吞吐量
选择(遗传算法)
计算机科学
领域(数学)
新兴技术
数据科学
人工智能
操作系统
无线
数学
纯数学
作者
Sumit Jangra,Vrantika Chaudhary,Ram C. Yadav,Neelam R. Yadav
出处
期刊:Phenomics
[Springer Nature]
日期:2021-04-01
卷期号:1 (2): 31-53
被引量:105
标识
DOI:10.1007/s43657-020-00007-6
摘要
Development of high-throughput phenotyping technologies has progressed considerably in the last 10 years. These technologies provide precise measurements of desired traits among thousands of field-grown plants under diversified environments; this is a critical step towards selection of better performing lines as to yield, disease resistance, and stress tolerance to accelerate crop improvement programs. High-throughput phenotyping techniques and platforms help unraveling the genetic basis of complex traits associated with plant growth and development and targeted traits. This review focuses on the advancements in technologies involved in high-throughput, field-based, aerial, and unmanned platforms. Development of user-friendly data management tools and softwares to better understand phenotyping will increase the use of field-based high-throughput techniques, which have potential to revolutionize breeding strategies and meet the future needs of stakeholders.
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