Effect of starch substitution with crude glycerol on growing rabbit and lactating doe performance

The aim of this work was to study the effect of dietary inclusion of 2.5 or 5.0% of glycerol in substitution for starch on performance of lactating does and fattening rabbits. Over four consecutive reproductive cycles, a total of 81 New Zealand ´ Californian rabbit does and 813 young rabbits weaned at 25 (fattening trial 1) or 35 (fattening trial 2) days of age were allocated at random to the experimental treatments. Inclusion of glycerol in the diet up to 5% did not influence total feed consumption of does and suckling rabbits, body weight and bioelectrical impedance of does at parturition or at day 21 of lactation and litter weight at weaning, or reproductive efficiency. Substitution of starch with glycerol did not affect feed intake, weight gain or mortality during fattening. The results of the current study indicate that crude glycerol from the biofuel industry can be used at levels up to 5% in rabbit diets without any detrimental or beneficial effect on performance

Essentials in Ontology Engineering: Methodologies, Languages, and Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative.