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

Aluminum tolerance association mapping in triticale

en
Abstract

Background: Crop production practices and industrialization processes result in increasing acidification of arable soils. At lower pH levels (below 5.0), aluminum (Al) remains in a cationic form that is toxic to plants, reducing growth and yield. The effect of aluminum on agronomic performance is particularly important in cereals like wheat, which has promoted the development of programs directed towards selection of tolerant forms. Even in intermediately tolerant cereals (i.e., triticale), the decrease in yield may be significant. In triticale, Al tolerance seems to be influenced by both wheat and rye genomes. However, little is known about the precise chromosomal location of tolerance-related genes, and whether wheat or rye genomes are crucial for the expression of that trait in the hybrid. Results: A mapping population consisting of 232 advanced breeding triticale forms was developed and phenotyped for Al tolerance using physiological tests. AFLP, SSR and DArT marker platforms were applied to obtain a sufficiently large set of molecular markers (over 3000). Associations between the markers and the trait were tested using General (GLM) and Multiple (MLM) Linear Models, as well as the Statistical Machine Learning (SML) approach. The chromosomal locations of candidate markers were verified based on known assignments of SSRs and DArTs or by using genetic maps of rye and triticale. Two candidate markers on chromosome 3R and 9, 15 and 11 on chromosomes 4R, 6R and 7R, respectively, were identified. The r(2) values were between 0.066 and 0.220 in most cases, indicating a good fit of the data, with better results obtained with the GML than the MLM approach. Several QTLs on rye chromosomes appeared to be involved in the phenotypic expression of the trait, suggesting that rye genome factors are predominantly responsible for Al tolerance in triticale. Conclusions: The Diversity Arrays Technology was applied successfully to association mapping studies performed on triticale breeding forms. Statistical approaches allowed the identification of numerous markers associated with Al tolerance. Available rye and triticale genetic maps suggested the putative location of the markers and demonstrated that they formed several linked groups assigned to distinct chromosomes (3R, 4R, 6R and 7R). Markers associated with genomic regions under positive selection were identified and indirectly mapped in the vicinity of the Al-tolerant markers. The present findings were in agreement with prior reports.

en
Year
2012
en
Country
  • PL
  • AU
Organization
  • IHAR_Plant_Breeding_&_Acclim_Inst (PL)
Data keywords
  • machine learning
en
Agriculture keywords
    en
    Data topic
    • big data
    • information systems
    • modeling
    en
    SO
    BMC GENOMICS
    Document type

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    Institutions 10 co-publis
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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.