1,720,967 research outputs found
Genome-wide association studies of nutritional traits in peas (Pisum sativum L.) for biofortification
No full textPea (Pisum sativum L.) is a high-nutrient, cool-season legume of increasing relevance in plant-based nutrition and sustainable agriculture. As demand for alternative protein sources increases, improving pea seeds’ nutritional content and quality through genomics-assisted breeding has become a priority. Despite its importance, limited research has explored the genetic basis of nutritional traits in pea. In this study, 267 accessions from the United States Department of Agriculture (USDA) Pea Single Plant Plus Collection were evaluated across 3 years at two USDA-certified organic farms in South Carolina to (1) assess phenotypic variation, (2) characterize the population structure and origin, and (3) perform a genome-wide association study (GWAS) using 54,316 single-nucleotide polymorphism markers on five nutritional traits: protein concentration, sulfur-containing amino acids (SAAs), dietary fiber, total starch, and protein digestibility (PDg). Population structure analysis using ADMIXTURE and principal components analyses identified 10 ancestral subpopulations. GWAS identified 17 marker-trait associations for protein, SAA, and PDg, including a genomic hotspot on the proximal end of chromosome 5 associated with both protein and SAA. This region harbors candidate genes involved in seed development, germination, and protein biosynthesis, suggesting potential roles in protein and SAAs accumulation. These findings provide valuable insights into the genetic architecture underlying key nutritional traits and highlight candidate target genes for breeding high-quality, biofortified pea cultivars. This research expands the genetic potential of pea as a sustainable and nutritious crop alternative for plant-based food systems
Archivo adicional 8 de Mapeo genético y análisis QTL para la resistencia al tizón del cacahuete
No full textFil: De Blas, Francisco Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: De Blas, Francisco Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.Fil: Bruno, Cecilia I. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Bruno, Cecilia I. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Arias, René S. USDA-ARS-National Peanut Research Laboratory; Estados Unidos.Fil: Ballén-Taborda, Carolina. Center for Applied Genetic Technologies and Institute of Plant Breeding, Genetics and Genomics, University of Georgia; Estados Unidos.Fil: Mamani, Eva. Instituto Nacional Tecnología Agropecuaria; Argentina.Fil: Odinno, Claudio. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Odinno, Claudio. Criadero El Carmen; Argentina.Fil: Rosso, Melina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Rosso, Melina. Criadero El Carmen; Argentina.Fil: Costero, Beatriz P. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Bressano, Marina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Soave, Juan H. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Soave, Juan H. Criadero El Carmen; Argentina.Fil: Soave, Sara J. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Soave, Sara J. Criadero El Carmen; Argentina.Fil: Buteler, Mario I. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Buteler, Mario I. Criadero El Carmen; Argentina.Fil: Seijo, J. Guillermo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura; Argentina.Fil: Seijo, J. Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Botánica del Nordeste; Argentina.Fil: Massa, Alicia N. USDA-ARS-National Peanut Research Laboratory; Estados Unidos.Additional file 8: Custom UNIX script for filtering the genotyping data generated in this study.Archivo adicional 8: Script UNIX personalizado para filtrar los datos de genotipado generados en este estudioFil: De Blas, Francisco Javier. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: De Blas, Francisco Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto Multidisciplinario de Biología Vegetal; Argentina.Fil: Bruno, Cecilia I. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Bruno, Cecilia I. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Arias, René S. USDA-ARS-National Peanut Research Laboratory; Estados Unidos.Fil: Ballén-Taborda, Carolina. Center for Applied Genetic Technologies and Institute of Plant Breeding, Genetics and Genomics, University of Georgia; Estados Unidos.Fil: Mamani, Eva. Instituto Nacional Tecnología Agropecuaria; Argentina.Fil: Odinno, Claudio. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Odinno, Claudio. Criadero El Carmen; Argentina.Fil: Rosso, Melina. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Rosso, Melina. Criadero El Carmen; Argentina.Fil: Costero, Beatriz P. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Bressano, Marina. Universidad Nacional de Córdoba. Facultad de Ciencias Agropecuarias; Argentina.Fil: Soave, Juan H. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Soave, Juan H. Criadero El Carmen; Argentina.Fil: Soave, Sara J. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Soave, Sara J. Criadero El Carmen; Argentina.Fil: Buteler, Mario I. Universidad Nacional de Río Cuarto. Facultad de Agronomía y Veterinaria; Argentina.Fil: Buteler, Mario I. Criadero El Carmen; Argentina.Fil: Seijo, J. Guillermo. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas y Naturales y Agrimensura; Argentina.Fil: Seijo, J. Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Botánica del Nordeste; Argentina.Fil: Massa, Alicia N. USDA-ARS-National Peanut Research Laboratory; Estados Unidos
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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