Mostrar el registro sencillo del ítem
Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat
| Autor: | Hassan, M.A. |
| Autor: | Mengjiao Yang |
| Autor: | Luping Fu |
| Autor: | Awais Rasheed |
| Autor: | Bangyou Zheng |
| Autor: | Xianchun Xia |
| Autor: | Yonggui Xiao |
| Autor: | He Zhonghu |
| Año: | 2019 |
| ISSN: | 1746-4811 (Print) |
| URI: | https://hdl.handle.net/10883/20808 |
| Formato: | |
| Lenguaje: | English |
| Editor: | BioMed Central |
| Copyright: | CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose. |
| Tipo: | Article |
| Lugar de publicación: | London (United Kingdom) |
| Número: | art. 37 |
| Volumen: | 15 |
| DOI: | 10.1186/s13007-019-0419-7 |
| Descripción: | Background. Plant height is an important selection target since it is associated with yield potential, stability and particularly with lodging resistance in various environments. Rapid and cost-effective estimation of plant height from airborne devices using a digital surface model can be integrated with academic research and practical wheat breeding programs. A bi-parental wheat population consisting of 198 doubled haploid lines was used for time-series assessments of progress in reaching final plant height and its accuracy was assessed by quantitative genomic analysis. UAV-based data were collected at the booting and mid-grain fill stages from two experimental sites and compared with conventional measurements to identify quantitative trait loci (QTL) underlying plant height. Results. A significantly high correlation of R2 = 0.96 with a 5.75 cm root mean square error was obtained between UAV-based plant height estimates and ground truth observations at mid-grain fill across both sites. Correlations for UAV and ground-based plant height data were also very high (R2 = 0.84–0.85, and 0.80–0.83) between plant height at the booting and mid-grain fill stages, respectively. Broad sense heritabilities were 0.92 at booting and 0.90–0.91 at mid-grain fill across sites for both data sets. Two major QTL corresponding to Rht-B1 on chromosome 4B and Rht-D1 on chromosome 4D explained 61.3% and 64.5% of the total phenotypic variations for UAV and ground truth data, respectively. Two new and stable QTL on chromosome 6D seemingly associated with accelerated plant growth was identified at the booting stage using UAV-based data. Genomic prediction accuracy for UAV and ground-based data sets was significantly high, ranging from r = 0.47–0.55 using genome-wide and QTL markers for plant height. However, prediction accuracy declined to r = 0.20–0.31 after excluding markers linked to plant height QTL. Conclusion. This study provides a fast way to obtain time-series estimates of plant height in understanding growth dynamics in bread wheat. UAV-enabled phenotyping is an effective, high-throughput and cost-effective approach to understand the genetic basis of plant height in genetic studies and practical breeding. |
| Agrovoc: | AERIAL SURVEYING |
| Agrovoc: | GENOMICS |
| Agrovoc: | QUANTITATIVE TRAIT LOCI |
| Agrovoc: | TRITICUM AESTIVUM |
| Agrovoc: | UNMANNED AERIAL VEHICLES |
| Datasets relacionados: | https://static-content.springer.com/esm/art%3A10.1186%2Fs13007-019-0419-7/MediaObjects/13007_2019_419_MOESM1_ESM.doc |
| Revista: | Plant Methods |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
Wheat
Wheat - breeding, phytopathology, physiology, quality, biotech