High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement

被引：0
作者：
Sumit Jangra
Vrantika Chaudhary
Ram C. Yadav
Neelam R. Yadav
机构：
[1] CCS Haryana Agricultural University,Department of Molecular Biology, Biotechnology, and Bioinformatics
来源：
Phenomics | 2021年 / 1卷
关键词：
High-throughput phenotyping; Imaging; Technologies; Platform; Crop improvement; Biotic and abiotic stress;
D O I：
暂无
中图分类号：
学科分类号：
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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页码：31 / 53
页数：22
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[1]  
Adam E(2017)Detecting the early stage of phaeosphaeria leaf spot infestations in maize crop using in situ hyperspectral data and guided regularized random forest algorithm J Spectrosc 2017 1-8
[2]  
Deng H(2016)Salinity tolerance loci revealed in rice using high-throughput non-invasive phenotyping Nat Commun 7 13342-76
[3]  
Odindi J(2014)Development and evaluation of a field-based high-throughput phenotyping platform Funct Plant Biol 41 68-498
[4]  
Abdel-Rahman EM(2009)Probing of photosynthetic reactions in four phytoplanktonic algae with a PEA fluorometer Photosynth Res 102 67-907
[5]  
Mutanga O(2004)Detecting sugarcane ‘orange rust’ disease using EO-1 Hyperion hyperspectral imagery Int J Remote Sens 25 489-1466
[6]  
Al-Tamimi N(2016)Quantitative monitoring of Sci Data 3 160055-192
[7]  
Brien C(2011) growth and development using high-throughput plant phenotyping New Phytol 191 895-1621
[8]  
Oakey H(2016)A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects Front Plant Sci 7 1414-522
[9]  
Berger B(2017)High-throughput non-destructive phenotyping of traits that contribute to salinity tolerance in Trans ASABE 60 1457-27
[10]  
Saade S(2016)Characterizing wheat response to water limitation using multispectral and thermal imaging Comput Electron Agric 128 181-57
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