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DOI10.3390/rs11101244
UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat
Gracia-Romero, Adrian1,2; Kefauver, Shawn C.1,2; Fernandez-Gallego, Jose A.1,2; Vergara-Diaz, Omar1,2; Teresa Nieto-Taladriz, Maria3; Araus, Jose L.1,2
发表日期2019
EISSN2072-4292
卷号11期号:10
英文摘要

Climate change is one of the primary culprits behind the restraint in the increase of cereal crop yields. In order to address its effects, effort has been focused on understanding the interaction between genotypic performance and the environment. Recent advances in unmanned aerial vehicles (UAV) have enabled the assembly of imaging sensors into precision aerial phenotyping platforms, so that a large number of plots can be screened effectively and rapidly. However, ground evaluations may still be an alternative in terms of cost and resolution. We compared the performance of red-green-blue (RGB), multispectral, and thermal data of individual plots captured from the ground and taken from a UAV, to assess genotypic differences in yield. Our results showed that crop vigor, together with the quantity and duration of green biomass that contributed to grain filling, were critical phenotypic traits for the selection of germplasm that is better adapted to present and future Mediterranean conditions. In this sense, the use of RGB images is presented as a powerful and low-cost approach for assessing crop performance. For example, broad sense heritability for some RGB indices was clearly higher than that of grain yield in the support irrigation (four times), rainfed (by 50%), and late planting (10%). Moreover, there wasn't any significant effect from platform proximity (distance between the sensor and crop canopy) on the vegetation indexes, and both ground and aerial measurements performed similarly in assessing yield.


WOS研究方向Remote Sensing
来源期刊REMOTE SENSING
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/97595
作者单位1.Univ Barcelona, Fac Biol, Plant Physiol Sect, Integrat Crop Ecophysiol Grp, E-08028 Barcelona, Spain;
2.AGROTECNIO Ctr Res Agrotechnol, Ave Rovira Roure 191, Lleida 25198, Spain;
3.Inst Nacl Invest & Tecnol Agr & Alimentaria INIA, Ctra Coruna Km 7-5, Madrid 28040, Spain
推荐引用方式
GB/T 7714
Gracia-Romero, Adrian,Kefauver, Shawn C.,Fernandez-Gallego, Jose A.,et al. UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat[J],2019,11(10).
APA Gracia-Romero, Adrian,Kefauver, Shawn C.,Fernandez-Gallego, Jose A.,Vergara-Diaz, Omar,Teresa Nieto-Taladriz, Maria,&Araus, Jose L..(2019).UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat.REMOTE SENSING,11(10).
MLA Gracia-Romero, Adrian,et al."UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat".REMOTE SENSING 11.10(2019).
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