomopsis sur feuille a été quantifiée. Sur le plan de la modélisation, plusieurs approches ont été menées : (i) Evaluation de la qualité prédictive d Asphodel, modèle épidémiologique prévoyant les émissions de ascospores de Phomopsis ; application à différentes conduites de culture et extension au phoma pour la partie inoculum primaire ; (ii) développement d un modèle prédictif de l incidence du phoma prenant en compte les effets climatiques, microclimatiques et agronomiques ; (iii) proposition d une modélisation conceptuelle des interactions plante-agent(s) pathogène(s)-environnement-conduite de culture. Ce travail pourra, à terme, contribuer à la conception de stratégies de gestion des principales maladies du tournesol, à l échelle de la parcelle ou du territoire.Phoma (Phoma macdonaldii / Leptosphaeria linquistii) and phomopsis (Phomopsis / Diaporthe helianthi) are two major sunflower fungal diseases. In a context of reduction of pesticides, a better understanding of the interactions between crop canopy, pathogens, environment and cropping practices is needed. Field and greenhouse experiments set up at Auzeville in 2010 and 2011 allowed to dissect the impact of sunflower crop management on disease appearance and development. Key variables of plant architecture and microclimate, modified by cropping practices (variety choice, sowing density, nitrogen fertilization, irrigation) were described and related to disease components. Thereby, for phomopsis, the key role of microclimate resulting from the level of development of leaf area during the initial stages of infection was confirmed. Leaf length and stem diameter are key characters for necrosis progression on leaf and stem. The impact of phomopsis leaf infection in term of damage mechanism was analysed and modelled. For phoma, the effect of nitrogen nutrition status on necrosis progression on stem and stem base was confirmed. The regulatory function of phoma towards phomopsis leaf infection was quantified. In terms of modelling, several approaches were developed: (i) evaluation of the predictive quality of Asphodel, an epidemiological model predicting Phomopsis ascospore release; application to different cropping practices and extension to phoma for primary inoculum; (ii) development of a predictive model for phoma incidence taking into account the climatic, microclimatic and agronomic effects; (iii) proposal of a conceptual model of the interactions between crop canopy, pathogens, environment and cropping practices. This study could contribute to the design of integrated management strategies for the main sunflower diseases, at field or at territory scale.TOULOUSE-INP (315552154) / SudocSudocFranceF

Analyse et modélisation des effets des pratiques culturales et de la situation de production sur les dégâts causés par les bioagresseurs des cultures. Application au blé d'hiver

La protection intégrée des cultures (PIC) apparaît comme une stratégie durable de protection des plantes contre les bioagresseurs, satisfaisant les exigences à la fois économiques, écologiques et sanitaires auxquelles est confrontée l agriculture. L amélioration des connaissances sur les interactions entre les bioagresseurs et les pratiques agricoles est indispensable afin de concevoir des méthodes de lutte plus économes en produits phytosanitaires Le modèle IPSIM (Injury Profile SIMulator), développé dans ce travail de thèse, vise à simuler l effet des pratiques culturales, du pédoclimat et de l environnement de la parcelle sur les dégâts causés par les bioagresseurs sur une culture. Ce modèle est basé sur une approche hiérarchique et agrégative. Ce travail décrit la base conceptuelle de la modélisation IPSIM et son application pour construire le modèle IPSIM-Wheat, simulant les profils de dégâts sur le blé en fonction des pratiques culturales et de l environnement biotique et abiotique. Plusieurs modèles ont été conçus pour prédire les sévérités de six maladies, un ravageur et les plantes adventices du blé. Ces modèles contribuent ainsi au développement d IPSIM-Wheat, dont une première version est présentée pour des bioagresseurs majeurs en interaction. Ce futur modèle pourra contribuer à concevoir des systèmes de culture incluant du blé, moins soumis aux pressions biotiques et moins dépendants des pesticides.Integrated pest management (IPM) appears as a sustainable strategy to protect plants against pest while answering the economical, ecological, and toxicological expectations that agriculture must face. The effects of cultural practices on pest dynamics have to be thoroughly analyzed in order to reduce the reliance of cropping systems on pesticides. A model, named IPSIM ((Injury Profile SIMulator), currently under development in this thesis, aims at simulating the effects of cropping practices, as well as soil, climate and field environment on the injuries caused by multiple pests of a given crop. This model is based on a hierarchical and aggregative approach. This study describes the conceptual basis of the modeling and its applications in order to develop IPSIM-Wheat, a model simulating injury profiles on wheat. Thus, several models have been designed to predict six diseases, one insect pest and weeds. This study thus contributes to the development of IPSIM-Wheat which will help design innovative sustainable wheat-based cropping system.TOULOUSE-INP (315552154) / SudocSudocFranceF

Potential yield simulated by global gridded crop models: using a process-based emulator to explain their differences

How global gridded crop models (GGCMs) differ in their simulation of potential yield and reasons for those differences have never been assessed. The GGCM Intercomparison (GGCMI) offers a good framework for this assessment. Here, we built an emulator (called SMM for simple mechanistic model) of GGCMs based on generic and simplified formalism. The SMM equations describe crop phenology by a sum of growing degree days, canopy radiation absorption by the Beer–Lambert law, and its conversion into aboveground biomass by a radiation use efficiency (RUE). We fitted the parameters of this emulator against gridded aboveground maize biomass at the end of the growing season simulated by eight different GGCMs in a given year (2000). Our assumption is that the simple set of equations of SMM, after calibration, could reproduce the response of most GGCMs so that differences between GGCMs can be attributed to the parameters related to processes captured by the emulator. Despite huge differences between GGCMs, we show that if we fit both a parameter describing the thermal requirement for leaf emergence by adjusting its value to each grid-point in space, as done by GGCM modellers following the GGCMI protocol, and a GGCM-dependent globally uniform RUE, then the simple set of equations of the SMM emulator is sufficient to reproduce the spatial distribution of the original aboveground biomass simulated by most GGCMs. The grain filling is simulated in SMM by considering a fixed-in-time fraction of net primary productivity allocated to the grains (frac) once a threshold in leaves number (nthresh) is reached. Once calibrated, these two parameters allow for the capture of the relationship between potential yield and final aboveground biomass of each GGCM. It is particularly important as the divergence among GGCMs is larger for yield than for aboveground biomass. Thus, we showed that the divergence between GGCMs can be summarized by the differences in a few parameters. Our simple but mechanistic model could also be an interesting tool to test new developments in order to improve the simulation of potential yield at the global scale

Future area expansion outweighs increasing drought risk for soybean in Europe

The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks. Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe. While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions