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Journal of Integrative Agriculture  2020, Vol. 19 Issue (10): 2429-2438    DOI: 10.1016/S2095-3119(20)63154-9
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High-throughput phenotyping identifies plant growth differences under well-watered and drought treatments
Seth TOLLEY1, Yang Yang2, Mohsen MoHAMMADI1
 
1 Department of Agronomy, Purdue University, West Lafayette, IN 47907, United States
2 College of Agriculture, Department of Agronomy, Purdue University, West Lafayette, IN 47907, United States
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Abstract  
The ability to screen larger populations with fewer replicates and non-destructive measurements is one advantage of high-throughput phenotyping (HTP) over traditional phenotyping techniques.  In this study, two wheat accessions were grown in a controlled-environment with a moderate drought imposed from stem elongation to post-anthesis.  Red-green-blue (RGB) imaging was performed on 17 of the 22 d following the start of drought imposition.  Destructive measurements from all plants were performed at the conclusion of the experiment.  The effect of line was significant for shoot dry matter, spike dry matter, root dry matter, and tiller number, while the water treatment was significant on shoot dry matter and root dry matter.  The temporal, non-destructive nature of HTP allowed the drought treatment to be significantly differentiated from the well-watered treatment after 6 d in a line from Argentina and 9 d in a line from Chile.  This difference of 3 d indicated an increased degree of drought tolerance in the line from Chile.  Furthermore, HTP from the final day of imaging accurately predicted reference plant height (r=1), shoot dry matter (r=0.95) and tiller number (r=0.91).  This experiment illustrates the potential of HTP and its use in modeling plant growth and development.
 
Keywords:  high-throughput phenotyping        drought        controlled-environment        wheat  
Received: 25 July 2019   Accepted:
Fund: Financial support was from the College of Agriculture of Purdue University to Mohsen Mohammadi, USDA (1013073). We would like to thank Institute for Plant Sciences and College of Agriculture for facilitating controlled environment phenotyping research.
Corresponding Authors:  Correspondence Mohsen Mohammadi, Tel: +1-765-4966885, E-mail: mohamm20@purdue.edu   

Cite this article: 

Seth TOLLEY, Yang Yang, Mohsen MOHAMMADI. 2020. High-throughput phenotyping identifies plant growth differences under well-watered and drought treatments. Journal of Integrative Agriculture, 19(10): 2429-2438.

raus J, Kefauver S, Zaman-Allah M, Olsen M, Cairns J. 2018. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science, 23, 451–466.
Chen D, Neumann K, Friedel S, Kilian B, Chen M, Altmann T, Klukas C. 2014. Dissecting the phenotypic components of crop plant growth and drought responses based on highthroughput image analysis. The Plant Cell, 26, 4636–4655.
Chenu K, Porter J, Martre P, Basso B, Chapman S, Ewert F, Bindi M, Asseng S. 2017. Contribution of crop models to adaptation in wheat. Trends in Plant Science, 22, 472–490.
Consultative Group for International Agricultural Research (CGIAR). 2018. Translating high-throughput phenotyping into genetic gain. Trends in Plant Science, 23, 451–466.
Dai A. 2011. Drought under global warming: A review. Wiley Interdisciplinary Reviews: Climate Change, 2, 45–65.
Fahlgren N, Feldman M, Gehan M, Wilson M, Shyu C, Bryant D, Hill S, McEntree C, Warnasooriya S, Kumar I, Ficor T, Turnipseed S, Gilbert K, Brutnell T, Carrington J, Mockler T, Baxter I. 2015. A versatile phenotyping system and analytics platform reveals diverse temporal responses to water availability in setaria. Molecular Plant, 8, 1520–1535.
FAO (Food and Agriculture Organization). 2009. The challenge. Rome, Italy. [2019-02-21]. http://www.fao.org/fileadmin/templates/wsfs/docs/Issues_papers/HLEF2050_Global_Agriculture.pdf
FAO (Food and Agriculture Organization). 2017. FAOSTAT. [2019-02-21]. http://www.fao.org/faostat/en/#data/QC
Ge Y, Bai G, Stoerger V, Schnable J. 2016. Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging. Computers and Electronics in Agriculture, 127, 625–632.
Ghanem M, Marrou H, Sinclair T. 2015. Physiological phenotyping of plants for crop improvement. Trends in Plant Science, 20, 139–144.
International Wheat Genome Sequencing Consortium. 2018. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science, 361, 1–13.
Ley T. 2003. Visual crop moisture stress symptoms. [2019-02-20]. http://sis.prosser.wsu.edu
Lollato R, DeWolf E, Knapp M. 2013. Drought conditions across most of Kansas starts to affect the wheat crop. [2019-02-21]. https://webapp.agron.ksu.edu/agr_social/m_eu_article.throck?article_id=890
Lopes M S, Reynolds M P. 2012. Stay-green in spring wheat can be determined by spectral reflectance measurements (normalized difference vegetation index) independently from phenology. Journal of Experimental Botany, 63, 3789–3798.
Maqbool M, Ali A, ul Haq T, Majeed M, Lee D. 2015. Response of spring wheat (Triticum aestivum L.) to induced water stress at critical growth stages. Sarhad Journal of Agriculture, 31, 53–58.
Nezhadahmadi A, Prodhan Z, Faruq G. 2013. Drought tolerance in wheat. The Scientific World Journal, 2013, 1–12.
Ogren E, Oquist G. 1985. Effects of drought on photosynthesis, chlorophyll fluorescence and photoinhibition susceptibility in intact willow leaves. Planta, 166, 380–388.
Palta J A, Chen X, Milroy S, Rebetzke G, Dreccer M, Wat M. 2011. Large root systems: Are they useful in adapting wheat to dry environments? Functional Plant Biology, 38, 347–354.
del Pozo A, Yanez A, Matus I, Tapia G, Castillo D, Sanchez-Jardon L, Araus J. 2016. Physiological traits associated with wheat yield potential and performance under water-stress in a Mediterranean environment. Frontiers in Plant Science, 7, 1–13.
R Core Team. 2014. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Ray D, Ramankutty N, Mueller N, West P, Foley J. 2012. Recent patterns of crop yield growth and stagnation. Nature Communications, 3, 1–7.
Shakoor N, Lee S, Mockler T. 2017. High throughput phenotyping to accelerate crop breeding and monitoring of diseases in the field. Current Opinion in Plant Biology, 38, 184–192.
Venables W N, Ripley B D. 2002. Modern Applied Statistics with S. 4th ed. Springer, New York.
Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X, Wang G, Luo Q, Zhang Q, Liu Q, Xiong L. 2014. Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nature Communications, 5, doi: 101038/ncomms6087
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