Abstract
The basic mechanisms of yield maintenance under drought conditions are far from being understood. Pre-symptomatic water stress recognition would help to get insides into complex plant mechanistic basis of plant response when confronted to water shortage conditions and is of great relevance in precision plant breeding and production. The plant reactions to drought stress result in spatial, temporal and tissue-specific pattern changes which can be detected using non-invasive sensor techniques, such as hyperspectral imaging. The “response turning time-point” in the temporal curve of plant response to stress rather than the maxima is the most relevant time-point for guided sampling to get insights into mechanistic basis of plant response to drought stress. Comparative hyperspectral image analysis was performed on barley (Hordeum vulgare) plants grown under well-watered and water stress conditions in two consecutive years. The obtained massive, high-dimensional data cubes were analysed with a recent matrix factorization technique based on simplex volume maximization of hyperspectral data and compared to several drought-related traits. The results show that it was possible to detect and visualize the accelerated senescence signature in stressed plants earlier than symptoms become visible by the naked eye.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abdeen, A., Schnell, J., & Miki, B. (2010). Transcriptome analysis reveals absence of unintended effects in drought-tolerant transgenic plants overexpressing the transcription factor ABF3. BMC Genomics, 11, 69. doi:10.1186/1471-2164-11-69.
Aldakheel, Y. Y., & Danson, F. M. (1997). Spectral reflectance of dehydrating leaves: Measurements and modelling. International Journal of Remote Sensing, 18(17), 3683–3690.
Boyer, J. S. (1982). Plant productivity and environment. Science, 218, 443–448.
Furbank, R. T., Cammerer, S., Sheehy, J., & Edwards, G. (2009). C4Rice: A challenge for plant phenomics. Functional Plant Biology, 36(11), 845–865.
Guo, P., Baum, M., Grando, S., Ceccarelli, S., Bai, G., Li, R., von Korff, M., Varshney, R. K., Graner, A., & Valkoun, J. (2009). Differentially expressed genes between drought-tolerant and drought-sensitive barley genotypes in response to drought stress during the reproductive stage. Journal of Experimental Botany, 60, 3531–3544.
Kersting, K., Wahabzada, M., Roemer, C., Thurau, C., Ballvora, A., Rascher, U., Leon, J., Bauckhage, C., Pluemer, L. (2012) Simplex distributions for embedding data matrices over time. In I. Davidson & C. Domeniconi (Eds.), Proceedings of the 12th SIAM International Conference on Data Mining (SDM), Anaheim, CA
Lebreton, C., Lazic-Jancic, V., Steed, A., Pekic, S., & Quarrie, S. A. (1995). Identification of QTL for drought responses in maize and their use in testing causal relationships between traits. Journal of Experimental Botany, 46, 853–865.
Malenovský, Z., Mishra, K. B., Zemek, F., Rascher, U., & Nedbal, I. (2009). Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence. Journal of Experimental Botany, 60, 2987–3004.
McKay, J. K., Richards, J. H., Sen, S., Mitchell-Olds, T., Sandra Boles, S., Stahl, E. A., Wayne, T., & Juenger, T. E. (2008). Genetics of drought adaptation in Arabidopsis thaliana II. QTL analysis of a new mapping population, Kas-1x TSU-1. Evolution, 62, 3014–3026.
Nguyen, T. T. T., Klueva, N., Chamareck, V., Aarti, A., Magpantay, G., Millena, A. C. M., Pathan, M. S., & Nguyen, H. T. (2004). Saturation mapping of QTL regions and identification of putative candidate genes for drought tolerance in rice. Molecular Genetic & Genomics, 272, 35–46.
Passioura, J. B. (2002). Environmental biology and crop improvement. Functional Plant Biology, 29, 537–554.
Penuelas, J., Pinol, J., Ogaya, R., & Filella, I. (1997). Photochemical reflectance index and leaf photosynthetic radiation-use-efficiency assessment in Mediterranean trees. Internat Journal of Remote Sensing, 18(13), 2869–2875.
Pinnisi, E. (2008). The blue revolution, drop by drop, gene by gene. Science, 320, 171–173.
Rabbani, M. A., Maruyama, K., Abe, H., Khan, M. A., Katsura, K., Ito, Y., Yoshiwara, K., Seki, M., Shinozaki, K., & Yamaguchi-Shinozaki, K. (2003). Monitoring expression profiles of rice genes under cold, drought, and high-salinity stresses and abscisic acid application using cDNA microarray and RNA gel-blot analyses. Plant Physiology, 133, 1755–1767.
Rascher, U., Nichol, C. L., Small, C., & Hendricks, L. (2007). Monitoring spatio-temporal dynamics of photosynthesis with a portable hyperspectral imaging system. Photogrammetric Engineering and Remote Sensing, 73, 45–56.
Rascher, U., Damm, A., van der Linden, S., Okujeni, A., Pieruschka, R., Schickling, A., & Hostert, P. (2010). Sensing of photosynthetic activity of crops. In E.-C. Oerke et al. (Eds.), Precision crop protection – The challenge and use of heterogeneity. Dordrecht/Heidelberg/London/New York: Springer.
Rascher, U., Blossfeld, S., Fiorani, F., Jahnke, S., Jansen, M., Kuhn, A. J., Matsubara, S., Märtin, L. L. A., Merchant, A., Metzner, R., Müller-Linow, M., Nagel, K. A., Pieruschka, R., Pinto, F., Schreiber, C. M., Temperton, V. M., Thorpe, M. R., Van Dusschoten, D., Van Volkenburgh, E., Windt, C. W., & Schurr, U. (2011). Non-invasive approaches for phenotyping of enhanced performance traits in bean. Functional Plant Biology, 38, 968–983.
Richards, R. A., Rebetzke, G. J., Watt, M., Condon, A. G., Spielmeyer, W., & Dolferus, R. (2010). Breeding for improved water productivity in temperate cereals: Phenotyping, quantitative trait loci, markers and the selection environment. Functional Plant Biology, 37(2), 85–97.
Sakma, Y., Maruyama, K., Osakabe, Y., Qin, F., Seki, M., Shinozaki, K., & Yamaguchi-Shinozaki, K. (2006). Functional analysis of an arabidopsis transcription factor, DREB2A, involved in drought-responsive gene expression. Plant Physiology, 18, 1292–1309.
Schreiber, A. W., Sutton, T., Caldo, R. A., Kalashyan, E., Lovell, B., Mayo, G., Muehlbauer, G. J., Druka, A., Waugh, R., Wise, R. P., Langridge, P., & Baumann, U. (2009). Comparative transcriptomics in the Triticeae. BMC Genomics, 10, 285. doi:10.1186/1471-2164-10-285.
Schulte, D., Close, T. J., Graner, A., Langridge, P., Matsumoto, T., Muehlbauer, G., Sato, K., Schulman, A. H., Waugh, R., Wise, R. P., & Stein, N. (2009). The international barley sequencing consortium–at the threshold of efficient access to the barley genome. Plant Physiology, 149, 142–147.
Talamé, V., Ozturk, N. Z., Bohnert, H. J., & Tuberosa, R. (2007). Barley transcript profiles underde hydration shock and drought stress treatments: A comparative analysis. Journal of Experimental Botany, 58, 229–240.
Tardieu, T., & Schurr, U. (2009). White paper on plant phenotyping. In EPSO Workshop on Plant Phenotyping, Jülich. Germany.
Tondelli, A., Francia, E., Barabaschi, D., Aprile, A., Skinner, J. S., Stockinger, E. J., Stanca, A. M., & Pecchioni, N. (2006). Mapping regulatory genes as candidates for cold and drought stress tolerance in barley. Theoretical and Applied Genetics, 112, 445–454.
Tran, L. S. P., Nakashim, K., Sakuma, Y., Simpson, S. D., Fujita, Y., Maruyama, K., Fujita, M.,Seki, M., Shinozaki, K., & Yamaguchi-Shinozaki, K. (2004). Isolation and functional analysis of Arabidopsis stress-inducible NAC transcription factors that bind to a drought-responsive cis-element in the early responsive to dehydration stress Promoter. Plant Cell, 16, 2481–2498.
Ueda, A., Kathiresan, A., Inada, M., Narita, Y., Nakamura, T., Weiming Shi, W., Tetsuko Takabe, T., & Bennett, J. (2004). Osmotic stress in barley regulates expression of a different set of genes than salt stress does. Journal of Experimental Botany, 55, 2213–2218.
Ustin, S., & Gamon, J. A. (2010). Remote sensing of plant functional types. New Phytologist, 186, 795–816.
Xiong, L., Wang, R., Mao, G., & Koczan, J. M. (2006). Identification of drought tolerance determinants by genetic analysis of root response to drought stress and abscisic acid. Plant Physiology, 142, 1065–1074.
Acknowledgements
This work has been carried in frame of a research programme funded by BMBF with project number 315309/ CROP.SENSe. The authors would like to thank Merle Noschinski for excellent technical assistance, Henrik Schumann, Melanie Herker and Sfefan Teutsch for their support with hyperspectrometry.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Zhejiang University Press and Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Ballvora, A. et al. (2013). “Deep Phenotyping” of Early Plant Response to Abiotic Stress Using Non-invasive Approaches in Barley. In: Zhang, G., Li, C., Liu, X. (eds) Advance in Barley Sciences. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4682-4_26
Download citation
DOI: https://doi.org/10.1007/978-94-007-4682-4_26
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-4681-7
Online ISBN: 978-94-007-4682-4
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)