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Evolution of the electrical conductivity of pound cake during baking by ohmic heating
No full textInternational audienc
La place de l’UE dans le commerce mondial de produits agricoles et agroalimentaires
No full textInternational audienceWorld trade in agricultural and agri-food products has been growing steadily for several decades under the influence of increasing food demand, particularly in Asia and Africa, and an unequal territorial distribution of agronomic and productive potential. With a trade balance of 39 billion euros in 2024, the European Union (EU-27) has become a major player in this trade. Using information from two databases (Baci and Comext), this article presents an analysis of the main trade dynamics observed in this sector over just over two decades.Le commerce mondial des produits agricoles et agroalimentaires connaît un développement soutenu depuis plusieurs décennies sous l'influence d'une demande alimentaire en croissance, notamment en Asie et en Afrique, et d'une répartition territoriale inégale des potentiels agronomiques et productifs. Avec un solde commercial de 39 milliards d'euros en 2024, l'Union européenne (UE-27) est devenue un acteur majeur de ce commerce. En utilisant les informations issues de deux bases de données (BACI et COMEXT), cet article présente une analyse des principales dynamiques commerciales observées dans ce secteur sur un peu plus de deux décennies
Rapid viral detection in milk using near infrared spectroscopy combined with Swiss knife partial least squares (SKPLS) 3-way multiblock
No full textInternational audienceHuman norovirus is the leading cause of foodborne illnesses, necessitating rapid, reliable, and cost-effective quantification methods. Near InfraRed Spectroscopy (NIRS) offers real-time analysis with minimal sample preparation. Two independent experiments, conducted 8 months apart in quadruplicate, produced 360 semi-skimmed milk measurement spiked with nine MS2 bacteriophage concentrations, a surrogate of human norovirus. Virus concentrations were modeled by 3-way partial least squares (PLS) regression correlating NIRS spectra with plaque-forming unit (PFU) measurements. A group-aware 5-fold cross-validation was applied to 72 sample groups using spectral pretreatments. The best performance was achieved with the extended multiplicative scatter correction (EMSC) and first derivative, yielding an R2 of 0.77 and 0.80 for validation. The limit of quantification (LOQ) was estimated at 4.9 × 103 PFU/mL, close to literature values for virus quantification in complex matrices. These results highlight the feasibility of NIRS as a rapid, non-destructive, and reagent-free approach for viral quantification in food systems
Synchronous Miocene radiations and geographic-dependent diversification of pantropical Xylopia (Annonaceae).
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RECHARGE, a model of potential recharge of aquifers applied to mainland France
No full textInternational audienceCalculating aquifer recharge provides a means of estimating the renewable fraction of groundwater resources, which is often difficult to quantify. This paper introduces the RECHARGE method, developed to calculate potential groundwater recharge from precipitation infiltration, and its application across mainland France over an extended historical period.The method relies on a simple soil water budget approach to estimate effective precipitation, using meteorological data and a spatial parameter that accounts for land cover and allows the seasonal variability of evapotranspiration to be reflected. An effective precipitation infiltration ratio (EPIR) is then derived for catchments with homogeneous geological lithology, based on linear regressions involving the baseflow index and a GIS-derived parameter. Given the low interannual variability of the baseflow index, the EPIR is assumed to remain constant over time and is subsequently used to convert effective precipitation into potential recharge at the scale of all groundwater bodies in mainland France.To validate this approach, annual effective precipitation estimates were compared for 556 selected catchments, both with observed annual river flows and with outputs from the physically based SURFEX model. The calculated potential recharge was also evaluated at both annual and seasonal scales for the entire French territory, using SURFEX as a reference. Results demonstrate that the RECHARGE model can effectively estimate annual and seasonal potential aquifer recharge. It is suitable for large-scale applications without requiring detailed knowledge of aquifer properties. Future improvements are envisioned, particularly to enhance monthlyscale accuracy in mountainous regions.</p
Adaptive LASSO Quantile Regression with Fixed Effects
No full textInternational audienceQuantile regression with fixed effects for longitudinal data accounts for individual-specific intercepts.When the number of individuals is large relative to the number of repeated measurements and the covariate dimension is high, we propose a dimension-reduction approach based on the least absolute shrinkage and selection operator (LASSO) penalty. Specifically, we extend adaptive LASSO quantile regression to accommodate longitudinal data. The proposed method retains oracle properties, including asymptotic normality and consistent variable selection. Monte Carlo simulations demonstrate that it performs best under moderate dimensionality, while also outperforming alternative methods in low-dimensional settings, though with smaller margins.The practical relevance of the approach is illustrated through two real-world applications: French electricity consumption and the Millennium Cohort Study. Using departmental-level data from France, we analyze non-residential electricity consumption to uncover patterns in energy demand. The log-transformed outcome remains markedly skewed, emphasizing the need for models capable of handling non-Gaussian distributions. Drawing on data from the Millennium Cohort Study, we examine factors associated with children's internalizing difficulties across different quantiles of the outcome distribution, identifying maternal mental health (Kessler scale) as the most influential predictor.</p
Temporal dynamics of hepatic mRNA levels of carbohydrate and lipid metabolism-related genes in rainbow trout: Impact of a plant-based diet from first feeding
No full textInternational audienceEarly-life nutrition plays a critical role in shaping metabolic trajectories in fish, particularly in carnivorous species like rainbow trout (Oncorhynchus mykiss), which displays limited capacity to utilize plant-based diets. This study investigated the temporal changes in mRNA abundance of key hepatic genes involved in carbohydrate and lipid metabolism from first feeding to 100 days post-first meal in rainbow trout fry fed either a commerciallike or fully plant-based diet. mRNA abundance was quantified by RT-qPCR at six time points, revealing marked ontogenetic shifts in metabolic gene profiles regardless of diet. Except for gck (encoding glucokinase), glycolytic and gluconeogenic enzymes generally showed declining expression over time, while genes involved in lipogenesis, notably fasn (encoding fatty acid synthase) and acly (encoding ATP citrate synthase), increased progressively-suggesting a developmental shift toward lipogenesis and energy storage pathways. Despite similar patterns observed under both dietary conditions, fish fed the plant-based diet exhibited attenuated temporal transcriptional changes in some genes. These patterns were consistent with previously reported growth deficits in the same fish, potentially reflecting impaired metabolic acclimation. Our findings highlight that while the liver undergoes dynamic metabolic maturation during early development, plant-based diets may hinder this process, particularly in lipid handling. This work provides a molecular basis for improving feed formulations and supports the need for strategies that enhance metabolic flexibility during critical early stages in aquaculture species
Assessing the reliability of camera-based identification, activity monitoring, and location in housing systems on dairy farms
No full textInternational audienceVideo-based livestock monitoring offers a noninvasive, cost-effective, and scalable alternative to direct human monitoring, but also to commonly used collar or ear tag devices on farms. It enables simultaneous real-time observation of multiple animals while avoiding stress and injuries from physical devices. However, single-camera systems face challenges such as blind spots and limited individual tracking, especially in barns lacking corridor layouts. These limitations can be overcome using multi-camera, multi-cow tracking (MCMCT) systems that integrate deep learning and statistical techniques to enable continuous detection, identification, activity classification, and zone location of animals in the barn, under commercial conditions. This environment is characterized by high stocking density (in m 2 per cow), occlusions, and variable lighting. In this study, a commercial MCMCT system was tested over 31 d (May 2025) on 3 Holstein dairy farms in western France. Herd size ranged from 70 to 250 lactating cows and used automatic milking systems (AMS), which allowed identification of all animals when milked. Individual detection performance of this MCMCT system was then validated compared with official AMS records. A dedicated hybrid confusion matrix framework was developed to jointly assess detection and identification errors in the sequential process, allowing precise calculation of recall, precision, and F1-scores at both stages. Overall, this MCMCT system achieved over 90% detection recall and 87% to 93% precision, successfully detecting continuously more than 9 out of 10 cows daily. Identification was more challenging, with recall varying from 69% to 78% and precision above 83%, resulting in F1-scores of 79% to 82%. The performance of detection varied significantly between day and night in 2 out of 3 farms (H1 and H2), with recall rates dropping to 76% at night and exceeding 94% during peak daylight, underscoring the impact of lighting and activity patterns. Activity classification and zone location were robust, with F1-scores exceeding 87%, demonstrating the system's capacity to provide practical insights for herd management such as monitoring individual behaviors, identifying high-density zones around resources, and supporting daily management decisions. This work confirms the system's practical viability as a scalable, noninvasive monitoring solution effective under commercial farm complexities such as crowding, occlusion, and lighting variability. The integration of day-night performance analysis and the hybrid confusion matrix provide a rigorous and transparent framework for assessing system reliability, critical for deploying precision livestock farming technologies. Identification performance decreased under overcrowded conditions. Overcrowding is defined here as a surface area of less than 9 m 2 per cow or less than than one cubicle per cow, as recommended by the EFSA Panel on Animal Health and Animal Welfare in 2023. The system demonstrates significant potential to support and enhance herd management, early disease detection, and animal welfare monitorin
SIESTA Project: Svalbard summer 2025 expedition report
No full textInternational audienceMicrobial dormancy plays an important role in the persistence, dispersal, and functioning of microbial communities in moderate to extreme environments. The activity or inactivity of microbial communities also has implications for rates of biogeochemical transformations and thus elemental stocks and redox conditions. Microbial communities inhabiting glacier surface environments encounter harsh and variable environmental conditions including nutrient limitation, low temperatures, and light availability across various micro-habitats including cryoconite and the bare ice surface. The metabolic states of cells within these microhabitats and in relation to their environment is fundamental to the functioning of the ecosystem and has implications for ecosystem resilience, responses to environmental change, and biogeochemical cycling. This report describes an expedition to Brøggerhalvøya, north-west Svalbard, carried out in July 2025, within the framework of the ERC SIESTA project. A major objective of the project is to resolve microbial activity and dormancy on an individual cell basis, to characterise the adaptive and functional traits of active and dormant fractions of the native glacier microbial population, and to link microbial metabolic states to broader ecological and biogeochemical dynamics. Here we report the site characteristics, the samples collected, the analyses undertaken, and the future analyses planned. Two small valley glaciers near to Ny-Ålesund were selected for investigation during this summer campaign: Midtre Lovénbreen and Austre Brøggerbreen. The data collected in the field, combined with subsequent laboratory analyses, will provide insights into the spectrum of dormancy and activity in situ</div
