e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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Title

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

en
Abstract

Background: Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal's life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality. Results: The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism. Conclusions: These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle.

en
Year
2013
en
Country
  • BR
Organization
  • Embrapa (BR)
  • Univ_Fed_Sao_Carlos_UFSCar (BR)
  • Univ_Fed_Lavras_UFLA (BR)
  • Univ_Estadual_Paulista_UNESP (BR)
Data keywords
  • machine learning
en
Agriculture keywords
  • cattle
  • livestock
en
Data topic
  • big data
  • modeling
en
SO
BMC GENETICS
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Embrapa (BR)
uid:/KMPS0TG3
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.