Collection HAL

[hal-05652738] Spatio-temporal field, landscape and meteorological datasets describing bruchid beetle populations, grain damage and parasitism in faba bean and lentil fields in France

This dataset provides a multi-scale and multi-year characterization of population, grain damage and larval parasitism of bruchid beetle populations (Coleoptera: Chrysomelidae: Bruchinae) populations, i.e. Bruchus rufimanus Boheman, 1833 and Bruchus signaticornis Gyllenhal, 1833. This dataset covers 45 faba bean (Vicia faba Linnaeus, 1753) and 60 lentil (Lens culinaris Medikus, 1787) fields across four major production regions in France. Data were collected over three consecutive growing seasons (2019-2020 to 2021-2022) across three phenological crop stages (vegetative, flowering, and young pods) and at five distances from field edge to capture spatio-temporal dynamics. Datasets include bruchid counts, grain damage as well as parasitism rates by micro-hymenoptera (mainly Triaspis cf.thoracica Curtis, 1860). Field observations are integrated with environmental variables, including GISbased landscape metrics (land use, semi-natural habitats, and hedgerow length) calculated at 500, 1000, and 2000 m buffer radii from field observation plots. Additionally, daily meteorological data from the SAFRAN platform (https://agroclim.inrae.fr/siclima/) at a resolution of 8-km grid and then aggregated per crop stage, covering temperature thresholds, precipitation, and wind speed.Agricultural management information, such as crop sowing dates, varieties, tillage and pest management, is also provided for each of the 105 fields. This integrated dataset allows for crossdisciplinary reuse in agronomy, ecology, and entomology to explore pest-enemy interactions, edge effects, and the influence of landscape and climate on crop-pest dynamics.

ano.nymous@ccsd.cnrs.fr.invalid (Cayetano Herrera) 12 Jun 2026

https://hal.inrae.fr/hal-05652738v2

[hal-05697915] When machine learning extrapolates in space: How local data shape spatial transferability

Reliable spatial prediction requires assessing model behaviour under extrapolation, a setting in which standard validation schemes and performance metrics may be misleading due to spatial autocorrelation and limited environmental support. We study how validation design, environmental novelty, and data support jointly shape predictive performance in spatial risk modelling. Using plant health surveillance data on Xylella fastidiosa in France (2015-2023), we analyse a high-dimensional spatial prediction problem combining climatic, soil, and land-use predictors. We propose a spatially informed modelling framework integrating ensemble-based feature selection under environmental block cross-validation, a spatially weighted variant of XGBoost based on predictor-specific smoothing of spatially structured predictors, and explicit diagnostics of prediction support through the Area of Applicability, and compare it to a Bayesian hierarchical spatial logistic regression benchmark. Motivated by the east-west spread of Xylella fastidiosa, we introduce a spatial transfer evaluation scheme that assesses predictive performance in previously unobserved regions under progressive incorporation of local data. This scheme reveals a non-linear transition from extrapolative to interpolative prediction regimes governed by expansion of the applicability domain. Resulting gains in discrimination and calibration dominate over the more limited stabilizing effect of spatial smoothing near the extrapolation boundary. These results emphasize the need to interpret spatial predictions conditionally on their domain of applicability and highlight the role of validation and support diagnostics in spatial statistical modelling.

ano.nymous@ccsd.cnrs.fr.invalid (Camille Portes) 20 Jul 2026

https://hal.inrae.fr/hal-05697915v1

[hal-05661572] Sequential area interaction sampling for early plant disease detection

We develop general novel sequential point process models for plant disease surveillance, aiming to accelerate early detection of disease presence in a study domain. The framework adapts to the level of knowledge about the propagation parameters: with full information, it reduces to a sequential hard-core process, whereas under uncertainty it becomes a sequential area-interaction process. By incorporating past observations at each step, the proposed models optimize detection time in an adaptive setting. The dynamics of the proposed sequential point process models are analyzed, compared to alternative sampling strategies through a simulation study, and illustrated in a real surveillance context.

ano.nymous@ccsd.cnrs.fr.invalid (François d'Alayer) 18 Jun 2026

https://hal.inrae.fr/hal-05661572v1

[hal-05490031] A marked sequential point process for disease surveillance: Modeling and optimization

Plant disease surveillance is essential for the management of disease outbreaks that pose significant threats to agricultural sustainability. In this study, we present a novel sequential point process model designed for disease surveillance. The model incorporates self-interaction mechanisms to account for the influence of the process' history. To analyze the dynamics of the model, we propose new sequential summary statistics that extend traditional point process methods to scenarios where sequential interactions are critical. This model serves a dual purpose: it is employed both to propose novel and efficient sampling designs, and to characterize existing sampling schemes, implemented in real-world situations, through parameter inference.

ano.nymous@ccsd.cnrs.fr.invalid (François D’alayer) 02 Feb 2026

https://hal.inrae.fr/hal-05490031v1

[hal-05695604] Assessing fruit tree vigor in peach and apple orchards through wood segmentation in ground-based RGB images

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ano.nymous@ccsd.cnrs.fr.invalid (Khac-Lan Nguyen) 17 Jul 2026

https://hal.science/hal-05695604v1

[hal-05627550] Intercropping chickpea with a competitive service plant and mowing the inter-rows controls weeds and ascochyta blight while mitigating interspecific competition

Chickpea (Cicer arietinum L.) is a promising crop for adapting to climate change and reducing the reliance of cropping systems on synthetic N fertilizers. However, its yield is highly variable, mainly due to weed competition and ascochyta blight (Ascochyta rabiei). Hence, this study investigated the effects of intercropping chickpea with a mowed service plant to control both weeds and ascochyta blight, while mitigating competition to minimise yield reductions. In a two-year field experiment in Western France, chickpea was grown as sole crop and intercropped with four single service plants (Egyptian clover, faba bean, oat, and Sudan grass) in alternate rows. These species were chosen for their contrasted traits, allowing to create different levels of interspecific competition. Chickpea’s inter-rows were either mowed at the beginning of flowering or left without mechanical regulation. Introducing oat decreased weed biomass in both years. Under high weed and disease pressures, adding unmowed oat reduced both weed biomass and ascochyta blight severity by 66% and 56% compared to the unmowed sole chickpea, respectively. No differences were found between the sole chickpea and the other intercrops. Unlike the other species, oat had a high biomass production early in the crop cycle, which partly explains its weed-suppression effect. However, adding oat reduced chickpea grain yield in 2023 by 72%, although mowing limited this reduction to 48%. This study highlights that intercropping chickpea with a mowed competitive service plant that generates an aerated canopy, like oat, can help to control both weeds and ascochyta blight, while mitigating interspecific competition.

ano.nymous@ccsd.cnrs.fr.invalid (Margaux Guy) 20 May 2026

https://hal.science/hal-05627550v1

[hal-05642655] Rethinking grapevine downy mildew management: opportunities to disrupt the sexual cycle of the pathogen as a preventive disease control strategy

Plant diseases caused by fungal and oomycete pathogens with mixed reproduction systems include some of the most damaging crop diseases. These pathogens reproduce asexually under low-stress conditions during the growing season in order to propagate rapidly and efficiently. They then shift to sexual reproduction when conditions become harsher, so as to survive and adapt. For those that are obligate biotroph pathogens with a deciduous host, sexual reproduction is a necessary step in their life cycle. Plasmopara viticola , the oomycete causing grapevine downy mildew (GDM), is a representative example, particularly in temperate regions in which grapevines enter dormancy in autumn. Current efforts to control GDM, including those comprising Integrated Pest Management (IPM), are typically limited to the grapevine’s growing season. They target the primary contamination and the asexual propagation of P. viticola and consist most typically of repeated fungicide applications whenever contamination conditions are met. However, strategies that would target the sexual cycle of P. viticola during the offseason are often overlooked, even though related approaches are successful in other plant-pathogen systems. We discuss several novel interventions informed by plant pathogen biology, epidemiology, and ecology that would disrupt the pathogen’s sexual cycle at several key points, reducing both the epidemic pressure and the ability of the pathogen to adapt from one growing season to the next. Furthermore, we identify the main scientific and technical challenges to be overcome. In line with IPM, we call for a shift toward a preventive, long-term vision of plant disease management and more sustainable agroecosystems.

ano.nymous@ccsd.cnrs.fr.invalid (Paige Breen) 03 Jun 2026

https://hal.science/hal-05642655v1

[hal-05681565] Quantitative resistance to aphanomyces root rot in legumes

Aphanomyces root rot, caused by the soilborne oomycete Aphanomyces euteiches Drechs., is an important threat to legume crop production. In susceptible grain legumes, such as pea (Pisum sativum) and lentil (Lens culinaris), the disease can cause total yield loss under favorable infection conditions. No effective and durable method of disease control is currently available. Therefore, farmers are advised to prevent the spread of the pathogen through crop rotations with non-host or resistant crops, and by monitoring soil inoculum levels using detection tests. Genetic resistance is an essential method to manage crop diseases. Indeed, significant progress has been achieved over the past three decades in identifying quantitative trait loci (QTL) for resistance to A. euteiches mainly in pea, but also in lentil, faba bean (Vicia faba), and the model species Medicago truncatula. These advances in genetics research have led to the recent registration in France of the first partially resistant pea varieties. This feature article provides a review of the research knowledge on A. euteiches x legumes pathosystem, as well as plant sources of resistance, genetic determinants, and molecular mechanisms of quantitative resistance to A. euteiches currently being deciphered in pulse grains and the model legume studied. It also highlights future research directions for the development of effective and durable resistance in legume varieties.

ano.nymous@ccsd.cnrs.fr.invalid (Théo Leprévost) 07 Sep 2026

https://hal.science/hal-05681565v1

[hal-03299446] Seed microbiota revealed by a large-scale meta-analysis including 50 plant species

Seed microbiota constitutes a primary inoculum for plants that is gaining attention owing to its role for plant health and productivity. Here, we performed a meta-analysis on 63 seed microbiota studies covering 50 plant species to synthesize knowledge on the diversity of this habitat. Seed microbiota are diverse and extremely variable, with taxa richness varying from one to thousands of taxa. Hence, seed microbiota presents a variable (i.e. flexible) microbial fraction but we also identified a stable (i.e. core) fraction across samples. Around 30 bacterial and fungal taxa are present in most plant species and in samples from all over the world. Core taxa, such as Pantoea agglomerans, Pseudomonas viridiflava, P. fluorescens, Cladosporium perangustum and Alternaria sp., are dominant seed taxa. The characterization of the core and flexible seed microbiota provided here will help uncover seed microbiota roles for plant health and design effective microbiome engineering.

ano.nymous@ccsd.cnrs.fr.invalid (Marie Simonin) 05 Sep 2026

https://hal.inrae.fr/hal-03299446v1

[hal-05081398] A cross-systems primer for synthetic microbial communities

The design and use of synthetic communities, or SynComs, is one of the most promising strategies for disentangling the complex interactions within microbial communities, and between these communities and their hosts. Compared to natural communities, these simplified consortia provide the opportunity to study ecological interactions at tractable scales, as well as facilitating reproducibility and fostering interdisciplinary science. However, the effective implementation of the SynCom approach requires several important considerations regarding the development and application of these model systems. There are also emerging ethical considerations when both designing and deploying SynComs in clinical, agricultural or environmental settings. Here we outline current best practices in developing, implementing and evaluating SynComs across different systems, including a focus on important ethical considerations for SynCom research.Here the authors outline best practices for the development, implementation and evaluation of synthetic microbial communities (or SynComs) across different systems.

ano.nymous@ccsd.cnrs.fr.invalid (Elijah Mehlferber) 23 May 2025

https://hal.inrae.fr/hal-05081398v1

[hal-05738301] Assessing government subsidies for reducing pesticide use: A meta-analysis

<div>In the efforts being made by governments to reduce pesticide use, subsidies are an important instrument to encourage farmers to adopt more sustainable practices. Yet, their effectiveness remains uncertain due to diverse designs and contexts. To date, there are no study that provide systematic synthesized evidence on the potentially heterogeneous effects of subsidies on pesticide use. The present study addresses this gap by conducting a meta-analysis of 39 empirical studies (208 models) from the EU and other developed countries that examine the effects of subsidies on (i) direct measurement of pesticide use and (ii) indirect measurement of pesticide use based on the adoption of pesticide-reducing practices. Using probit meta-regressions and qualitative appraisal, we find two key results. First, for EU studies, Pillar I and Pillar II subsidies have opposite effects on pesticide use: Pillar II subsidies are more likely than Pillar I subsidies to reduce pesticide use. Second, if we consider studies from both the EU and the US, subsidies that target adoption of whole-farm systems or bundles of practices outperform those targeting a single practice in reducing pesticide use. We provide some policy recommendations for policy design and highlight future research priorities.</div>

ano.nymous@ccsd.cnrs.fr.invalid (Gaëlle Leduc) 04 Sep 2026

https://hal.inrae.fr/hal-05738301v1

[hal-05633888] Untargeted metabolomic dataset of leaves from twenty-four accessions of wild and cultivated tomato plants

Tomato (Solanum lycopersicum var. lycopersicum), one of the most important crops worldwide, has a complex domestication history that began in Latin America, region hosting also fourteen wild relative species and subspecies. Domestication and subsequent breeding efforts have led to the development of the modern cultivated tomato, prized for its agronomic performance and economic value. However, this process also resulted in a substantial erosion of genetic and metabolic diversity, potentially limiting the plant’s adaptive capacity and resilience to environmental stresses. Previous comparative studies between domesticated tomato cultivars and wild relative species have underscored the evolutionary shifts in various plant traits associated with biotic stress. Yet, most of these studies relied on a limited number of wild accessions, reflecting a general tendency to underestimate their genetic and metabolic diversity. In this study, we sought to characterize both intra- and inter-specific metabolic diversity in tomato and its wild relatives. Using Liquid Chromatography High Resolution Mass Spectrometry (LC-HRMS) analysis, we profiled the chemical composition of hydro-methanolic leaf extracts from twenty-four accessions representing five Solanum species and subspecies, each with distinct natural histories and domestication levels. This dataset provides a comprehensive overview of leaf metabolic diversity across cultivated and wild tomato species, offering insights into the evolutionary and ecological forces shaping specialized metabolism within the tomato clade. It is available at https://doi.org/10.57745/QM0BOR.

ano.nymous@ccsd.cnrs.fr.invalid (Komla Exonam Amegan) 27 May 2026

https://hal.science/hal-05633888v1

[hal-04455685] Induction of common bean OVATE Family Protein 7 (PvOFP7) promotes resistance to common bacterial blight

Common bacterial blight of bean (CBB) is a devastating seed-transmitted disease caused by Xanthomonas phaseoli pv. phaseoli and Xanthomonas citri pv. fuscans on common bean (Phaseolus vulgaris L.). The genes responsible for CBB resistance are largely unknown. moreover, the lack of reproducible and universal transformation protocol limits the study and improvement of genetic traits in common bean. We produced X. phaseoli pv. phaseoli strains expressing artificially-designed Transcription-Activator Like Effectors (dTALEs) to target 14 candidate genes and performed in planta assays in a susceptible common bean genotype to analyse if the transcriptional induction of these genes could confer resistance to CBB. Induction of PvOFP7, PvAP2-ERF71 and PvExpansinA17 resulted in CBB symptom reduction. In particular, PvOFP7 induction led to strong symptom reduction, linked to reduced bacterial growth in planta at early colonisation stages. RNA-Seq analysis revealed up-regulation of cell wall formation and primary metabolism, and major downregulation of Heat Shock Proteins. Our results demonstrate that PvOFP7 is contributes to CBB resistance, and underline the usefulness of dTALEs for highlighting genes of quantitative activity.

ano.nymous@ccsd.cnrs.fr.invalid (Charlotte Gaudin) 13 Feb 2024

https://hal.science/hal-04455685v1

[hal-04756712] dTALE approach demonstrates that induction of common bean OVATE Family Protein 7 (PvOFP7) promotes resistance to common bacterial blight

Common bacterial blight of bean (CBB) is a devastating seed-transmitted disease caused by Xanthomonas phaseoli pv. phaseoli and Xanthomonas citri pv. fuscans on common bean (Phaseolus vulgaris L.). The genes responsible for CBB resistance are largely unknown. Moreover, the lack of a reproducible and universal transformation protocol limits the study of genetic traits in common bean. We produced X. phaseoli pv. phaseoli strains expressing artificially-designed Transcription-Activator Like Effectors (dTALEs) to target 14 candidate genes for resistance to CBB based on previous transcriptomic data. In planta assays in a susceptible common bean genotype showed that induction of PvOFP7, PvAP2 ‐ ERF71 or PvExpansinA17 expression by dTALEs resulted in CBB symptom reduction. After PvOFP7 induction, in planta bacterial growth was reduced at early colonisation stages and RNA-Seq analysis revealed up-regulation of cell wall formation and primary metabolism, together with major down-regulation of Heat Shock Proteins. Our results demonstrate that PvOFP7 contributes to CBB resistance, and underline the usefulness of dTALEs for functional validation of genes whose induction impacts Xanthomonas-plant interaction.

ano.nymous@ccsd.cnrs.fr.invalid (Charlotte Gaudin) 28 Oct 2024

https://hal.science/hal-04756712v1

[hal-05723807] Extrapolation spatiale du risque de présence de Xylella fastidiosa basée sur XGBoost

Nous proposons une méthodologie complète pour évaluer et cartographier le risque de présence de la bactérie Xylella fastidiosa en intégrant les composantes spatiales dans le processus de modélisation. Notre approche est basée sur l’apprentissage automatique, tenant compte des particularités des données : hétérogénéité spatiale et déséquilibre. Une pré-sélection de facteurs est réalisée à l’aide d’une approche ensembliste couplée à une validation croisée spatiale. Nous proposons ensuite une adaptation du modèle XGBoost dans laquelle les composantes spatiales sont intégrées au modèle, notamment en considérant des facteurs spatialement pondérés et en basant la sélection de modèle sur une validation croisée par blocs environnementaux. Cette approche nous permet d’obtenir un modèle robuste, généralisable à une zone géographique éloignée de celle utilisée pour l’entraînement du modèle et donc adaptée à l’extrapolation

ano.nymous@ccsd.cnrs.fr.invalid (Camille Portes) 22 Aug 2026

https://hal.science/hal-05723807v1

[hal-04665509] A stage‐dependent seed defense response to explain efficient seed transmission of Xanthomonas citri pv. fuscans to common bean

Although seed represents an important means of plant pathogen dispersion, the seed–pathogen dialogue remains largely unexplored. A multiomic approach was performed at different seed developmental stages of common bean ( Phaseolus vulgaris L.) during asymptomatic colonization by Xanthomonas citri pv. fuscans ( Xcf ), At the early seed developmental stages, we observed high transcriptional changes both in seeds with bacterial recognition and defense signal transduction genes, and in bacteria with up‐regulation of the bacterial type 3 secretion system. This high transcriptional activity of defense genes in Xcf ‐colonized seeds during maturation refutes the widely diffused assumption considering seeds as passive carriers of microbes. At later seed maturation stages, few transcriptome changes indicated a less intense molecular dialogue between the host and the pathogen, but marked by changes in DNA methylation of plant defense genes, in response to Xcf colonization. We showed examples of pathogen‐specific DNA methylations in colonized seeds acting as plant defense silencing to repress plant immune response during the germination process. Finally, we propose a novel plant–pathogen interaction model, specific to the seed tissues, highlighting the existence of distinct phases during seed–pathogen interaction with seeds being actively interacting with colonizing pathogens, then both belligerents switching to more passive mode at later stages.

ano.nymous@ccsd.cnrs.fr.invalid (Armelle Darrasse) 31 Jul 2024

https://hal.inrae.fr/hal-04665509v1

[tel-05734808] Effets de la diversification et de la pérennisation des couverts végétaux sur les productions de blé et prairies et sur les cycles du carbone et de l'azote

Enhancing the diversity and the perennity of plant cover promotes numerous ecological interactions and regulations that benefit plant nutrition and production, improve soil health, and reduce plant pathogens. This makes diversification and perennialization of plant covers promising avenues for increasing the sustainability of agroecosystems, and ensuring crop production while reducing the use of inputs (mineral fertilizers, pesticides). However, establishing a perennial, multi-species plant cover with more than two or three species remains a challenge for cereal crops, which are mostly annual and low in diversity. In this context, a field experiment was set up at INRAe in Clermont-Ferrand to test a new agroecosystem termed “agroprairies.” Agroprairies consist of a combination of an annual cereal crop with perennial, multi-species prairies (n &gt; 10), arranged in narrow alternating strips (~40 cm). The thesis, which is mainly based on this experiment, aims to study the effects of these diversification and perennialization practices on plant interactions, agricultural productions, and the functioning of carbon (C) and nitrogen (N) cycles in the soil. It also includes the study of another diversification practice for cereal crops: wheat variety mixtures. The thesis is divided into four chapters. The first chapter is based on a dataset collected in an experiment conducted prior to the thesis, which aimed to study the effects of intraspecific diversity in wheat by manipulating the number of wheat varieties and functional clusters within varietal mixtures. We show that intraspecific wheat diversity in mixtures has no significant effect on wheat aboveground and belowground biomass or on 15N recovery in the plant-soil system, but has slight effects on the content of certain nutrients in wheat (Cu, Fe, Zn, Na, and P). The second chapter explores the effects of four types of prairies on the nutrition, phenology, growth, and biomass production of wheat in agroprairies, with or without fertilization. We show that trait syndromes associated with a resource-acquisitive strategy and a high proportion of legumes in the prairie strips significantly improve wheat nutrition, earliness, growth, and biomass production, and that N fertilization reduces the effect of prairie strips on wheat development. Chapter 3 evaluates the effects of various agroprairies in terms of production (total, grain, forage), compared to wheat monoculture and/or prairies alone, over two consecutive years and without inputs. A key finding is that certain agroprairies can increase overall crop production by up to 49% and maintain a grain yield equivalent to that of a wheat monoculture, while providing additional forage production. The fourth chapter examines the effects of different plant cover – wheat, prairies, and agroprairies – on a set of microbial functions related to C and N cycles over two consecutive years, in winter and spring. Our results indicate C availability for microorganisms is higher in prairies and in agroprairies than in wheat monocultures, which, in some cases, is associated with an increase in microbial C and N immobilization, and the release of available nutrient for plants. Overall, this thesis presents new systems for cereals and forage production, that make it possible to enhance production without the use of inputs. It also provides insights into plant ecology and agronomic practices that can leverage positive interactions within agroecosystems to boost crop production and improve soil microbial functioning.

ano.nymous@ccsd.cnrs.fr.invalid (Thomas Bécu) 01 Sep 2026

https://hal.inrae.fr/tel-05734808v1

[hal-05384699] Regardez sous vos pieds, ces sols vivants

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ano.nymous@ccsd.cnrs.fr.invalid (Cordeau, S.) 27 Nov 2025

https://hal.inrae.fr/hal-05384699v1

[hal-05215187] A functional ecology approach to define a conceptual and participatory method for designing species mixtures: a case study on nitrogen cycling and weed control

In agriculture, species mixtures can provide ecosystem services and make agroecosystems more resilient. In particular, weed control and improved nitrogen cycling are much sought-after services provided by species mixtures. However, there is a lack of knowledge about the choice of species to mix to provide these services. Using different sources of knowledge, we therefore investigated the utilization of the Trait-Function-Service (TFS) approach of functional ecology as a way of representing the functioning of species mixtures in order to help in the choice of species. The novelty here is the use of a generalizable framework integrating empirical knowledge and scientific knowledge to establish the link between species traits and the ecosystem services they provide. Consequently, our objective is to (i) create functional trees that reflect how mixtures of species work to control weeds and improve nitrogen cycling; and (ii) identify the rules for assembling the traits that enable these two ecosystem services to be provided, which can be used to design mixtures. To do this, we organized four knowledge exchange workshops, two on weed control and two on improving nitrogen cycling. These workshops involved scientists, advisors, and farmers to mobilize their expertise. Our results show that the improvement of nitrogen cycling depends on the achievement of the meta-functions “favour and diversify the sources of nitrogen”, “reduce nitrogen losses” and “improve nitrogen use efficiency”. The weed control service is composed of the meta-functions “increase the competition towards the weeds” and “avoid weed germination/emergence”. We show that providing an ecosystem service depends on multiple traits and that the same trait can be important for providing different ecosystem services. The empirical knowledge of farmers can differ significantly from that of scientists. Integrating the knowledge of farmers into functional trees highlights that expert knowledge, derived from experience gained in specific contexts, can be decontextualized to produce generic knowledge.

ano.nymous@ccsd.cnrs.fr.invalid (Malick Sidiki Ouattara) 25 Feb 2026

https://hal.inrae.fr/hal-05215187v1

[hal-05690913] Biocontrol of grapevine downy mildew: A Synthetic Microbial Community (SynCom) approach

Culturomic approaches, involving the use of a range of different culture conditions coupled with a high-throughput method of identification, are recommended to isolate and identify microorganisms in environmental samples. In the case of plant samples, a number of studies have shown that microorganism cultivability can be increased by using plant-based culture media rather than conventional media that contain chemically synthesized or animalbased extracts. Being able to access this microbial biodiversity is crucial to the development of microbial biocontrol for plant diseases. Particularly in vineyards, where the majority of fungicide treatments target two major pathogens, the oomycete Plasmopara viticola that causes downy mildew and the fungus Erysiphe necator that causes powdery mildew, the development of new microbial biocontrol products is expected to reduce fungicide use. Tapping into the existing reservoir of naturally occurring disease biocontrol agents and growth-promoting microorganisms associated with grapevines is the first step to formulate effective biocontrol products and move towards more sustainable viticulture.This study aimed to use a culturomic approach to build a collection of grapevine foliar microorganisms which can subsequently be used to assemble Synthetic Microbial Communities (SynComs) for biocontrol of downy mildew. Alongside three conventional culture media, we developed a grapevine leaf-based culture medium to cultivate epiphytic and endophytic bacteria, yeast and filamentous fungi. Overall, we isolated 1090 microorganisms, including 543 bacteria, 243 yeast/yeast-like fungi and 304 filamentous fungi. Using MALDI-TOF MS and Sanger sequencing, we were able to identify 88 % of the isolates with 91 total genera identified across the 4 culture media used. Using the grapevine leaf-based culture medium enabled the cultivation of 4 genera of bacteria, 1 yeast genus and 12 genera of filamentous fungi that were not seen on the other media. We proceeded to build a SynCom of 42 isolates, selecting candidates from the collection that were either known to be representative of the natural grapevine leaf microbiota or to have biocontrol activity against downy mildew or other plant diseases. In vitro confrontation tests on leaf discs revealed that the SynCom significantly reduced downy mildew symptoms. Over a hundred subsets of the whole SynCom were then tested against Plasmopara viticola to test hypotheses on the effect of community diversity and composition on leaf colonization as well as resistance to invasion by the pathogen. These findings could be useful in informing the design of eventual commercial multi-strain biocontrol products.

ano.nymous@ccsd.cnrs.fr.invalid (Aarti D Jaswa) 13 Jul 2026

https://hal.science/hal-05690913v1

[hal-04572831] Biology-Informed inverse problems for insect pests detection using pheromone sensors

Most insects have the ability to modify the odor landscape in order to communicate with their conspecies during key phases of their life cycle such as reproduction. They release pheromones in their nearby environment, volatile compounds that are detected by insects of the same species with exceptional specificity and sensitivity. Efficient pheromone detection is then an interesting lever for insect pest management in a precision agroecological culture context. A precise and early detection of pests using pheromone sensors offers a strategy for pest management before infestation. In this paper, we develop a biology-informed inverse problem framework that leverages temporal signals from a pheromone sensor network to build insect presence maps. Prior biological knowledge is introduced in the inverse problem by the mean of a specific penalty, using population dynamics PDE residuals. We benchmark the biological-informed penalty with other regularization terms such as Tikhonov, LASSO or composite penalties in a simplified toy model. We use classical comparison criteria, such as target reconstruction error, or Jaccard distance on pest presence-absence. But we also use more task-specific criteria such as the number of informative sensors during inference. Finally, the inverse problem is solved in a realistic context of pest infestation in an agricultural landscape by the fall armyworm (Spodoptera frugiperda).

ano.nymous@ccsd.cnrs.fr.invalid (Thibault Malou) 28 Jan 2025

https://hal.inrae.fr/hal-04572831v3

[hal-03777604] Pest detection by inversion of a pheromone dispersion model

One third of the annual world's crop production is directly or indirectly damaged by insects. Early detection of invasive insect pests is key for optimal treatment before infestation. Existing detection devices are based on pheromone traps: attracting pheromones are released to lure insects into the traps, with the number of captures indicating the population levels. Promising new sensors are now available to directly detect pheromones produced by the pests themselves and dispersed in the environment. Tracing the source of pheromone emission would allow locating the pest's habitat and performing pesticide-free elimination treatments, in a precision agriculture context. We formalized a 3D diffusion-convection model of pheromone concentration dispersion in the environment that include vegetation-dependant pheromone settling coefficients, in agreement with existing chemical transport models [1]. This model is converted into a 2D reaction-diffusion-convection model after integration. A sensitivity analysis of this direct dispersion (forward) model is performed. An inverse (backward) model is then derived to identify the sources of pheromone emission from signals produced by sensors spatially positioned in the landscape. A priori biological knowledge on pest behaviour (favourite habitat, insect clustering for reproduction...) is introduced to constrain the inverse problem towards biologically relevant solutions. The accuracy of the inverse solution is assessed on simulated noisy data. This work was carried out with the financial support of the French Research Agency (ANR), Pherosensor project (https://pherosensor.inrae.fr/).

ano.nymous@ccsd.cnrs.fr.invalid (Thibault Malou) 14 Sep 2022

https://hal.science/hal-03777604v1

[hal-04481765] Pest detection from a biology-informed inverse problem and pheromone sensors

One third of the annual world's crop production is directly or indirectly damaged by insects. Early detection of invasive insect pests is key for optimal treatment before infestation. Existing detection devices are based on pheromone traps: attracting pheromones are released to lure insects into the traps, with the number of captures indicating the population levels. Promising new sensors are on development to directly detect heromones produced by the pests themselves and dispersed in the environment. Inferring the pheromone emission would allow locating the pest's habitat, before infestation. This early detection enables to perform pesticide-free elimination treatments, in a precision agriculture framework. In order to identify the sources of pheromone emission from signals produced by sensors spatially positioned in the landscape, the inference of the pheromone emission (inverse problem) is performed. Classical inference is conducted by combining the data and the so-called direct model [1]. In the present case, this entails combining the data from the pheromone sensors and the pheromone concentration dispersion that is a 2D reaction-diffusion-convection model [2]. In the proposed method, the inference involves not only the coupling of the pheromone dispersion model with the pheromone sensors data but also incorporates a priori biological knowledge on pest behaviour (favourite habitat, insect clustering for reproduction, population dynamic behaviour...). This information is introduced to constrain the inverse problem towards biologically relevant solutions. Different biology-informed constraints are tested, and the accuracy of the solutions of the inverse problems is assessed on simulated noisy data. [1] Bocquet, M. (2014). Introduction to the Principles and Methods of Data Assimilation in the Geosciences. Lectures note. [2] Stockie, J.M. (2011). The Mathematics of Atmospheric Dispersion Modeling. SIAM Review.

ano.nymous@ccsd.cnrs.fr.invalid (Thibault Malou) 28 Feb 2024

https://hal.science/hal-04481765v1

[hal-05613501] From Concept to Perspective: Digital Twins of Microbial Systems

Digital twins (DTs) are increasingly recognized across diverse sectors for their capacity to enhance the control, efficiency, and comprehension of the physical or biological systems they represent. For microbial systems, DTs could allow model-guided improvements of the services provided by the microbial communities in the agrifood chain. While DTs definitions are generally built on the same core idea of bi-directional exchanges between digital and physical counterparts, where realtime data feeds digital models and model-driven insights guide the real system, a wide variety of definitions of what is a DT still co-exist across domains. This variability underscores the need for a clear, system-specific definition of DTs for microbial ecosystems. In this perspective paper, we propose a conceptual framework for microbial system digital twins (MSDTs), defined as a collection of models dynamically linked to the microbiological system through in-line, at-line or off-line data and control flows. We illustrate this framework with examples spanning environmental, bioprocess, plant, animal, food, and human microbial systems, in a One Health perspective. For each ecosystem, we explore the potential applications of MSDTs. We also identify the scientific challenges that remain in experiments, bioinformatics, data science, modeling, control and microbial ecosystem engineering to build accurate MSDTs. We advocate for the development of MSDT in laboratory settings, as a catalyst for interdisciplinary sciences, and we stress practical and ethical issues preventing the generalization of MSDT for large-scale applications. However, high-tech MSDTs in laboratory environments may pave the way for low-tech, generalizable microbial solutions for improved ecosystemic microbial services.

ano.nymous@ccsd.cnrs.fr.invalid (Simon Labarthe) 06 May 2026

https://hal.inrae.fr/hal-05613501v1

[hal-05421240] Comparative genomic analysis of QTL for resistance to Aphanomyces euteiches between pea, lentil, faba bean, and the model species Medicago truncatula

Key message: QTL mapping and GWAS detected resistance QTL to Aphanomyces euteiches in faba bean, lentil, and Medicago truncatula. Weak genomic conservation between resistance QTL was identified between these legumes and pea. Abstract: QTL mapping and GWAS detected resistance QTL to Aphanomyces euteiches in faba bean, lentil, and Medicago truncatula. Weak genomic conservation between resistance QTL was identified between these legumes and pea. Aphanomyces root rot, caused by Aphanomyces euteiches, is a damaging disease affecting various legume species. Quantitative trait loci (QTL) for partial resistance have been mainly identified in pea, and to a lesser extent in lentil and Medicago truncatula. This study aimed to identify novel resistance loci from available lentil and faba bean populations, and examine genomic conservation of resistance QTL across legume host species. QTL mapping in the Pop2 faba bean recombinant inbred line (RIL) population and genome-wide association study (GWAS) in the AGILE lentil diversity panel were performed for resistance to A. euteiches under controlled conditions, using genotyping data previously reported. A previous QTL mapping in the LR3 M. truncatula RIL population was updated using 1,536 new SNPs (single-nucleotide polymorphisms). Synteny between resistance QTL to A. euteiches was analyzed based on gene orthology in QTL regions projected onto genomes, using the OrthoLegKB graph database. Four loci, including a major-effect QTL on chromosome 3, Ae-Vf3.1, were associated with resistance in faba bean. In lentil, six minor-effect GWAS-SNPs and two favorable haplotypes at Ae-Lc1.1 and Ae-Lc2.1 loci were identified. Updated analyses in M. truncatula narrowed to 8 Kb the interval of the major-effect locus AER1 and revealed three candidate genes. No synteny between major-effect QTL, detected in this study or previously reported in the literature, was identified across grain legume genomes. These results pave the way for translational genomics approaches facilitating resistance gene discovery and for resistance QTL deployment strategies in legume rotations to preserve their durability.

ano.nymous@ccsd.cnrs.fr.invalid (Théo Leprévost) 10 Aug 2026

https://hal.science/hal-05421240v1

[hal-04644219] Reducing chemical inputs in agriculture requires a system change

Many countries have implemented policies to reduce the use of chemical inputs in agriculture. However, these policies face many obstacles that limit their effectiveness. The purpose of this paper is to review the main challenges associated with reducing chemical inputs in agriculture and to propose potential solutions. Our analysis, based on a literature review linking agronomy and economics, shows that several agronomic options have proven effective in reducing chemical inputs or mitigating their negative impacts. We argue that the organization of the agri-food system itself is a major barrier to their implementation. Involving all stakeholders, from the chemical input industry to consumers, and designing appropriate policy frameworks are key to address this issue. We recommend combining different policy instruments, such as standards, taxes and subsidies, in a simplified and coherent way to increase effectiveness and ensure better coordination in the adoption of sustainable practices.

ano.nymous@ccsd.cnrs.fr.invalid (Thierry Brunelle) 11 Jul 2024

https://hal.science/hal-04644219v1

[hal-05725262] Occurrence of Fusarium proliferatum and Fusarium oxysporum in garlic throughout the crop cycle and in surrounding potential reservoirs

Fusarium dry rot (FDR) is a major threat to garlic in all production areas. In France, Fusarium proliferatum (Fp) and F. oxysporum (Fox) are the primary pathogens responsible for symptoms appearing during bulbs storage. A better understanding of the mechanism underlying the disease development could help in developing strategies for managing FDR. This study evaluates the occurrence of Fp and Fox in garlic tissues throughout the crop cycle and the impact of alternative treatments on their prevalence. Additionally, environmental reservoirs – including air, rainwater, soil, and crops grown in rotation with garlic – were surveyed to determine their potential as inoculum sources. The presence of Fp and Fox in garlic and in environmental samples was assessed using three detection methods: microbial isolations, loop-mediated isothermal amplification, and droplet digital PCR. Glasshouse and field trials demonstrated that Fp and Fox remain present in garlic tissues throughout the crop cycle. Although newly formed tissues showed no symptoms, at least 70% of new bulbs and 89% of bulbils harboured these fungi at harvest. After two months of storage, over 85% of asymptomatic cloves tested positive for Fp. These results confirm the ability of Fp and Fox to live as endophytes in garlic. Furthermore, the treatments tested (biocontrol and UV-C) had no significant impact on the presence of the fungi or on post-harvest symptoms. Fp was infrequently detected in the air, rainwater, soil, and crops grown in rotation with garlic, indicating that these are not the primary sources of inoculum; rather, garlic cloves are the major source.

ano.nymous@ccsd.cnrs.fr.invalid (Christel Leyronas) 24 Aug 2026

https://hal.inrae.fr/hal-05725262v1

[hal-05719855] A Highly Expressed Odorant Receptor Detects the Aggregation Pheromone Rhynchophorol in the Invasive American Palm Weevil

ABSTRACT Communication via aggregation pheromones is responsible for the behavioural and ecological characteristics of many species of weevils (Coleoptera). In insects, pheromones are detected by specialized odorant receptors (ORs), called pheromone receptors (PRs), which are usually highly expressed in olfactory sensory neurons localized in the antennae. Yet, PRs in Coleoptera remain understudied, which limits our understanding of their response characteristics and potential multiple evolutionary origins. In this study, we search for PRs in the American palm weevil, Rhynchophorus palmarum , a pest species that poses a major threat to oil palm and coconut production in the Americas, for which no PR responding to its aggregation pheromone (2E)‐6‐methyl‐2‐hepten‐4‐ol (rhynchophorol) has been characterized. Combining published RNA‐seq data with new data generated in this study, we identified two ORs highly expressed in the weevil antennae that represent strong candidate aggregation PRs. Sequence‐based binding pocket prediction revealed overall structural similarity between these two ORs, but amino acid differences were identified, suggesting functional divergence. Using the Xenopus oocyte heterologous expression system, we demonstrated that RpalOR32 displayed specificity and strong sensitivity to the aggregation pheromone rhynchophorol, with minor responses to several structurally related compounds, while RpalOR25 showed no responses to pheromones or host plant volatiles. The newly identified PR in R. palmarum appeared phylogenetically distant from the aggregation PR previously identified in the related species R. ferrugineus , confirming the independent origin of weevil PRs, even at the genus level.

ano.nymous@ccsd.cnrs.fr.invalid (Sai Zhang) 21 Aug 2026

https://hal.inrae.fr/hal-05719855v1

[hal-04590908] Développement et validation d'une méthode d'évaluation de la durabilité des exploitations agricoles. IDEA4, ses outils et ses usages

Le projet ACTION a validé l’usage de la méthode IDEA4 (Indicateurs de Durabilité d’une Exploitation Agricole version 4) avec trois résultats majeurs : 1) sa capacité à être utilisée pour différents usages (enseignement, recherche conseil, accompagnement, action publique) et pour la majorité des systèmes (grandes cultures, élevages, arboriculture, viticulture et maraîchage), 2) son opérationnalité avec ses trois outils libres d’accès (calculateur Excel, IDEATools et plateforme WEB-IDEA), 3) la création d’une large communauté collaborative d’environ 300 utilisateurs d’IDEA4 (conseillers, enseignants, chercheurs et agriculteurs) ayant réalisé un peu plus de 800 diagnostics d’exploitation. Dans l’enseignement, sa double lecture de la durabilité (3 dimensions et 5 propriétés de la durabilité) renouvelle sa capacité pédagogique. En recherche, IDEA4 élargit les connaissances sur la durabilité des transitions. La future plateforme WEB- IDEA 2.0 ouvre la voie de l’open data national des données de la durabilité de la Ferme France.

ano.nymous@ccsd.cnrs.fr.invalid (Frédéric Zahm) 28 May 2024

https://hal.inrae.fr/hal-04590908v1

[hal-03834661] Single seed microbiota: assembly and transmission from parent plant to seedling

The seed acts as the primary inoculum source for the plant microbiota. Understanding the processes involved in its assembly and dynamics during germination and seedling emergence has the potential to allow for the improvement of crop establishment. Changes in the bacterial community structure were tracked in 1,000 individual seeds that were collected throughout seed developments of beans and radishes. Seeds were associated with a dominant bacterial taxon that represented more than 75% of all reads. The identity of this taxon was highly variable between the plants and within the seeds of the same plant. We identified selection as the main ecological process governing the succession of dominant taxa during seed filling and maturation. In a second step, we evaluated the seedling transmission of seed-borne taxa in 160 individual plants. While the initial bacterial abundance on seeds was not a good predictor of seedling transmission, the identities of the seed-borne taxa modified the phenotypes of seedlings. Overall, this work revealed that individual seeds are colonized by a few bacterial taxa of highly variable identity, which appears to be important for the early stages of plant development.

ano.nymous@ccsd.cnrs.fr.invalid (Guillaume Chesneau) 05 Sep 2024

https://hal.inrae.fr/hal-03834661v1

[hal-04982331] Biology-Informed inverse problems for insect pests detection using pheromone sensors

Most insects have the ability to modify the odor landscape in order to communicate with their conspecies during key phases of their life cycle such as reproduction. They release pheromones in their nearby environment, volatile compounds that are detected by insects of the same species with exceptional specificity and sensitivity. Efficient pheromone detection is then an interesting lever for insect pest management in a precision agroecological culture context. A precise and early detection of pests using pheromone sensors offers a strategy for pest management before infestation. In this paper, we develop a biology-informed inverse problem framework that leverages temporal signals from a pheromone sensor network to build insect presence maps. Prior biological knowledge is introduced in the inverse problem by the mean of a specific penalty, using population dynamics PDE residuals. We benchmark the biological-informed penalty with other regularization terms such as Tikhonov, LASSO or composite penalties in a simplified toy model. We use classical comparison criteria, such as target reconstruction error, or Jaccard distance on pest presence-absence. But we also use more task-specific criteria such as the number of informative sensors during inference. Finally, the inverse problem is solved in a realistic context of pest infestation in an agricultural landscape by the fall armyworm (Spodoptera frugiperda).

ano.nymous@ccsd.cnrs.fr.invalid (Thibault Malou) 07 Mar 2025

https://hal.science/hal-04982331v1

[hal-04206539] Be high on emotion: Coping with emotions and emotional intelligence when querying data

Emotional Intelligence (EI) is the capacity to use emotions to properly guide our actions. In this paper, we adopt the EI approach to explore the interplay between data, emotions, and actions, thus lying the foundations for an emotional approach to querying. The framework we propose relies on a four-layer model that describes (i) how emotions are connected to each other, (ii) which data may give rise to emotions, (iii) which emotions will be triggered in each user when seeing each piece of data, and (iv) which actions will be done as a consequence. The application scenario we propose for our framework is that of Business Intelligence, specifically, of a set of KPIs connected to the users' goals. To illustrate our proposal, we introduce a working example in the field of e-commerce and use the Datalog syntax to formalize it.

ano.nymous@ccsd.cnrs.fr.invalid (Sandro Bimonte) 13 Sep 2023

https://hal.inrae.fr/hal-04206539v1

[hal-04072544] Logical design of multi-model data warehouses

Multi-model DBMSs, which support different data models with a fully integrated backend, have been shown to be beneficial to data warehouses and OLAP systems. Indeed, they can store data according to the multidimensional model and, at the same time, let each of its elements be represented through the most appropriate model. An open challenge in this context is the lack of methods for logical design. Indeed, in a multi-model context, several alternatives emerge for the logical representation of dimensions and facts. The goal of this paper is to devise a set of guidelines for the logical design of multi-model data warehouses so that the designer can achieve the best trade-off between features such as querying, storage, and ETL. To this end, for each model considered (relational, document-based, and graph-based) and for each type of multidimensional element (e.g., non-strict hierarchy) we propose some solutions and carry out a set of intra-model and inter-model comparisons. The resulting guidelines are then tested on a case study that shows all types of multidimensional elements.

ano.nymous@ccsd.cnrs.fr.invalid (Sandro Bimonte) 07 Aug 2023

https://hal.inrae.fr/hal-04072544v1

[hal-04848563] Tailored policies for perennial woody crops are crucial to advance sustainable development

Perennial woody crops, which are crucial to our diets and global economies, have the potential to play a major role in achieving multiple UN Sustainable Development Goals pertaining to biodiversity conservation, socio-economic development and climate change mitigation. However, this potential is hindered by insufficient scientific and policy attention on perennial woody crops, and by the intensification of perennial crop cultivation in the form of monocropping with high external inputs. In this Perspective, we highlight the potential of properly managed and incentivized perennial woody crops to support holistic sustainable development and urge scientists and policymakers to develop an effective agenda to better harness their benefits.

ano.nymous@ccsd.cnrs.fr.invalid (Carlos Martinez-Nuñez) 19 Dec 2024

https://hal.science/hal-04848563v1

[hal-05567992] The red palm weevil chemical ecology in the OMICS and post-genomic eras

[...]

ano.nymous@ccsd.cnrs.fr.invalid (Emmanuelle Jacquin-Joly) 26 Mar 2026

https://hal.inrae.fr/hal-05567992v1

[hal-05567453] Plam weevil odorant receptors: Omics, functional characterization, and evolution

The Red Palm Weevil, Rhynchophorus ferrugineus (Olivier), is the most destructive and invasive insect pest of palm trees worldwide. The weevils synchronizes mass gathering on palm trees for feeding and mating, regulated by a male-produced pheromone. As an environmental-friendly control solution, this pheromone is used in blend with plant volatile compounds as synergists to trap weevils for population monitoring and mass trapping. However, the molecular bases of the red palm weevil olfactory mechnisms are still poorly understood. To fullfil this gap, we generated omics data using Illumina and PacBio, and manually curated chemosensory genes, especially chemosensory receptors. In insects, chemosensory receptors include three main families, the odorant receptors (ORs) involved in volatile detection at a distance or close range, the gustatory receptors (GRs) involved in detection at contact, and the ionotropic receptors (IRs) involved in olfaction and taste. Manual curation allowed us to annotate an impressive number of IRs, the highest number of IRs described in Coleoptera so far. We identified less GRs than reported earlier, and extended the previously described repertoire of ORs. We evidenced tandem duplication of key ORs, whose function could be addressed by heterologous expression in Drosophila neurons coupled to single-sensillum recording and extensive screenings of volatile organic compounds. The observed response spectra led us to proposing a scenario for OR functional specialization. Our collection of curated chemosensory genes constitutes a valuable resource for such functional characterization, and our functional data pinpoint interesting volatiles to be included in olfactory-based control strategies of this weevil.

ano.nymous@ccsd.cnrs.fr.invalid (Emmanuelle Jacquin-Joly) 25 Mar 2026

https://hal.inrae.fr/hal-05567453v1

[hal-05567471] Red palm weevil omics bring insights into its chemical ecology and the evolution of Coleoptera pheromone receptors

[...]

ano.nymous@ccsd.cnrs.fr.invalid (Nicolas Montagné) 25 Mar 2026

https://hal.inrae.fr/hal-05567471v1

[hal-04191716] Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case on grain legumes

While the continuing decline in genotyping and sequencing costs has largely benefited plant research, some key species for meeting the challenges of agriculture remain mostly understudied. As a result, heterogeneous datasets for di erent traits are available for a significant number of these species. As gene structures and functions are to some extent conserved through evolution, comparative genomics can be used to transfer available knowledge from one species to another. However, such a translational research approach is complex due to the multiplicity of data sources and the non-harmonized description of the data. Here, we provide two pipelines, referred to as structural and functional pipelines, to create a framework for a NoSQL graph-database (Neo j) to integrate and query heterogeneous data from multiple species. We call this framework Orthology-driven knowledge base framework for translational research (Ortho_KB). The structural pipeline builds bridges across species based on orthology. The functional pipeline integrates biological information, including QTL, and RNA-sequencing datasets, and uses the backbone from the structural pipeline to connect orthologs in the database. Queries can be written using the Neo j Cypher language and can, for instance, lead to identify genes controlling a common trait across species. To explore the possibilities o ered by such a framework, we populated Ortho_KB to obtain OrthoLegKB, an instance dedicated to legumes. The proposed model was evaluated by studying the conservation of a flowering-promoting gene. Through a series of queries, we have demonstrated that our knowledge graph base provides an intuitive and powerful platform to support research and development programmes.

ano.nymous@ccsd.cnrs.fr.invalid (Baptiste Imbert) 30 Aug 2023

https://hal.inrae.fr/hal-04191716v1

[hal-04130857] Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case on grain legumes

Legumes, and especially pulses, are an important source of protein for food and feed, and are appreciated for their positive impact on the “one health”. However, their unstable yields and their susceptibility to biotic and abiotic stresses highlight the need for varietal improvement in order to increase the cultivated areas and productivity. With the advent of sequencing technologies, a large pool of genetic and -omics resources, heterogeneous at the inter- and intra-species scale, is emerging. Thus, it is important to capitalize on these scattered heterogeneous data to develop translational research to boost breeding projects and crop diversification. To meet this need, we undertook the development of the Orthology-driven knowledge base framework for translational research (Ortho_KB). For a set of species of interest, it infers orthologous relationships between genes, proposes associated syntenic blocks between chromosomes and creates a graph database linking genetic and RNA-seq data. To explore the possibilities of this framework, we populated Ortho_KB to obtain OrthoLegKB, an instance dedicated to legumes. This database includes four cultivated crops, namely Pisum sativum, Vicia faba, Lens culinaris and Vigna radiata, and the model legume Medicago truncatula. Available information on quantitative trait loci (QTL) for multiple traits are being integrated as well as expression data. The proposed database model was evaluated by studying the conservation of a flowering-promoting gene

ano.nymous@ccsd.cnrs.fr.invalid (Baptiste Imbert,) 16 Jun 2023

https://hal.inrae.fr/hal-04130857v1

[hal-05567958] The red palm weevil Rhynchophorus ferrugineus in the OMICS and post-genomic eras

[...]

ano.nymous@ccsd.cnrs.fr.invalid (Stéphanie Robin) 26 Mar 2026

https://hal.inrae.fr/hal-05567958v1

[hal-05587455] A new genome assembly of the pea cultivar ‘Caméor’ provides resources for functional genomics and genetics

Significant improvements in sequencing technologies have allowed the development of more contiguous genome assemblies in many plant species. The pea genome is characterized by its richness in repeated elements and its long and complex centromeres. This makes its assembly challenging. In this paper, we present an improved version of the genome sequence of the French cultivar ‘Caméor’. This sequence was obtained by combining Nanopore and PacBio long-read sequencing, Hi-C contact maps and Bionano maps. The assembly of centromeres was refined using a combination of FISH and ultra-long Nanopore read analyses. Overall, Cameor_v2 genome assembly is a highly continuous pea genome assembly with small total gap size and a large contig N50. In this version, the orientation of chromosomes was revised according to internationally accepted karyotype rules. Gene annotation statistics indicated a high completeness of gene sequences, with most gene sequences with 3’ and 5’ UTR. This genome assembly with its associated data constitute a useful resource for pea genetics, comparative mapping and functional genomics.

ano.nymous@ccsd.cnrs.fr.invalid (Jonathan Kreplak) 30 Jul 2026

https://hal.inrae.fr/hal-05587455v1

[hal-05249655] Promotion of Translational Research in Plants by the Development of a Knowledge Graph Framework: A case Study on Grain Legumes

With global population growth, climate change and evolving regulations on the use of pesticides herbicides, researchers and breeders must adapt and accelerate crop improvement to meet the challenges ahead. Major crops have benefited from genomic efforts, which have enabled the identification of key genetic drivers that can be rapidly implemented to ensure food security. Thanks to translational research, less studied crops, including some legumes, can benefit from both the wealth of research and, in particular, the knowledge available from closely related crops or species. This requires the correct identification of functional orthologs, the retrieval of available data and knowledge, and the linking of diverse heterogeneous data, which becomes more difficult as the number of species increases. To facilitate this process of translational research, we have developed two pipelines, namely the structural and the functional pipeline, to create a framework for a NoSQL graph database (Neo4j) to integrate and query heterogeneous data from multiple species. The structural pipeline identifies orthologous genes and syntenic chromosomal regions to highlight functional orthologs that serve as bridges between species for knowledge transfer. The functional pipeline integrates published and unpublished biological information, including quantitative trait loci (QTL) and RNA-seq datasets, and uses the backbone from the structural pipeline to connect orthologs in the database. The constructed graph, called Ortho_KB and its instance for legumes OrthoLegKB, can be queried to make quasi-instantaneous use of the included datasets. This platform can be useful, for example, for comparing current knowledge on complex genetic traits, checking the conservation of genes of interest within QTL intervals, crossing information on gene expression profiles or suggesting pleiotropy.

ano.nymous@ccsd.cnrs.fr.invalid (Baptiste Imbert) 11 Sep 2025

https://hal.inrae.fr/hal-05249655v1

[hal-05709975] Progressing toward agroecology in vineyards through systemic innovation

Viticulture is facing major challenges, and agroecology is recognized as an innovative approach to enhance food system sustainability. However, knowledge is lacking about how winegrowers design innovations to support agroecology, which limits the ability of farmers and advisers to effectively steer and assess progress toward agroecology. This study aims to develop a tool to assess the agroecology level of vineyards, and to investigate the link between progress in the agroecological transition and the systemic and farm-scale reasoning of innovations. To this end, we interviewed 24 winegrowers, developed a table to characterize the agroecology level of the farms and identified the farmers’ agronomic rationales. Agroecology levels varied widely among the surveyed farms. The agroecology elements of synergy, efficiency, and a circular and solidarity-based economy explained most of the differences between farms at the extreme ends of the score ranges. We used semi-quantitative and qualitative indicators to highlight systemic reasoning in highly agroecological farms. The winegrowers from the most agroecological farms changed their practices more frequently, mainly by implementing practices that rely on system reorganization and redesign and by addressing a wider variety of results when changing their practices. The analysis of these farms revealed several success factors, including the adjustment of other practices after a change, careful observation of the agroecosystem, and a paradigm shift involving long-term reflection on practice effects. Moreover, successful farms are smaller, and have often reduced land areas to gain increased flexibility in production factors. They seek autonomy regarding inputs and promote synergies with respect to the farm’s different business activities. This work provides valuable support to winegrowers and advisers by offering them a simple tool to track the progress of vineyards when transitioning to a more agroecological system. This study also identifies key traits of agroecological farms that can inspire and be adopted on other farms.

ano.nymous@ccsd.cnrs.fr.invalid (Elsa Robelot) 03 Aug 2026

https://hal.inrae.fr/hal-05709975v1

[hal-05682255] Towards lucerne varieties used as living mulch for cereal crops in agroecological systems

Lucerne, a perennial legume known for its nitrogen fixation, persistence, and soil-covering capacity, shows strong potential as a living mulch for cereal cropping. However, its vigorous growth often results in excessive competition with cash crops. The selection of lucerne varieties adapted to living mulch could be a solution to reduce this competition. We synthetize the state of the art on this subject. Wheat–lucerne interactions occur from the earliest stages of wheat cycle until its harvest and are mainly driven by lucerne morphological and phenological traits. Autumn dormancy, growth habit, height, and cover state of lucerne determine the trade-off between reducing competition with wheat and maintaining the ecosystem services provided by lucerne. An intermediate dormancy, combined with moderate height and upright cover, appears to provide the most favourable balance. Genetic correlations between traits measured in spaced plants and living mulch conditions reveal that some traits, such as height, remain stable across designs, whereas others are highly design-dependent. This supports a two-step breeding strategy combining early indirect selection in nursery of spaced plants with an indirect selection under living mulch conditions. Finally, molecular markers used for genomic prediction could accelerate the identification of genotypes suited for living mulch systems. This knowledge can be used to create dedicated varieties.

ano.nymous@ccsd.cnrs.fr.invalid (Zineb El Ghazzal) 06 Jul 2026

https://hal.inrae.fr/hal-05682255v1

[hal-04900081] When nudges backfire: evidence from a randomised field experiment to boost biological pest control

Nudges are increasingly used to alter the behaviour of economic agents as an alternative to monetary incentives. However, little is known as to whether nudges can backfire, that is, how and when they may generate effects opposite to those they intend to achieve. We provide the first field evidence of a nudge that is designed to encourage pro-environmental behaviour, which instead backfires. We randomly allocate a social comparison nudge inviting wine-growers to adopt biological pest control as an alternative to chemical pesticide use. We find that our nudge decreases by half the adoption of biological pest control among the largest vineyards, where the bulk of adoption occurs. We show that this result can be rationalised in an economic model where wine-growers and wine-grower cooperative managers bargain over future rents generated by the adoption of biological pest control. This study highlights the importance of experimenting on a small scale with nudges aimed at encouraging adoption of virtuous behaviours in order to detect unexpected adverse effects, particularly in contexts where negotiations on the sharing of the costs of adoption are likely to occur.

ano.nymous@ccsd.cnrs.fr.invalid (Sylvain Chabé-Ferret) 20 Jan 2025

https://brgm.hal.science/hal-04900081v1

[hal-05353058] Digital droplet PCR quantification and field-scale spatial distribution of Plasmopara viticola oospores in vineyard soil

Grapevine downy mildew, caused by the oomycete Plasmopara viticola, is one of the most devastating diseases affecting grapevine worldwide. Primary inoculum (i.e., oospores) plays a decisive role in downy mildew epidemics, but we still know very little about its abundance in vineyard soil. This study presents a novel molecular method for quantifying P. viticola oospore concentration in vineyard soil using digital droplet PCR (ddPCR). The development of this method enabled the characterization of both the abundance and spatial distribution of oospores in a vineyard at the onset of the growing season. Following a regular grid, a total of 198 soil samples (0-15 cm horizon) were collected in March 2022 in grapevine rows in a 0.22 ha vineyard planted with cv. Merlot and conducted according to French organic viticulture specifications. Additional samples were collected from the same field within five nested sampling plots with three distance levels, including samples collected in the inter-rows. Using ddPCR, we found P. viticola DNA in all soil samples except one, and we estimated that oospore concentration ranged from 0 to 1,858 oospores per gram of soil (303 ± 308 on average). The distribution of oospores at field scale was not random but characterized by 15-m diameter patches of concentrically increasing oospore concentration. Oospores accumulated five times more below the vine stocks than in the inter-row. Using a leaf disc bioassay, we found that soil infectious potential significantly increased with oospore concentration assessed by ddPCR. However, the low coefficient of determination of the relationship indicated that DNA-based oospore quantification lacked clear epidemiologi cal significance. Both ddPCR and bioassay methods are valuable tools that could be used to assess reservoirs of P. viticola primary inoculum across different agroclimatic contexts, thereby bringing greater genericity. Further methodological improvement will also help refine the accuracy of DNA-based assessment of primary inoculum reservoir and improve our understanding of the relationship between primary inoculum reservoir and epidemic dynamics. Ultimately, these data will be essential for improving epidemic risk models and evaluating new preventive disease management strategies targeting the primary inoculum.IMPORTANCE Grapevine downy mildew caused by the oomycete Plasmopara viticola affects leaves and bunches and leads to important economic losses for viticulturists. Recently, evidence has accumulated that soilborne primary inoculum (i.e., oospores in the soil) importantly contributes to disease progress. The significance of our work is in presenting a direct and sensitive method for assessing soil oospore concentration, as well as quantitative and spatially explicit data on downy mildew primary inoculum. This opens the way to new research, the evaluation of new disease control strategies based on primary inoculum management and the improvement of epidemic risk models, which will potentially contribute to lower fungicide use in viticulture in fine.

ano.nymous@ccsd.cnrs.fr.invalid (Charlotte Poeydebat) 28 Jan 2026

https://hal.inrae.fr/hal-05353058v2

[hal-03850506] Neighbourhood effect of weeds on wheat root endospheric mycobiota

1. Micro-organisms associated with plants provide essential functions to their hosts, and therefore affect ecosystem productivity. Agricultural intensification has modified microbial diversity in the soil reservoir and may affect plant–microbial recruitment. Weeds develop spontaneously in crop fields, and could influence micro-organisms associated with crop plants through a neighbourhood effect. We explore the effect of weed species on crop plant microbiota as potentially auxiliary plants that affect agricultural productivity. 2. We combined field and controlled laboratory studies to analyse the neighbourhood effect of weeds on wheat root endospheric mycobiota (i.e. fungi within roots) and growth. First, we analysed the effect of weed species diversity and identity recorded in the neighbourhood of individual wheat plants on soil and wheat root mycobiota in the field. Second, we used a plant-matrix design in laboratory conditions to test the effect of weed identity (nine weed treatments) and their ability to transmit root mycobiota to wheat roots, and the resulting impact on wheat growth. 3. In contrast to soil mycobiota, we demonstrated that wheat root endospheric mycobiota was influenced by the diversity and identity of weeds developing in their 1 m2 neighbourhood. Wheat root endospheric microbiota strongly differs in terms of richness and composition depending on the neighbouring weed plant species. Weed species transmitted from 13% to 74% of their root microbiota to wheat roots depending on weed identity in controlled conditions. 4. Synthesis. Weed neighbours modified wheat plant performance, possibly as a result of competitive interactions and changes in microbiota. Our findings suggest that crop root mycobiota was variable and was modulated by their weed neighbourhood. Synergistic effects between mycobiota of crops and weeds could therefore contribute to soil biodiversity and sustainable agriculture.

ano.nymous@ccsd.cnrs.fr.invalid (Jie Hu) 31 May 2023

https://hal.inrae.fr/hal-03850506v1

[hal-05299472] Altered Behavioural Response of Whitefly (Bemisia tabaci) on Tomato Associated with Biocontrol Plants

The whitefly, Bemisia tabaci , is a significant pest in tomato production, causing extensive damage and economic losses. In pursuing sustainable pest management strategies, this study investigates the deterrent effects of Tagetes species ( T. erecta , T. patula , and T. minuta ) and Crotalaria juncea on B. tabaci settlement and oviposition on tomato plants. Two free dual-choice experimental setups were conducted in a climate-controlled chamber. The study confirmed the efficacy of the experimental setup, with similar B. tabaci dispersion and oviposition on the sides with tomato plants alone. When Tagetes or C. juncea was introduced, a significant reduction in B. tabaci settlement and oviposition was observed compared to the tomato control side. To identify the modes of action of the companion plants on B. tabaci , a follow-up experiment, modifying the spatial arrangement of the plants, was set up to discriminate between physical barrier and chemical repellent effects. The findings suggest a potential crossing between repellence and barrier effects for Tagetes species when C. juncea acted as a sinkhole, trapping the whiteflies. A DHS-ATD-GC-MS analysis revealed that the repellent effect seems more associated with the composition than the intensity of the blend. Some already known repellent volatile compounds of Tagetes , such as limonene, were identified, but the major ketone compounds must also be tested. This study demonstrates the effectiveness of Tagetes and Crotalaria species as biocontrol plants in pest management for tomato production. These plants reduce pest pressure and support sustainable agriculture, offering an alternative to chemical pesticides. Further research should investigate mechanisms, field applications, and broader agroecological benefits.

ano.nymous@ccsd.cnrs.fr.invalid (Cliven Njekete) 27 Jul 2026

https://hal.science/hal-05299472v1

[hal-05651321] A Modeling Approach to Separate Within-Leaf Pathogen Growth from Whole-Plant Pathogen Dispersal – A Case Study on Pea Fungal Diseases

Describing and predicting epidemic progress is critical for effective reduction of crop losses due to infectious diseases. Disease progression is commonly characterized using quantitative or semi-quantitative indicators of severity, influenced by both pathogen growth at the organ scale and its spread at the plant scale. Although these two processes cannot be disentangled from raw data alone, we developed a mechanistic model that, for the first time, distinguishes disease growth within organs from dispersal between organs. We fitted this model to a set of experimental data on the severity of foliar anthracnose and Ascochyta blight on four susceptible pea cultivars (Flambo, Hamino, Smiley, and Spencer) at five time points in pure stand plots or in plots intercropped with wheat under natural infection conditions. Disease spread and growth over thermal time (degree days) and space (leaf levels) was modeled by a two-variable logistic function, derived from an approximation of the traveling wave Fisher–KPP model solution. Results showed that the apparent diffusion speed of the disease varied across cultivars, years, and cropping systems and was consistently reduced under intercropping. By interpreting model parameters biologically, we identified apparent diffusion as a novel quantitative trait to characterize pathogen strategies and epidemic speed. This new metric offers plant pathologists and breeders a useful tool to better describe within-plant disease progression across environments and genotypes.

ano.nymous@ccsd.cnrs.fr.invalid (Manu Affichard) 10 Jun 2026

https://hal.science/hal-05651321v1

[hal-04478362] Évolutions réglementaires et adaptations en grandes cultures

L’utilisation de mélanges, qu’ils soient de variétés ou d’espèces, pose des questions en termes de réglementation, mais aussi de sélection, d’évaluation ou encore de commercialisation.

ano.nymous@ccsd.cnrs.fr.invalid (Virginie Bertoux) 26 Feb 2024

https://hal.science/hal-04478362v1

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Collection HAL

Consulter les publications scientifiques du PPR Cultiver et Protéger Autrement

HAL : Dernières publications

[hal-05652738] Spatio-temporal field, landscape and meteorological datasets describing bruchid beetle populations, grain damage and parasitism in faba bean and lentil fields in France

[hal-05697915] When machine learning extrapolates in space: How local data shape spatial transferability

[hal-05661572] Sequential area interaction sampling for early plant disease detection

[hal-05490031] A marked sequential point process for disease surveillance: Modeling and optimization

[hal-05695604] Assessing fruit tree vigor in peach and apple orchards through wood segmentation in ground-based RGB images

[hal-05627550] Intercropping chickpea with a competitive service plant and mowing the inter-rows controls weeds and ascochyta blight while mitigating interspecific competition

[hal-05642655] Rethinking grapevine downy mildew management: opportunities to disrupt the sexual cycle of the pathogen as a preventive disease control strategy

[hal-05681565] Quantitative resistance to aphanomyces root rot in legumes

[hal-03299446] Seed microbiota revealed by a large-scale meta-analysis including 50 plant species

[hal-05081398] A cross-systems primer for synthetic microbial communities

[hal-05738301] Assessing government subsidies for reducing pesticide use: A meta-analysis

[hal-05633888] Untargeted metabolomic dataset of leaves from twenty-four accessions of wild and cultivated tomato plants

[hal-04455685] Induction of common bean OVATE Family Protein 7 (PvOFP7) promotes resistance to common bacterial blight

[hal-04756712] dTALE approach demonstrates that induction of common bean OVATE Family Protein 7 (PvOFP7) promotes resistance to common bacterial blight

[hal-05723807] Extrapolation spatiale du risque de présence de Xylella fastidiosa basée sur XGBoost

[hal-04665509] A stage‐dependent seed defense response to explain efficient seed transmission of Xanthomonas citri pv. fuscans to common bean

[tel-05734808] Effets de la diversification et de la pérennisation des couverts végétaux sur les productions de blé et prairies et sur les cycles du carbone et de l'azote

[hal-05384699] Regardez sous vos pieds, ces sols vivants

[hal-05215187] A functional ecology approach to define a conceptual and participatory method for designing species mixtures: a case study on nitrogen cycling and weed control

[hal-05690913] Biocontrol of grapevine downy mildew: A Synthetic Microbial Community (SynCom) approach

[hal-04572831] Biology-Informed inverse problems for insect pests detection using pheromone sensors

[hal-03777604] Pest detection by inversion of a pheromone dispersion model

[hal-04481765] Pest detection from a biology-informed inverse problem and pheromone sensors

[hal-05613501] From Concept to Perspective: Digital Twins of Microbial Systems

[hal-05421240] Comparative genomic analysis of QTL for resistance to Aphanomyces euteiches between pea, lentil, faba bean, and the model species Medicago truncatula

[hal-04644219] Reducing chemical inputs in agriculture requires a system change

[hal-05725262] Occurrence of Fusarium proliferatum and Fusarium oxysporum in garlic throughout the crop cycle and in surrounding potential reservoirs

[hal-05719855] A Highly Expressed Odorant Receptor Detects the Aggregation Pheromone Rhynchophorol in the Invasive American Palm Weevil

[hal-04590908] Développement et validation d'une méthode d'évaluation de la durabilité des exploitations agricoles. IDEA4, ses outils et ses usages

[hal-03834661] Single seed microbiota: assembly and transmission from parent plant to seedling

[hal-04982331] Biology-Informed inverse problems for insect pests detection using pheromone sensors

[hal-04206539] Be high on emotion: Coping with emotions and emotional intelligence when querying data

[hal-04072544] Logical design of multi-model data warehouses

[hal-04848563] Tailored policies for perennial woody crops are crucial to advance sustainable development

[hal-05567992] The red palm weevil chemical ecology in the OMICS and post-genomic eras

[hal-05567453] Plam weevil odorant receptors: Omics, functional characterization, and evolution

[hal-05567471] Red palm weevil omics bring insights into its chemical ecology and the evolution of Coleoptera pheromone receptors

[hal-04191716] Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case on grain legumes

[hal-04130857] Development of a knowledge graph framework to ease and empower translational approaches in plant research: a use-case on grain legumes

[hal-05567958] The red palm weevil Rhynchophorus ferrugineus in the OMICS and post-genomic eras

[hal-05587455] A new genome assembly of the pea cultivar ‘Caméor’ provides resources for functional genomics and genetics

[hal-05249655] Promotion of Translational Research in Plants by the Development of a Knowledge Graph Framework: A case Study on Grain Legumes

[hal-05709975] Progressing toward agroecology in vineyards through systemic innovation

[hal-05682255] Towards lucerne varieties used as living mulch for cereal crops in agroecological systems

[hal-04900081] When nudges backfire: evidence from a randomised field experiment to boost biological pest control

[hal-05353058] Digital droplet PCR quantification and field-scale spatial distribution of <i>Plasmopara viticola</i> oospores in vineyard soil

[hal-03850506] Neighbourhood effect of weeds on wheat root endospheric mycobiota

[hal-05299472] Altered Behavioural Response of Whitefly (Bemisia tabaci) on Tomato Associated with Biocontrol Plants

[hal-05651321] A Modeling Approach to Separate Within-Leaf Pathogen Growth from Whole-Plant Pathogen Dispersal – A Case Study on Pea Fungal Diseases

[hal-04478362] Évolutions réglementaires et adaptations en grandes cultures