El papel de la biblioteca en la formación de competencias informacionales e informáticas

Se destaca la importancia de la biblioteca en la implantación y desarrollo de la Alfabetización Informacional como medio imprescindible de formación en competencias informacionales y digitales en la actual sociedad de información. Dicho papel es impulsado por diferentes instituciones internacionales y nacionales. Se hace especial mención de las bibliotecas universitarias en el nuevo Espacio Europeo de Educación Superior y, sobre todo, en el ámbito español donde REBIUN ha adoptado el término de “Competencias Informacionales e Informáticas” (CI2) y ha influido en el paso de una formación tradicional de usuarios a una formación basada en competencias que deben adquirir los alumnos, contribuyendo a mejorar la calidad de la educación. Todo ello apoyado en una planificación y en la transformación de las bibliotecas en Centros de Recursos de Información y Aprendizaje. En este proceso de cambio, la web social 2.0 y 3.0 es elemento esencial de interacción y motivación interna para conseguir que el alumno se convierta en sujeto activo de su propio aprendizaje. La implementación por parte de numerosas bibliotecas de las diferentes herramientas sociales como Facebook y Twitter ha logrado una visibilidad mayor y un elemento dinamizador.The importance of the library in the implementation and development of information literacy as an essential means of training in Information and Digital Competency in the current information society is emphasized. This paper is driven by various international and national institutions. Special mention of university libraries in the new European Higher Education and is made especially in the area where REBIUN Spanish adopted the term "Informational and Computer Literacy" (CI2) and has influenced the passage of a training traditional users to a competency-based training that students should acquire, helping to improve the quality of education. All supported in planning and in the transformation of libraries in Resource Centers Information and Learning. In this process of change, social web 2.0 and 3.0 is an essential element of interaction and internal motivation to get students to become active subjects of their own learning. The implementation by numerous libraries of different social tools such as Facebook and Twitter has achieved greater visibility and a dynamic element

Citation patterns in Educational Science theses at the University of Córdoba

This paper analyses citation patterns in 30 doctoral theses in the field of Education Sciences, submitted at the University of Córdoba (Spain) between 1997 and 2010. A preference was found for citing books as opposed to articles. The most widely-cited journal was a Spanish education-specific publication, Enseñanza de las ciencias. Only a small number of journals from the stock of periodical publications held and managed by the Faculty of Education Sciences Library were cited

Citation patterns in Educational Science theses at the University of Córdoba

This paper analyses citation patterns in 30 doctoral theses in the field of Education Sciences, submitted at the University of Córdoba (Spain) between 1997 and 2010. A preference was found for citing books as opposed to articles. The most widely-cited journal was a Spanish education-specific publication, Enseñanza de las ciencias. Only a small number of journals from the stock of periodical publications held and managed by the Faculty of Education Sciences Library were cited

High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques

The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of "linking genotype and phenotype," considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders

Citation patterns in Educational Science theses at the University of Córdoba

This paper analyses citation patterns in 30 doctoral theses in the field of Education Sciences, submitted at the University of Córdoba (Spain) between 1997 and 2010. A preference was found for citing books as opposed to articles. The most widely-cited journal was a Spanish education-specific publication, Enseñanza de las ciencias. Only a small number of journals from the stock of periodical publications held and managed by the Faculty of Education Sciences Library were cited

High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques

The need for the olive farm modernization have encouraged the research of more efficient crop management strategies through cross-breeding programs to release new olive cultivars more suitable for mechanization and use in intensive orchards, with high quality production and resistance to biotic and abiotic stresses. The advancement of breeding programs are hampered by the lack of efficient phenotyping methods to quickly and accurately acquire crop traits such as morphological attributes (tree vigor and vegetative growth habits), which are key to identify desirable genotypes as early as possible. In this context, an UAV-based high-throughput system for olive breeding program applications was developed to extract tree traits in large-scale phenotyping studies under field conditions. The system consisted of UAV-flight configurations, in terms of flight altitude and image overlaps, and a novel, automatic, and accurate object-based image analysis (OBIA) algorithm based on point clouds, which was evaluated in two experimental trials in the framework of a table olive breeding program, with the aim to determine the earliest date for suitable quantifying of tree architectural traits. Two training systems (intensive and hedgerow) were evaluated at two very early stages of tree growth: 15 and 27 months after planting. Digital Terrain Models (DTMs) were automatically and accurately generated by the algorithm as well as every olive tree identified, independently of the training system and tree age. The architectural traits, specially tree height and crown area, were estimated with high accuracy in the second flight campaign, i.e. 27 months after planting. Differences in the quality of 3D crown reconstruction were found for the growth patterns derived from each training system. These key phenotyping traits could be used in several olive breeding programs, as well as to address some agronomical goals. In addition, this system is cost and time optimized, so that requested architectural traits could be provided in the same day as UAV flights. This high-throughput system may solve the actual bottleneck of plant phenotyping of “linking genotype and phenotype,” considered a major challenge for crop research in the 21st century, and bring forward the crucial time of decision making for breeders.The breeding field trials in which the experiments were performed are funded by Interaceituna (Spanish Inter-professional Association for Table Olives) through the FIUS projects PR201402347 and PRJ201703174. This research was partly financed by the AGL2017-83325-C4-4-R (Spanish Ministry of Science, Innovation and Universities and AEI/EU-FEDER funds), and Intramural-CSIC 201940E074 Projects. Research of AC was supported by the Juan de la Cierva Program-Incorporación of the Spanish MINECO funds.Peer reviewe

Exploring UAV-imagery to support genotype selection in olive breeding programs

Airborne methodologies based on unmanned aerial vehicles (UAV) are becoming an extraordinary tool for implementing fast, accurate and affordable phenotyping strategies within plant breeding programs. The aim of this paper was to study the potential use of a previously developed UAV-OBIA platform, to fasten and support decision making for olive breeders regarding the selection of the most promising genotypes in terms of tree geometric traits. In particular, we have studied the feasibility of the system to efficiently classify and select olive genotypes according to four architectural parameters: tree height, crown diameter, projected crown area and canopy volume. These vegetative growth traits and their evolution during the first months after planting are key selection criteria in olive breeding programs. On-ground measurements and UAV estimations were recorded over two years (when trees were 15 and 27 months old, respectively) in two olive breeding trials using different training systems, namely intensive open vase and super high-density hedgerows. More than 1000 young trees belonging to 39 olive accessions, including new cross-bred genotypes and traditional cultivars, were assessed. Even though the accuracy in the UAV estimation compared to the on-ground measurements largely improved the second year, both methodologies detected in both years a high variability and significant differences among the studied genotypes, allowing for statistical comparisons among them. Genotype rankings based on the on-ground measures and UAV estimations were compared. The resulting Spearman’s rank coefficient correlations were very high, at above 0.85 in most cases, which highlights that very similar genotype classifications were achieved from either field-measured or airborne-estimated data. Thus, UAV imagery may be used to assess geometric traits and to develop rankings for the efficient screening and selection of genotypes in olive breeding programs.The breeding field trials in which the experiments were performed are funded by Interaceituna (Spanish Inter-Professional Association for Table Olives) through the FIUS projects PR201402347 and PRJ201703174. This research was partly financed by the AGL2017-83325-C4-4-R Project (Spanish Ministry of Science, Innovation and Universities and AEI-EU-FEDER funds), and Intramural-CSIC 201840E002 Projects. Research of A.I. de Castro was supported by the Juan de la Cierva Incorporación Program of the Spanish MINECO funds

Fenotipado de olivar mediante análisis de imágenes procedentes de vehículo aéreo no tripulado

Este trabajo se ha realizado conjuntamente por investigadores de diversas áreas pertenecientes a tres Instituciones Públicas localizadas en Andalucía (IAS-CSIC-Córdoba, Universidad de Sevilla e IFAPA-Córdoba). De forma resumida se presenta una tecnología consistente en el análisis automatizado de imágenes procedentes de un vehículo aéreo no tripulado (UAV) para el fenotipado de genotipos de olivo dentro de varios Programas de Mejora Genética. Se demuestra la utilidad en condiciones de campo de los modelos 3D que se han generado para la reconstrucción de cada olivo con dos objetivos agronómicos: i) fenotipado de variedades y selecciones de olivo en árboles muy jóvenes, y ii) cuantificación del efecto enanizante de variedades de bajo vigor utilizadas como patrones en la variedad "Picual". Los resultados obtuvieron precisiones >85 % en la cuantificación de la arquitectura de cada árbol respecto a los datos tomados desde tierra. Estos resultados han permitido: i) la discriminación entre variedades, y ii) la cuantificación de reducciones de hasta 50 % del volumen copa de `Picual¿ dependiendo del patrón utilizado. La información de la arquitectura 3D (altura, área proyectada o volumen de copa) de cada olivo en una parcela de olivar podría ser asimismo de gran utilidad para conocer numerosos aspectos relacionados con el manejo de las plantaciones, tales como el estados sanitario, nutricional e hídrico y respuesta a la poda, entre otros