Analysis of vineyard differential management zones and relation to vine development, grape maturity and quality
The objective of research was to analyse the potential of Normalized Difference Vegetation Index (NDVI) maps from satellite images, yield maps and grapevine fertility and load variables to delineate zones with different wine grape properties for selective harvesting. Two vineyard blocks located in NE Spain (Cabernet Sauvignon and Syrah) were analysed. The NDVI was computed from a Quickbird-2 multi-spectral image at veraison (July 2005). Yield data was acquired by means of a yield monitor during September 2005. Other variables, such as the number of buds, number of shoots, number of wine grape clusters and weight of 100 berries were sampled in a 10 rows × 5 vines pattern and used as input variables, in combination with the NDVI, to define the clusters as alternative to yield maps. Two days prior to the harvesting, grape samples were taken. The analysed variables were probable alcoholic degree, pH of the juice, total acidity, total phenolics, colour, anthocyanins and tannins. The input variables, alone or in combination, were clustered (2 and 3 Clusters) by using the ISODATA algorithm, and an analysis of variance and a multiple rang test were performed. The results show that the zones derived from the NDVI maps are more effective to differentiate grape maturity and quality variables than the zones derived from the yield maps. The inclusion of other grapevine fertility and load variables did not improve the results.
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. Precis Agric 9: 285-302. http://dx.doi.org/10.1007/s11119-008-9073-1
Arno J, Bordes X, Ribes-Dasi M, Blanco R, Rosell JR, Esteve J, 2005. Obtaining grape yield maps and analysis of within-field variability in Raimat (Spain). In: Precision Agriculture’05 (Stafford JV, ed). Science Publ Inc., Enfield, US, pp: 899-906.
Arno J, Martinez-Casasnovas JA, Ribes-Dasi M, Rosell JR, 2009. Review. Precision viticulture. Research topics, challenges and opportunities in site-specific vineyard management. Span J Agric Res 7(4): 779-790.
Bramley RGV, 2005. Understanding variability in winegrape production systems. 2. Within vineyard variation in quality over several vintages. Aust J Grape Wine Res 11: 33-42. http://dx.doi.org/10.1111/j.1755-0238.2005.tb00277.x
Bramley RGV, Williams SK, 2001. A protocol for the construction of yield maps from data collected using commercially available grape yield monitors. Cooperative Research Centre for Viticulture. Available on line in http://www.cse.csiro.au/client_serv/resources/CRCVYield_Mapping_Protocol.pdf [25 July 2011].
Bramley RGV, Lamb D, 2003. Making sense of vineyard variability in Australia. In: Precision viticulture. Proc Int Symp held as part of the IX Congreso Latinoamericano de Viticultura y Enología (Ortega R, Esser A, eds). Centro de Agricultura de Precisión, Pontificia Universidad Católica de Chile, Santiago. pp: 35-54.
Bramley RGV, Hamilton RP, 2004. Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Aust J Grape Wine Res 10: 32-45. http://dx.doi.org/10.1111/j.1755-0238.2004.tb00006.x
Bramley RGV, Janik LJ, 2005. Precision agriculture demands a new approach to soil and plant sampling and analysis-Examples from Australia. Commun Soil Sci Plant Anal 36: 9-22. http://dx.doi.org/10.1081/CSS-200042958
Bramley RGV, Hamilton RP, 2007. Terroir and precision viticulture: Are they compatible? J Int Sci Vigne Vin 41(1): 1-8.
Bramley RGV, Ouzman J, Boss PK, 2011. Variation in vine vigour, grape yield and vineyard soils and topography as indicators of variation in the chemical composition of grapes, wine and wine sensory attributes. Aust J Grape Wine Res 17: 217-219. http://dx.doi.org/10.1111/j.1755-0238.2011.00136.x
Chavez PS, 1996. Image-based atmospheric corrections. Revisited and improved. Photogramm Eng Rem Sens 55: 339-348.
Cortell JM, Halbleib M, Gallagher AV, Righetti TL, Kennedy J, 2005. Influence of vine vigor on grape (Vitis vinifera L. cv. Pinot Noir) and wine proanthocyanidins. J Agr Food Chem 53: 5798-5808. http://dx.doi.org/10.1021/jf0504770 PMid:15998151
Corwin DL, Lesch SM, 2005. Apparent soil electrical conductivity measurements in agriculture. Comput Electron Agr 46: 11-43. http://dx.doi.org/10.1016/j.compag.2004.10.005
Da Silva PR, Ducati JR, 2009. Spectral features of vineyards in south Brazil from ASTER imaging. Int J Remote Sens 30: 6085-6098. http://dx.doi.org/10.1080/01431160902810612
Hall A, Lamb DW, Holzapfel B, Louis J, 2002. Optical remote sensing applications in viticulture-a review. Aust J Grape Wine Res 8: 36-47. http://dx.doi.org/10.1111/j.1755-0238.2002.tb00209.x
Hall A, Louis J, Lamb D, 2003. Characterising and mapping vineyard canopy using high-spatial-resolution aerial multispectral images. Comput Geosci-UK 29: 813-822. http://dx.doi.org/10.1016/S0098-3004(03)00082-7
Iland P, Bruer N, Edwards G, Weeks S, Wilkes E, 2004. Chemical analysis of grapes and wine: techniques and concepts. Patric Iland Wine Promotions PTY Ltd., Campbelltown, Australia.
Jensen JR, 1996. Introductory digital image processing: a remote sensing perspective. 2nd ed. Prentice-Hall, Englewood Cliffs, NJ, USA.
Johnson LF, Bosch DF, Williams DC, Lobitz BM, 2001. Remote sensing of vineyard management zones: implications for wine quality. Appl Eng Agr 17: 557-560.
Krause K, 2003. Radiance conversion of Quickbird data-Technical note. DigitalGlobe Inc., Longmont, CO, USA.
Lamb DW, Weedon MM, Bramley RGV, 2004. Using remote sensing to predict grape phenolics and colour at harvest in a Cabernet Sauvignon vineyard: timing observations against vine phenology and optimising image resolution. Aust J Grape Wine Res 10: 46-54. http://dx.doi.org/10.1111/j.1755-0238.2004.tb00007.x
Martinez-Casasnovas JA, Bordes X, 2005. Viticultura de precisión: Predicción de cosecha a partir de variables del cultivo e índices de vegetación. Revista de Teledetección 24: 67-71. [In Spanish].
Martinez-Casasnovas JA, Valles Bigorda D, Ramos MC, 2009. Irrigation management zones for precision viticulture according to intra-field variability. EFITA Conf (Bregt A, Wolfert S, Wien JE, Lokhorst C, eds). Wageningen Acad Publ, Wageningen, The Netherlands. pp: 523-529.
Mazzetto F, Calcante A, Mena A,Vercesi A, 2010. Integration of optical and analogue sensors for monitoring canopy health and vigour in precision viticulture. Precis Agric 11: 636-649. http://dx.doi.org/10.1007/s11119-010-9186-1
Minasny B, McBratney AB, Whelan BM, 2005. VESPER version 1.62. Australian Centre for Precision Agriculture. The University of Sydney, Australia.
Myneni RB; Hall FG; Sellers PJ, Marshak AL, 1995. The interpretation of spectral vegetation indexes. IEEE T Geosci Remote Sens 33: 481-486. http://dx.doi.org/10.1109/36.377948
Proffitt APB, Pearse B, 2004. Adding value to the wine business precisely: using precision viticulture technology in Margaret River. Aust NZ Grapegrower Winemaker 491: 40-44.
Proffitt APB, Malcolm A, 2005. Zonal vineyard management through airbone remote sensing. Aust NZ Grapegrower Winemaker 502: 22-27.
Proffitt APB, Bramley RGV, Lamb D, Winter E, 2006. Precision viticulture-A new era in vineyard management and wine production. Winetitles Pty Ltd., Ashford, Australia.
Rodriguez-Perez JR, Plant RE, Lambert JJ, Smart DR, 2011. Using apparent soil electrical conductivity (ECa) to characterize vineyard soils of high clay content. Precis Agric 12: 775-794. http://dx.doi.org/10.1007/s11119-011-9220-y
Rouse JW Jr, Haas RH, Schell JA, Deering DW, 1973. Monitoring vegetation systems in the great plains with ERTS. Proc Third ERTS Symp NASA SP-351 1, pp: 309-317.
Samouëlian A, Cousin I, Tabbagh A, Bruand A, Richard G, 2005. Electrical resistivity survey in soil science: a review. Soil Till Res 83: 173-193. http://dx.doi.org/10.1016/j.still.2004.10.004
Santesteban LG, Royo JB, 2006. Water status, leaf area and fruit load influence on berry weight and sugar accumulation of cv. “Tempranillo” under semiarid conditions. Sci Hortice 109(1): 60-65. http://dx.doi.org/10.1016/j.scienta.2006.03.003
Santesteban LG, Tisseyre B, Royo JB, Guillaume S, 2008. Is it relevant to consider remote sensing information for targeted plant monitoring? VIIth Int Terroir Cong, ACW, Agroscope Changins-Wädenswil, Nyon (Switzerland). Vol 1, pp: 469-474.
Soil Survey Staff, 2006. Keys to soil taxonomy, 10th ed. USDA-Natural Resources Conservation Service, Washington, DC.
Taylor JA, Acevedo-Opazo C, Ojeda H, Tisseyre B, 2010. Identification and significance of sources of spatial variation in grapevine water status. Aust J Grape Wine Res 16: 218-226. http://dx.doi.org/10.1111/j.1755-0238.2009.00066.x
© INIA. Manuscripts published are the property of the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, and quoting this source is a requirement for any partial or full reproduction.
SJAR is an Open Access Journal. All articles are distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the license CC-by must be expressly stated in this way when necessary.