Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions

Plant Methods

Volumn 12, Issue 1, 2016, Pages

  Friedli, Michael ^a   Kirchgessner, Norbert ^a   Grieder, Christoph ^a   Liebisch, Frank ^a   Mannale, Michael ^a   Walter, Achim ^a  

^a ETH ZURICH   (Switzerland)

Author keywords

Canopy height growth; Laser scanning; Maize; Scan point cloud; Soybean; Wheat

Indexed keywords

EID: 84956689620     PISSN: None     EISSN: 17464811     Source Type: Journal    
DOI: 10.1186/s13007-016-0109-7     Document Type: Article

References (53)

1. Walter A, Silk WK, Schurr U. Environmental effects on spatial and temporal patterns of leaf and root growth. Annu Rev Plant Biol. 2009;60:279-304.
2. Walter A, Liebisch F, Hund A. Plant phenotyping: from bean weighing to image analysis. Plant Methods. 2015;11:14.
3. Banziger M, Edmeades GO, Lafitte HR. Selection for drought tolerance increases maize yields across a range of nitrogen levels. Crop Sci. 1999;39:1035-40.
4. Lipiec J, Doussan C, Nosalewicz A, Kondracka K. Effect of drought and heat stresses on plant growth and yield: a review. Int Agrophys. 2013;27:463-77.
5. Ha S, Tran LS. Understanding plant responses to phosphorus starvation for improvement of plant tolerance to phosphorus deficiency by biotechnological approaches. Crit Rev Biotechnol. 2014;34:16-30.
6. Sritarapipat T, Rakwatin P, Kasetkasem T. Automatic rice crop height measurement using a field server and digital image processing. Sensors. 2014;14:900-26.
7. Biskup B, Scharr H, Schurr U, Rascher U. A stereo imaging system for measuring structural parameters of plant canopies. Plant Cell Environ. 2007;30:1299-308.
8. 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.
9. Chéné Y, Belin E, Rousseau D, Chapeau-Blondeau F. Multiscale analysis of depth images from natural scenes: scaling in the depth of the woods. Chaos Soliton Fract. 2013;54:135-49.
10. Khanna R, Möller M, Pfeifer J, Liebisch F, Walter A, Siegwart R. Beyond point clouds-3D mapping and field parameter measurements using UAVs. International Conference on Emerging Technologies and Factory Automation. vol 20. Luxembourg: IEEE; 2015.
11. Aasen H, Burkart A, Bolten A, Bareth G. Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: from camera calibration to quality assurance. ISPRS J Photogramm. 2015;108:245-59.
12. Anthony D, Elbaum S, Lorenz A, Detweiler C. On crop height estimation with UAVs. IEEE Int C Int Robot. 2014:4805-12.
13. Zheng BY, Shi LJ, Ma YT, Deng QY, Li BG, Guo Y. Comparison of architecture among different cultivars of hybrid rice using a spatial light model based on 3D digitising. Funct Plant Biol. 2008;35:900-10.
14. Wiechers D, Kahlen K, Stutzel H. Evaluation of a radiosity based light model for greenhouse cucumber canopies. Agr For Meteorol. 2011;151:906-15.
15. Rosell JR, Sanz R. A review of methods and applications of the geometric characterization of tree crops in agricultural activities. Comput Electron Agr. 2012;81:124-41.
16. Omasa K, Hosoi F, Konishi A. 3D lidar imaging for detecting and understanding plant responses and canopy structure. J Exp Bot. 2007;58:881-98.
17. Parker GG, Harding DJ, Berger ML. A portable LIDAR system for rapid determination of forest canopy structure. J Appl Ecol. 2004;41:755-67.
18. Hopkinson C, Chasmer L, Young-Pow C, Treitz P. Assessing forest metrics with a ground-based scanning lidar. Can J Forest Res. 2004;34:573-83.
19. Clawges R, Vierling L, Calhoon M, Toomey M. Use of a ground-based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis). Int J Remote Sens. 2007;28:4331-44.
20. Hosoi F, Omasa K. Detecting seasonal change of broad-leaved woody canopy leaf area density profile using 3D portable LIDAR imaging. Funct Plant Biol. 2009;36:998-1005.
21. Eitel JUH, Vierling LA, Long DS. Simultaneous measurements of plant structure and chlorophyll content in broadleaf saplings with a terrestrial laser scanner. Remote Sens Environ. 2010;114:2229-37.
22. Rosell JR, Llorens J, Sanz R, Arno J, Ribes-Dasi M, Masip J, et al. Obtaining the three-dimensional structure of tree orchards from remote 2D terrestrial LIDAR scanning. Agr Forest Meteorol. 2009;149:1505-15.
23. Polo JRR, Sanz R, Llorens J, Arno J, Escola A, Ribes-Dasi P, et al. A tractor-mounted scanning LIDAR for the non-destructive measurement of vegetative volume and surface area of tree-row plantations: a comparison with conventional destructive measurements. Biosyst Eng. 2009;102:128-34.
24. Arno J, Escola A, Valles JM, Llorens J, Sanz R, Masip J, et al. Leaf area index estimation in vineyards using a ground-based LiDAR scanner. Precis Agric. 2013;14:290-306.
25. Llorens J, Gil E, Llop J, Escola A. Ultrasonic and LIDAR sensors for electronic canopy characterization in vineyards: advances to improve pesticide application methods. Sensors. 2011;11:2177-94.
26. Andujar D, Rueda-Ayala V, Moreno H, Rosell-Polo JR, Escola A, Valero C, et al. Discriminating crop, weeds and soil surface with a terrestrial LIDAR sensor. Sensors. 2013;13:14662-75.
27. Eitel JUH, Vierling LA, Long DS, Hunt ER. Early season remote sensing of wheat nitrogen status using a green scanning laser. Agr Forest Meteorol. 2011;151:1338-45.
28. Saeys W, Lenaerts B, Craessaerts G, De Baerdemaeker J. Estimation of the crop density of small grains using LiDAR sensors. Biosyst Eng. 2009;102:22-30.
29. Tilly N, Hoffmeister D, Cao Q, Huang SY, Lenz-Wiedemann V, Miao YX, et al. Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice. J Appl Remote Sens. 2014;8(1):083671.
30. Lumme J, Karjalainen M, Kaartinen H, Kukko A, Hyyppä J, Hyyppä H et al. Terrestrial laser scanning of agricultural crops. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2008;XXXVII Part B5:563-6.
31. Gebbers R, Ehlert D, Adamek R. Rapid mapping of the leaf area index in agricultural crops. Agron J. 2011;103:1532-41.
32. Hosoi F, Nakabayashi K, Omasa K. 3-D modeling of tomato canopies using a high-resolution portable scanning lidar for extracting structural information. Sensors. 2011;11:2166-74.
33. Sirault X, Fripp J, Paproki A, Kuffner P, Nguyen C, Li R et al. PlantScan™: a three-dimensional phenotyping platform for capturing the structural dynamic of plant development and growth. Proceedings of the 7th international conference on functional-structural plant models. 2013:45-8.
34. Ehlert D, Adamek R, Horn HJ. Laser rangefinder-based measuring of crop biomass under field conditions. Precis Agric. 2009;10:395-408.
35. Eitel JUH, Magney TS, Vierling LA, Brown TT, Huggins DR. LiDAR based biomass and crop nitrogen estimates for rapid, non-destructive assessment of wheat nitrogen status. Field Crop Res. 2014;159:21-32.
36. Hofle B. Radiometric correction of terrestrial LiDAR point cloud data for individual maize plant detection. IEEE Geosci Remote Sens Lett. 2014;11:94-8.
37. Dornbusch T, Wernecke P, Diepenbrock W. A method to extract morphological traits of plant organs from 3D point clouds as a database for an architectural plant model. Ecol Model. 2007;200:119-29.
38. Paulus S, Dupuis J, Riedel S, Kuhlmann H. Automated analysis of barley organs using 3D laser scanning: an approach for high throughput phenotyping. Sensors. 2014;14:12670-86.
39. Kaminuma E, Heida N, Tsumoto Y, Yamamoto N, Goto N, Okamoto N, et al. Automatic quantification of morphological traits via three-dimensional measurement of Arabidopsis. Plant J. 2004;38:358-65.
40. Kjaer KH, Ottosen CO. 3D laser triangulation for plant phenotyping in challenging environments. Sensors. 2015;15:13533-47.
41. Hosoi F, Omasa K. Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging. ISPRS J Photogramm. 2009;64:151-8.
42. Hoffmeister D, Waldhoff G, Curdt C, Tilly N, Bendig J, Bareth G. Spatial variability detection of crop height in a single field by terrestrial laser scanning. Precision Agriculture '13. Wageningen: Wageningen Academic Publishers; 2013. p. 267-74.
43. Paulus S, Dupuis J, Mahlein AK, Kuhlmann H. Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping. BMC Bioinformatics. 2013;14:238.
44. Paulus S, Schumann H, Kuhlmann H, Leon J. High-precision laser scanning system for capturing 3D plant architecture and analysing growth of cereal plants. Biosyst Eng. 2014;121:1-11.
45. Hammerle M, Hofle B. Effects of reduced terrestrial LiDAR point density on high-resolution grain crop surface models in precision agriculture. Sensors. 2014;14:24212-30.
46. White JW, Andrade-Sanchez P, Gore MA, Bronson KF, Coffelt TA, Conley MM, et al. Field-based phenomics for plant genetics research. Field Crop Res. 2012;133:101-12.
47. Poiré R, Wiese-Klinkenberg A, Parent B, Mielewczik M, Schurr U, Tardieu F, et al. Diel time-courses of leaf growth in monocot and dicot species: endogenous rhythms and temperature effects. J Exp Bot. 2010;61:1751-9.
48. Ainsworth EA, Walter A, Schurr U. Glycine max leaflets lack a base-tip gradient in growth rate. J Plant Res. 2005;118:343-6.
49. Friedli M, Walter A. Diel growth patterns of young soybean (Glycine max) leaflets are synchronous throughout different positions on a plant. Plant, Cell Environ. 2015;38:514-24.
50. Faro. Phase shift measurement and time of flight measurement. 2011. http://www.faro.com/en-sg/resource-centre-ap/white-papers. Accessed 10 July 2015.
51. Kirchgessner N, Liebisch F, Hund A, Walter A. Field imaging platform (FIP)-an automated system for plant phenotyping in the field. 20. und 21. Workshop Computer-Bildanalyse in der Landwirtschaft - 3. Workshop Unbemannte autonom fliegende Systeme (UAS) in der Landwirtschaft, Bornimer Agrartechnische Berichte 88:74.
52. Grieder C, Hund A, Walter A. Image based phenotyping during winter: a powerful tool to assess wheat genetic variation in growth response to temperature. Funct Plant Biol. 2015;42:387-96.
53. Taati B. EstimateRigidTransform. MATLAB Central File Exchange. 2010. http://www.mathworks.com/matlabcentral/fileexchange/28305-estimaterigidtransform. Accessed 22 July 2014.