Evaluation of the use of LIDAR laser scanner to map pruning wood in vineyards and its potential for management zones delineation

  • A. C. Tagarakis
  • S. Koundouras
  • S. Fountas
  • T. Gemtos
Article

Abstract

Vine vigour assessment has been a major concern of precision viticulture studies in order to identify areas of uniform vine performance within vineyards. Moreover, the counting and weighing of winter dormant canes is considered as the most informative measurement to indicate vine balance and is commonly performed manually by grape growers for management purposes. The main concern of this measurement is that it is time consuming and laborious and it cannot accommodate detailed sampling density. In the present study, the potential of using laser scanner technology as an automated, easy and rapid way to perform mapping of the winter pruning wood across the vineyard was investigated. The study was conducted during 2010 and 2011, in a one hectare commercial vineyard in central Greece, planted with cv. Agiorgitiko, a traditional Greek variety for the production of red wine. Parameters of topography, soil depth, soil texture, canopy properties (NDVI), yield, and grape quality were mapped and analysed in conjunction to winter canes weighing at pruning time. The mapping of the dormant canes was carried out using a 2D laser scanner sensor prior to pruning and manually measuring the pruning weight on a 10 × 20 m grid. Laser scanner measurements showed significant relationship in both 2010 and 2011 with pruning weight (r = 0.809 and r = 0.829 respectively, p < 0.001), yield and early season NDVI, showing the potential of using laser scanner measurements to assess variability in vine vigour within vineyards. These results suggest that laser scanners offer great promise to characterize within field variability in vine performance.

Keywords

Laser scanner Pruning wood estimation Vine vigour NDVI 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Acevedo-Opazo, C., Tisseyre, B., Guillaume, S., & Ojeda, H. (2008). The potential of high spatial resolution information to define within-vineyard zones related to vine water status. Precision Agriculture, 9, 285–302.CrossRefGoogle Scholar
  2. Arno, J., Escola, A., & Rosell-Polo, J. R. (2017). Setting the optimal length to be scanned in rows of vines by using mobile terrestrial laser scanners. Precision Agriculture, 18(2), 145–151.CrossRefGoogle Scholar
  3. Bramley, R. G. V. (2005). Understanding variability in winegrape production systems. 2. Within vineyard variation in quality over several vintages. Australian Journal of Grape and Wine Research, 11, 33–42.CrossRefGoogle Scholar
  4. Bramley, R. G. V., & Hamilton, R. P. (2005). Hitting the zone—making viticulture more precise. In: R. J. Blair, P. J. Williams & I. S. Pretorius (Eds.), Proceedings of the 12th Australian Wine Industry Technical Conference (pp. 57–61). Winetitles, Adelaide SA.Google Scholar
  5. Bramley, R., & Hamilton, R. (2007). Terroir and precision viticulture: Are they compatible? International Journal of Vine and Wine Sciences, 41(1), 1–8.Google Scholar
  6. Bramley, R. G. V., Trought, M. C. T., & Praat, J. P. (2011). Vineyard variability in Marlborough, New Zeland: Characterizing variation. Australian Journal of Grape and Wine Research, 17, 72–78.CrossRefGoogle Scholar
  7. Ehlert, D., Heisig, M., & Adamek, R. (2010). Suitability of a laser rangefinder to characterize winter wheat. Precision Agriculture, 11(6), 650–663.CrossRefGoogle Scholar
  8. Ehsani, R., & Lang, L. (2002). A sensor for rapid estimation of plant biomass. In P. Robert (Ed.), Proceedings of the 6th international conference on precision agriculture. ASA/CSSA/SSSA, Madison, WI, USA.Google Scholar
  9. Gil, E., Escola, A., Rosell, J. R., Planas, S., & Val, L. (2007). Variable-rate application of plant protection products in vineyard using ultrasonic sensors. Crop Protection, 26(8), 1287–1297.CrossRefGoogle Scholar
  10. Grocholsky, B., Nuske, S., Aasted, M., Achar, S., & Bates, T. (2011). A camera and laser system for automatic vine balance assessment. Transactions of the ASABE, 7, 5530–5544.Google Scholar
  11. Hall, A., Lamb, D. W., Holzapfel, B. P., & Louis, J. P. (2011). Within-season temporal variation in correlations between vineyard canopy and winegrape composition and yield. Precision Agriculture, 12, 103–117.CrossRefGoogle Scholar
  12. Hansen, P. M., & Schjoerring, J. K. (2003). Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote sensing Environment, 86, 542–553.CrossRefGoogle Scholar
  13. Johnson, L. F., Roczen, D. E., Youkhana, S. K., Nemani, R. R., & Bosch, D. F. (2003). Mapping vineyard leaf area with multispectral satellite imagery. Computers and Electronics in Agriculture, 38, 33–44.CrossRefGoogle Scholar
  14. Keightleya, K. E., & Bawden, G. W. (2010). 3D volumetric modeling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74, 305–312.CrossRefGoogle Scholar
  15. Lamb, D. W., Weedon, M. M., & Bramley, R. G. V. (2004). Using remote sensing to predict phenolics and color at harvest in a Cabernet Sauvignon vineyard: Timing observations against vine phenology and optimizing image resolution. Australian Journal of Grape and Wine Research, 10, 46–54.CrossRefGoogle Scholar
  16. Lee, K. H., & Ehsani, R. (2008). Comparison of two 2D laser scanners for sensing object distances, shapes, and surface patterns. Computers and electronics in agriculture, 60, 250–262.CrossRefGoogle Scholar
  17. Llorens, J., Gil, E., Llop, J., & Queraltó, M. (2011). Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11, 6237–6256.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Lumme, J., Karjalainen, M., Kaartinen, H., Kukko, A., Hyyppä, J., Hyyppä, H., et al. (2008). Terrestrial laser scanning of agricultural crops. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37(B5), 563–566.Google Scholar
  19. Monta, M., Namba, K., & Kondo, N. (2004). Three dimensional sensing system using laser scanner. ASAE/CSAE Paper No. 041158, St. Joseph, MI, USA.Google Scholar
  20. Palacin, J., Salse, J. A., Sanz, R., Ribes-Dasi, M., Masip, J., Arnó, J., et al. (2007). Real-time tree-foliage surface estimation using a ground laser scanner. Transactions on Instrumentation and Measurement (IEEE), 56(4), 1377–1383.CrossRefGoogle Scholar
  21. Poni, S., Casalini, L., Bernizzoni, F., Civardi, S., & Intrieri, C. (2006). Effects of early defoliation on shoot photosynthesis, yield components, and grape quality. American Journal of Enology and Viticulture, 57, 397–407.Google Scholar
  22. Rosell-Polo, J. R., Sanz, R., Llorens, J., Arno, J., Escola, A., Ribes-Dasi, M., et al. (2009). 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. Biosystems Engineering, 102, 128–134.CrossRefGoogle Scholar
  23. Saint-Criq, N., Vivas, N., & Glories, Y. (1998). Maturité phénolique: définition et contrôle. Revue franc¸aise d’Oenologie, 173, 22–25.Google Scholar
  24. Sanz-Cortiella, R., Llorens-Calveras, J., Escolà, A., Arnó-Satorra, J., Ribes-Dasi, M., Masip-Vilalta, J., et al. (2011). Innovative LIDAR 3D dynamic measurement system to estimate fruit-tree leaf area. Sensors, 11(6), 5769–5791.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Smart, R., & Robinson, M. (1991). Sunlight into wine: A handbook for winegrape and canopy management. Adelaide: Winetitles.Google Scholar
  26. Stamatiadis, S., Taskos, D., Tsalida, E., Christoforides, C., Tsalidas, C., & Schepers, J. S. (2010). Comparison of passive and active canopy sensors for the estimation of vine biomass production. Precision Agriculture, 11, 306–315.CrossRefGoogle Scholar
  27. Stamatiadis, S., Taskos, D., Tsalidas, C., Christoforides, C., Tsalida, E., & Schepers, J. S. (2006). Relation of ground-sensor canopy reflectance to biomass production and grape color in two merlot vineyards. American Journal of Enology and Viticulture, 57, 415–422.Google Scholar
  28. Tagarakis, A., Liakos, V., Fountas, S., Koundouras, S., & Gemtos, T. (2013). Management zones delineation using fuzzy clustering techniques in grapevines. Precision Agriculture, 14(1), 18–39.CrossRefGoogle Scholar
  29. Tardaguila, J., Baluja, J., Arpon, L., Balda, P., & Oliveira, M. (2011). Variations in soil properties affect the vegetative growth and yield components of “Tempranillo” grapevines. Precision Agriculture, 12, 762–773.CrossRefGoogle Scholar
  30. Thosink, G., Preckwinkel, J., Linz, A., Ruckelshausen, A., & Marquering, J. (2004). Optoelektronisches Sensorsystem zur Messung der flanzenbestandesdichte. (Optoelectronic sensor system for crop density measurement). Landtechnik, 59(2), 78–79.Google Scholar
  31. Tumbo, S. D., Salyani, M., Whitney, J. D., Wheaton, T. A., & Miller, W. M. (2002). Investigation of laser and ultrasonic ranging sensors for measurements of citrus canopy volume. Applied Engineering in Agriculture, 18(3), 367–372.CrossRefGoogle Scholar
  32. Urretavizcaya, I., Santesteban, L. G., Tisseyre, B., Guillaume, S., Miranda, C., & Royo, J. B. (2014). Oenological significance of vineyard management zones delineated using early grape sampling. Precision Agriculture, 15, 111–129.CrossRefGoogle Scholar
  33. Van der Zande, D., Hoet, W., Jonckheere, I., van Aardt, J., & Coppin, P. (2006). Influence of Measurement Set-Up of Ground-Based LiDAR for Derivation of Tree Structure. Agricultural and Forest Meteorology, 141, 147–160.CrossRefGoogle Scholar
  34. Walklate, P. J., Cross, J. V., Richardson, G. M., Murray, R. A., & Baker, D. E. (2002). Comparison of different spray volume deposition models using LIDAR measurements of apple orchards. Biosystems Engineering, 82(3), 253–267.CrossRefGoogle Scholar
  35. Wei, J., & Salyani, M. (2004). Development of a laser scanner for measuring tree canopy characteristics: Phase 1. Prototype development. Transactions of the ASAE, 47(6), 2101–2107.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • A. C. Tagarakis
    • 1
  • S. Koundouras
    • 2
  • S. Fountas
    • 3
  • T. Gemtos
    • 4
  1. 1.Nutrient Management Spear ProgramCornell UniversityIthacaUSA
  2. 2.Laboratory of Viticulture, School of AgricultureAristotle University of ThessalonikiThessalonikiGreece
  3. 3.Laboratory of Agricultural Engineering, School of Natural Resources Management and Agricultural EngineeringAgricultural University of AthensAthensGreece
  4. 4.Laboratory of Farm Mechanization, School of Agricultural SciencesUniversity of ThessalyIoiniaGreece

Personalised recommendations