Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species.

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  • Additional Information
    • NAICS/Industry Codes:
      111999 All other miscellaneous crop farming
    • Abstract:
      Forage breeding is essential for animal production, and its effectiveness depends on available genetic diversity. However, breeding is challenged when there is limited evaluation of genebank accessions. Predictive characterisation based on ecogeographic information is a promising approach to address the urgent need to expedite evaluation of target traits in existing collections of forage genetic resources. Using white clover (Trifolium repens L.) as an example, we applied predictive characterisation to model the expression of cyanogenesis, an important process related to the generation of anti-quality compounds. Data on genebank accessions and other population occurrences were divided into two subsets, one including accessions that had been evaluated for this trait, and the other with those that had not. The occurrence sites of the records with the best geo-referencing quality were characterised ecogeographically. The cyanogenesis trait was predicted using the calibration method, in which some selected ecogeographic variables were used as independent variables. Thus, we identified 470 populations with high probability of being acyanogenic. A small sample of populations (18 accessions) was evaluated to ratify the usefulness of this approach. Seventeen of the evaluated accessions showed a complete acyanogenic response and one showed 95% acyanogenic plants. Our study also expanded the areas previously rated as highly acyanogenic. In conclusion, our results contribute in a predictive way and with minimum cost to increase the knowledge of wild populations and genebank accessions in relation to a target trait. This facilitation in the generation of evaluation data may encourage greater investment in forage plant breeding and boost germplasm utilisation. Is it possible to locate plants with a desired trait without performing any field or lab trial? As cyanoglucosides, which are toxic for cattle, may be present in white clover, we successfully applied a method to find cyanoglucoside-free white clover populations based on a previous association between the presence of this compound and certain environmental conditions. The potential to predict traits using this method may encourage greater investment in forage plant breeding and boost utilisation of seeds preserved in genebanks. [ABSTRACT FROM AUTHOR]
    • Abstract:
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    • Author Affiliations:
      1Escuela Internacional de Doctorado, Universidad Rey Juan Carlos, Calle Tulipán s/n, 28933 Móstoles, Madrid, Spain.
      2Centro Nacional de Recursos Fitogenéticos, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Autovía A-2 Km 36, 28800 Alcalá de Henares, Madrid, Spain.
      3Facultad de Ciencias Agrarias, Universidad Nacional de Colombia, Sede Bogotá, Ciudad Universitaria, A.A. 14490, Bogotá D.C., Colombia.
      4National Laboratory for Genetic Resources Preservation, USDA ARS, Fort Collins, CO, USA.
      5Área de Biodiversidad y Conservación, Universidad Rey Juan Carlos, Calle Tulipán s/n, 28933 Móstoles, Madrid, Spain.
    • Full Text Word Count:
      6739
    • ISSN:
      1836-0947
    • Accession Number:
      10.1071/CP18346
    • Accession Number:
      137186864
  • Citations
    • ABNT:
      GARCÍA SÁNCHEZ, R. M. et al. Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species. Crop & Pasture Science, [s. l.], v. 70, n. 6, p. 546–554, 2019. Disponível em: . Acesso em: 12 nov. 2019.
    • AMA:
      García Sánchez RM, Parra-Quijano M, Greene S, Iriondo JM. Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species. Crop & Pasture Science. 2019;70(6):546-554. doi:10.1071/CP18346.
    • APA:
      García Sánchez, R. M., Parra-Quijano, M., Greene, S., & Iriondo, J. M. (2019). Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species. Crop & Pasture Science, 70(6), 546–554. https://doi.org/10.1071/CP18346
    • Chicago/Turabian: Author-Date:
      García Sánchez, Rosa María, Mauricio Parra-Quijano, Stephanie Greene, and José María Iriondo. 2019. “Predictive Characterisation Identifies Global Sources of Acyanogenic Germplasm of a Key Forage Species.” Crop & Pasture Science 70 (6): 546–54. doi:10.1071/CP18346.
    • Harvard:
      García Sánchez, R. M. et al. (2019) ‘Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species’, Crop & Pasture Science, 70(6), pp. 546–554. doi: 10.1071/CP18346.
    • Harvard: Australian:
      García Sánchez, RM, Parra-Quijano, M, Greene, S & Iriondo, JM 2019, ‘Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species’, Crop & Pasture Science, vol. 70, no. 6, pp. 546–554, viewed 12 November 2019, .
    • MLA:
      García Sánchez, Rosa María, et al. “Predictive Characterisation Identifies Global Sources of Acyanogenic Germplasm of a Key Forage Species.” Crop & Pasture Science, vol. 70, no. 6, June 2019, pp. 546–554. EBSCOhost, doi:10.1071/CP18346.
    • Chicago/Turabian: Humanities:
      García Sánchez, Rosa María, Mauricio Parra-Quijano, Stephanie Greene, and José María Iriondo. “Predictive Characterisation Identifies Global Sources of Acyanogenic Germplasm of a Key Forage Species.” Crop & Pasture Science 70, no. 6 (June 2019): 546–54. doi:10.1071/CP18346.
    • Vancouver/ICMJE:
      García Sánchez RM, Parra-Quijano M, Greene S, Iriondo JM. Predictive characterisation identifies global sources of acyanogenic germplasm of a key forage species. Crop & Pasture Science [Internet]. 2019 Jun [cited 2019 Nov 12];70(6):546–54. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=137186864&custid=s8280428