High-throughput phenotyping in cotton: a review

被引:0
|
作者
Irish Lorraine B. PABUAYON
Yazhou SUN
Wenxuan GUO
Glen L. RITCHIE
机构
[1] Texas Tech Univ,Department of Plant and Soil Science
[2] Texas A&M AgriLife Research and Extension Center,undefined
关键词
Cotton; High-throughput phenotyping; Remote sensing; Sensors; Spectral; Fluorescence; Thermal; Platforms; Aerial-based; Ground-based;
D O I
暂无
中图分类号
学科分类号
摘要
Recent technological advances in cotton (Gossypium hirsutum L.) phenotyping have offered tools to improve the efficiency of data collection and analysis. High-throughput phenotyping (HTP) is a non-destructive and rapid approach of monitoring and measuring multiple phenotypic traits related to the growth, yield, and adaptation to biotic or abiotic stress. Researchers have conducted extensive experiments on HTP and developed techniques including spectral, fluorescence, thermal, and three-dimensional imaging to measure the morphological, physiological, and pathological resistance traits of cotton. In addition, ground-based and aerial-based platforms were also developed to aid in the implementation of these HTP systems. This review paper highlights the techniques and recent developments for HTP in cotton, reviews the potential applications according to morphological and physiological traits of cotton, and compares the advantages and limitations of these HTP systems when used in cotton cropping systems. Overall, the use of HTP has generated many opportunities to accurately and efficiently measure and analyze diverse traits of cotton. However, because of its relative novelty, HTP has some limitations that constrains the ability to take full advantage of what it can offer. These challenges need to be addressed to increase the accuracy and utility of HTP, which can be done by integrating analytical techniques for big data and continuous advances in imaging.
引用
收藏
相关论文
共 50 条
  • [31] High-throughput phenotyping for trait detection in vineyards
    Kicherer, Anna
    Herzog, Katja
    Toepfer, Reinhard
    38TH WORLD CONGRESS OF VINE AND WINE (PART 1), 2015, 5
  • [32] Radiomics: a primer on high-throughput image phenotyping
    Lafata, Kyle J.
    Wang, Yuqi
    Konkel, Brandon
    Yin, Fang-Fang
    Bashir, Mustafa R.
    ABDOMINAL RADIOLOGY, 2022, 47 (09) : 2986 - 3002
  • [33] High-throughput plant phenotyping: a role for metabolomics?
    Hall, Robert D.
    D'Auria, John C.
    Ferreira, Antonio C. Silva
    Gibon, Yves
    Kruszka, Dariusz
    Mishra, Puneet
    van de Zedde, Rick
    TRENDS IN PLANT SCIENCE, 2022, 27 (06) : 549 - 563
  • [34] Plant chip for high-throughput phenotyping of Arabidopsis
    Jiang, Huawei
    Xu, Zhen
    Aluru, Maneesha R.
    Dong, Liang
    LAB ON A CHIP, 2014, 14 (07) : 1281 - 1293
  • [35] High-throughput phenotyping technology for maize roots
    Grift, T. E.
    Novais, J.
    Bohn, M.
    BIOSYSTEMS ENGINEERING, 2011, 110 (01) : 40 - 48
  • [36] High-throughput physical phenotyping of cell differentiation
    Jonathan Lin
    Donghyuk Kim
    Henry T. Tse
    Peter Tseng
    Lillian Peng
    Manjima Dhar
    Saravanan Karumbayaram
    Dino Di Carlo
    Microsystems & Nanoengineering, 3
  • [37] High-throughput mechanical phenotyping for diagnostic applications
    Prinz, Christelle
    Selhuber-Unkel, Christine
    EUROPEAN BIOPHYSICS JOURNAL WITH BIOPHYSICS LETTERS, 2023, 52 (SUPPL 1): : S46 - S46
  • [38] High-throughput phenotyping of rice growth traits
    Esther Lau
    Nature Reviews Genetics, 2014, 15 (12) : 778 - 778
  • [39] High-throughput physical phenotyping of cell differentiation
    Lin, Jonathan
    Kim, Donghyuk
    Tse, Henry T.
    Tseng, Peter
    Peng, Lillian
    Dhar, Manjima
    Karumbayaram, Saravanan
    Di Carlo, Dino
    MICROSYSTEMS & NANOENGINEERING, 2017, 3
  • [40] Radiomics: a primer on high-throughput image phenotyping
    Kyle J. Lafata
    Yuqi Wang
    Brandon Konkel
    Fang-Fang Yin
    Mustafa R. Bashir
    Abdominal Radiology, 2022, 47 : 2986 - 3002