- Open Access
Correction to: Soybean iron deficiency chlorosis high throughput phenotyping using an unmanned aircraft system
Plant Methods volume 15, Article number: 113 (2019)
The original article was published in Plant Methods 2019 15:97
Correction to: Plant Methods (2019) 15:97 https://doi.org/10.1186/s13007-019-0478-9
In the original article , under the subheading “Image data processing”, last paragraph, last sentence that reads as “The least …… data collection” was incorrectly published. The correct sentence should read as “Least-significant differences (P < 0.20) were calculated for all 36 trials on both ground-based and UAS-image based scores for both dates of data collection.” The original article has been corrected.
Dobbels AA, Lorenz AJ. Soybean iron deficiency chlorosis high throughput phenotyping using an unmanned aircraft system. Plant Methods. 2019;15:97.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
The original article can be found online at https://doi.org/10.1186/s13007-019-0478-9.
About this article
Cite this article
Dobbels, A.A., Lorenz, A.J. Correction to: Soybean iron deficiency chlorosis high throughput phenotyping using an unmanned aircraft system. Plant Methods 15, 113 (2019) doi:10.1186/s13007-019-0495-8