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Improving the prediction of soil organic carbon content using field-acquired hyperspectral data by accounting for soil moisture and surface roughness
No full textInternational audienceSoil surface conditions such as moisture, roughness, and vegetation complicate accurate Soil Organic Carbon (SOC) prediction by altering spectral reflectance. Most studies consider these factors separately and under controlled conditions. Soil roughness has rarely been included [1,2], and typically not alongside soil moisture, which has mostly been studied in laboratory settings [3]. Common methods to reduce moisture effects on spectra, such as external parameter orthogonalization (EPO) and direct standardization (DS), rely heavily on lab-based datasets [3]. To address this, we assessed the influence of soil moisture and surface roughness as co-variables in models predicting SOC content from reflectance spectra of bare Luvisols near Versailles, France. Spectral data were collected under naturallight at 76 points, along with volumetric soil moisture (θ) and 7 roughness indicators from photogrammetry [4]. SOC was predicted using Partial Least Squares Regression (PLSR) and Random Forest (RF), with 4-fold cross-validation repeated 10 times. Six wavelength-selection (WS) strategies were tested: two from satellite simulations (EnMAP, Sentinel-2), two from model variable importance (PLSR, RF), one expert-based, and one using all wavelengths. Moisture and roughness were added individually. In-field spectra enabled reasonably accurate predictions, with RF outperforming PLSR (SOC RMSE: 1.6–1.8 g.kg⁻¹). WS methods improved accuracy only when co-variables were added.Moisture had little effect, while roughness improved prediction quality in most cases, especially shadow percentage for PLSR and the semivariogram sill parameter for RF. These results highlight the benefit of including surface roughness to improve large-scale SOC prediction from remote sensing
Citizen-based identification of earthworm morphotypes: insights from a large-scale biodiversity monitoring network in France
No full textInternational audienceMonitoring soil biodiversity remains difficult, particularly due to the high spatial and temporal resolution required to accurately reflect the dynamics of soil communities in cultivated landscapes. Earthworms, as key soil organisms, are commonly used as indicators, but their identification in the field is constrained by the difficulty of assigning individuals to species without expert knowledge. As a result, classification into morphotypes is often used as a practical alternative. This study examines the reliability of such classification within the French ‘500 ENI’ (Non-Intended Effects) Monitoring Network, which involves annual sampling in agricultural plots, followed by expert verification of identifications. Using data from over 48,000 earthworms collected across more than 950 plots, we calculated two indicators to assess classification reliability: the misclassification rate (MR) and the undetected rate (UR). Results showed an average MR of 28% and an average UR of 32%, with substantial variation depending on morphotype. Endogeic individuals were classified more reliably than epigeic types and anecics (both red- and black-headed). The reliability of classification was strongly influenced by the sampler's experience as well as by community characteristics, particularly total abundance, proportion of adults, and morphotype diversity. Our findings emphasize the need for strengthened support for participants with limited experience. In particular, we recommend developing targeted training materials and decision aids to improve classification accuracy. Specific attention should be given to plots with low-density communities, few adults, or low morphotype diversity, where classification is most error-prone. Additionally, promoting sampling during periods with favorable conditions for earthworm activity and maturity could help improve both detection and reliability. These measures would contribute to increasing the robustness of large-scale biodiversity monitoring efforts relying on morphotype-based assessments
Mélange de processus de Dirichlet pour la détection de stades phénologiques par imagerie
No full textInternational audienceDans cette communication, nous proposons un couplage innovant entre l'apprentissage profond, représenté par un réseau de neurones convolutifs (CNN) classique, et les modèles de mélange de processus de Dirichlet (DPMM) dans le cadre de la détection automatique des stades phénologiques de croissance des plantules. Le réseau CNN sert à extraire des caractéristiques pertinentes des données d'entrée, ici des séquences d'images couleur RVB, et à les transformer dans un espace latent. Cet espace latent, qui contient des représentations compactes et informatives des données d'origine, est ensuite utilisé comme entrée pour le DPMM. Ce dernier exploite ces représentations pour effectuer des tâches de classification, en adaptant automatiquement le nombre de classes (stades phénologiques) en fonction de la complexité des données. Nous testons ce couplage CNN-DPMM sur diverses espèces de plantes (colza, tomate et pois) afin d'évaluer les performances de la méthod
Genetic and epigenetic selection signatures from pool sequencing expeiment
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Transgenerational transmission of an environmental modification in quails: changes in phenotypic variance components across three generations
No full textWhile epigenetic variations can contribute to shaping phenotypic diversity, it can be challenging to isolate and quantify the portion of trait variability under epigenetic influence. The present study compares the phenotypic response for different phenotypes of two epilines of Japanese quails ( Coturnix japonica ), with similar genetic structure across three generations following an initial genistein ingestion in the ancestors’ diet. Linear and linear mixed models were fitted to extract the fraction of variance allocated to multiple factors such as dam, family, sex, reproductive status and epiline. The latter was found to be significantly associated with body weight and with heart, abdominal fat and testicle weight adjusted by body weight. The proportion of phenotypic variance explained by the epiline progressively increased from the first generation (G0) to the last (G2), leading - for example in body weight at slaughter - to an average difference for adult males and females in G2 of 9 grams and 14 grams respectively, between genistein treated offspring (epi+) and controls (epi-). These findings suggest a possible transgenerational effect of the initial diet disruption. In tissue weights, production and behavioural traits, the effect of the epiline accounted for smaller fractions of phenotypic variability and overall large residual variances were observed, underlining the complex nature of the analysed traits. This innovative experimental design allowed for a characterization of the impact of transgenerational effects on a variety of phenotypic traits, which will be useful for prioritizing traits for future genetic and epigenetic association studies. Implications Nowadays, changes in the environment occur more frequently and livestock species can struggle to adapt to these rapid shifts. It is therefore important to understand the impact of the environment on animals. In this study, we evaluate how an initial modification in prior generations can also affect subsequent ones. By collecting different traits of interest (growth, tissues, production, and behaviour), we compare the response to a change in the ancestors diet across three successive generations. Our findings highlight the importance of considering the potential multi-generational effects of changes to the environment. This could provide guidelines for better poultry management in order to ensure animal welfare while maintaining sustainable production yields
Estimation des flux de commerce de fruits et légumes de l’Occitanie: Une approche gravitaire
No full textInternational audienceThe study of the relocation of food requires the availability of data at a sub-national level. Unfortunately, there is no knowledge of intra- and inter-regional agricultural and food trade flows. The objective of this work is to estimate the fruit and vegetables trade flows of the French Occitanie region over the period 2015-2019. Using a structural gravity model the authors estimate these flows within Occitanie as well as between Occitanie and the rest of France. Their results show that although Occitanie has strong trade in fruit and vegetables with the rest of France and abroad, its local trade flows are very low. Thanks to their results the authors compute the subsidy necessary to relocate a part of the region Occitanie’s fruit and vegetables production.L’étude de la relocalisation de l’alimentation nécessite l’existence de données à un niveau infranational. Or nous ne connaissons pas ou peu les flux commerciaux agricoles et alimentaires intra- et inter-régionaux. L’objectif de ce papier est d’estimer les flux de commerce de fruits et légumes de la région Occitanie sur la période 2015-2019. En utilisant un modèle de gravité structurel les auteurs estiment ces flux au sein de l’Occitanie ainsi qu’entre l’Occitanie et le reste de la France. Les résultats montrent que bien que l’Occitanie ait des échanges commerciaux de fruits et légumes intenses avec le reste de la France et l’étranger, ses flux de commerce locaux sont très faibles. Les auteurs en déduisent le montant de subvention nécessaire pour relocaliser une partie de la production de fruits et légumes dans la région Occitanie
Preface: ICFM9 – River Basin Disaster Resilience and Sustainability by All
No full textInternational audienceUnder the main theme of “River Basin Disaster Resilience and Sustainability by All: Integrated Flood Management in the Post-Corona Era”, the 9th International Conferenceon Flood Management (ICFM9) was held in Tokyo and Tsukuba, Japan, from 18 to 22 February 2023 with the participation of 394 flood experts from 41 countries and regions(212 from Japan, 100 from Asia, 78 from the rest of the world, including four unknown). During the event, 24 parallel sessions were organized, with 143 oral presentations inthe parallel sessions and 48 poster presentations under the following nine themes.....
Impact of Explanation Technique and Representation on Users' Comprehension and Confidence in Explainable AI
No full textInternational audienceLocal explainability, an important sub-field of eXplainable AI, focuses on describing the decisions of AI models for individual use cases by providing the underlying relationships between a model's inputs and outputs. While the machine learning community has made substantial progress in improving explanation accuracy and completeness, these explanations are rarely evaluated by the final users. In this paper, we evaluate the impact of various explanation and representation techniques on users' comprehension and confidence. Through a user study on two different domains, we assessed three commonly used local explanation techniquesfeature-attribution, rule-based, and counterfactual-and explored how their visual representation-graphical or text-based-influences users' comprehension and trust. Our results show that the choice of explanation technique primarily affects user comprehension, whereas the graphical representation impacts user confidence.CCS Concepts: • Human-centered computing → Empirical studies in HCI; • Computing methodologies → Artificial intelligence.</p
GESTE : GEStion Territorialisée des Effluents d'élevage: Élaboration d’outils pour en faciliter l’émergence et la mise en œuvre sur le terrain.
No full textLe projet GESTE s'intéresse à la gestion collective des effluents d'élevage avec ses conditions de mise en œuvre et ses performances de durabilité, pour les éleveurs et acteurs du collectif et pour le territoire lui-même. L'objectif du projet est de produire des outils pour favoriser l'émergence et la mise en œuvre de ces solutions (épandage collectif, séparation de phase, traitement biologique, compostage de fumier, méthanisation, filtration membranaire, évapoconcentration, stripping).Une analyse d'une vingtaine d'expériences existantes identifie les freins et leviers à leur mise en place et lors de leur fonctionnement. A l'issue du projet, trois outils sont disponibles pour accompagner des animateurs de territoire ou des collectifs d'agriculteurs dans leur réflexion autour d'une gestion collective de leurs effluents :1/ une brochure technique pour découvrir les options possibles et leurs conditions de mise en œuvre à des échelles collectives ;2/ un simulateur pour tester sur un territoire donné la mise en œuvre d'une solution et quantifier les incidences (flux des matières, bilans N et P, émissions gazeuses en ammoniac et gaz à effet de serre, transport…) ;3/ un jeu de rôle pour faire expérimenter aux acteurs d'un territoire différentes façons de gérer collectivement les effluents d'élevage et anticiper les modifications de pratiques. Enfin, un territoire pilote associé au projet a avancé dans sa réflexion sur la gestion collective des effluents grâce à une démarche d'accompagnement : une représentation du territoire avec sa problématique a été coconstruite avec les acteurs qui ont ensuite testé le jeu de rôle
Rheological response of whey protein deposits forming under shear in concentrated conditions
No full textInternational audienceAbstract Dairy fouling consists in the accumulation of whey proteins and minerals on equipment walls. While heat-induced protein denaturation is a primary cause, fouling also occurs below the denaturation threshold (≈ 70 °C). This leads to a renewed interest in other driving forces influencing fouling mechanisms. In this wake, this study investigates the role of shear on the formation of whey protein deposits under sub-denaturation temperature and concentrated conditions. We compared morphology and rheological behavior of shear-induced and unsheared structures formed at 15 and 20 wt% protein concentrations. While unsheared gel-like deposits were compact and stiff, shear led to the formation of weaker, more porous, and highly crosslinked structures. This effect was more pronounced at higher concentrations, where shear counteracted heat-induced aggregation, resulting in an alternative structural organization. These findings provide new insights not only into whey protein gelation but also into dairy fouling mechanisms, highlighting a concentration-dependent shear effect. Graphical Abstrac