Crop phenotyping studies with application to crop monitoring
Crop phenotyping studies with application to crop monitoring
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DOI：
10.1016/j.cj.2022.09.001
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发表时间：
2022-10
期刊：
影响因子：
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通讯作者：
Xiuliang Jin;Wanneng Yang;J. Doonan;C. Atzberger
中科院分区：
文献类型：
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作者：
Xiuliang Jin;Wanneng Yang;J. Doonan;C. Atzberger
面对植物压力和有限的资源，必须紧急可持续地提高作物产量，以适应未来几十年不断增长的全球人口和预期的气候变化[1]。常规作物育种受到表型选择和育种效率的限制。作物表型鉴定被定义为应用协议和方法获得与植物生化、功能或结构相关的特定性状表型，从全株或冠层水平到细胞水平[2]，[3]。基因组学辅助育种促进了粮食安全，但作物育种界需要更有效的方法来研究表型和基因型之间的关系。尽管高通量基因分型的成本很低，但作物表型和相关数据管理和分析仍然相对昂贵。高通量作物表型鉴定方法因其利用基因组资源进行作物产量遗传改良的潜力而受到越来越多的关注。它们提供了强大的工具来测量生理和农艺性状表型，在多个时间和空间尺度上量化和监测田间试验和育种苗圃中的大型遗传定义种群[4]、[5]、[6]、[7]、[8]。为了做到这一点，他们应用了先进的机器人技术、高科技传感器、数据处理系统和图像。几个新的生物信息学平台包括多维、大规模的性状表型数据集以及基因类型和组学信息。基因功能和环境响应现在可以利用基因分型、表型和多组学数据以前所未有的时间和空间分辨率进行剖析。这种能力将有助于克服作物产量逐步提高的限制。这期特刊的目的是调查遥感技术、传感器开发、技术平台以及基于多源数据流和图像估计作物性状表型的应用方面的最新创新研究。推出了题为《作物表型研究及其在作物监测中的应用》的特刊。在这里，我们按照主题的分类对这些论文进行了总结，并添加了我们的观点。
Crop yield must urgently be sustainably increased to accommodate a rising global population and anticipated climate change in the coming decades, in the face of plant stresses and limited resources [1]. Conventional crop breeding is limited by phenotypic selection and breeding efficiency. Crop phenotyping is defined as the application of protocols and methodologies to obtain a specific trait phenotype, ranging from whole plant or canopy level to cellular level, associated with plant biochemistry, function, or structure [2],[3]. Genomics-assisted breeding advances food security, but the crop breeding community needs more effective ways to study the relationship between phenotype and genotype. Although high-throughput genotyping is available at low cost, crop phenotyping and related data management and analysis remain relatively expensive. High-throughput crop phenotyping methods have received increasing attention for their potential for using genomic resources for the genetic improvement of crop yield. They provide powerful tools for measuring physiological and agronomic trait phenotypes, quantifying and monitoring large genetically defined populations in field experiments and breeding nurseries on multiple temporal and spatial scales [4],[5],[6],[7],[8]. To do this, they apply advanced robotics, high-tech sensors, data processing systems, and images. Several new bioinformatic platforms include multi-dimensional, large-scale trait phenotype datasets and genotypic and omics information. Gene functions and environmental responses can now be dissected with unprecedented temporal and spatial resolution using combined genotyping, phenotyping, and multi-omics data. This ability will help to overcome the limitation of incremental improvements in crop yield. The aim of this special issue is to investigate the latest innovative research in remote sensing technologies, sensor development, technological platforms, and applications for estimating crop trait phenotype based on multisource data streams and imagery. The special issue titled “Crop phenotyping studies with application to crop monitoring” is launched. Here we summarize these papers according to the classification of topics and add our perspectives.