Field Phenotyping: Concepts and Examples to Quantify Dynamic Plant Traits across Scales in the Field

Terrestrial Ecosystem Research Infrastructures: Challenges and Opportunities

Volumn , Issue , 2017, Pages 53-80

  Cendrero Mateo, M Pilar ^a   Muller, Onno ^a   Albrecht, Hendrik ^a   Burkart, Andreas ^a   Gatzke, Simone ^a   Janssen, Benedikt ^a   Keller, Beat ^a   Körber, Niklas ^a   Kraska, Thorsten ^b   Matsubara, Shizue ^a   Li, Jinquan ^a   Müller Linow, Mark ^a   Pieruschka, Roland ^a   Pinto, Francisco ^a   Rischbeck, Pablo ^a   Schickling, Anke ^a   Steier, Angelina ^a   Watt, Michelle ^a   Schurr, Ulrich ^a   Rascher, Uwe ^a  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

^b UNIVERSITY OF BONN   (Germany)

Author keywords

Active thermography; Airplanes; Chlorophyll fluorescence; Environmental monitoring; Ground positioning systems; Hyperspectral; LIDAR; Plant phenotyping; RGB camera; Root; Stereo cameras; Thermal imaging; UAV; Vegetation indices

Indexed keywords

EID: 85137462012     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/9781315368252-4     Document Type: Chapter

References (81)

1. 2] effects on soybean (glycine max) physiology, growth and yield. Global Change Biology 8(8): 695-709. doi: 10.1046/j.1365-2486.2002.00498.x.
2. Alchanatis, V., Y. Cohen, S. Cohen, M. Moller, M. Sprinstin, M. Meron, J. Tsipris, Y. Saranga, and E. Sela. 2009. Evaluation of different approaches for estimating and mapping crop water status in cotton with thermal imaging. Precision Agriculture 11(1): 27-41. doi: 10.1007/s11119-009-9111-7.
3. Alonso, L., L. Gomez-Chova, J. Amoros-Lopez, L. Guanter, and J. Calpe. 2007. Sensitivity analysis of the FLD method for the measurement of chlorophyll fluorescence Using a Field Spectroradiometer. In Proceedings of the 3rd International Workshop on Remote Sensing of Vegetation Fluorescence, Florence, Italy.
4. Asner, G. P., D. E. Knapp, J. Boardman, R. O. Green, T. Kennedy-Bowdoin, M. Eastwood, R. E. Martin, C. Anderson, and C. B. Field. 2012. Carnegie airborne observatory-2: Increasing science data dimensionality via high-fidelity multi-sensor fusion. Remote Sensing of Environment 124(September): 454-465. doi: 10.1016/j.rse.2012.06.012.
5. Auernhammer, H. 2001. Precision farming-The environmental challenge. Computers and Electronics in Agriculture 30(1-3): 31-43. doi: 10.1016/S0168-1699(00)00153-8.
6. Baker, N. R. 2008. Chlorophyll fluorescence: A probe of photosynthesis in vivo. Annual Review of Plant Biology 59(1): 89-113. doi: 10.1146/annurev.arplant.59.032607.092759.
7. Barton, C. V. M and P. R. J North. 2001. Remote sensing of canopy light use efficiency using the photochemical reflectance index: Model and sensitivity analysis. Remote Sensing of Environment 78(3): 264-73. doi: 10.1016/S0034-4257(01)00224-3.
8. Bellasio, C., J. Olejníčková, R. Tesař, D. Šebela, and L. Nedbal. 2012. Computer reconstruction of plant growth and chlorophyll fluorescence emission in three spatial dimensions. Sensors 12(1): 1052-71. doi: 10.3390/s120101052.
9. Bendig, J., A. Bolten, S. Bennertz, J. Broscheit, S. Eichfuss, and G. Bareth. 2014. Estimating biomass of barley using crop surface models (CSMs) derived from UAV-based RGB imaging. Remote Sensing 6(11): 10395-10412. doi: 10.3390/rs61110395.
10. Biskup, B., H. Scharr, U. Schurr, and U. Rascher. 2007. A stereo imaging system for measuring structural parameters of plant canopies. Plant, Cell and Environment 30(10): 1299-1308. doi: 10.1111/j.1365-3040.2007.01702.x.
11. Burkart, A., S. Cogliati, A. Schickling, and U. Rascher. 2014. A novel UAV-based ultralight weight spectrometer for field spectroscopy. IEEE Sensors Journal 14(1): 62-67. doi: 10.1109/JSEN.2013.2279720.
12. Burkart, A., A. Schickling, M. P. C. Mateo, T. J. Wrobel, M. Rossini, S. Cogliati, T. Julitta, and U. Rascher. 2015. A method for uncertainty assessment of passive sun-induced chlorophyll fluorescence retrieval using an infrared reference light. IEEE Sensors Journal 15(8): 4603-4611. doi: 10.1109/JSEN.2015.2422894.
13. 2O-flux measurements in crop canopies. Environmental and Experimental Botany 61(1): 25-34. doi: 10.1016/j.envexpbot.2007.02.007.
14. Busemeyer, L., D. Mentrup, K. Möller, E. Wunder, K. Alheit, V. Hahn, H. P. Maurer et al. 2013. BreedVision-A multi-sensor platform for non-destructive field-based phenotyping in plant breeding. Sensors 13(3): 2830-2847. doi: 10.3390/s130302830.
15. Chuvieco, E. and A. Huete. 2010. Fundamentals of Satellite Remote Sensing. CRC Press, Boca Raton, FL.
16. Cohen, Y., V. Alchanatis, M. Meron, Y. Saranga, and J. Tsipris. 2005. Estimation of leaf water potential by thermal imagery and spatial analysis. Journal of Experimental Botany 56(417): 1843-1852. doi: 10.1093/jxb/eri174.
17. Comar, A., F. Baret, F. Viénot, L. Yan, and B. de Solan. 2012. Wheat leaf bidirectional reflectance measurements: Description and quantification of the volume, specular and hot-spot scattering features. Remote Sensing of Environment 121(June): 26-35. doi: 10.1016/j.rse.2011.01.028.
18. Deery, D., J. Jimenez-Berni, H. Jones, X. Sirault, and R. Furbank. 2014. Proximal remote sensing buggies and potential applications for field-based phenotyping. Agronomy 4(3): 349-379. doi: 10.3390/agronomy4030349.
19. Diekötter, T., F. Peter, B. Jauker, V. Wolters, and F. Jauker. 2014. Mass-flowering crops increase richness of cavity-nesting bees and wasps in modern agro-ecosystems. GCB Bioenergy 6(3): 219-226. doi: 10.1111/gcbb.12080.
20. Eiden, M., S. Van Der Linden, J. H. Schween, C. Gerbig, B. Neininger, Y. Brunet, N. Jarosz, O. Traullé, H. Geiss, and U. Rascher. 2007. Elucidating physiology of plant mediated exchange processes using airborne hyperspectral reflectance measurements in synopsis with eddy covariance data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 34: 473-481.
21. Eversole, K., C. Feuillet, K. F. X. Mayer, and J. Rogers. 2014. Slicing the wheat genome. Science 345(6194): 285-287. doi: 10.1126/science.1257983.
22. Farrar, K., D. N. Bryant, L. Turner, J. A. Gallagher, A. Thomas, M. Farrell, M. O. Humphreys, and I. S. Donnison. 2011. Breeding for bio-ethanol production in Lolium perenne L.: Association of allelic variation with high water-soluble carbohydrate content. BioEnergy Research 5(1): 149-157. doi: 10.1007/s12155-011-9156-0.
23. Feilhauer, H., G. P. Asner, R. E. Martin, and S. Schmidtlein. 2010. Brightnessnormalized partial least squares regression for hyperspectral data. Journal of Quantitative Spectroscopy and Radiative Transfer 111(12-13): 1947-1957. doi: 10.1016/j.jqsrt.2010.03.007.
24. Fiorani, F., U. Rascher, S. Jahnke, and U. Schurr. 2012. Imaging plants dynamics in heterogenic environments. Current Opinion in Biotechnology 23(2): 227-235. doi: 10.1016/j.copbio.2011.12.010.
25. Fiorani, F. and U. Schurr. 2013. Future scenarios for plant phenotyping. Annual Review of Plant Biology 64(1): 267-291. doi: 10.1146/annurev-arplant-050312-120137.
26. Ford, E. D., A. Cocke, L. Horton, M. Fellner, and E. Van Volkenburgh. 2008. Estimation, variation and importance of leaf curvature in Zea mays hybrids. Agricultural and Forest Meteorology 148(10): 1598-1610. doi: 10.1016/j.agrformet.2008.05.015.
27. Gamon, J. A., C. B. Field, W. Bilger, O. Björkman, A. L. Fredeen, and J. Peñuelas. 1990. Remote sensing of the xanthophyll cycle and chlorophyll fluorescence in sunflower leaves and canopies. Oecologia 85(1): 1-7. doi: 10.1007/BF00317336.
28. Garbulsky, M. F., J. Peñuelas, J. Gamon, Y. Inoue, and I. Filella. 2011. The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis. Remote Sensing of Environment 115(2): 281-297. doi: 10.1016/j.rse.2010.08.023.
29. Grant, O. M., M. M. Chaves, and H. G. Jones. 2006. Optimizing thermal imaging as a technique for detecting stomatal closure induced by drought stress under greenhouse conditions. Physiologia Plantarum 127(3): 507-518. doi: 10.1111/j.1399-3054.2006.00686.x.
30. Greenham, K. and C. R. McClung. 2015. Integrating circadian dynamics with physiological processes in plants. Nature Reviews Genetics 16(10): 598-610. doi: 10.1038/nrg3976.
31. Hinsinger, P., A. G. Bengough, D. Vetterlein, and I. M. Young. 2009. Rhizosphere: Biophysics, biogeochemistry and ecological relevance. Plant and Soil 321(1-2): 117-152. doi: 10.1007/s11104-008-9885-9.
32. Hostert, P., A. Röder, and J. Hill. 2003. Coupling spectral unmixing and trend analysis for monitoring of long-term vegetation dynamics in mediterranean rangelands. Remote Sensing of Environment 87(2): 183-197.
33. Jackson, R. D. and A. R. Huete. 1991. Interpreting vegetation indices. Preventive Veterinary Medicine 11(3-4): 185-200. doi: 10.1016/S0167-5877(05)80004-2.
34. Jackson, R. D., S. B. Idso, R. J. Reginato, and P. J. Pinter. 1981. Canopy temperature as a crop water stress indicator. Water Resources Research 17(4): 1133-1138. doi: 10.1029/WR017i004p01133.
35. Jansen, M., F. Pinto, K. A. Nagel, D. van Dusschoten, F. Fiorani, U. Rascher, H. U. Schneider, A. Walter, and U. Schurr. 2014. Non-invasive phenotyping methodologies enable the accurate characterization of growth and performance of shoots and roots. In Genomics of Plant Genetic Resources. Eds. R. Tuberosa, A. Graner, and E. Frison. Springer, Dordrecht, the Netherlands, pp. 173-206. http://link.springer.com/chapter/10.1007/978-94-007-7572-5_8.
36. Jones, H. G. 1999. Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant, Cell and Environment 22(9): 1043-1055. doi: 10.1046/j.1365-3040.1999.00468.x.
37. Kjaer, K. H. and C.-O. Ottosen. 2015. 3D laser triangulation for plant phenotyping in challenging environments. Sensors 15(6): 13533-13547. doi: 10.3390/s150613533.
38. Kolber, Z., D. Klimov, G. Ananyev, U. Rascher, J. Berry, and B. Osmond. 2005. Measuring photosynthetic parameters at a distance: Laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation. Photosynthesis Research 84(1-3): 121-129. doi: 10.1007/s11120-005-5092-1.
39. 2 enrichment. Ecological Applications 10(6): 1590-1619. doi: 10.1890/1051-0761(2000)010[1590:BRTCE]2.0.CO;2.
40. Kuijken, R. C. P., F. A. van Eeuwijk, L. F. M. Marcelis, and H. J. Bouwmeester. 2015. Root phenotyping: From component trait in the lab to breeding. Journal of Experimental Botany June: erv239. doi: 10.1093/jxb/erv239.
41. Leuning, R., J. Grace, J. L. Monteith, J. R. Milford, M. H. Unsworth, and D. Fowler. 1989. Leaf energy balances: Developments and applications [and discussion]. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences 324(1223): 191-206.
42. Maxwell, K. and G. N. Johnson. 2000. Chlorophyll fluorescence-A practical guide. Journal of Experimental Botany 51(345): 659-668. doi: 10.1093/jexbot/51.345.659.
43. McCormick, K. and N. Kautto. 2013. The bioeconomy in Europe: An overview. Sustainability 5(6): 2589-2608. doi: 10.3390/su5062589.
44. Meroni, M., M. Rossini, L. Guanter, L. Alonso, U. Rascher, R. Colombo, and J. Moreno. 2009. Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications. Remote Sensing of Environment 113(10): 2037-2051. doi: 10.1016/j.rse.2009.05.003.
45. Möller, M., V. Alchanatis, Y. Cohen, M. Meron, J. Tsipris, A. Naor, V. Ostrovsky, M. Sprintsin, and S. Cohen. 2007. Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. Journal of Experimental Botany 58(4): 827-838. doi: 10.1093/jxb/erl115.
46. Moran, S., G. Fitzgerald, A. Rango, C. Walthall, E. Barnes, W. Bausch, T. Clarke et al. 2003. Sensor development and radiometric correction for agricultural applications. Photogrammetric Engineering and Remote Sensing 69(6): 705-718. doi: 10.14358/PERS.69.6.705.
47. Müller-Linow, M., F. Pinto-Espinosa, H. Scharr, and U. Rascher. 2015. The leaf angle distribution of natural plant populations: Assessing the canopy with a novel software tool. Plant Methods 11(1): 1. doi: 10.1186/s13007-015-0052-z.
48. Munns, R., R. A. James, X. R. R. Sirault, R. T. Furbank, and H. G. Jones. 2010. New phenotyping methods for screening wheat and barley for beneficial responses to water deficit. Journal of Experimental Botany 61(13): 3499-3507. doi: 10.1093/jxb/erq199.
49. O’Toole, J. C. and R. T. Cruz. 1980. Response of leaf water potential, stomatal resistance, and leaf rolling to water stress. Plant Physiology 65(3): 428-432. doi: 10.1104/pp.65.3.428.
50. Papageorgiou, G. C. and Govindjee. 2004. Chlorophyll a Fluorescence: A Signature of Photosynthesis. Springer, New York.
51. Pieruschka, R., H. Albrecht, O. Muller, J. A. Berry, D. Klimov, Z. S. Kolber, Z. Malenovský, and U. Rascher. 2014. Daily and seasonal dynamics of remotely sensed photosynthetic efficiency in tree canopies. Tree Physiology, June: tpu035. doi: 10.1093/treephys/tpu035.
52. Pieruschka R., D. Klimov, Z. S. Kolber, and J. A. Berry. 2010. Monitoring of cold and light stress impact on photosynthesis by using the laser induced fluorescence transient (LIFT) approach. Functional Plant Biology 37(5): 395-402.
53. Pinto, F., A. Damm, A. Schickling, C. Panigada, S. Cogliati, M. Müller-Linow, A. Balvora, and U. Rascher. 2016. Sun-induced chlorophyll fluorescence from high-resolution imaging spectroscopy data to quantify spatio-temporal patterns of photosynthetic function in crop canopies. Plant, Cell and Environment 39: 1500-1512.
54. Plascyk, J. 1975. The MKII Fraunhofer line discriminator (FLD-II) for airborne and orbital remote sensing of solar stimulated luminescence. Optical Engineering 14: 339-346.
55. Plascyk, J. and F. Grabriel. 1975. The Fraunhofer line discriminator MKII-An airbone instrument for precise and standarized ecological luminescence measurements. IEEE Transactions on Instrumentation and Measurement 24: 306-313.
56. Porcar-Castell, A., E. Pfündel, J. F. J. Korhonen, and E. Juurola. 2008. A new monitoring PAM fluorometer (MONI-PAM) to study the short- and long-term acclimation of photosystem II in field conditions. Photosynthesis Research 96(2): 173-179. doi: 10.1007/s11120-008-9292-3.
57. Porcar-Castell, A., E. Tyystjärvi, J. Atherton, C. van der Tol, J. Flexas, E. Pfündel, J. Moreno, C. Frankenberg, and J. A. Berni. 2014. Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. Journal of Experimental Botany, eru191.
58. Raesch, A. R., O. Muller, R. Pieruschka, and U. Rascher. 2014. Field observations with laser-induced fluorescence transient (LIFT) method in barley and sugar beet. Agriculture 4(2): 159-169. doi: 10.3390/agriculture4020159.
59. Rascher, U., G. Agati, L. Alonso, G. Cecchi, S. Champagne, R. Colombo, A. Damm et al. 2009. CEFLES2: The remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands. Biogeosciences 6(7): 1181-1198.
60. Rascher, U., L. Alonso, A. Burkart, C. Cilia, S. Cogliati, R. Colombo, A. Damm et al. 2015. Sun-induced fluorescence-A new probe of photosynthesis: First maps from the imaging spectrometer HyPlant. Global Change Biology 21(12): 4673-4684. doi: 10.1111/gcb.13017.
61. 2. Photosynthesis Research 105(1): 15-25. doi: 10.1007/s11120-010-9548-6.
62. Rascher, U. and L. Nedbal. 2006. Dynamics of photosynthesis in fluctuating light. Current Opinion in Plant Biology, Cell Biology/Edited by L. G. Smith and U. Mayer, 9(6): 671-678. doi: 10.1016/j.pbi.2006.09.012.
63. Rascher, U. and R. Pieruschka. 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. Precision Agriculture 9(6): 355-366. doi: 10.1007/s11119-008-9074-0.
64. Rich, P. M. 1990. characterizing plant canopies with hemispherical photographs. Remote Sensing Reviews 5(1): 13-29. doi: 10.1080/02757259009532119.
65. Roberti, J. A., M. D. SanClements, H. W. Loescher, and E. Ayres. 2014. Traceable calibration, performance metrics, and uncertainty estimates of minirhizotron digital imagery for fine-root measurements. PLoS ONE 9(11): e112362. doi: 10.1371/journal.pone.0112362.
66. Roemer, C., M. Wahabzada, A. Ballvora, F. Pinto, M. Rossini, C. Panigada, J. Behmann et al. 2012. Early drought stress detection in cereals: Simplex volume maximisation for hyperspectral image analysis. Functional Plant Biology 39(10-11): 878-890. doi: 10.1071/FP12060.
67. Rossini, M., M. Meroni, M. Migliavacca, G. Manca, S. Cogliati, L. Busetto, V. Picchi, A. Cescatti, G. Seufert, and R. Colombo. 2010. High resolution field spectroscopy measurements for estimating gross ecosystem production in a rice field. Agricultural and Forest Meteorology 150(9): 1283-1296. doi: 10.1016/j.agrformet.2010.05.011.
68. Rossini, M., L. Nedbal, L. Guanter, A. Ač, L. Alonso, A. Burkart, S. Cogliati et al. 2015. Red and far red sun-induced chlorophyll fluorescence as a measure of plant photosynthesis. Geophysical Research Letters 42(6): 2014GL062943. doi: 10.1002/2014GL062943.
69. Sakamoto, T., A. A. Gitelson, A. L. Nguy-Robertson, T. J. Arkebauer, B. D. Wardlow, A. E. Suyker, S. B. Verma, and M. Shibayama. 2012. An alternative method using digital cameras for continuous monitoring of crop status. Agricultural and Forest Meteorology 154-155(March): 113-126. doi: 10.1016/j.agrformet.2011.10.014.
70. Sampoux, J.-P., P. Baudouin, B. Bayle, V. Béguier, P. Bourdon, J.-F. Chosson, F. Deneufbourg et al. 2011. Breeding perennial grasses for forage usage: An experimental assessment of trait changes in diploid perennial ryegrass (Lolium perenne L.) cultivars released in the last four decades. Field Crops Research 2(123): 117-129. doi: 10.1016/j.fcr.2011.05.007.
71. Sanz-Cortiella, R., J. Llorens-Calveras, A. Escolà, J. Arnó-Satorra, M. Ribes-Dasi, J. Masip-Vilalta, F. Camp et al. 2011. Innovative LIDAR 3D dynamic measurement system to estimate fruit-tree leaf area. Sensors 11(6): 5769-5791. doi: 10.3390/s110605769.
72. Schreiber, U. 1986. Detection of rapid induction kinetics with a new type of high-frequency modulated chlorophyll fluorometer. In Current Topics in Photosynthesis, Eds. J. Amesz, A. J. Hoff, and H. J. Van Gorkum. Springer, Dordrecht, the Netherlands, pp. 259-270. http://link.springer.com/chapter/10.1007/978-94-009-4412-1_24.
73. Schreiber, U. 2004. Pulse-amplitude-modulation (PAM) fluorometry and saturation pulse method: An overview. In Chlorophyll A Fluorescence: A Signature of Photosynthesis, Advances in Photosynthesis and Respiration, Eds. G. C. Papageorgiou and Govindjee. Springer, Dordrecht, the Netherlands, Vol. 19, pp. 279-319.
74. Sequencing Project, International Rice Genome. 2005. The map-based sequence of the rice genome. Nature 436(7052): 793-800. doi: 10.1038/nature03895.
75. Thorup-Kristensen, K. and R. van den Boogaard. 1998. Temporal and spatial root development of cauliflower (Brassica oleracea L. var. botrytis L.). Plant and Soil 201(1): 37-47. doi: 10.1023/A:1004393417695.
76. Trachsel, S., S. M. Kaeppler, K. M. Brown, and J. P. Lynch. 2010. Shovelomics: High throughput phenotyping of maize (Zea mays L.) root architecture in the field. Plant and Soil 341(1-2): 75-87. doi: 10.1007/s11104-010-0623-8.
77. Van Wittenberghe, S., L. Alonso, J. Verrelst, I. Hermans, J. Delegido, F. Veroustraete, R. Valcke, J. Moreno, and R. Samson. 2013. Upward and downward solarinduced chlorophyll fluorescence yield indices of four tree species as indicators of traffic pollution in Valencia. Environmental Pollution 173(February): 29-37. doi: 10.1016/j.envpol.2012.10.003.
78. Wasson, A. P., G. J. Rebetzke, J. A. Kirkegaard, J. Christopher, R. A. Richards, and M. Watt. 2014. Soil coring at multiple field environments can directly quantify variation in deep root traits to select wheat genotypes for breeding. Journal of Experimental Botany 65(21): 6231-6249. doi: 10.1093/jxb/eru250.
79. York, L. M. and J. P. Lynch. 2015. Intensive field phenotyping of maize (Zea mays L.) root crowns identifies phenes and phene integration associated with plant growth and nitrogen acquisition. Journal of Experimental Botany 66(18): 5493-5505. doi: 10.1093/jxb/erv241.
80. Zarco-Tejada, P. J., V. González-Dugo, and J. A. J. Berni. 2012. Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sensing of Environment, Remote Sensing of Urban Environments, 117(February): 322-337. doi: 10.1016/j.rse.2011.10.007.
81. Zhu, X.-G., S. P. Long, and D. R. Ort. 2010. Improving photosynthetic efficiency for greater yield. Annual Review of Plant Biology 61(1): 235-261. doi: 10.1146/annurev-arplant-042809-112206.