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Rice Yellow Mottle Virus resistance by genome editing of the Oryza sativa L. ssp. japonica nucleoporin gene OsCPR5.1 but not OsCPR5.2
No full textInternational audienceRice yellow mottle virus (RYMV) causes one of the most devastating rice diseases in Africa. Management of RYMV is challenging. Genetic resistance provides the most effective and environment-friendly control. The recessive resistance locus rymv2 (OsCPR5.1) had been identified in African rice (Oryza glaberrima), however, introgression into Oryza sativa ssp. japonica and indica remains challenging due to crossing barriers. Here, we evaluated whether CRISPR/Cas9 genome editing of the two rice nucleoporin paralogs OsCPR5.1 (RYMV2) and OsCPR5.2 can be used to introduce RYMV resistance into the japonica variety Kitaake. Both paralogs had been shown to complement the defects of the Arabidopsis atcpr5 mutant, indicating partial redundancy. Despite striking sequence and structural similarities between the two paralogs, only oscpr5.1 loss-of-function mutants were fully resistant, while loss-of-function oscpr5.2 mutants remained susceptible, intimating that OsCPR5.1 plays a specific role in RYMV susceptibility. Notably, edited lines with short in-frame deletions or replacements in the N-terminal domain (predicted to be unstructured) of OsCPR5.1 were hypersusceptible to RYMV. In contrast to mutations in the single Arabidopsis AtCPR5 gene, which caused severely dwarfed plants, oscpr5.1 and oscpr5.2 single and double knockout mutants showed neither substantial growth defects nor symptoms indicative lesion mimic phenotypes, possibly reflecting functional differentiation. The specific editing of OsCPR5.1, while maintaining OsCPR5.2 activity, provides a promising strategy for generating RYMV-resistance in elite Oryza sativa lines as well as for effective stacking with other RYMV resistance genes or other traits
Changes in light use efficiency explains why diversity effect on biomass production is lower at high planting density in mixed-species plantations of Eucalyptus grandis and Acacia mangium
No full textInternational audienceUnderstanding the effect of planting densities and species proportions on light absorption and light use efficiency can help to improve the management of mixed-species forest plantations. Our study aimed to disentangle the role of light interception and light use efficiency (LUE) on the biomass production of Eucalyptus grandis (E), a highly productive species in tropical conditions, and Acacia mangium (A), a N2-fixing species, in monocultures and mixed-species plantations for contrasting planting densities. A randomized block experiment set up over 4 ha in southern Brazil was intensively monitored for 14 months at mid rotation. The absorbed photosynthetically active radiation (APAR) was simulated for each tree of the experiment using the tri-dimensional MAESPA model parameterized with detailed in situ measurements of tree and foliage. LUE for stem wood production was estimated as the ratio of measured stem biomass production (SBP) and simulated APAR. The APAR of Eucalyptus trees did not significantly differ between monocultures and mixed plantations, the reduction of Eucalyptus density being compensated by an increase in light absorption of Eucalyptus individuals. The LUE of Eucalyptus trees in monoculture and mixed-species stands was found to be comparable only at low planting densities. The replacement of Eucalyptus trees with Acacia trees resulted in a reduction in Eucalyptus LUE only at high planting density. The SBP of Eucalyptus trees was mainly explained by differences in APAR, while both APAR and LUE explained the SBP of Acacia trees. The maximum stand production was obtained with monoculture of Eucalyptus at high density and no mixture reached this productivity. Reducing the proportion of Eucalyptus in mixture lead to a substantial decrease in stand production at high planting density due to a decrease in LUE, while this stand production reduction was offset at low planting density, underlying a higher diversity effect at low planting density. In the perspective of increasing diversity in forest plantations to foster multifunctionality, mixed plantations of Acacia and Eucalyptus at low planting density can be an interesting option to maintain a relatively high productivity, which is similar to Eucalyptus monocultures at the same low planting density
Stillbirth of a mandrill (Mandrillus sphinx) in the wild: perinatal behaviors and delivery sequences
No full textInternational audienceBirth is a fundamental event in the life of animals, including our own species. More reports of wild non-human primate births and stillbirths are thus needed to better understand the evolutionary pressures shaping parturition behaviors in our lineage. In diurnal non-human primates, births generally occur at night, when individuals are resting. Consequently, they are difficult to observe in the wild and most of the current knowledge regarding perinatal behaviors comes from rare daytime births. Information about stillbirths is even rarer and their proximate causes are generally unknown. Here, we present detailed observations of a daytime birth of a stillborn wild mandrill ( Mandrillus sphinx ). During this event, which lasted an entire day, we recorded the behaviors of the parturient female ad libitum, using video recordings and photos. The 5-year-old female was primiparous and of low dominance rank. The length of her pregnancy was shorter than usual and the partum phase was extremely long compared to other birth reports in non-human primates. The female disappeared shortly after this event and was assumed to have died. We discuss the possible causes of this stillbirth including the infant’s presentation at birth and maternal inexperience
Quantification of soil organic carbon in particle size fractions using a near-infrared spectral library in West Africa
No full textInternational audienceParticle size fractionation enables a better understanding of soil organic carbon (C) dynamics since it separates fractions that differ in composition, residence time and function. However, this method is time-consuming and tedious; thus, its use has been greatly limited. Our objective was to evaluate the ability of an existing soil spectral library (SSL) from different regions of West Africa to predict the C amount in the fractions (gC kg-1 soil) of the samples in a new target set from Benin. The SSL included 181 samples from five countries, and the target set included 94 samples (depth ≤ 40 cm), most of which were coarse-textured; near-infrared reflectance (NIR) spectra were collected for 2 mm sieved samples (non-fractionated samples). The predicted variables were the C amounts in the non-fractionated soil and in the 50 μm fractions (F50, respectively). Different methods were tested to optimize the predictions: (i) SSL enrichment with 10 or 15 samples selected from the target set (spiking) and replicated six times (i.e. extra-weighted); (ii) locally weighted (local) partial least squares regression (PLSR), which is calibration by the spectral neighbours with the highest weights attributed to closest neighbours, and was compared to “global” (i.e., common) PLSR, where all calibration samples equally contribute; and (iii) spectrum pretreatments (e.g., smoothing, centring, derivatization). In addition, the intermediate precision of the conventional data (standard error of laboratory; SELint) was estimated through triplicate fractionation of three samples carried out by three operators (one per replicate). When the SSL alone was used for calibration, the predictions were inaccurate for the C amounts in the nonfractionated soil and in F50, with minimal benefit from the local PLSR over the global PLSR in general. For the non-fractionated soil, F50, the ratios of performance to the interquartile range in the validation set, RPIQVAL, were 1.6–1.8, 1.6–1.7, 1.9 and 1.9–2.1, respectively. Calibration with SSL spiked (i.e., completed with spiking samples) yielded an increase in RPIQVAL from 33 to 56% for the C amount in the non-fractionated soil and F50 (RPIQVAL reached 2.4–2.5, 2.2–2.3, 1.9–2.0 and 2.1–2.3, respectively), and the benefit of local PLSR was still limited. The SELint was based on a few samples and thus only provided a rough estimation; this estimate represented at least 65% of the prediction error for the C amounts in the fractions. Therefore, the SELint needs to be determined more extensively to both improve the model accuracy and refine the interpretation of the predictions based on NIR spectra. This library should be enriched with samples from other sites to represent other soil types
Chronic and immediate refined carbohydrate consumption and facial attractiveness
No full textInternational audienceThe Western diet has undergone a massive switch since the second half of the 20 th century, with the massive increase of the consumption of refined carbohydrate associated with many adverse health effects. The physiological mechanisms linked to this consumption, such as hyperglycaemia and hyperinsulinemia, may impact non medical traits such as facial attractiveness. To explore this issue, the relationship between facial attractiveness and immediate and chronic refined carbohydrate consumption estimated by glycemic load was studied for 104 French subjects. Facial attractiveness was assessed by opposite sex raters using pictures taken two hours after a controlled breakfast. Chronic consumption was assessed considering three high glycemic risk meals: breakfast, afternoon snacking and between-meal snacking. Immediate consumption of a high glycemic breakfast decreased facial attractiveness for men and women while controlling for several control variables, including energy intake. Chronic refined carbohydrate consumption had different effects on attractiveness depending on the meal and/or the sex. Chronic refined carbohydrate consumption, estimated by the glycemic load, during the three studied meals reduced attractiveness, while a high energy intake increased it. Nevertheless, the effect was reversed for men concerning the afternoon snack, for which a high energy intake reduced attractiveness and a high glycemic load increased it. These effects were maintained when potential confounders for facial attractiveness were controlled such as age, age departure from actual age, masculinity/femininity (perceived and measured), BMI, physical activity, parental home ownership, smoking, couple status, hormonal contraceptive use (for women), and facial hairiness (for men). Results were possibly mediated by an increase in age appearance for women and a decrease in perceived masculinity for men. The physiological differences between the three meals studied and the interpretation of the results from an adaptive/maladaptive point of view in relation to our new dietary environment are discussed
Présentation du Projet INNOGOUV : Gouvernance, innovation et performance durable dans les coopératives agricoles. Le cas des coopératives vinicoles françaises
No full textLe secteur du vin en France est précurseur en terme d’ancrage territorial, particulièrement grâce aux coopératives vinicoles : elles représentent 40% des appellations d’origine protégée (AOP) de ce secteur et 70% des Indications Géographiques Protégées (IGP). La gouvernance, l’ innovation et le développement durable sont considérés comme étant les principaux enjeux de ces organisations à taille humaine (FranceAgriMer, 2017) et au mode de gouvernance démocratique. Cela conduit à la question centrale de notre projet de recherche : « quel est l’impact de la gouvernance des coopératives vinicoles sur l’innovation et la performance durable de ces organisations spécifiques ? » - Dates du projet : Février 2023 - janvier 202
Cartographie de l’habitat de reproduction du tétras-lyre (Lyrurus tetrix) dans les Alpes françaises
No full textThe Black Grouse (Lyrurus tetrix) is an emblematic alpine species with high conservation importance. The population size of these mountain bird tends to decline on the reference sites and shows differences according to changes in local landscape characteristics. Habitat changes are at the centre of the identified pressures impacting part or all of its life cycle, according to experts. Hence, an approach to monitor population dynamics, is trough modelling the favourable habitats of Black Grouse breeding (nesting sites). Then, coupling modelling with multi-source remote sensing data (medium and very high spatial resolution), allowed the implementation of a spatial distribution model of the species. Indeed, the extraction of variables from remote sensing helped to describe the area studied at appropriate spatial and temporal scales: horizontal and vertical structure (heterogeneity), functioning (vegetation indices), phenology (seasonal or inter-annual dynamics) and biodiversity. An annual time series of radiometric indices (NDVI, NDWI, BI …) from Sentinel-2 has made it possible to generate Dynamic Habitat Indices (DHIs) to derive phenological indications on the nature and dynamics of natural habitats. In addition, very high resolution images (SPOT6) provided access to the fine structure of natural habitats, i.e. the vertical and horizontal organisation by states identified as elementary (mineral, herbaceous, low and high woody). Indeed, one of the essential limiting factors for brood rearing is the presence of a well-developed herbaceous or ericaceous stratum in the northern Alps and larch forests in the southern region. A deep learning model was used to classify elementary strata. Finally, Biomod2 R platform, using an ensemble approach, was applied to model, the favourable habitat of Black Grouse reproduction. Of all the models, Random Forest and Extreme Boosted Gradient are the best performing, with TSS and ROC scores close to 1. For the SDM, we selected only Random Forest models (ensemble modelling) because of their low susceptibility to overfitting and coherent predictions (after comparing model predictions).In this ensemble model, the most important explanatory variables are altitude, the proportion of heathland, and the DHI (NDVI Max and NDWI Max). Results from the habitat model can be used as an operational tool for monitoring forest landscape shifts and changes. In addition, to delimiting potential areas to protect the species habitat, which constitute a valuable decision-making tool for conservation management of mountain open forest.Le tétras-lyre (Lyrurus tetrix) est une espèce de galliforme emblématique des Alpes aujourd’hui menacée à court et moyen terme par les activités humaines (notamment touristiques) et à plus long terme par le changement climatique. Les modifications de l'habitat sont au coeur des pressions identifiées ayant un impact sur une partie ou la totalité de son cycle de vie. Pour suivre la dynamique des populations de tétras-lyre, une approche possible consiste à modéliser les habitats favorables à la reproduction (sites de nidification). Dans le cadre de notre travail, nous avons réalisé un Modèle de Distribution d’Espèce (SDM) permettant de prédire la probabilité de présence des nichées en fonction de variables paysagères dérivées de la télédétection. De cette manière, nous pouvons estimer l’adéquation ou le niveau de « favorabilité » de l’habitat pour la reproduction du tétras-lyre et déterminer quelles variables ont le plus d’influence sur la qualité de l’habitat. Un autre enjeu majeur de notre travail a été réaliser cette cartographie de l’habitat à l’échelle des Alpes françaises. En fonction des connaissances de terrain sur les aires de présence principale du tétras-lyre, nous nous sommes concentrés sur les Alpes Internes du Nord.Les variables dérivées de la télédétection (images Sentinel-2 et SPOT6-7 acquises en 2020) nous ont permis de décrire trois dimensions du paysage : composition, structure et fonctionnement. La composition du paysage a été abordée à partir d’une classification en apprentissage profond (deep learning) des images à Très Haute Résolution Spatiale SPOT6-7 afin de cartographier différentes composantes du paysage. Cette approche a permis de produire une cartographie à l’échelle des Alpes Internes du Nord distinguant 6 classes : surfaces minérales, eau, prairies, landes ligneuses à éricacées, forêt et surfaces ombragées. L'un des facteurs limitants essentiels pour l'élevage des nichées est la présence d'une strate herbacée ou éricacée bien développée dans les Alpes du Nord et de forêts de mélèzes dans la région méridionale. La structure du paysage a été décrite par une variable topographique (altitude) dérivée d’un Modèle Numérique de Terrain, essentielle en contexte montagnard, et un indice de texture (l’entropie d’Haralick) basée sur l’analyse des niveaux de gris. Cette dernière variable peut être reliée au niveau d’hétérogénéité de l’environnement. Enfin, le fonctionnement du paysage a été traitée du point de vue de la phénologie. Les valeurs maximales annuelles des indices radiométriques NDVI et NDWI, renseignant sur les propriétés de la végétation (productivité et contenu en eau), ont été déterminée à partir de séries temporelles Sentinel-2. Ces indices peuvent être considérés comme des indices dynamiques d'habitat (Dynamic Habitat Index) et renseignent sur la nature et la dynamique de la végétation.Le modèle de distribution d’espèce a été réalisé à l’aide du package R biomod2 (Thullier et al., 2023) qui fournit à la fois un cadre d’analyse et un ensemble de méthodes permettant de prédire la probabilité de présence d’espèces. Pour réaliser la modélisation, nous avons utilisé les variables paysagères précédemment décrites ainsi que les observations des nichées fournies par l’OGM (années 2015 à 2021). Parmi les algorithmes testés, nous avons choisi de conserver le Random Forest (RF) en raison de sa performance très élevée (TSS et ROC proches de 1) et sa faible susceptibilité au sur-apprentissage. Un modèle d’ensemble de RF a été réalisé (médiane des prédictions des modèles individuels) afin de limiter la variabilité. Les variables les plus importantes se sont révélées être : l’altitude (24%), le NDVIMax (16%) suivi du taux de landes ligneuses à éricacées et du NDWIMax (14%). La confrontation des résultats avec la connaissance de terrain des experts de l’OGM a montré la cohérence de la distribution spatiale des motifs d’habitats favorables. D’autre part, la classification de l’occupation du sol dans les Alpes Internes du Nord constitue un résultat en soi susceptible d’être utile au suivi des habitats alpins
High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach
No full textInternational audienceIn intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10---20 m) is needed to capture the differences in canopy height. In this work, we developed a deep learning model based on multi -sensor remote sensing measurements to create a high -resolution canopy height map over the "Landes de Gascogne" forest in France, a large maritime pine plantation of 13,000 km2 with flat terrain and intensive management. This area is characterized by even -aged and mono -specific stands, of a typical length of a few hundred meters, harvested every 35 to 50 years. Our deep learning U -Net model uses multi -band images from Sentinel -1 and Sentinel -2 with composite time averages as input to predict tree height derived from GEDI waveforms. The evaluation is performed with external validation data from forest inventory plots and a stereo 3D reconstruction model based on Skysat imagery available at specific locations. We trained seven different U -Net models based on combinations of Sentinel -1 and Sentinel -2 bands to evaluate the importance of each sensor in the dominant height retrieval. The model outputs allow us to generate a 10 m resolution canopy height map of the whole "Landes de Gascogne" forest area for 2020 with a mean absolute error of 2.02 m on the test dataset. The best predictions were obtained using all available bands from Sentinel -1 and Sentinel -2 but using only one satellite source also provided good predictions. For all validation datasets in coniferous forests, our model showed better metrics than previous canopy height models available in the same region
Nutritional optimization through linear programming of climate-smart and gluten free pasta
No full textInternational audienceDesigning food formulations is an important approach to meet a set of nutritional needs and to address malnutrition issues. Linear programming is an appropriate tool for designing novel nutritionally optimized formulations based on a combination of gluten-free climate-smart crops. Four nutritionally optimized cowpea-based pasta formulations in association or not with teff and/or amaranth leaves (AL) were designed to meet a woman's protein requirements in terms of quantity and quality, fibers, ω6/ω3, iron, zinc and B9 vitamin, while limiting antinutritional factors such as phytates. To predict the processability of the flours into pasta and the visual acceptance of future pasta by consumers, the antioxidant and oxidant capacities of flours were measured and their color compared with the color of durum wheat semolina (DWS). The formulation combining cowpea and AL had the highest nutritional composition and lowest impact of phytates. The formulation with cowpea, teff and AL seems to be the easiest to process thanks to its lower lipoxygenase activity and the higher antioxidant capacity, followed by the teff-cowpea formulation. The color of the formulation that only contained cowpea was closest to DWS
Tous les chemins mènent-ils au rhum ? Le rôle de l’alliance sur la performance des coalitions d’acteurs dans les filières canne à sucre et maraîchage en Martinique
No full textInternational audienceIn order to identify the performance factors of a coalition in agriculture, the social sciences have the theoretical and conceptual tools to carry out macro-sociological structural and strategic analyses and micro-sociological cognitive and relational analyses. Our article aims at completing the latter by specifying the characterization of ‘relational and cognitive’ variables, based on the theory of alliance in psychology. On the basis of this theoretical contribution, we highlight the performance factors of coalitions in agriculture. Applied to the case of Martinique, we empirically compare the rum industry, organized around a historically dominant coalition and a durable alliance, with the vegetable sector, whose attempts at structuring have not benefited from a durable alliance of actors.Afin d’identifier les facteurs de performance d’une coalition d’acteurs en agriculture, les sciences sociales disposent d’outils théoriques et conceptuels permettant de réaliser des analyses structurelles et stratégiques macro-sociologiques, et des analyses cognitives et relationnelles micro-sociologiques. Notre article invite à compléter ces dernières en précisant la caractérisation des variables « relationnelles et cognitives », à partir de la théorie de l’alliance en psychologie. En se basant sur cet apport théorique, nous mettons au jour les facteurs de performance des coalitions en agriculture. Appliquée au cas martiniquais, nous comparons empiriquement la filière rhumière, organisée autour d’une coalition historiquement dominante et d’une alliance durable, avec la filière maraîchère, dont les tentatives de structuration n’ont pas bénéficié d’une alliance d’acteurs pérenne