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

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.

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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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

  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.

    Article  Google Scholar 

  7. Ehlert, D., Heisig, M., & Adamek, R. (2010). Suitability of a laser rangefinder to characterize winter wheat. Precision Agriculture, 11(6), 650–663.

    Article  Google 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.

  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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    CAS  Article  Google 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.

    Article  Google Scholar 

  17. Llorens, J., Gil, E., Llop, J., & Queraltó, M. (2011). Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11, 6237–6256.

    Article  PubMed  PubMed Central  Google 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.

  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.

    Article  Google 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.

    Article  Google Scholar 

  23. Saint-Criq, N., Vivas, N., & Glories, Y. (1998). Maturité phénolique: définition et contrôle. Revue franc¸aise d’Oenologie, 173, 22–25.

  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.

    Article  PubMed  PubMed Central  Google 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.

    Article  Google 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.

    CAS  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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google 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.

    Article  Google Scholar 

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Correspondence to A. C. Tagarakis.

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Tagarakis, A.C., Koundouras, S., Fountas, S. et al. Evaluation of the use of LIDAR laser scanner to map pruning wood in vineyards and its potential for management zones delineation. Precision Agric 19, 334–347 (2018). https://doi.org/10.1007/s11119-017-9519-4

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Keywords

  • Laser scanner
  • Pruning wood estimation
  • Vine vigour
  • NDVI