dataesr/scientific-paragraphs-categorization huggingface dataset:
The objective of this study was to determine and describe relationship between the chemical composition and the rumen degradation characteristics of dry matter (DM), organic matter (OM), crude protein (CP), starch and neutral detergent fibre (NDF) of maize silages. Seventy-five maize silage samples were selected, with a broad range in chemical composition and quality parameters. The samples were incubated in the rumen of three cows for 2, 4, 8, 16, 32, 72 and 336 h, using the nylon bag technique under uniform experimental conditions and protocols. The new database with in situ rumen degradation characteristics of DM, OM, CP, starch and NDF of the maize silages was obtained under uniform experimental conditions; same cows, same incubation protocol and same chemical analysis procedures. Regression equations were developed with significant predictors (P<0.
Much of this diversity will be in regions of copy number variation (CNV), however, the imputation of CNV status is unlikely to be as successful as SNP alleles. New tools and resources, including improved assemblies of the reference genomes and alternate assemblies in CNV regions, and a better understanding of the relationship between the genome and the expression of the genes across the different tissues, will provide the foundation for a much broader utilisation of the sheep and goat genomic resources by their respective industries in the future. This work was partially supported by the EU FP7 3SR project (no. 245140). Latvia; anda. valdovska@llu. lv  The feeding trial was conducted to investigate the effect of dietary supplementation of synbiotic and probiotic Jerusalem artichoke on piglets production values, and gut microbiology and architecture.
This project receives financial support from Apis-Gène, UE 7 th PCRDT, Ministry of Agriculture (CASDAR), FranceAgriMer and FGE. In French dairy goats, 2,246 females and 872 males from Alpine and Saanen breeds were recently genotyped with the Illumina 50K SNP bead chip, as part of a large genomic project supported by the dairy goat industry stakeholders. The first goal of this study was to investigate linkage disequilibrium (LD) within the population and between the two breeds. The second objective was to examine the effect of adding males, females or males and females in the reference population on the ranking and accuracy of genomic breeding values for young bucks. The level of LD in the multi-breed population (0. 14 for 50 kb) was lower than the one found in each breed (0. 17) or in literature for cattle (0.
Do selective sweeps in sheep breeds indicate the genomic sites of breed characteristics? G. E. Pollott RVC, Royal College Street, London NW1 0TU, United Kingdom; gpollott@rvc. ac. uk  Most breeds are the result of recent selection for phenotypic characteristics which make that breed unique, often referred to as a selective sweep in natural populations. This process should result in long runs of homozygosity (ROH) around the genomic polymorphisms which determine a breed's key characteristics, particularly if their mode of inheritance is autosomal recessive. Since recombination in each generation has the potential to breakdown ROH, the length of a ROH is indicative of its age; more recent mutations being associated with longer runs. The 67 breeds in the Sheep HapMap dataset, with >20 genotyped animals, were analysed to identify the distribution of ROH within each breed.
A ROH was identified when an individual animal had consecutive homozygous SNP genotypes of the majority type, within the breed, at each locus. Missing genotypes were scored as if they were homozygous. Thus a ROH score represents the length, in numbers of SNP, of a continuous run of homozygosity comprising the majority homozygous genotype for the breed at each SNP. The probability of any given score, within a breed, was calculated by 1000 permutations of the whole HapMap dataset drawing 20 animals at random at each permutation. Over 30 breeds were found to have long ROH (>50 SNP; P<0. 05). For example, the various Texel subgroups were found to have a long ROH on OAR2 between bp positions  116,277,389 and 127,499,743. This contains the Myostatin gene and a mRNA previously identified as being a characteristic of the breed.
In the model the probability on re-introduction of BTV-8 through cattle imports per year was based on the probability that one imported cow was BTV-8 virus positive multiplied by the number of imported cattle per year. Where the probability of being BTV-8 virus positive at the moment of import depended on: (1) the BTV-8 status in the country of origin; (2) the probability that vertical transmission took place; (3) the probability that a calf received enough colostrum; (4) the age at import; (5) the probability that horizontal transmission took place; (6) the infectious period. To quantify each parameter available data and literature were used. When no data were available, an expert group made assumptions, which were evaluated using sensitivity analyses. Furthermore, 5 scenario's including expanding the risk towards all BTV types were added to the model.
Session 56b Theatre 4 Session 56b Theatre 3 Standardisation of milk MIR spectra: a first step to create new tools of dairy farm management C. Grelet, J. A. Fernandez Pierna, F. Dehareng and P. Dardenne Walloon Agricultural Research Center, Valorisation of Agricultural Products, 24 Chaussée de Namur, 5030 Gembloux, Belgium; c. grelet@cra. wallonie. be  This work is performed in the framework of the OptiMIR EU project that aims to use mid infrared (MIR) spectrum of milk as the mirror of the cow status. Spectra from different countries are matched with physiological data in a common database to create calibrations predicting cow fertility, health, environmental and feeding indicators. In order to reach this goal, a procedure to standardize dairy milk MIR spectra from different apparatus from several brands inside this European dairy network is necessary to create a common and transnational spectral database.
The method used is Piecewise Direct Standardization (PDS), which match slave apparatus spectra on those obtained with a 'master', wavelength by wavelength. The procedure is validated using different prediction models applied on the master and slaves spectra before and after its application. In the case of fat prediction, for instance, a decrease after the application of PDS from 0. 3781 to 0 and from 0. 4609 to 0. 0156 for bias and RMSE respectively has been obtained. Stability of these results in time has been proved by the application of the PDS coefficients on slave spectra collected one month later. Bias and RMSE also decreased, respectively from 0. 4118 to 0. 0350 and from 0. 4458 to 0. 0393. These results have shown that the PDS method reduces the inherent spectra variability between apparatus, and then allowing the grouping of spectra in a common database.
One of the challenges is to combat subclinical states causing increased risk of disease and suboptimal performance and reproduction. This calls for e. g. physiologically based measures from easily accessible samples, e. g. milk, that can be collected and analysed automatically in-line and used real-time. Challenges for future disease prevention and management of individual dairy cows are believed to include monitoring of physiological imbalance and understanding how e. g. nutrition and management of the individual cow should be changed to bring the cow in balance and thereby reduce risk of disease and suboptimal performance and improve welfare. Session 57 Theatre 2 Session 57 Theatre 1 A graph database to store and manage phenotypic, pedigree and genotypic data of livestock F. Biscarini, M.
Picciolini, D. Iamartino, A. Stella, F. Strozzi and E. Nicolazzi PTP (Parco Tecnologico Padano), Bioinformatics, Via Einstein, Loc. Cascina Codazza, 26900 Lodi, Italy; filippo. biscarini@tecnoparco. org  Thanks to recent developments in sequencing and genotyping technologies, increasing amounts of data are being generated for the livestock industry and research. This is urging operators to find solutions for the storage, manipulation, visualization and analysis of large data sets. Livestock examples are pedigree records, phenotypes, SNP genotypes, and whole-genome sequences. Binary or ASCII files are often used to archive and transfer such data, but have shortcomings: are cumbersome to manipulate, need to be read and parsed each time, and are far from having standard formats. Databases offer a better way to handle big data in terms of space, data safety and stability, ease of access and format standardization.
In relational databases data are represented in tables related through unique keys. Graph databases are composed of nodes (the elements) and edges (the connections among the elements). For instance, nodes may represent animals and markers, and the relationships between nodes model the animal genotypes at marker loci. We have implemented a graph database using the Neo4j technology. Data on 529 Italian Mediterranean buffaloes were used as case study. Pedigree, lactation records and Affymetrix 90k SNP-chip genotypes were available. We modelled a base node for the entire database and a category node for each of the three layers of elements: animal nodes (ID, sex, age), SNP nodes (name, chromosome, position) and trait nodes (name, class, value range). Connections between nodes modelled SNP genotypes, phenotypic observations and pedigree relationships.
Cypher and Neo4j native methods were used as query languages to extract, add, edit and remove records. Graph databases are well suited to represent interconnected data, may have billions of nodes and relationships, are traversed and queried much faster than relational databases, and allow for the ready implementation of algorithms (e. g. minimum spanning tree). EOL: a new ontology for livestock system and rearing conditions L. Joret 1 , J. Bugeon 1 , J. Aubin 2 , J. P. The development of ontologies is prerequisite for better organizing and exploiting the knowledge coming from the large quantity of data available nowadays in biology. ATOL (http://www. atol-ontology. com) for 'Animal Trait Ontology for Livestock' has been devoted to the definition and organisation of the phenotypic characters of farming animals (fish, poultry, mammals).
Taking into account that a phenotype arises from the action of both the genotype and the environment (plus eventually epigenetics mechanism), a precise description of the animal rearing environments is critical. EOL for 'Environmental Ontology for Livestock' has been created to describe, in a generic manner, the livestock systems and the rearing conditions. In February 2013, EOL contains about 600 concepts distributed in 4 main branches: (1) the livestock farming system describing shortly how and for what reasons the system was conceived; (2) the farming structure for the physical environment of animal; (3) the farming environment for the biological, chemical and physical rearing conditions; (4) the feed nature, quality and distribution conditions. The combination of animal's traits concepts (ATOL) and the rearing conditions concepts (EOL) will allow a powerful annotation of animal phenotypic databases with explicit metadata.
The pedigree file consisted of 505,848 animals, including 218,727 males and 287,121 females. The predicted breeding values were obtained using the program PEST 2, and the complete pedigree analysis was performed by PopReport software. The results demonstrated that for the four different selection intensities considered, TOP 10, 1%, 10% and 30%, selection loss and reclassification of animals in ranking were detected for all evaluated traits when the two methodologies of analyses were compared. From the previous results could be concluded that multivariate joint analyses is the more appropriated method of genetic evaluation, especially for large databases. Funded by FAPESP and Fundação Araucária.
Sauvant 1 , P. Noziere 2 and J. L. Peyraud 3 1INRA-AgroParisTech, 16 rue C. Bernard, 75005 Paris, France, 2 UMR-URH, INRA, Theix, France, 3 UMR- Pegase, INRA, St Gilles, France; sauvant@agroparistech. fr    An INRA steering group is working in France to update the feed energy and protein units by 2013. An ultimate target is to predict the absorbed flows of nutrients and the animal responses to diets, particularly extreme diets. Recent publications demonstrated the interest of meta-analysis of experimental databases to predict feeding practices influences on quantitative digestion of substrates and absorption of nutrients. In Systali, similar approaches were applied to obtain new models of responses and to update the previous feed units. For that, large data bases of digestion have been built: 'Bovidig' (cattle digestion; 800 Exp, 2106 Tr), 'Rumener' (calorimetric studies on ruminants; 186 Exp, 1100 Tr) and 'Ovidig'(sheep digestion; 116  Exp, 384 Tr).
Evaluation on sheep of the INRA-Systali model of digestive interactions P. Nozière 1 , P. Chapoutot 2 and D. Sauvant 2 1 INRA,UMR 1213 Herbivores, Theix, 63122 St Genès Champanelle, France, 2 INRA-AgroParisTech, UMR  791 MoSAR, Paris, 75005, France; pierre. noziere@clermont. inra. fr   Renewing feeding systems to better predict animal responses to diets requires a more precise representation of digestive interactions. An aggregated model of digestion developed under the INRA 'Systali' project ensures consistency across empirical relationships obtained from large databases on digestion and metabolic balances. It allows predictions of the main digestive events involved in the renewed calculation of feed units. We aimed to evaluate the direct application on sheep of this model, mainly developed from data in cattle.
A database gathering measurements of digestion in sheep(Ovidig, 116 Experiments, 384 Treatments), has been build, carefully coded according to the experimental factors, to allow dissociation between intra-and inter-experiment variations. Treatments were characterized according to INRA feed tables at the entry of the model, implemented under Excel ('Systool'). The predictions (P) of the model were compared to the observed (O) data. Special care was devoted to effects of feeding level (FL), percentage of concentrates (PCO), and rumen protein balance (RPB), which are the main factors of digestive interactions introduced in the model. Session 05a Poster 5 Session 05b Theatre 1 The FL, PCO and RPB ranked from 0. 9 to 5. 1 (mean 2. 2) %BW, 0 to 100 (mean 42) %, -63 to 174 (mean 18) g/kg DMI, respectively.
The potential of milk MIR spectra to certify milk geographic origin L. M. Dale 1 , A. Laine 1 , A. Goubau 1 , H. Bel Mabrouk 1 , H. Hammami 1,2 and N. Gengler 1 1 Gembloux Agro Bio Tech, Animal Science, 2 Passage desDéportés, 5030, Gembloux, Belgium, 2 National  Fund for Scientific Research, 5 rue d'Egmont, 1000 Bruxelles, Belgium; lmdale@ulg. ac. be   Protecting and supporting local production systems, regional authorities, as well as producers, give a very important role to milk quality. Therefore, this study was aimed to investigate the potential of mid-infrared spectroscopy (MIR) for certifying the geographic origin of milk. Because milk MIR spectral databases and extra phenotypes (breed, testday, livestock herd and origin appellation of traditional products) were available in the Walloon Region of Belgium via European project OptiMIR (INTERREG IVB North West Europe Program), discrimination studies were conducted to distinguish the Ardennes region (which is linked to PDO 'Beurre d'Ardennes') from the rest of Wallonia.
821; P=0. 029), as activity level was higher before (mean ± standard error; 394±4 units) than after (387±4 units) trimming. The effects of hoof trimming on milk yield, ruminating time and locomotion score were indirect through interaction effects with other variables. The results show that hoof trimming affects dairy cow behaviour and performance. This study is part of the Marie Curie Initial Training Network BioBusiness (FP7-PEOPLE-ITN-2008), and contribution number 459-4398-951 funded by the Israeli Agricultural Research Organization (ARO).
Faecal near infrared spectroscopy to assess diet quality in tropical and temperate grassland V. Decruyenaere 1 , M. Boval 2 , S. Giger-Reverdin 3 , J. A. Fernández Pierna 1 and P. Dardenne 1 1 Walloon Agricultural Research Centre (CRAW), 9 ruede Liroux, 5030 Gembloux, Belgium, 2 INRA Centre West-Indies, Animal Production Unit (URZ), Domaine Duclos, 97170 Guadeloupe, France, 3 INRA-AgroParisTech, UMR 791 MoSAR, 75005 Paris, France; decruyenaere@cra. wallonie. be Near infrared reflectance spectroscopy (NIRS) is a rapid technology currently used for predicting the forage chemical composition. It now appears possible to estimate in vivo organic matter digestibility (OMD) and dry matter voluntary intake (DMVI) using NIRS applied to faeces (F. NIRS). In this study, the F. NIRS potential is demonstrated by building a large faecal database in terms of forage (temperate, tropical) and animal (sheep, goat, cattle) for predicting OMD and DMVI at grazing.
Both OMD and DMVI F. NIRS databases needs to generate diet-faecal pairs. So, OMD and DMVI reference values are obtained during digestibility trials. The final database contained 2214 faecal spectra (OMD range=0. 303-0. 849; DMVI range=24. 0-163. 0 g/kg metabolic weight (MW)) including 931 from tropical origin. Calibration equations have been built using two chemometric methods, a Modified Partial Least Squares (MPLS) procedure with cross validation and the Support Vector Machines (SVM) technique. MPLS model gives good precision for OMD (R 2 >0. 8 and standard error of cross-validation (SECV or prediction precision) close to 0. 03 digestibility units, SECV/ mean<4%). DMVI appears more difficult to predict as the MPLS model is poor (R 2 <0. 8, SECV>12 g/kg MW or more than 18% of the mean), probably due to a slightly non-linearity.
For this reason, the SVM technique has been applied with as result an improvement of the precision of OMD and DMVI prediction models. With SVM technique, R 2 is higher than 0. 85 for both parameters. The improvement is for DMVI, where the SECV became of 8. 6 g/kg MW (13% of the mean). Based on these results, if appropriate chemometric equations are developed, it seems possible to use temperate and tropical merged F. NIRS databases for predicting in vivo diet characteristics.
In these regions, caseins (BTA6), β-lactoglobulin (BTA11) and GHR (BTA20) genes are good candidates. Moreover, other significant QTL effects (P<10 -5 ), partially overlapping across breeds, were highlighted on BTA1, 2, 14, 17 and 19. These first results pave the way to causal mutation identification. This project receives financial support from ANR, Apis-Gène, Ministry of Agriculture (CASDAR), Cniel, FranceAgriMer and FGE.
An innovate methodology, the near-infrared spectroscopy (NIRS), has been developed to provides fast, nondestructive, and cost-effective measurements. NIRS has potential for rapid routine measurements of FA composition. Previous studies reported a correct prediction of major FA (C16:0, C18:0, C18:1 cis 9, saturated FA, monounsaturated FA) in meat with NIRS whereas prediction of essential FA as polyunsaturated FA (PUFA) is low. Thus, to compensate NIRS's deficiencies, our study aimed to develop predictive equations for PUFA from major FA. For this purpose, a database integrating data from the literature or obtained in our laboratory on the impact of breeding factors on the FA content of beef was built (91 publications, 407 treatments). Multiple linear regression analysis were performed for each FA to obtain correlation coefficients.
On the basis of results from a survey on fattening units located in Veneto region (north east Italy), this study aimed to provide reference values on main productive characteristics of intensive young bulls production system of north Italy. Data were collected in 17 herds and included information on growth performance and diets characteristics such as ingredients and chemical composition. The reference unit of the survey was a farm batch, intended as a group of young bulls homogeneous for genotype, fattening period and diets. The final database included 237 batches with an average size of 67 young bulls. Productive data and diet composition were analyzed using ANOVA with farm and breed as fixed effects. Average weight at starting and finishing fattening period was 370 and 669 kg, respectively, average length of fattening period was 232 d and average daily gain was 1.
Extensive list-building efforts resulted in a database of over 31,000 equine operations. Questionnaires were mailed to 15,000 operations, stratified by operation size and geographic location. Non-responders were contacted by telephone or field enumerators. The response rate was 71. 4%. The economic impact analysis included collecting expenditure data from equine event attendees (n=1,500 Session 18 Theatre 6 The 2012 Kentucky equine survey R. J. Session 18 Theatre 7 A study on equestrian tourists motivation and involvement J. Wu The University of Hull, Business School, Cottingham Road, Hull, United Kingdom, HU6 7RX, United  Kingdom; jie. wu@2007. hull. ac. uk     With an increasing diversity in leisure interests in 21 st century, individual tourism demand is changing from General Interest Tourism or Mixed Interest Tourism to Special Interest Tourism , which can be defined as the provision of customized leisure and recreational experiences driven by specific expressed interest of individuals and groups (Derrett, 2001).
heat stress episode in lactating Saanen and Alpine goats L. S. Jaber 1 , C. Duvaux-Ponter 2,3 , S. Hamadeh 1 and S. Giger-Reverdin 2,3 1 American University ofBeirut, Riad El Solh 1107-2020, 110236-Beirut, Lebanon, 2 AgroParisTech,  16 rue Claude Bernard, 75005 Paris, France, 3 INRA, 16 Rue Claude Bernard, 75005 Paris, France;  lj01@aub. edu. lb    ). These results show a good ODM ability of the Lacaune ewes. This research was supported by the ROQUEFORT'IN contract funded by FUI, Midi-Pyrénées region, Aveyron & Tarn departements & Rodez town. Responses to a.
A lot of products can be analysed by IRS: forages and feeds, effluents, faeces, milk, meat. All spectral information can be used in qualitative and quantitative ways to develop DST able to improve livestock system sustainability, herd management in regard to diet and animal welfare, to select efficient animals and this, for various animal species. Many developments are underway to merge databases of several research centres. So, NIRS is used to predict forage chemical composition; to estimate, from F. Maroto-Molina 1 , A. Gómez-Cabrera 1 , J. E. Guerrero-Ginel 1 , A. Garrido-Varo 1 , D. Sauvant 2 , G. Tran 2 , V. Heuzé 2 and D. C. Pérez-Marín 1 1 Universidad de Córdoba, Ctra. Nacional IV km 396, 14014 Córdoba, Spain, 2 AgroParisTech, 16 rue Claude Bernard, 75005 Paris, France; gilles. tran@zootechnie.
fr Data about the nutritional aspects of feed are systematically obtained in laboratories. Some initiatives are collecting them into large databases, but this information is highly variable, so data pre-processing is essential to ensure reliable results. The objective of this paper is to evaluate the performance of various methods regarding 2 aspects of pre-processing: outliers and missing data. A database containing nutritional data on roughly 18,000 alfalfa samples was used. Several methods, both univariate and multivariate, were examined for detecting outliers: Z-score, Chauvenet's, regression residuals, principal components, adjusted Wilks' and Local Outlier Factor. Detected outliers were traced and characterized. Various methods for handling missing data were tested as well, both deletion methods (listwise and pairwise) and imputation methods, univariate (mean substitution) and multivariate (regression imputation, Expectation-Maximization and Data Augmentation).