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遥感连续性:HTP平台比较及野外应用中的潜在挑战

Remote sensing continuity: a comparison of HTP platforms and potential challenges with field applications.

作者信息

Herr Andrew W, Carter Arron H

机构信息

Department of Crop and Soil Sciences, Washington State University, Pullman, WA, United States.

出版信息

Front Plant Sci. 2023 Sep 18;14:1233892. doi: 10.3389/fpls.2023.1233892. eCollection 2023.

DOI:10.3389/fpls.2023.1233892
PMID:37790786
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10544974/
Abstract

In an era of climate change and increased environmental variability, breeders are looking for tools to maintain and increase genetic gain and overall efficiency. In recent years the field of high throughput phenotyping (HTP) has received increased attention as an option to meet this need. There are many platform options in HTP, but ground-based handheld and remote aerial systems are two popular options. While many HTP setups have similar specifications, it is not always clear if data from different systems can be treated interchangeably. In this research, we evaluated two handheld radiometer platforms, Cropscan MSR16R and Spectra Vista Corp (SVC) HR-1024i, as well as a UAS-based system with a Sentera Quad Multispectral Sensor. Each handheld radiometer was used for two years simultaneously with the unoccupied aircraft systems (UAS) in collecting winter wheat breeding trials between 2018-2021. Spectral reflectance indices (SRI) were calculated for each system. SRI heritability and correlation were analyzed in evaluating the platform and SRI usability for breeding applications. Correlations of SRIs were low against UAS SRI and grain yield while using the Cropscan system in 2018 and 2019. Dissimilarly, the SVC system in 2020 and 2021 produced moderate correlations across UAS SRI and grain yield. UAS SRI were consistently more heritable, with broad-sense heritability ranging from 0.58 to 0.80. Data standardization and collection windows are important to consider in ensuring reliable data. Furthermore, practical aspects and best practices for these HTP platforms, relative to applied breeding applications, are highlighted and discussed. The findings of this study can be a framework to build upon when considering the implementation of HTP technology in an applied breeding program.

摘要

在气候变化和环境变异性增加的时代,育种者正在寻找工具来维持和提高遗传增益及整体效率。近年来,高通量表型分析(HTP)领域作为满足这一需求的一种选择受到了更多关注。HTP有许多平台选项,但地面手持和遥控航空系统是两种常见的选择。虽然许多HTP设置具有相似的规格,但不同系统的数据是否可以互换处理并不总是很清楚。在本研究中,我们评估了两个手持辐射计平台,即Cropscan MSR16R和Spectra Vista公司(SVC)的HR - 1024i,以及一个配备Sentera Quad多光谱传感器的基于无人机的系统。在2018 - 2021年期间收集冬小麦育种试验数据时,每个手持辐射计与无人机系统同时使用了两年。计算了每个系统的光谱反射指数(SRI)。在评估平台和SRI在育种应用中的可用性时,分析了SRI的遗传力和相关性。在2018年和2019年使用Cropscan系统时,SRI与无人机SRI和籽粒产量的相关性较低。不同的是,2020年和2021年的SVC系统在无人机SRI和籽粒产量之间产生了中等程度的相关性。无人机SRI一直具有更高的遗传力,广义遗传力范围为0.58至0.80。在确保数据可靠方面,数据标准化和采集窗口是需要考虑的重要因素。此外,还强调并讨论了这些HTP平台相对于应用育种应用的实际方面和最佳实践。本研究的结果可以作为在应用育种计划中考虑实施HTP技术时的一个基础框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/dc7d859d136a/fpls-14-1233892-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/ac9245ae4047/fpls-14-1233892-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/fc0dc426d20b/fpls-14-1233892-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/3b16457f870c/fpls-14-1233892-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/dc7d859d136a/fpls-14-1233892-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/ac9245ae4047/fpls-14-1233892-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/fc0dc426d20b/fpls-14-1233892-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/3b16457f870c/fpls-14-1233892-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2582/10544974/dc7d859d136a/fpls-14-1233892-g004.jpg

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本文引用的文献

1
Climate change challenges plant breeding.气候变化给植物育种带来挑战。
Curr Opin Plant Biol. 2022 Dec;70:102308. doi: 10.1016/j.pbi.2022.102308. Epub 2022 Oct 21.
2
Breeder friendly phenotyping.繁殖友好表型鉴定。
Plant Sci. 2020 Jun;295:110396. doi: 10.1016/j.plantsci.2019.110396. Epub 2020 Jan 18.
3
Genomic Prediction and Indirect Selection for Grain Yield in US Pacific Northwest Winter Wheat Using Spectral Reflectance Indices from High-Throughput Phenotyping.利用高通量表型的光谱反射指数对美国太平洋西北地区冬小麦的产量进行基因组预测和间接选择。
Int J Mol Sci. 2019 Dec 25;21(1):165. doi: 10.3390/ijms21010165.
4
High-throughput phenotyping for crop improvement in the genomics era.高通量表型分析在基因组时代的作物改良中的应用。
Plant Sci. 2019 May;282:60-72. doi: 10.1016/j.plantsci.2019.01.007. Epub 2019 Jan 12.
5
Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral Indices for Early-Growth Evaluation of Maize Performance under Phosphorus Fertilization.地面与空中评估的RGB和多光谱指数在磷肥作用下玉米早期生长性能评估中的比较表现
Front Plant Sci. 2017 Nov 27;8:2004. doi: 10.3389/fpls.2017.02004. eCollection 2017.
6
Imaging the Photosystem I/Photosystem II chlorophyll ratio inside the leaf.在叶内对光系统 I/光系统 II 叶绿素比值进行成像。
Biochim Biophys Acta Bioenerg. 2017 Mar;1858(3):259-265. doi: 10.1016/j.bbabio.2017.01.008. Epub 2017 Jan 15.
7
A Direct Comparison of Remote Sensing Approaches for High-Throughput Phenotyping in Plant Breeding.植物育种中高通量表型分析遥感方法的直接比较
Front Plant Sci. 2016 Aug 3;7:1131. doi: 10.3389/fpls.2016.01131. eCollection 2016.
8
The Quest for Understanding Phenotypic Variation via Integrated Approaches in the Field Environment.通过田间环境中的综合方法探索表型变异
Plant Physiol. 2016 Oct;172(2):622-634. doi: 10.1104/pp.16.00592. Epub 2016 Aug 1.
9
Field high-throughput phenotyping: the new crop breeding frontier.大田高通量表型分析:作物新的育种前沿。
Trends Plant Sci. 2014 Jan;19(1):52-61. doi: 10.1016/j.tplants.2013.09.008. Epub 2013 Oct 16.
10
Yield Trends Are Insufficient to Double Global Crop Production by 2050.单产趋势不足以在2050年前使全球作物产量翻番。
PLoS One. 2013 Jun 19;8(6):e66428. doi: 10.1371/journal.pone.0066428. Print 2013.