Skip to main content
Download PDF

Correction to: Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture

Plant Methods volume 14, Article number: 57 (2018) Cite this article

The Original Article was published on 11 June 2018

Correction to: Plant Methods (2018) 14:46 https://doi.org/10.1186/s13007-018-0314-7

Unfortunately, in the original version [1] of this article, a funder note was missed out in the acknowledgement. The corrected acknowledgement is given below:

Acknowledgements

The authors thank all the field and lab assistants of CIMMYT’s Global Wheat Breeding Program who collected and processed the agronomic and breeding field data as well as the image data. The data used in this study was collected under projects supported by Bill and Melinda Gates Foundation and USAID.

Reference

  1. Montesinos-Lopez A, Montesinos-Lopez OA, de los Campos G, Crossa J, Burgueño J, Luna‑Vazquez FJ. Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture. Plant Methods. 2018;14:46.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Authors and Affiliations

  1. Departamento de Matemáticas, Centro Universitario de Ciencias Exactas e Ingenierías (CUCEI), Universidad de Guadalajara, 44430, Guadalajara, Jalisco, Mexico

    Abelardo Montesinos-López

  2. Facultad de Telemática, Universidad de Colima, 28040, Colima, Colima, Mexico

    Osval A. Montesinos-López & Francisco Javier Luna-Vazquez

  3. Epidemiology and Biostatistics and Statistics and Probability Departments, Michigan State University, 909 Fee Road, East Lansing, MI, 48824, USA

    Gustavo de los Campos

  4. Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT), Apdo. Postal 6-641, 06600, Mexico City, Mexico

    José Crossa & Juan Burgueño

Authors
  1. Abelardo Montesinos-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Osval A. Montesinos-López
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gustavo de los Campos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. José Crossa
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Juan Burgueño
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Francisco Javier Luna-Vazquez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Osval A. Montesinos-López or Gustavo de los Campos.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Montesinos-López, A., Montesinos-López, O.A., de los Campos, G. et al. Correction to: Bayesian functional regression as an alternative statistical analysis of high-throughput phenotyping data of modern agriculture. Plant Methods 14, 57 (2018). https://doi.org/10.1186/s13007-018-0321-8

Download citation

  • Published:

  • DOI: https://doi.org/10.1186/s13007-018-0321-8

Plant Methods

ISSN: 1746-4811