Uav-based thermal imaging for high-throughput field phenotyping of black poplar response to drought

Frontiers in Plant Science

Volumn 8, Issue , 2017, Pages

  Ludovisi, Riccardo ^a   Tauro, Flavia ^a   Salvati, Riccardo ^a   Khoury, Sacha ^b   Mugnozza, Giuseppe Scarascia ^a   Harfouche, Antoine ^a  

^a UNIVERSITY OF TUSCIA   (Italy)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

Drought; High throughput field phenotyping (HTFP); Image processing; Phenomics; Poplar thermal imagery; Stomatal conductance; UAV remote sensing

Indexed keywords

EID: 85030838277     PISSN: None     EISSN: 1664462X     Source Type: Journal    
DOI: 10.3389/fpls.2017.01681     Document Type: Article

References (109)

1. Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements. FAO Irrigation and Drainage Paper No. 56. Rome: FAO.
2. Alvarez, E., Scheiber, S. M., Beeson, R. C. Jr., and Sandrock, D. R. (2007). Drought tolerance responses of purple Lovegrass and ‘Adagio’ maiden grass. HortScience 42, 1695-1699.
3. Amichev, B. Y., Johnston, M., and Van Rees, K. C. N. (2010). Hybrid poplar growth in bioenergy production systems: biomass prediction with a simple process-based model (3PG). Biomass Bioenerg. 34, 687-702. doi: 10.1016/j.biombioe.2010.01.012
4. Araus, J. L., and Cairns, J. E. (2014). Field high-throughput phenotyping: the new crop breeding frontier. Trends Plant Sci. 19, 52-61. doi: 10.1016/j.tplants.2013.09.008
5. Attia, Z., Domec, J.-C., Oren, R., Way, D. A., and Moshelion, M. (2015). Growth and physiological responses of isohydric and anisohydric poplars to drought. J. Exp. Bot. 66, 4373-4381. doi: 10.1093/jxb/erv195
6. Ballester, C., Castel, J., Jiménez-Bello, M. A., Castel, J. R., and Intrigliolo, D. S. (2013a). Thermographic measurement of canopy temperature is a useful tool for predicting water deficit effects on fruit weight in citrus trees. Agric. Water Manage. 122, 1-6. doi: 10.1016/j.agwat.2013.02.005
7. Ballester, C., Jiménez-Bello, M. A., Castel, J. R., and Intrigliolo, D. S. (2013b). Usefulness of thermography for plant water stress detection in citrus and persimmon trees. Agric. For. Meteorol. 168, 120-129. doi: 10.1016/j.agrformet.2012.08.005
8. Benetka, V., Novotná, K., and Štochlová, P. (2012). Wild populations as a source of germplasm for black poplar (Populus nigra L.) breeding programmes. Tree Genet. Genomes 8, 1073-1084. doi: 10.1007/s11295-012-0487-6
9. Berni, J. A. J., Zarco-Tejada, P. J., Suárez, L., and Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Trans. Geosci. Remote Sens. 47, 722-738. doi: 10.1109/TGRS.2008.2010457
10. Box, G. E. P., and Cox, D. R. (1964). An analysis of transformations. J. Roy. Stat. Soc. B 26, 211-252.
11. Bréda, N., and Badeau, V. (2008). Forest tree responses to extreme drought and some biotic events: towards a selection according to hazard tolerance? C. R. Geosci. 340, 651-662. doi: 10.1016/j.crte.2008.08.003
12. Bréda, N., Huc, R., Granier, A., and Dreyer, E. (2006). Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long-term consequences. Ann. For. Sci. 63, 625-644. doi: 10.1051/forest:2006042
13. Cairns, J. E., Impa, S. M., O’Toole, J. C., Jagadish, S. V. K., and Price, A. H. (2011). Influence of the soil physical environment on rice (Oryza sativa L.) response to drought stress and its implications for drought research. Field Crop Res. 121, 303-310. doi: 10.1016/j.fcr.2011.01.012
14. Cantero-Martínez, C., Angás, P., and Lampurlanés, J. (2007). Long-term yield and water use efficiency under various tillage systems in Mediterranean rainfed conditions. Ann. Appl. Biol. 150, 293-305. doi: 10.1111/j.1744-7348.2007.00142.x
15. Chamaillard, S., Fichot, R., Vincent-Barbaroux, C., Bastien, C., Depierreux, C., Dreyer, E., et al. (2011). Variations in bulk leaf carbon isotope discrimination, growth and related leaf traits among three Populus nigra L. populations. Tree Physiol. 31, 1076-1087. doi: 10.1093/treephys/tpr089
16. Chaves, M. M., Maroco, J. P., and Pereira, J. S. (2003). Understanding plant responses to drought-from genes to the whole plant. Funct. Plant Biol. 30, 239-264. doi: 10.1071/FP02076
17. Chéné, Y., Rousseau, D., Lucidarme, P., Bertheloot, J., Caffier, V., Morel, P., et al. (2012). On the use of depth camera for 3D phenotyping of entire plants. Comput. Electron. Agric. 82, 122-127. doi: 10.1016/j.compag.2011.12.007
18. Cocozza, C., Cherubini, P., Regier, N., Saurer, M., Frey, B., and Tognetti, R. (2010). Early effects of water deficit on two parental clones of Populus nigra grown under different environmental conditions. Funct. Plant Biol. 37, 244-254. doi: 10.1071/FP09156
19. Costa, J. M., Grant, O. M., and Chaves, M. M. (2013). Thermography to explore plant-environment interactions. J. Exp. Bot. 64, 3937-3949. doi: 10.1093/jxb/ert029
20. Deery, D., Berni, J. A. J., Jones, H., Sirault, X., and Furbank, R. (2014). Proximal remote sensing buggies and potential applications for field-based phenotyping. Agronomy 5, 349-379. doi: 10.3390/agronomy4030349
21. Deery, D. M., Rebetzke, G. J., Berni, J. A. J., James, R. A., Condon, A. G., Bovill, W. D., et al. (2016). Methodology for high-throughput field phenotyping of canopy temperature using airborne thermography. Front. Plant Sci. 7:1808. doi: 10.3389/fpls.2016.01808
22. DeWoody, J. D., Trewin, H. T., and Taylor, G. T. (2015). Genetic and morphological differentiation in Populus nigra L.: isolation by colonization or isolation by adaptation? Mol. Ecol. 24, 2641-2655. doi: 10.1111/mec.13192
23. Dhondt, S., Wuyts, N., and Inzé, D. (2013). Cell to whole-plant phenotyping: the best is yet to come. Trends Plant Sci. 18, 428-439. doi: 10.1016/j.tplants.2013.04.008
24. Díaz-Varela, R. A., de la Rosa, R., León, L., and Zarco-Tejada, P. J. (2015). High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: application in breeding trials. Remote Sens. 7, 4213-4232. doi: 10.3390/rs70404213
25. Dillen, S. Y., Marron, N., Sabatti, M., Ceulemans, R., and Bastien, C. (2009). Relationships among productivity determinants in two hybrid poplar families grown during three years at two contrasting sites. Tree Physiol. 29, 975-987. doi: 10.1093/treephys/tpp036
26. Djomo, S. N., Ac, A., Zenone, T., De Groote, T., Bergante, S., Facciotto, G., et al. (2015). Energy performances of intensive and extensive short rotation cropping systems for woody biomass production in the EU. Renew. Sustain. Energy Rev. 41, 845-854. doi: 10.1016/j.rser.2014.08.058
27. Edrisi, S. A., and Abhilash, P. C. (2016). Exploring marginal and degraded lands for biomass and bioenergy production: an Indian scenario. Renew. Sustain. Energy Rev. 54, 1537-1551. doi: 10.1016/j.rser.2015.10.050
28. Fahlgren, N., Feldman, M., Gehan, M. A., Wilson, M. S., Shyu, C., Bryant, D. W., et al. (2015a). A versatile phenotyping system and analytics platform reveals diverse temporal responses to water availability in Setaria. Mol. Plant 8, k1520-1535. doi: 10.1016/j.molp.2015.06.005
29. Fahlgren, N., Gehan, M. A., and Baxter, I. (2015b). Lights, camera, action: high-throughput plant phenotyping is ready for a close-up. Curr. Opin. Plant Biol. 24, 93-99. doi: 10.1016/j.pbi.2015.02.006
30. FAO (2016). “Poplars and other fast-growing trees-Renewable resources for future green economies-Synthesis of country progress reports,” in 25th Session of the International Poplar Commission, 13-16 September 2016, Berlin.
31. Farooq, M., Wahid, A., Kobayashi, N., Fujita, D., and Basra, S. M. A. (2009). Plant drought stress: effects, mechanisms and management. Agron. Sustain. Dev. 29, 185-212. doi: 10.1051/agro:2008021
32. Fischer, R., and Maurer, R. (1978). Drought resistance in spring wheat cultivars. I. Grain yield responses. Crop Pasture Sci. 29, 897-912. doi: 10.1071/AR9780897
33. Fuchs, M. (1990). Infrared measurement of canopy temperature and detection of plant water stress. Theor. Appl. Climatol. 42, 253-261. doi: 10.1007/BF00865986
34. Gago, J., Douthe, C., Coopman, R. E., Gallego, P. P., Ribas-Carbo, M., Flexas, J., et al. (2015). UAVs challenge to assess water stress for sustainable agriculture. Agric. Water Manage. 153, 9-19. doi: 10.1016/j.agwat.2015.01.020
35. Ghanem, M. E., Marrou, H., and Sinclair, T. R. (2015). Physiological phenotyping of plants for crop improvement. Trends Plant Sci. 20, 139-144. doi: 10.1016/j.tplants.2014.11.006
36. Goggin, F. L., Lorence, A., and Topp, C. N. (2015). Applying high-throughput phenotyping to plant-insect interactions: picturing more resistant crops. Curr. Opin. Insect. Sci. 9, 69-76. doi: 10.1016/j.cois.2015.03.002
37. Gómez-Candón, D., Virlet, N., Labbé, S., Jolivot, A., and Regnard, J.-L. (2016). Field phenotyping of water stress at tree scale by UAV-sensed imagery: new insights for thermal acquisition and calibration. Precis. Agric. 17, 786-800. doi: 10.1007/s11119-016-9449-6
38. Gonzalez-Dugo, V., Zarco-Tejada, P., Berni, J. A. J., Suárez, L., Goldhamer, D., and Fereres, E. (2012). Almond tree canopy temperature reveals intra-crown variability that is water stress-dependent. Agric. For. Meteorol. 15, 156-165. doi: 10.1016/j.agrformet.2011.11.004
39. Griffiths, A. J. F., Miller, J. H., Suzuki, D. T., Lewontin, R. C., and Gelbart, W. M. (eds). (2000). “Quantifying heritability,” in An Introduction to Genetic Analysis, 7th Edn (New York, NY: W. H. Freeman).
40. Guidi, W., Piccioni, E., and Bonari, E. (2008). Evapotranspiration and crop coefficient of poplar and willow short-rotation coppice used as vegetation filter. Bioresour. Technol. 99, 4832-4840. doi: 10.1016/j.biortech.2007.09.055
41. Harfouche, A., Meilan, R., and Altman, A. (2014). Molecular and physiological responses to abiotic stress in forest trees and their relevance to tree improvement. Tree Physiol. 34, 1181-1198. doi: 10.1093/treephys/tpu012
42. Harfouche, A., Meilan, R., Kirst, M., Morgante, M., Boerjan, W., Sabatti, M., et al. (2012). Accelerating the domestication of forest trees in a changing world. Trends Plant Sci. 17, 64-72. doi: 10.1016/j.tplants.2011.11.005
43. Herr, J. R., and Carlson, J. E. (2013). “Traditional breeding, Genomics-assisted breeding, and biotechnology modification of forest trees and short rotation woody crops,” in Wood-Based Energy in the Northern Forests, eds M. Jacobson and D. Ciolkosz (New York, NY: Springer Science + Business Media),k69-89.
44. Hopkins, A. A., Saha, M. C., and Wang, Z. Y. (2009). “Breeding, genetics, and cultivars,” in Tall Fescue for the Twenty-first Century. Agronomy Monographs, eds H. A. Fribourg, D. B. Hannaway, and C. P. West (Madison, WI: American Society of Agronomy), 339-366.
45. Huang, X., Xiao, X., Zhang, S., Korpelainen, H., and Li, C. (2009). Leaf morphological and physiological responses to drought and shade in two Populus cathayana populations. Biol. Plant. 53, 588-592. doi: 10.1007/s10535-009-0107-y
46. IPCC (2014). “Climate change 2014: synthesis report. contribution of working groups I, II and III to the fifth assessment report of the intergovernmental panel on climate change,” in Core Writing Team, eds R. K. Pachauri and L. A. Meyer (Geneva: IPCC), 151.
47. Izawa, T. (2015). Deciphering and prediction of plant dynamics under field conditions. Curr. Opin. Plant Biol. 24, 87-92. doi: 10.1016/j.pbi.2015.02.003
48. Jackson, R. D., Idso, S. B., Reginato, R. J., and Pinter, P. J. Jr. (1981). Canopy temperature as a crop water stress indicator. Water Resour. Res. 17, 1133-1138. doi: 10.1029/WR017i004p01133
49. Jähne, B. (2005). Digital Image Processing. Berlin: Springer.
50. Jiménez-Bello, M. A., Ballester, C., Caste, J. R., and Intrigliolo, D. S. (2011). Development and validation of an automatic thermal imaging process for assessing plant water status. Agric. Water Manage. 98, 1497-1504. doi: 10.1016/j.agwat.2011.05.002
51. Jones, H. G. (1992). Plants and Microclimate, 2nd Edn. Cambridge: Cambridge University Press, 423.
52. Jones, H. G. (1999). Use of thermography for quantitative studies of spatial and temporal variation of stomatal conductance over leaf surfaces. Plant Cell Environ. 22, 1043-1055. doi: 10.1046/j.1365-3040.1999.00468.x
53. Jones, H. G., Serraj, R., Loveys, B. R., Xiong, L., Wheaton, A., and Price, A. H. (2009). Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field. Funct. Plant Biol. 36, 978-989. doi: 10.1071/FP09123
54. Jones, H. G., and Sirault, X. R. R. (2014). Scaling of thermal images at different spatial resolution: the mixed pixel problem. Agronomy 4, 380-396. doi: 10.3390/agronomy4030380
55. Kaluthota, S., Pearce, D. W., Evans, L. M., Letts, M. G., Whitham, T. G., and Rood, S. B. (2015). Higher photosynthetic capacity from higher latitude: foliar characteristics and gas exchange of southern, central and northern populations of Populus angustifolia. Tree Physiol. 35, 936-948. doi: 10.1093/treephys/tpv069
56. Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F. (2006). World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 15, 259-263. doi: 10.1127/0941-2948/2006/0130
57. Levitt, J. (1972). Responses of Plants to Environmental Stresses. New York, NY: Academic Press, 698.
58. Lindner, M., Fitzgerald, J. B., Zimmermann, N. E., Reyer, C., Delzon, S., van der Maaten, E., et al. (2014). Climate change and European forests: what do we know, what are the uncertainties, and what are the implications for forest management? J. Environ. Manage. 146, 69-83. doi: 10.1016/j.jenvman.2014.07.030
59. Maes, W. H., and Steppe, K. (2012). Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture: a review. J. Exp. Bot. 67, 4671-4712. doi: 10.1093/jxb/ers165
60. Mahan, J. R., and Upchurch, D. R. (1988). Maintenance of constant leaf temperature by plant. 1. Hypothesis limited homeothermy. Environ. Exp. Bot. 28, 351-357. doi: 10.1016/0098-8472(88)90059-7
61. Marron, N., Delay, D., Petit, J. M., Dreyer, E., Kahlem, G., Delmotte, F. M., et al. (2002). Physiological traits of two Populus × euramericana clones, Luisa avanzo and dorskamp, during water stress and re-watering cycle. Tree Physiol. 22, 849-858. doi: 10.1093/treephys/22.12.849
62. McKown, A. D., Guy, R. D., Klápště, J., Geraldes, A., Friedmann, M., Cronk, Q. C. B., et al. (2013). Geographical and environmental gradients shape phenotypic trait variation and genetic structure in Populus trichocarpa. New Phytol. 201, 1263-1276. doi: 10.1111/nph.12601
63. Monclus, R., Dreyer, E., Villar, M., Delmotte, F. M., Delay, D., Petit, J. M., et al. (2006). Impact of drought on productivity and water use efficiency in 29 genotypes of Populus deltoids × Populus nigra. New Phytol. 169, 765-777. doi: 10.1111/j.1469-8137.2005.01630.x
64. Moshelion, M., Halperin, O., Wallach, R., Oren, R., and Way, D. A. (2014). Role of aquaporins in determining transpiration and photosynthesis in water-stressed plants: crop water-use efficiency, growth and yield. Plant Cell Environ. 38, 1785-1793. doi: 10.1111/pce.12410
65. Neale, D. B., and Kremer, A. (2011). Forest tree genomics: growing resources and applications. Nat. Rev. Genet. 12, 111-122. doi: 10.1038/nrg2931
66. Ngao, J., Boris, A., and Saudreau, M. (2017). Intra-crown spatial variability of leaf temperature and stomatal conductance enhanced by drought in apple tree as assessed by the RATP model. Agric. For. Meteorol. 23, 340-354. doi: 10.1016/j.agrformet.2017.02.036
67. Otsu, N. (1979). A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9, 62-66. doi: 10.1109/TSMC.1979.4310076
68. Passioura, J. B. (2012). Phenotyping for drought tolerance in grain crops: when is it useful to breeders? Funct. Plant Biol. 39, 851-859. doi: 10.1071/FP12079
69. Paulson, M., Bardos, P., Harmsen, J., Wilczek, J., Barton, M., and Edwards, D. (2003). The practical use of short rotation coppice in land restoration. Land Contam. Reclam. 11, 323-338. doi: 10.2462/09670513.624
70. Pintó-Marijuan, M., and Munné-Bosch, S. (2014). Photo-oxidative stress markers as a measure of abiotic stress-induced leaf senescence: advantages and limitations. J. Exp. Bot. 65, 3845-3857. doi: 10.1093/jxb/eru086
71. Poland, J. (2015). Breeding-assisted genomics. Curr. Opin. Plant Biol. 24, 119-124. doi: 10.1016/j.pbi.2015.02.009
72. Rae, A. M., Street, N. R., Robinson, K. M., Harris, N., and Taylor, G. (2009). Five QTL hotspots for yield in short rotation coppice bioenergy poplar: the poplar biomass loci. BMC Plant Biol. 9:23. doi: 10.1186/1471-2229-9-23
73. Rebetzke, G. J., Condon, A. G., Richards, R. A., and Read, J. J. (2001). Phenotypic variation and sampling for leaf conductance in wheat (Triticum aestivum L.) breeding populations. Euphytica 121, 335-341. doi: 10.1023/A:1012035720423
74. Rebetzke, G. J., Rattey, A. R., Farquhar, G. D., Richards, R. A., and Condon, A. G. (2013). Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat. Funct. Plant Biol. 40, 14-33. doi: 10.1071/FP12184
75. Regier, N., Streb, S., Cocozza, C., Schaub, M., Cherubini, P., Zeeman, S. C., et al. (2009). Drought tolerance of two black poplar (Populus nigra L.) clones: contribution of carbohydrates and oxidative stress defence. Plant Cell Environ. 32, 1724-1736. doi: 10.1111/j.1365-3040.2009.02030.x
76. Richards, L. R., and Weaver, L. A. (1944). Moisture retention by some irrigated soils as related to soil moisture tension. J. Agric. Res. 69, 215-235.
77. Richardson, J., Isebrands, J. G., and Ball, J. B. (2014). “Ecology and physiology of poplars and willows,” in Poplars and Willows: Trees for Society and the Environment, eds J. G. Isebrands and J. Richardson (Rome: The Food and Agriculture Organization of United Nations and CABI), 92-123. doi: 10.1079/9781780641089.0092
78. Rizhsky, L., Liang, H., and Mittler, R. (2002). The combined effect of drought stress and heat shock on gene expression in tobacco. Plant Physiol. 130, 1143-1151. doi: 10.1104/pp.006858
79. Rizhsky, L., Liang, H., Shuman, J., Shulaev, V., Davletova, S., and Mittler, R. (2004). When defense pathways collide. The response of Arabidopsis to a combination of drought and heat stress. Plant Physiol. 134, 1683-1696. doi: 10.1104/pp.103.033431
80. Rockwood, D. L., Naidu, C. V., Carter, D. R., Rahmani, M., Spriggs, T. A., Lin, C., et al. (2004). Short-rotation woody crops and phytoremediation: opportunities for agroforestry? Agroforest. Syst. 61, 51-63. doi: 10.1023/B:AGFO.0000028989.72186.e6
81. Rohde, A., Bastien, C., and Boerjan, W. (2011). Temperature signals contribute to the timing of photoperiodic growth cessation and bud set in poplar. Tree Physiol. 31, 472-482. doi: 10.1093/treephys/tpr038
82. Sabatti, M., Fabbrini, F., Harfouche, A., Beritognolo, I., Mareschi, L., Carlini, M., et al. (2014). Evaluation of biomass production potential and heating value of hybrid poplar genotypes in a short-rotation culture in Italy. Ind. Crop Prod. 61, 62-73. doi: 10.1016/j.indcrop.2014.06.043
83. Sade, N., Gebremedhin, A., and Moshelion, M. (2012). Risk-taking plants. Anisohydric behavior as a stress-resistance trait. Plant Signal. Behav. 7, 767-770. doi: 10.4161/psb.20505
84. Sade, N., and Moshelion, M. (2014). The dynamic isohydric-anisohydric behavior of plants upon fruit development: taking a risk for the next generation. Tree Physiol. 34, 1199-1202. doi: 10.1093/treephys/tpu070
85. Sánchez, E., Scordia, D., Lino, G., Aries, A., Cosentino, S. L., and Nogués, S. (2015). Salinity and water stress effects on biomass production in different Arundo donax L. clones. Bioenerg. Res. 8, 1461-1479. doi: 10.1007/s12155-015-9652-8
86. Sannigrahi, P., Ragauskas, A. J., and Tuskan, G. (2010). Poplar as a feedstock for biofuels: a review of compositional characteristics. Biofuels Bioprod. Bioref. 4, 209-226. doi: 10.1002/bbb.206
87. Sehgal, D., Skot, L., Singh, R., Srivastava, R. K., Das, S. P., Taunk, J., et al. (2015). Exploring potential of pearl millet germplasm association panel for association mapping of drought tolerance traits. PLOS ONE 10:e0122165. doi: 10.1371/journal.pone.0122165
88. Sepulcre-Canto, G., Zarco-Tejada, P., Jimenez-Munoz, J., Sobrino, J., de Miguel, E., and Villalobos, F. J. (2006). Detection of water stress in an olive orchard with thermal remote sensing imagery. Agric. For. Meteorol. 136, 31-44. doi: 10.1016/j.agrformet.2006.01.008
89. Sepulcre-Canto, G., Zarco-Tejada, P., Jimenez-Munoz, J., Sobrino, J., Soriano, M., Fereres, E., et al. (2007). Monitoring yield and fruit quality parameters in open-canopy tree crops under water stress. Implications for ASTER. Remote Sens. Environ. 107, 455-470. doi: 10.1016/j.rse.2006.09.014
90. Shi, Y., Thomasson, J. A., Murray, S. C., Pugh, N. A., Rooney, W. L., Shafian, S., et al. (2016). Unmanned aerial vehicles for high-throughput phenotyping and agronomic research. PLOS ONE 11:e0159781. doi: 10.1371/journal.pone.0159781
91. Sims, R. E. H., and Venturi, P. (2004). All-year round harvesting of short rotation coppice Eucalyptus compared with the delivered costs of biomass from more conventional short season, harvesting systems. Biomass Bioenerg. 26, 27-37. doi: 10.1016/S0961-9534(03)00081-3
92. Stanton, B. J., Neale, D. B., and Li, S. (2010). “Populus breeding: from the classical to the genomic approach,” in Genetics and Genomics of Populus (Plant Genetics and Genomics: Crop and Models), eds S. Jansson, R. Bhalerao, and A. Groover (New York, NY: Springer Science + Business Media), 309-348. doi: 10.1007/978-1-4419-1541-2_14
93. Stanton, B. J., Serapiglia, M. J., and Smart, L. B. (2013). “The domestication and conservation of Populus and Salix genetic resources,” in Poplars and Willows: Trees for Society and the Environment, eds J. G. Isebrands and J. Richardson (Rome: The Food and Agriculture Organization of United Nations and CABI), 124-199.
94. Stettler, R. F., Fenn, R. C., Heilman, P. E., and Stanton, B. J. (1988). Populus trichocarpa × Populus deltoides hybrids for short rotation culture: variation patterns and 4-year field performance. Can. J. For. Res. 18, 745-753. doi: 10.1139/x88-114
95. Street, N. R., Skogstrom, O., Sjodin, A., Tucker, J., Rodriguez-Acosta, M., Nilsson, P., et al. (2006). The genetics and genomics of the drought response in Populus. Plant J. 48, 321-341. doi: 10.1111/j.1365-313X.2006.02864.x
96. Struthers, R., Ivanova, A., Tits, L., Swennen, R., and Coppin, P. (2015). Thermal infrared imaging of the temporal variability in stomatal conductance for fruit trees. Int. J. Appl. Earth Obs. 39, 9-17. doi: 10.1016/j.jag.2015.02.006
97. Tardieu, F., and Simonneau, T. (1998). Variability among species of stomatal control under fluctuating soil water status and evaporative demand: modelling isohydric and anisohydric behaviours. J. Exp. Bot. 49, 419-432. doi: 10.1093/jxb/49.Special_Issue.419
98. Tardieu, F., and Tuberosa, R. (2010). Dissection and modelling of abiotic stress tolerance in plants. Curr. Opin. Plant Biol. 13, 206-212. doi: 10.1016/j.pbi.2009.12.012
99. Testi, L., Goldhamer, D. A., Iniesta, F., and Salinas, M. (2008). Crop water stress index is a sensitive water stress indicator in pistachio trees. Irrig. Sci. 26, 395-405. doi: 10.1007/s00271-008-0104-5
100. Torresan, C., Berton, A., Carotenuto, F., Di Gennaro, S. F., Gioli, B., Matese, A., et al. (2016). Forestry applications of UAVs in Europe: a review. Int. J. Remote Sens. 38, 2427-2447. doi: 10.1080/01431161.2016.1252477
101. van der Schoot, J., Pospíšková, M., Vosman, B., and Smulders, M. J. M. (2000). Development and characterization of microsatellite markers in black poplar (Populus nigra L.). Theor. Appl. Genet. 101, 317-322. doi: 10.1007/s001220051485
102. Viger, M., Smith, H. K., Cohen, D., Dewoody, J., Trewin, H., Steenackers, M., et al. (2016). Adaptive mechanisms and genomic plasticity for drought tolerance identified in European black poplar (Populus nigra L.). Tree Physiol. 36, k909-928. doi: 10.1093/treephys/tpw017
103. Virlet, N., Lebourgeois, V., Martinez, S., Costes, E., Labbé, S., and Regnard, J. (2014). Stress indicators based on airborne thermal imagery for field phenotyping a heterogeneous tree population for response to water constraints. J. Exp. Bot. 65, 5429-5442. doi: 10.1093/jxb/eru309
104. Way, D. A., and Oren, R. (2010). Differential responses to changes in growth temperature between trees from different functional groups and biomes: a review and synthesis of data. Tree Physiol. 30, 669-688. doi: 10.1093/treephys/tpq015
105. White, J. F., Andrade-Sanchez, P., Gore, M. A., Bronson, K. F., Coffelt, T. A., Conley, M. M., et al. (2012). Field-based phenomics for plant genetics research. Field Crop Res. 133, 101-112. doi: 10.1016/j.fcr.2012.04.003
106. White, T. L., Adams, W. T., and Neale, D. B. (eds). (2007). “Quantitative genetics-polygenic traits, heritabilities and genetic correlations,” in Forest Genetics (Wallingford: CABI), 113-148. doi: 10.1079/9781845932855.0113
107. Wu, R., and Stettler, R. F. (1994). Quantitative genetics of growth and development in Populus. I. A three-generation comparison of tree architecture during the first 2 years of growth. Theor. Appl. Genet. 89, 1046-1054. doi: 10.1007/BF00224537
108. Zarco-Tejada, P. J., González-Dugo, V., and Berni, J. A. J. (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 Sens. Environ. 117, 322-337. doi: 10.1016/j.rse.2011.10.007
109. Zarco-Tejada, P. J., Suárez, L., and González-Dugo, V. (2013). Spatial resolution effects on chlorophyll fluorescence retrieval in a heterogeneous canopy using hyperspectral imagery and radiative transfer simulation. IEEE Geosci. Remote Sens. Lett. 10, 937-941. doi: 10.1109/LGRS.2013.2252877