Abstract
Precise and accurate measurement of traits plays an important role in the genetic improvement of crop plants. Therefore, a lot of development has taken place in the area of phenomics in the recent past. Both forward and reverse phenomics have been evolved, which can help in identification of either the best genotype having the desirable traits or mechanism and genes that make a genotype the best. This includes development of high throughput non-invasive imaging technologies including colour imaging for biomass, plant structure, phenology and leaf health (chlorosis, necrosis); near infrared imaging for measuring tissue and soil water contents; far infrared imaging for canopy/leaf temperature; fluorescence imaging for physiological state of photosynthetic machinery; and automated weighing and watering for water usage imposing drought/salinity. These phenomics tools and techniques are paving the way in harnessing the potentiality of genomic resources in genetic improvement of crop plants. These techniques have become much more advanced and have now entered the era of high throughput integrated phenotyping platforms to provide a solution to genomics-enabled improvement and address our need of precise and efficient phenotyping of crop plants.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alenyà G, Dellen B, Foix S, Torras C (2012) Leaf segmentation from time-of-flight data for robotized plant probing. IEEE Robot Autom Mag 20:50–59
Annicchiarico P (2002) Genotype × environment interaction: challenges and opportunities for plant breeding and cultivar recommendations. FAO Plant Production and Protection Paper 74, FAO, Rome, pp 132
Baker NR (2008) Chlorophyll fluorescence: a probe of photosynthesis in vivo. Annu Rev Plant Biol 59:89–113
Barbagallo RP, Oxborough K, Pallett KE, Baker NR (2003) ***Rapid, non-invasive screening for perturbations of metabolism and plant growth using chlorophyll fluorescence imaging. Plant Physiol 132:485–493, 37
Berger B, Parent B, Tester M (2010) High throughput shoot imaging to study drought responses. J Exp Bot 61:3519–3528
Bruinsma J (2003) World agriculture: towards 2015/2030: an FAO perspective. Earthscan, London
Chaerle L, Lenk S, Leinonen I, Jones HG, Van Der Straeten D, Buschmann C (2009) Multi-sensor plant imaging: towards the development of a stress-catalogue. Biotechnol J 4:1152–1167
Comar A, Burger PH, de Solan B, Baret F, Daumard F, Hanocq JF (2012) A semi-automatic system for high throughput phenotyping wheat cultivars in-field conditions: description and first results. Funct Plant Biol 39:914–924
Delseny M, Han B, Hsing YI (2010) High throughput DNA sequencing: the new sequencing revolution. Plant Sci 179:407–422
Diamond J (1997) Guns, germs, and steel: the fates of human societies. Norton and Company, New York
Dornbusch T, Lorrain S, Kuznetsov D, Fortier A, Liechti R, Xenarios I, Fiorani F, Rascher U, Jahnke S, Schurr U (2012) Imaging plants dynamics in heterogenic environments. Curr Opin Biotechnol 23:227–235
Finkel E (2009) With ‘phenomics’ plant scientists hope to shift breeding into overdrive. Science 325:380–381
Fiorani F, Rascher U, Jahnke S, Schurr U (2012) Imaging plants dynamics in heterogenic environments. Curr Opin Biotechnol 23:227–235
Fisher RA (1925) Statistical methods for research workers. Oliver & Boyd, Edinburgh
Furbank RT, Tester M (2011) Phenomics – technologies to relieve the phenotyping bottleneck. Trends Plant Sci 16:635–644
Furbank RT, von Caemmerer S, Sheehy J, Edwards G (2009) C4 rice: a challenge for plant phenomics. Funct Plant Biol 36:845–856
Granier C, Aguirrezabal L, Chenu K, Cookson SJ, Dauzat M, Hamard P, Thioux JJ, Rolland G, Bouchier-Combaud S, Lebaudy A, Muller B, Simonneau T, Tardieu F (2006) PHENOPSIS, an automated platform for reproducible phenotyping of plant responses to soil water deficit in Arabidopsis thaliana permitted the identification of an accession with low sensitivity to soil water deficit. New Phytol 169:623–635
Grime JP (1979) Plant strategies and vegetation processes. Wiley, Chichester
Grime JP, Hunt R (1975) Relative growth rate: its range and adaptive significance in a local flora. J Ecol 63:393–422
Harris BN, Sadras VO, Tester M (2010) A water-centred framework to assess the effects of salinity on the growth and yield of wheat and barley. Plant Soil 336:377–389
Houle D (2010) Numbering the hairs on our heads: the shared challenge and promise of phenomics. PNAS USA 107:1793–1799
Houle D, Govindaraju DR, Omholt S (2010) Phenomics: the next challenge. Nat Rev Genet 11:855–866
Huala E, Dickerman AW, Garcia-Hernandez M, Weems D, Reiser L, LaFond F, Hanley D, Kiphart D, Zhuang M, Huang W, Mueller LA, Bhattacharyya D, Bhaya D, Sobral BW, Beavis W, Meinke DW, Town CD, Somerville C, Rhee SY (2001) The Arabidopsis Information Resource (TAIR): a comprehensive database and web-based information retrieval, analysis, and visualization system for a model plant. Nucleic Acids Res 29:102–105
Jansen M, Gilmer F, Biskup B, Nagel K, Rascher U, Fischbach A, Briem S, Dreissen G, Tittmann S, Braun S, De Jaeger I, Metzlaff M, Schurr U, Scharr H, Walter A (2009) Simultaneous phenotyping of leaf growth and chlorophyll fluorescence via GROWSCREEN FLUORO allows detection of stress tolerance in Arabidopsis thaliana and other rosette plants. Funct Plant Biol 36:902–914
Jefferies SP, Barr AR, Karakousis A, Kretschmer JM, Manning S, Chalmers KJ, Nelson JC, Islam AKMR, Langridge P (1999) Mapping of chromosome regions conferring boron toxicity tolerance in barley (Hordeum vulgare L.). Theor Appl Genet 98:1293–1303
Johannsen W (1911) The genotype conception of heredity. Am Nat 45(531):129–159
Jones HG, Vaughan RA (2010) Remote sensing of vegetation: principles, techniques and applications. Oxford University Press, Oxford
Knox J, Hess T, Daccache A, Wheeler T (2012) Climate change impacts on crop productivity in Africa and South Asia. Environ Res Lett 7:034032
Kolukisaoglu U, Thurow K (2010) Future and frontiers of automated screening in plant sciences. Plant Sci 178:476–484
Langridge P, Fleury D (2011) Making the most of ‘omics’ for crop breeding. Trends Biotechnol 29:33–40
Leakey ADB, Ainsworth EA, Bernacchi CJ, Rogers A, Long SP, Ort DR (2009) Elevated CO2 effects on plant carbon, nitrogen, relations: six important lessons from FACE. J Exp Bot 60:2859–2876
Mahlein AK, Oerke EC, Steiner U, Dehne HW (2012) Recent advances in sensing plant diseases for precision crop protection. Eur J Plant Pathol 133:197–209
Mahner M, Kary M (1997) What exactly are genomes, genotypes and phenotypes? And what about phenomes? J Theor Biol 186:55–63
Mayr LM, Bojanic D (2009) Novel trends in high-throughput screening. Curr Opin Pharmacol 9:580–588. doi:10.1016/j.coph.2009. 08.004
Meinke DW, Cherry JM, Dean C, Rounsley SD, Koornneef M (1998) Arabidopsis thaliana: a model plant for genome analysis. Science 282:662–682
Miyao A, Iwasaki Y, Kitano H, Itoh J, Maekawa M, Murata K, Yatou O, Nagato Y, Hirochika H (2007) A large-scale collection of phenotypic data describing an insertional mutant population to facilitate functional analysis of rice genes. Plant Mol Biol 63:625–635
Noldus LPJJ, Spink AJ, Tegelenbosch RAJ (2001) Etho vision: a versatile video tracking system for automation of behavioral experiments. Behav Res Methods 3:398–414
Pearson CH, Ernst SM, Barbarick KA, Hatfield JL, Peterson GA, Buxton DR (2008) Agronomy Journal turns one hundred. Agron J 100:1–8
Pieruschka R, Klimov D, Kolber Z, Berry JA (2010) Continuous measurements of the effects of cold stress on photochemical efficiency using laser induced fluorescence transient (LIFT) approach. Funct Plant Biol 37:395–402
Poorter H, Pot CS, Lambers H (1988) The effect of an elevated atmospheric CO2 concentration on growth, photosynthesis and respiration of Plantago major. Physiol Plant 73:553–559
Poorter H, Remkes C, Lambers H (1990) Carbon and nitrogen economy of 24 wild species differing in relative growth rate. Plant Physiol 94:621–627
Poorter H, Niinemets Ü, Walter A, Fiorani F, Schurr U (2010) A method to construct dose–response curves for a wide range of environmental factors and plant traits by means of a meta-analysis of phenotypic data. J Exp Bot 61:2043–2055
Rascher U, Pieruschka R (2008) Spatio-temporal variations of photosynthesis: the potential of optical remote sensing to better understand and scale light use efficiency and stresses of plant ecosystems. Precis Agric 9:355–366
Reich PB, Walters MB, Ellsworth DS (1992) Leaf life-span in relation to leaf, plant, and stand characteristics among diverse ecosystems. Ecol Monogr 62:365–392
Riano-Pachon DM, Nagel A, Neigenfind J, Wagner R, Basekow R, Weber E, Mueller-Roeber B, Diehl S, Kersten B (2009) GabiPD: the GABI primary database – plant integrative ‘omics’ database. Nucleic Acids Res 37:D954–D959
Ruiz-Garcia L, Lunadei L, Barreiro P, Robla JI (2009) A review of wireless sensor technologies and applications in agriculture and food industry: state of the art and current trends. Sensors (Basel, Switzerland) 9:4728–4750
Schnurbusch T, Hayes JE, Sutton TJ (2010) Boron toxicity tolerance in wheat and barley: Australian perspectives. Breed Sci 60:297–304
Scotford IM, Miller PCH (2005) Applications of spectral reflectance techniques in northern European cereal production: a review. Biosyst Eng 90:235–250
Sirault XRR, James RA, Furbank RT (2009) A new screening method for osmotic component of salinity tolerance in cereals using infrared thermography. Funct Plant Biol 36:970–977
Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (2007) Climate change 2007: the physical science basis: contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge Univ Press, New York, pp 1–8
Soulé M (1967) Phenetics of natural populations I. Phenetic relationships of insular populations of the side-blotched lizard. Evolution 21:584–591
Sticklen MB (2007) Feedstock crop genetic engineering for alcohol fuels. Crop Sci 47:2238–2248
Suzuki DT, Griffiths AJF, Lewontin RC (1981) An introduction to genetic analysis, 2nd edn. W H Freeman, New York
Swarbrick PJ, Schulze-Lefert P, Scholes JD (2006) The metabolic consequences of susceptibility and the activation of race specific or broad spectrum resistance pathways in barley leaves challenged with the powdery mildew fungus. Plant Cell Environ 29:1061–1076
Tester M, Langridge P (2010) Breeding technologies to increase crop production in a changing world. Science 327:818–822
Wheeler T, von Braun J (2013) Climate change impacts on global food security. Science 341:508–513
Walter A, Studer B, Kolliker R (2012) Advanced phenotyping offers opportunities for improved breeding of forage and turf species. Ann Bot 110:1271–1279
Woo N, Badger MR, Pogson BJ (2008) A rapid non-invasive procedure for quantitative assessment of drought survival using chlorophyll fluorescence. Plant Methods 4:27
Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, Lamont BB, Lee T, Lee W, Lusk C, Midgley JJ, Navas ML, Niinemets Ü, Oleksyn J, Osada N, Poorter H, Poot P, Prior L, Pyankov VI, Roumet C, Thomas SC, Tjoelker MG, Veneklaas EJ, Villar R (2004) The worldwide leaf economics spectrum. Nature 428:821–827
Zamir D (2013) Where Have All the Crop Phenotypes Gone? PLoS Biol 11(6): e1001595. doi:10.1371/journal.pbio.1001595
Ziska LH, Bunce JA (2007) Predicting the impact of changing CO2 on crop yields: some thoughts on food. New Phytol 175:607–618
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer India
About this chapter
Cite this chapter
Kumar, J., Pratap, A., Kumar, S. (2015). Plant Phenomics: An Overview. In: Kumar, J., Pratap, A., Kumar, S. (eds) Phenomics in Crop Plants: Trends, Options and Limitations. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2226-2_1
Download citation
DOI: https://doi.org/10.1007/978-81-322-2226-2_1
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2225-5
Online ISBN: 978-81-322-2226-2
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)