Accuracy Assessment of Plant Height Estimates from UAVs
Plant height is an important trait that correlates with yield potential and lodging resistance. Real-time, accurate measurement of plant height across large area is a key to the successful implementation of the high-throughput phenotyping yet logistically challenging. Awais Rasheed and Zhonghu He from CIMMYT co-authored a research paper on the assessment of plant height measurement using unmanned aerial vehicles (UAVs). The paper, Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat, compared the conventional in-field measurements of plant height with the UAV-based estimates and found that their correlations are significant throughout the growth stages.
Abstract
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. 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.
Hassan, M.A., Yang, M., Fu, L., Rasheed, A., Zheng, B., Xia, X., Xiao, Y. and He, Z., 2019. Accuracy assessment of plant height using an unmanned aerial vehicle for quantitative genomic analysis in bread wheat. Plant methods, 15(1), p.37.
May 22, 2019
CGIAR-CSI
