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