Portail Hal-l'Institut Agro Rennes-Angers
Not a member yet
9270 research outputs found
Sort by
Cytokinin-induced bud outgrowth depends on sugar metabolism and signalling
No full textInternational audienceShoot branching is a key process of plant growth and development, finely controlled by cytokinin and sugars. However, cytokinin fails to induce bud outgrowth in the absence of sugar and so far nothing is known about its ability to antagonize auxin when sugar availability is limited. Here we demonstrate in rose that cytokinin requires sugars metabolism and signalling to promote bud outgrowth, to downregulate the expression of RhBRC1, a transcription factor that inhibits axillary bud growth, and to antagonise the inhibitory effect of auxin on bud outgrowth. Cytokinin regulation of bud sink strength was tightly associated to sugar metabolism, which was evidenced by the gene expression in sugar metabolism (e.g. glycolysis, the tricarboxylic acid and the oxidative phosphate pentose phosphate: OPPP), metabolomic approach and the quantification of total carbon and nitrogen in buds. Cytokinin supply is associated with a significant upregulation of OPPP and nitrogen accumulation. Meanwhile, sugar upregulated bud sensitivity to cytokinin, associating with a significant down-regulation of cytokinin signalling regulator RhARR1. These findings highlight the key role of sugars metabolism and signalling in the cytokinin-induced bud outgrowth and provide new insights into the importance of nutrient-hormone crosstalk in the regulation of shoot branching
Influence of drying parameters on the density of skim milk powder
No full textInternational audienceThe quality of a dairy powder is evaluated through a variety of properties, depending on its end use application, such as water activity, bulk density and rehydration properties, which are of primary importance.Controlling the density of dairy powders is crucial for manufacturers as it directly impacts production efficiency and packaging costs. However, although density is a key functionality, there are few studies in the literature focusing on it, more especially on the production parameters that influence the density of spray dried powders. Experimental data that evidence the effects of operating parameters on density are scarce. The objective of this work was to investigate the effects of operating factors for the production of skim milk powder on some powder functionalities such as apparent density, particle size distribution and flowability. The parameters studied were the conditions of liquid milk thermal treatment, the dry matter content of the concentrate at the inlet of dryer and the drying conditions (air flow rate, spray pressure, air inlet temperature).48 trials of skim milk powder production were conducted at semi-industrial scale yielding robust results that evidenced some relationships between variables. Our findings showed that (i) interstitial air was significantly higher for concentrates with lower dry matter content, (ii) larger span led to higher apparent and tapped densities, and (iii) in trials with fine powder recycling and increasing dry matter content of concentrate, the span remained relatively unchanged, but mean particle diameter decreased.All these experimental results form a database which is currently used to develop models for predicting powder characteristics. Artificial intelligence, specifically machine learning is used to build these models. Promising results were already obtained for the prediction of the concentration factor during the vacuum evaporation step (results presented in another abstract**).** Goussé et al. Modelling of the concentration and drying steps for skim milk powder production using machine learning approache
Insecticide management and alternative plant host modulate the effects of landscape complexity on an aphid pest and its natural enemies in apple orchards
No full textInternational audienceThe effects of landscape complexity on natural pest control have been widely studied but remain difficult to predict, as they often interact with local management practices and other environmental factors. In this study, we tested whether and to what extent landscape complexity (compositional and configurational heterogeneity) interacts with local pesticide use intensity and the presence of a non-crop host plant (Pyracantha coccinea), to influence the incidence of Eriosoma lanigerum, its parasitism by Aphelinus mali, and the abundance of generalist predators. We surveyed 18 apple orchards across a landscape complexity gradient in central Chile, assessing their landscape characteristics within a 1-km buffer, pesticide use intensity, and the presence of P. coccinea hedgerows. Our results highlight the significant role of configurational heterogeneity, with smaller patch sizes favoring predator abundance, while larger, less fragmented patches were associated with increased aphid incidence and parasitism rates. Intensive insecticide use strongly suppressed aphid populations but also reduced parasitism by A. mali and the abundance of predators. The presence of P. coccinea hedgerows modulated these effects, partially compensating for the reduction of insecticides and serving as a population reservoir for A. mali, but its influence varied depending on the proportion of seminatural habitat in the landscape. These findings emphasize the importance of integrating landscape structure, local management, and key non-crop habitat features when designing biological control strategies. Key message• We investigated how landscape and pesticides use interact to shape pest and natural enemy dynamics. • Configurational heterogeneity is a key factor affecting both pests and natural enemies. • Reducing insecticide use has a stronger effect on predators than landscape complexity alone. • P. coccinea supports parasitism, counteracting pesticide effects and seminatural habitat impact. • Integrating landscape structure and high-quality hedgerows improves sustainable pest control.</div
Landscape anthropization drives composition and diversity of butterfly communities at a regional scale
No full textAim While landscape anthropization is a key driver of biodiversity change, its effects on communities are underexplored, especially at regional scales. In the Anthropocene, climate and habitat diversity alone are insufficient to explain community structure. However, until recently, ecologists lacked accessible, synthesized data describing anthropization gradients, which limited studies to macro-ecological scales. Yet, a deeper understanding of how anthropization shapes species pool and local communities is crucial for biodiversity conservation, especially in historically anthropized areas. Location France Time period 2010-2020 Major taxa studied Butterfly Methods Using a high-resolution (20 m) anthropization map describing anthropization on a continuous gradient across France, we examined the influence of landscape anthropization on taxonomic, functional, and phylogenetic diversities and composition of butterfly communities in Brittany (France). This taxon is known to be widely impacted by landscape changes and is an indicator of ecosystem health. We compiled 175,000 butterfly occurrences recorded from 2010 to 2020, spanning 2,447 communities across the anthropization gradient with multi-facet biodiversity indices. Results We showed that anthropization significantly shapes community structure, sometimes even exerting a stronger influence than habitat diversity or landscape heterogeneity. Relationships between anthropization and community diversity within the same biogeographical region were often linear rather than Gaussian, with diversity decreasing as anthropization increased. Highly anthropized sites hosted communities with lower habitat and dispersal specialization and lower species richness. Main conclusions These results highlight the importance of landscape matrix and typical habitats, rather than habitat quantity, in shaping biodiversity. Integrating local scale anthropization in public policies and conservation strategies is essential for effective ecological conservation and restoration
Référendum sur le Brexit et commerce régional agricole et alimentaire
No full textWe conduct a structural gravity econometric analysis, evaluating the impact of the UK's decision to exit the EU on trade in six groups of agricultural products (poultry, other meat, dairy, cereals, vegetables, and fruit) of British and French regions. Results indicate that the UK started restructuring its mix of suppliers and destination markets before the post-Brexit trade rules took effect in early 2020. Anticipating the increase in trade costs with the EU, the UK took advantage of its free trade with EU partners, increasing purchases from these suppliers (+19%) to the detriment of countries with which it had no trade agreement (-15%).At the same time, it reoriented its exports to these latter partners in reaction to the expected deterioration of its competitiveness on EU market. However, these results mask substantial heterogeneity across regions and products. England & Wales largely drives the impact at country level, while Scotland and Northern Ireland often feature opposite evolutions in imports and exports. Regional disparities are the strongest for trade with extra-EU countries in cereals, dairy, and non-poultry meat. Still, despite some large percentage changes, these opposite shifts correspond to quite small traded amounts. French regions' trade with the UK was also heterogeneously affected. The strongest impacts are concentrated on their exports.The exports of crop products generally decline, while the exports of non-poultry meat and dairy products generally increase. Suppliers of animal products from a few top producing regions register important export gains: Bretagne for non-poultry meat, Normandie and Auvergne-Rhone-Alpes for dairy.Nous évaluons l’impact de la décision du Royaume-Uni de quitter l’UE sur les échanges commerciaux des régions britanniques et françaises pour six groupes de produits agricoles (volaille, autres viandes, produits laitiers, céréales, légumes et fruits). Nous mobilisons une analyse économétrique basée sur un modèle de gravité structurelle. Les résultats indiquent que le Royaume-Uni a commencé à restructurer ses marchés d’origine et de destination avant l’entrée en vigueur des règles commerciales post-Brexit début 2020. Anticipant l’augmentation des coûts commerciaux avec l’UE, le Royaume-Uni a tiré profit de son libre-échange avec ses partenaires de l’UE, augmentant ses achats auprès de ces fournisseurs (+19 %) au détriment des pays avec lesquels il n’avait pas d’accord commercial (-15 %). Dans le même temps, il a réorienté ses exportations vers ces derniers en réaction à la détérioration attendue de sa compétitivité sur le marché de l’UE. Cependant, ces résultats masquent une hétérogénéité substantielle selon les régions et les produits. L’Angleterre et le Pays de Galles déterminent en grande partie l’impact au niveau national tandis que l’Écosse et l’Irlande du Nord présentent souvent des évolutions opposées sur les importations et les exportations. Les disparités régionales sont les plus fortes pour les échanges avec les pays hors UE de céréales, de produits laitiers et de viande autre que la volaille. En outre, malgré quelques variations de pourcentage importantes, ces évolutions opposées correspondent à des volumes d’échanges assez faibles. Le commerce des régions françaises avec le Royaume-Uni a également été affecté de manière hétérogène. Les impacts les plus forts sont concentrés sur les exportations. Les exportations de produits végétaux diminuent généralement, tandis que celles de viande non avicole et de produits laitiers augmentent. Les fournisseurs de produits animaux de quelques grandes régions productrices enregistrent des hausses importantes des exportations : la Bretagne pour la viande autre que la volaille, la Normandie et l’Auvergne-Rhône-Alpes pour les produits laitiers
Proper account of auto-correlations improves decoding performances of state-space (semi) Markov models
No full textInternational audienceState-space models are widely used in ecology to infer hidden behaviors. This study develops an extensive numerical simulation-estimation experiment to evaluate the state decoding accuracy of four simple state-space models. These models are obtained by combining different Markovian specifications (Markov and semi-Markov) for the hidden layer with the absence (model AR0) and presence (AR1) of auto-correlation for the observation layer. Model parameters are issued from two sets of real annotated trajectories. Three metrics are developed to help interpret model performance. The first is the Hellinger distance between Markov and semi-Markov sojourn time probability distributions. The second is sensitive to the overlap between the probability density functions of state-dependent variables (e.g., speed variables). The third quantifies the deterioration of the inference conditions between AR0 and AR1 formulations. It emerges that the most sensitive model choice concerns the auto-correlation of the random processes describing the state-dependent variables. Opting for the absence of auto-correlation in the model while the state-dependent variables are actually auto-correlated, is detrimental to state decoding performance. Regarding the hidden layer, imposing a Markov structure while the state process is semi-Markov (with negative Binomial sojourn times) does not impair the state decoding performances. The real-life estimates are consistent with our experimental finding that performance deteriorates when there are significant temporal correlations that are not accounted for in the model. In light of these findings, we recommend that researchers carefully consider the structure of the statistical model they suggest and confirm its alignment with the process being modeled, especiallywhen considering the auto-correlation of observed variables
Exclusion of ants conditions the efficiency of an attract and reward strategy against Dysaphis plantaginea in apple orchards
No full textInternational audienceThe rosy apple aphid is a major pest of apple orchards, it is also potentially ant tended. Attract&Reward strategy is a promising pest management method, combining semiochemicals as attractant and companion plants as food sources for natural enemies. However, this method is difficult to implement owing to complex multi-tropic interactions (including mutualist interactions) at play in agroecosystems. Using sentinel plants (apple seedlings bearing rosy apple aphid) we investigated individual and combined effect(s) of Attract&Reward components on aphid biocontrol in early and late spring in apple orchards. The attract component was implemented by adding apple seedlings treated with a plant defense stimulator (inducing plant semiochemicals attractive for natural enemies). The reward component was implemented by adding potted plants producing extrafloral nectar. Moreover, the impact of ant tending on aphids (in exchange of honeydew) was evaluated using exclusion device. We demonstrated that the Attract&Reward strategy enabled increasing aphid biocontrol (vs. control) but only when ants were excluded, and only in early spring. The exclusion device successfully excluded ants in early and late spring but not Araneae and Syrphidae. Araneae and Syrphidae were not affected by the individual Attract&Reward components or their combination. The combination of Attract&Reward components is an effective strategy but only when ants are excluded. This is among the few studies showing experimentally that presence of ants conditions the efficiency of biocontrol strategies, including those based on Attract&Reward concept. A better understanding of trophic and mutualistic interactions is required to design effective conservation biocontrol strategies
A novel “ceasefire” model to explain efficient seed transmission of Xanthomonas citri pv. fuscans to common bean
No full textSummary Although seed represents an important means of plant pathogen dispersion, the seed-pathogen dialogue remains largely unexplored. A multi-omic approach ( i.e. dual RNAseq, plant small RNAs and methylome) was performed at different seed developmental stages of common bean ( Phaseolus vulgaris L.) during asymptomatic colonization by Xanthomonas citri pv. fuscans ( Xcf ). In this condition, Xcf did not produce disease symptoms, neither affect seed development. Although, an intense molecular dialogue, via important transcriptional changes, was observed at the early seed developmental stages with down-regulation of plant defense signal transduction, via action of plant miR, and upregulation of the bacterial Type 3 Secretion System. At later seed maturation stages, molecular dialogue between host and pathogen was reduced to few transcriptome changes, but marked by changes in DNA methylation of plant defense and germination genes, in response to Xcf colonization, potentially acting as defense priming to prepare the host for the post-germination battle. This distinct response of infected seeds during maturation, with a more active role at early stages refutes the widely diffused assumption considering seeds as passive carriers of microbes. Finally, our data support a novel plant-pathogen interaction model, specific to the seed tissues, which differs from others by the existence of distinct phases during seed-pathogen interaction with seeds first actively interacting with colonizing pathogens, then both belligerents switch to more passive mode at later stages. We contextualized this observed scenario in a novel hypothetical model that we called “ceasefire”, where both the pathogen and the host benefit from temporarily laying down their weapons until the moment of germination
Crop modelling in and for horticulture: paradigms, methods, workflows and scales
No full textInternational audienceThe workflow from experimentation to modelling and decision-support is in many cases still going in one direction, and modellers are too little involved in the early stages of experimental design, with negative repercussions on data quality for parameterization. Data acquisition techniques are evolving rapidly, with highthroughput phenotyping devices becoming increasingly available. The challenge here is to (re)organize the workflow as to avoid data redundancy or lack of usability. Coupling model design with data acquisition and analysis at an early stage in the project, with mutual sharing of the responsibility for success or failure, sounds trivial but is the way to go forward. This keynote attempts to give a systematic overview of crop modelling paradigms, methods, workflows and hierarchical scales. While inevitably being biased due to personal experience and gridlocked opinions, it is meant to provide some orientation for the identification of knowledge gaps and future requirements in crop modelling applied to horticulture.</div