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Potential of thermal image analysis for screening salt stress-tolerant soybean (Glycine max)

Published online by Cambridge University Press:  16 July 2014

Jin-Won Kim
Affiliation:
Department of Plant Science, Research Institute for Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
Tae-Young Lee
Affiliation:
Department of Plant Science, Research Institute for Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
Gyoungju Nah
Affiliation:
Department of Plant Science, Research Institute for Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
Do-Soon Kim*
Affiliation:
Department of Plant Science, Research Institute for Agriculture and Life Sciences, College of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea
*
* Corresponding author. E-mail: [email protected]

Abstract

Non-destructive high-throughput phenotyping based on phenomics is an emerging technology for assessing the genetic diversity of various traits and screening in breeding programmes. In this study, non-destructive measurements of leaf temperature and chlorophyll fluorescence were conducted to investigate the physiological responses of soybean (Glycine max) to salt stress so as to set up a non-destructive screening method. Two-week-old seedlings of soybean in the V2 stage were treated with 0, 12.5, 25, 50 and 100 mM NaCl to induce salt stress. Three parameters, photosynthesis rate, stomatal conductance and chlorophyll fluorescence, decreased significantly, while soybean leaf temperature increased by exhibiting a positive correlation with NaCl concentration (P< 0.001). Soybean leaf temperature increased significantly at 50 mM NaCl when compared with the untreated control, although no visual symptom was observed. We selected leaf temperature as a major physiological parameter of salt stress as its measurement is much easier, faster and cheaper than that of other physiological parameters. Therefore, leaf temperature can be used for evaluating the responses to salt stress in soybean as a non-destructive and phenomic parameter. The results of this study suggest that non-destructive parameters such as chlorophyll fluorescence and leaf temperature are useful tools for assessing the genetic diversity of soybean with regard to salt stress tolerance and to screen salt stress-tolerant soybean for breeding.

Type
Research Article
Copyright
Copyright © NIAB 2014 

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References

Balota, M, Payne, WA, Evett, SR and Peters, TR (2008) Morphological and physiological traits associated with canopy temperature depression in three closely related wheat lines. Crop Science 48: 18971910.Google Scholar
Chen, D, Huang, J and Jackson, TJ (2005) Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands. Remote Sensing of Environment 98: 225236.Google Scholar
Cobb, JN, DeClerck, G, Greenberg, A, Clark, R and McCouch, S (2013) Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement. Theoretical and Applied Genetics 126: 867887.Google Scholar
Comar, A, Burger, P, de Solan, B, Baret, F, Daumard, F and Hanocq, J-F (2012) A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results. Functional Plant Biology 39: 914924.Google Scholar
Furbank, RT and Tester, M (2011) Phenomics – technologies to relieve the phenotyping bottleneck. Trends in Plant Science 16: 635644.CrossRefGoogle ScholarPubMed
Genty, B, Briantais, J-M and Baker, NR (1989) The relationship between the quantum yield of photosynthetic electron transport and quenching of chlorophyll fluorescence. Biochimica et Biophysica Acta (BBA) - General Subjects 990: 8792.CrossRefGoogle Scholar
Jones, H (1999) Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant, Cell & Environment 22: 10431055.Google Scholar
Jones, HG, Serraj, R, Loveys, BR, Xiong, L, Wheaton, A and Price, AH (2009) Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field. Functional Plant Biology 36: 978989.CrossRefGoogle ScholarPubMed
Jossier, M, Kroniewicz, L, Dalmas, F, Le Thiec, D, Ephritikhine, G, Thomine, S, Barbier-Brygoo, H, Vavasseur, A, Filleur, S and Leonhardt, N (2010) The Arabidopsis vacuolar anion transporter, AtCLCc, is involved in the regulation of stomatal movements and contributes to salt tolerance. The Plant Journal 64: 563576.Google Scholar
Katerji, N, van Hoorn, JW, Hamdy, A and Mastrorilli, M (2000) Salt tolerance classification of crops according to soil salinity and to water stress day index. Agricultural Water Management 43: 99109.Google Scholar
Katul, GG, Ellsworth, DS and Lai, CT (2000) Modelling assimilation and intercellular CO2 from measured conductance: a synthesis of approaches. Plant, Cell & Environment 23: 13131328.CrossRefGoogle Scholar
McAusland, L, Davey, P, Kanwal, N, Baker, N and Lawson, T (2013) A novel system for spatial and temporal imaging of intrinsic plant water use efficiency. Journal of Experimental Botany 64: 49935007.Google Scholar
Rascher, U, Blossfeld, S, Fiorani, F, Jahnke, S, Jansen, M, Kuhn, AJ, Matsubara, S, Märtin, LL, Merchant, A and Metzner, R (2011) Non-invasive approaches for phenotyping of enhanced performance traits in bean. Functional Plant Biology 38: 968983.CrossRefGoogle ScholarPubMed
Sirault, XR, James, RA and Furbank, RT (2009) A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography. Functional Plant Biology 36: 970977.Google Scholar
White, JW, Andrade-Sanchez, P, Gore, MA, Bronson, KF, Coffelt, TA, Conley, MM, Feldmann, KA, French, AN, Heun, JT, Hunsaker, DJ, Jenks, MA, Kimball, BA, Roth, RL, Strand, RJ, Thorp, KR, Wall, GW and Wang, G (2012) Field-based phenomics for plant genetics research. Field Crops Research 133: 101112.Google Scholar
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