The leaf angle distribution of natural plant populations: Assessing the canopy with a novel software tool

Plant Methods

Volumn 11, Issue 1, 2015, Pages

  Müller Linow, Mark ^a   Pinto Espinosa, Francisco ^a   Scharr, Hanno ^a   Rascher, Uwe ^a  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

Author keywords

3 d reconstruction; Canopy; Leaf angle; Leaf angle distribution; Leaf modeling; Leaf segmentation; Stereo imaging; Structural canopy straits

Indexed keywords

BETA VULGARIS SUBSP. VULGARIS;

EID: 84928718366     PISSN: None     EISSN: 17464811     Source Type: Journal    
DOI: 10.1186/s13007-015-0052-z     Document Type: Article

References (61)

1. Rascher U, Nedbal L. Dynamics of plant photosynthesis under fluctuating natural conditions. Curr Opin Plant Biol. 2006; 9:671-8.
2. Rosa LM, Forseth IN. Diurnal patterns of soybean leaf inclination angles and azimuthal orientation under different levels of UVb radiation. Agric For Meteorol. 1995; 78:107-19.
3. Wofford TJ, Allen FL. Variation in leaflet orientation among soybean cultivars. Crop Sci. 1982; 22:999-1004.
4. Bawhey CI, Grant RH, Gao W. Digital measurement of heliotropic leaf response in soybean cultivars and leaf exposure to solar uvb radiation. Agric For Meteorol. 2003; 120:161-76.
5. Long SP, Zhu XG, Naidu SL, Ort DR. Can improvement in photosynthesis increase crop yields?Plant Cell Environ. 2006; 29:315-30.
6. Schurr U, Walter A, Rascher U. Functional dynamics of plant growth and photosynthesis ? from steady-state to dynamics ? from homogeneity to heterogeneity. Plant Cell Environ. 2006; 29:340-52.
7. Biskup B, Kuesters R, Scharr H, Walter A, Rascher U. Quantification of plant surface structures from small baseline stereo images to measure the three-dimensional surface from the leaf to the canopy scale. Nova Acta Leopoldina. 2009; 96(357):31-47.
8. Loomis RS, Williams WA, Duncan WG. Community architecture and the productivity of terrestrial plant communities. New York, USA: New York Academic; 1967, pp. 291-308.
9. Rascher U, Biskup B, Leakey ADB, McGrath JM, Ainsworth EA. Altered physiological function, not structure, drives increased radiation-use efficiency of soybean grown at elevated CO2. Photosynth Res. 2010; 105(1):15-25.
10. Zhu X-GZ, Long SP, Ort DR. Improving photosynthetic efficiency for greater yield. Annu Rev Plant Biol. 2010; 61:235-61.
11. Hosoi F, Omasa K. Factors contributing to accuracy in the estimation of the woody canopy leaf area densitiy profile using 3d portable LIDAR imaging. J Exp Bot. 2007; 58:3463-73.
12. Hosoi F, Nakai Y, Omasa K. Estimation and error analysis of woody canopy leaf area density profiles using 3-d airborne and ground-based scanning lidar remote-sensing techniques. IEEE Trans Geosci Remote Sens. 2010; 48(5):2215-23.
13. Hosoi F, Omasa K. Estimation of vertical plant area density profiles in a rice canopy at different growth stages by high-resolution portable scanning LIDAR with a lightweight mirror. ISPRS J Photogram Remote Sens. 2012; 74:11-9.
14. Bellasio C, Olejnickova J, Tesar R, Sebela D, Nedbal L. Computer reconstruction of plant growth and chlorophyll fluorescence emission in three spatial dimensions. Sensors. 2012; 12:1052-71.
15. Mullen JL, Weinig C, Hangarter RP. Shade avoidance and the regulation of leaf inclination in Arabidopsis. Plant Cell Environ. 2006; 29:1099-106.
16. Dornbusch T, Lorrain S, Kuznetsov D, Fortier A, Liechti R, Xenarios I, et al. Measuring the diurnal pattern of leaf hyponasty and growth in Arabidopsis - a novel phenotyping approach using laser scanning. Func Plant Biol. 2012; 39:860-9.
17. Watanabe T, Hanan JS, Room PM, Hasegawa T, Nakagawa H, Takahashi W. Rice morphogenesis and plant architecture: Measurement, specification and the reconstruction of structural development by 3d architectural modelling. Ann Bot. 2005; 95:1131-43.
18. Vos J, Evers JB, Buck-Sorlin GH, Andrieu B, Chelle M, de Visser PHB. Functional-structural plant modelling: a new versatile tool in crop science. J Exp Bot. 2010; 61(8):2101-15.
19. Sarlikioti V, de Visser PHB, Marcelis LFM. Exploring the spatial distribution of light interception and photosynthesis of canopies by means of a functional-structural plant model. Ann Bot. 2011; 107:875-83.
20. Deckmyn G, Nijs I, Ceulemans R. A simple method to determine leaf angles of grass species. J Exp Bot. 2000; 51(349):1467-70.
21. Ivanov N, Boissard P, Chapron M, Valery P. Estimation of the height and angles of orientation of the upper leaves in the maize canopy using stereovision. Agronomie. 1994; 2:183-94.
22. Hosoi F, Omasa K. Voxel-based 3-d modeling of individual trees for estimating leaf area density using high-resolution portable scanning LIDAR. IEEE Trans Geosci Remote Sensing. 2006; 44:3610-8.
23. Pisek J, Ryu Y, Alikas K. Estimating leaf inclination and g-function from leveled digital camera photography in broadleaf canopies. Trees. 2011; 25:919-24.
24. Duvick DN, Smith JSC, Cooper M. Long-Term Selection in a Commercial Hybrid Maize Breeding Program. Hoboken, New Jersey, USA: John Wiley & Sons, Inc.; 2010, pp. 109-51.
25. Ford ED, Cocke A, Horton L, Fellner E, Van Volkenburgh M. Estimation, variation and importance of leaf curvature in zea mays hybrids. Agric Forest Meteorol. 2008; 148(10):1598-610.
26. Paproki A, Sirault X, Berry S, Furbank R, Fripp J. A novel mesh processing based technique for 3d plant analysis. BMC Plant Biol. 2012; 12(63):13.
27. Biskup B, Scharr H, Schurr U, Rascher U. A stereo imaging system for measuring structural parameters of plant canopies. Plant Cell Environ. 2007; 30(10):1299-308.
28. Ehlert D, Heisig M, Adamek R. Assessment of a Laser Scanner on Agricultural Machinery. In: Engineering for Rural Development - 9th International Scientific Conference. University of Agriculture, Jelgava, Latvia: 2010. p. 32-36.
29. Sanz-Cortiella R, Llorens-Calveras J, Escolà A, Arnó-Satorra J, Ribes-Dasi M, Masip-Vilalta J, et al. Innovative LIDAR 3d dynamic measurement system to estimate fruit-tree leaf area. Sensors. 2011; 11(6):5769-91.
30. Lumme J, Karjalainen M, Kaartinen H, Kukko A, Hyyppä J, Hyyppä H, et al. Terrestrial laser scanning of agricultural crops. In: Proceedings of the XXI. IS-PRS Congress: Silk Road for Information from Imagery. Bejing, China: 2008. p. 563-66.
31. Bouguet J-Y. Calibration toolbox for Matlab. 2005. http://vision.caltech.edu/bouguetj/calib_doc/index.html.
32. Fusiello A, Trucco E, Verri A. A compact algorithm for rectification of stereo pairs. Mach Vis Appl. 2000; 12(1):16-22.
33. Vedaldi A, Fulkerson B. VLFeat: An Open and Portable Library of Computer Vision Algorithms. 2008. http://www.vlfeat.org/.
34. Engwirda D. MESH2D - Automatic Mesh Generation. 2009. http://www.mathworks.de/matlabcentral/fileexchange/25555-mesh2d-automatic-mesh-generation.
35. Agoston M. Computer Graphics and Geometric Modeling: Implementation and Algorithms. London, UK: Springer; 2005, pp. 300-306.
36. Shapiro L, Stockman G. Computer Vision. Upper Saddle River, New Jersey, USA: Prentice Hall; 2001.
37. Hartley R, Zisserman A. Multiple View Geometry in Computer Vision. Cambridge, United Kingdom: Cambridge University Press; 2003.
38. Zhang Z. Flexible camera calibration by viewing a plane from unknown orientations. In: ICCV. Kerkyra, Corfu, Greece: 1999. p. 666-73.
39. Zhang Z. A flexible new technique for camera calibration. IEEE Trans Pattern Anal Mach Intell. 2000; 22:1330-4.
40. Brown MZ, Burschka D, Hager GD. Advances in computational stereo. IEEE Trans Pattern Anal Mach Intell. 2003; 25(8):993-1008.
41. Scharstein D, Szeliski R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. Int J Comput Vis. 2002; 47(1-3):7-42.
42. Trucco E, Verri A. Introductory Techniques for 3D Computer Vision. New Jersey, USA: Prentice Hall; 1998.
43. Lowe DG. Distinctive image features from scale-invariant keypoints. Int J Comput Vis. 2004; 60(2):91-110.
44. Fusiello A, Roberto V, Trucco E. Efficient Stereo with Multiple Windowing. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Juan, Puerto Rico: 1997. p. 858-863.
45. Fua P. Combining Stereo and Monocular Information to Compute Dense Depth Maps that Preserve Depth Discontinuities. In: 12th International Joint Conferences on Artificial Intelligence: 1991. p. 1292-1298.
46. Fua P. A parallel stereo algorithm that produces dense depth maps and preserves image features. Mach Vis Appl. 1993; 6:35-49.
47. Khongsab P. Signal processing and performance evaluation of a PMD camera for space docking. Kiruna: Master's thesis, Lulea University of Technology; 2009.
48. Lejeune A, Piérard S, Van Droogenbroeck M, Verly J. A new jump edge detection method for 3D cameras. In: International Conference on 3D Imaging (IC3D). Liège, Belgium: 2011. http://hdl.handle.net/2268/103459.
49. Huang T, Yang G, Tang G. A fast two-dimensional median filtering algorithm. IEEE Trans Acoust Speech Signal Process. 1979; 27(1):13-8.
50. Ma Z, He K, Wei Y, Sun J, Wu E. Constant Time Weighted Median Filtering for Stereo Matching and Beyond. In: IEEE International Conference on Computer Vision. Sydney, NSW, Australia: 2013. p. 49-56.
51. Felzenszwalb PF, Huttenlocher DP. Efficiently computing a good segmentation. In: Proceedings DARPA Image Understanding Workshop. Monterey, California, USA: 1998. p. 251-8.
52. Desbrun M, Meyer M, Schröder P, Barr AH. Implicit fairing of irregular meshes using diffusion and curvature flow. In: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques. New York, NY, USA: ACM Press/Addison-Wesley Publishing Co.: 1999. p. 317-324.
53. Zhang Y, Hamza AB. Vertex-based diffusion for 3-d mesh denoising. IEEE Trans Image Process. 2007; 16(4):1036-45.
54. Hansen GA, Douglass RW, Zardecki A. Mesh enhancement: selected elliptic methods, foundations and applications. London, UK: London Imperial College Press; 2005.
55. Delaunay BN. Sur la sphere vide. Bull Acad Sci USSR. 1934; 7:793-800.
56. de Berg M, Cheong O, van Kreveld M, Overmars M. Computational Geometry: Algorithms and Applications. London, UK: Springer; 2008.
57. Golub G, van Loan C. Matrix Computations. Baltimore, Maryland, USA: Johns Hopkins University Press; 1996.
58. Fischler M, Bolles R. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Comm ACM. 1981; 24(6):381-95.
59. Welles JM. Some indirect methods of estimating canopy structure. Remote Sensing Rev. 1990; 5:31-43.
60. Breda NJJ. Ground-based measurement of leaf area index: a review of methods, instruments and current controversies. J Exp Bot. 2003; 54(392):2403-17.
61. Li G, Zucker SW. Differential Geometric Consistency Extends Stereo to Curved Surfaces. In: ECCV (3). London, UK: Springer: 2006. p. 44-57.