eKhSACIR інституційному репозитарії Харківської державної академії культури
Not a member yet
7410 research outputs found
Sort by
Improving gut health by modulating the digestive microbiota of chickens? How metagenomics can help.
No full textInternational audienc
Development of key synthetic biology technologies for the high-throughput construction of semi-synthetic Bacillus subtilis -derived chassis strains
No full textUMR BFP - Equipe MollcutesInternational audienc
Wood formation and tree adaptation to climate
No full textInternational audienceKey message This special issue of Annals of Forest Science compiles ten papers on "Wood formation and tree adaptation to climate", which were presented at "Le Studium" International Conference in May 2018 in Orleans (France). These papers present observational, experimental and modelling studies investigating the influence of climatic changes on tree growth from the hour to the century, and from the cell to the landscape
La nature du sol et la composition floristique comme facteurs de modulation de la diversité et de la fonctionnalité des communautés microbiennes en prairie permanente
No full textProd 2019-286f EA BIOmE INRA AGROSUPNational audienceLa composition floristique, le mode d’exploitation (fauche, pâturage), l’intensité d’exploitation (chargement, fréquence des coupes, fertilisation) et la pérennité de la couverture végétale sont connus comme étant des facteurs déterminants du fonctionnement des prairies permanentes (Gaujour et al. 2012). Ces pratiques de gestion peuvent modifier les stocks de C directement en modulant les entrées de matières organiques (MO) (litière et/ou effluents d’élevage) et indirectement en orientant la composition et le fonctionnement des communautés végétales ce qui pourrait agir sur le temps de résidence et la localisation de la MO (Hassink et Neeteson 1991). Ce projet a pour objectif de caractériser les pools de C organique du sol et les communautés bactériennes sous des prairies permanentes différant selon leur composition floristique et la nature de l’antécédent en termes de couverture de sol (3 habitats : culture, forêt, prairie). L’hypothèse de ce travail est que ces facteurs en modifiant la nature des pools de C du sol (labile vs récalcitrant) ont sélectionné des communautés bactériennes différentes tant du point de vue de la diversité génétique que de leurs traits fonctionnels en lien avec la minéralisation des MO. Pour valider cette hypothèse, des échantillons de sol ont été prélevés en mai 2017 sur 12 parcelles de prairies (4 parcelles par habitat) sur lesquelles des relevés de composition floristique ont été effectués. Les résultats montrent que la composition floristique des 12 parcelles de prairies permanentes échantillonnées se différencie selon la nature de l’antécédent. Des différences de pH et de teneurs en C entre les sols de 3 types de prairies étudiées. Les activités enzymatiques (en lien avec les cycles biogéochimiques) mettent en évidence des différences selon l’antécédent de couverture du sol suggérant des fonctionnalités différentielles liées d’une part au temps de résidence des pools de C et d’autre part à des différences de diversité des communautés microbiennes du sol
Séquençage du génome entier et diversité génétique de populations sauvages et domestiques de pintade
No full textA REPRENDRE - AUTEURSInternational audienc
Régénération de lignées de truite par transplantation de cellules souches germinales
No full textSession : ReproductionNational audienc
Key Note speaker Plant resistance and architecture for protection of pulses against biotic stresses
No full textProd 2019-88l BAP GEAPSI INRA DOCTNational audienceMajor diseases and pests, such as root rots, ascochyta blights and aphids, are limiting factors to cool season pulse production in many countries worldwide, especially in Europe. In the context of pesticide reduction, plant genetic resistance and architecture are main traits that can be mobilised in breeding for disease and pest management. Knowledge of quantitative resistance to major diseases and pests of pea and faba bean in France has benefited from the development of sequenced genomes and massive SNP markers [1], which have recently been highly valuable to identify candidate genes controlling resistance. Fine mapping and sequencing of major resistance QTL [2], as well as Linkage Analysis (LA) [3] and Genome-Wide Association Studies (GWAS) coupled with Genotyping By Sequencing (GBS) technologies, have been developed to identify, compare and study synteny of loci and candidate genes for resistance. Plant and canopy architectures have been studied in pea for their effect on limiting disease severity and epidemics. Alleles at genes controlling aerial or root plant architectural traits were found to cosegregate with resistance alleles at QTL controlling aerial or root diseases [4]. Combining plant resistance and architecture traits unfavourable to diseases and pests will be a key strategy for durable crop protection. Future research will combine other plant traits with resistance and architecture, such as plant ability to select useful micro-organisms or to produce compounds that are beneficial to plant protection, as well as agricultural practices
Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cows
No full textInternational audienc
Modélisation interactive en agro-alimentaire: l’outilLiDeoGraM
No full textNational audienceModelling complex agrifood processes like for instance cheese ecosystems is challenging due to the complex multi-scale nature of interactions among and between the constituent components. Furthermore, producing experimental data in this context is both tedious and expensive, resulting in scarce datasets, where the number of dimensions far exceeds the number of data samples. We present here LiDeoGraM, a visual analytics tool that combines data-driven machine learning with domain experts’ knowledge to produce multi-scale models of living ecosystems. This tool is inspired from the idea of model stacking where an ensemble of simple local models are generated for each component of the studied system. The modelling process is carried out in three iterative steps: (a) using regression, LiDeoGraM proposes a set of local models for each component; (b) via a graphical interface, domain experts evaluate those local models; (c) an interactive evolutionary algorithm builds a global model while mediating between expert’s subjective assessment, and an automatic evaluation based on fitting error and complexity. A first validation of our approach has been performed at three levels, combining computational and human-centered evaluations: (i) automatic tests to assess the robustness of the local model generation; (ii) a toy model test to evaluate how domain experts use our tool to discover a ‘known’ model; and (iii) a use case study to examine how domain experts use LiDeoGraM to model real-life multi-scale biological systems. Our results show that domain experts are able to operate our tool to discover a known model, and are able to generate new hypotheses when exploring their own datasets
Genetic of the 3D morphology of jumping horses using geometric morphometrics
No full textInternational audienceMorphological data were recorded on 2,097 jumping horses aged 4 and 5 with 3D technology using 3 cameras. For each horse, the anatomical landmarks of the main joints, including the head, have been identified, leading to a 25 point file describing the morphology of the horse with their coordinates in 3 dimensions. The study was made by dissociating the shapes of the general size through a Procrusted type analysis. After creation of new Procrustes coordinates, a principal component analysis reveals the predominant forms in playing simultaneously on all points. The Geomorph package under R was used. The heritability of these components has been estimated after correcting the influence of the person who made the marks on the images of the horses, the place and the date of measure, the age and sex of the horse, and the angle of the anterior and posterior canons with the vertical on the chosen image. The genealogies over 6 generations were used (18,029 horses). ASREML software was used. 10 components are needed to explain 80% of the variance. The first two components are the orientation of the limbs in the frontal plane: the first distinguishes the horses whose posteriors marks are close to the midline of the hoof point. The second is similar for the forelegs with a width at shoulders following the same movement. The third component is mainly explained on the sagittal plane and distinguishes big and short horses of long and small for the same general size. The heritability of the overall size is 0.21. The two first components are not heritable (0.09 and 0.06). Only components 3, 6 (length of the neckline) and 8 (high neck tie, long shoulder, short withers and hollow back line) are really heritable (respectively 0.27, 0.26 and 0.21). Genetic correlation with overall size were not null, denoting a strong allometry. Multiple phenotypic regression with performances in jumping competition do not exceed a r2 of 2%