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Management zones delineation using fuzzy clustering techniques in grapevines

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Abstract

Precision viticulture aims at managing vineyards at a sub-field scale according to the real needs of each part of the field. The current study focused on delineating management zones using fuzzy clustering techniques and developing a simplified approach for the comparison of zone maps. The study was carried out in a 1.0 ha commercial vineyard in Central Greece during 2009 and 2010. Variation of soil properties across the field was initially measured by means of electrical conductivity, soil depth and topography. To estimate grapevine canopy properties, NDVI was measured at different stages during the vine growth cycle. Yield and grape composition (must sugar content and total acidity) mapping was carried out at harvest. Soil properties, yield and grape composition parameters showed high spatial variability. All measured data were transformed on a 48-cell grid (10 × 20 m) and maps of two management zones were produced using the MZA software. Pixel-by-pixel comparison between maps of electrical conductivity, elevation, slope, soil depth and NDVI with yield and grape composition maps, set as reference parameters, allowed for the calculation of the degree of agreement, i.e. the percentage of pixels belonging to the same zone. The degree of agreement was used to select the best-suited parameters for final management zones delineation. For the year 2009 soil depth, early and mid season NDVI were used for yield-based management zones while for quality-based management zones ECa, early and mid season NDVI were utilized. For the year 2010 ECa, elevation and NDVI acquired during flowering and veraison were used for the delineation of yield-based management zones while for quality-based management zones ECa and NDVI acquired during flowering and harvest were utilized. Results presented here could be the basis for simple management zone delineation and subsequent improved vineyard management.

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References

  • 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 

  • Arnó, J., Bordes, X., Ribes-Dasi, M., Blanco, R., Rosell, J. R., & Esteve, J. (2005). Obtaining grape yield maps and analysis of within-field variability in Raimat (Spain). In J. V. Stafford (Ed.), Proceedings of the fifth European conference on precision agriculture (pp. 899–906). Wageningen: Wageningen Academic Publishers.

  • Best, S., León, L., & Claret, M. (2005). Use of precision viticulture tools to optimize the harvest of high quality grapes. In Proceedings of the fruits and nuts and vegetable production engineering TIC (Frutic05) (pp. 249–258), Montpellier.

  • Boydell, B., & McBratney, A. B. (1999). Identifying potential within field management zones from cotton yield estimates. In: J. V. Stafford (Ed.), Proceedings of the second European conference on precision agriculture (pp. 331–341).

  • Bramley, R. G. V. (2003). Smarter thinking on soils survey. Australian and New Zealand Wine Industry Journal, 18, 88–94.

    Google Scholar 

  • 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 

  • Bramley, R. G. V. (2010). Precision viticulture: Mapping vineyard variability for improved quality outcomes. In A. G. Reynolds (Ed.), Managing wine quality (Vol. 1, pp. 445–480), Viticulture and wine quality Cambridge: Woodhead Publishing Limited.

    Chapter  Google Scholar 

  • Bramley, R. G. V., & Hamilton, R. P. (2004). Understanding variability in winegrape production systems. 1. Within vineyard variation in yield over several vintages. Australian Journal of Grape and Wine Research, 10, 32–45.

    Article  Google Scholar 

  • 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). Adelaide: Winetitles.

    Google Scholar 

  • Bramley, R., Pearse, B, & Chamberlain, P. (2003). Being profitable precisely—A case study of precision viticulture from Margaret River. Australian and New Zealand Grapegrower and Winemaker, 473(a), 84–87.

    Google Scholar 

  • Bramley, R. G. V., & Proffitt, A. P. B. (1999). Managing variability in viticultural production. Australian and New Zealand Grapegrower and Winemaker, 427, 11–16.

    Google Scholar 

  • Bramley, R. G. V., Trought, M. C. T., & Praat, J. P. (2011). Vineyard variability in Marlborough, New Zealand: Characterizing variation. Australian Journal of Grape and Wine Research, 17, 72–78.

    Article  Google Scholar 

  • Conde, C., Silva, P., Fontes, N., Dias, A. C. P., Tavares, R. M., Sousa, M. J., et al. (2007). Biochemical changes throughout grape berry development and fruit and wine quality. Food, 1, 1–22.

    Google Scholar 

  • Corwin, D. L., & Plant, R. E. (2005). Editorial: Applications of apparent soil electrical conductivity in precision agriculture. Computers and Electronics in Agriculture, 46, 1–10.

    Article  Google Scholar 

  • Dobermann, A., Ping, J. L., Adamchuk, V. I., Simbahan, G. C., & Ferguson, R. B. (2003). Classification of crop yield variability in irrigated production fields. Agronomy Journal, 95, 1105–1120.

    Article  Google Scholar 

  • Dokoozlian, N., & Kliewer, M. W. (1995). The light environment within grapevine canopies. I. Description and seasonal changes during fruit development. American Journal of Enology and Viticulture, 46, 209–218.

    Google Scholar 

  • Duteau, J. (1990). Relations entre l’état de maturité des raisins (Merlot noir) et un indice climatique. Utilisation pour fixer la date des vendanges en année faiblement humide dans les crus de Bordelais. In P. Ribereau-Gayon & A. Lonvaud (Eds.), Actualités œnologiques 89 (pp. 7–12). Paris: Dunod.

  • El Nahry, A. H., Ali, R. R., & El Baroudy, A. A. (2011). An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques. Agricultural Water Management, 98, 517–531.

    Article  Google Scholar 

  • Fraisse, C. W., Sudduth, K. A., & Kitchen, N. R. (2001). Delineation of site-specific management zones by unsupervised classification of topographic attributes and soil electrical conductivity. Transactions of the ASAE, 44(1), 155–166.

    Google Scholar 

  • Fridgen, J. J., Kitchen, N. R., Sudduth, K. A., Drummond, S. T., Wiebold, W. J., & Fraisse, C. W. (2004). Management zone analyst (MZA): Software for subfield management zone delineation. Agronomy Journal, 96, 100–108.

    Article  Google Scholar 

  • Guastaferro, F., Castrignano, A., De Benedetto, D., Sollitto, D., Troccoli, A., & Cafarelli, B. (2010). A comparison of different algorithms for the delineation of management zones. Precision Agriculture, 11, 600–620.

    Article  Google Scholar 

  • 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 

  • 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 

  • He, Y., Guo, X., & Wilmshurst, J. (2006). Studying mixed grassland ecosystems I: suitable hyperspectral vegetation indices. Canadian Journal of Remote Sensing, 32, 98–107.

    Article  Google Scholar 

  • 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 

  • Kazmierski, M., Glemas, P., Rousseau, J., & Tisseyre, B. (2011). Temporal stability of within field patterns of NDVI in non irrigated Mediterranean vineyards. Journal International des Sciences de la Vigne et du Vin, 45, 61–73.

    Google Scholar 

  • Kitchen, N. R., Sudduth, K. A., Myers, D. B., Drummond, S. T., & Hong, S. Y. (2005). Delineating productivity zones on claypan soil fields apparent soil electrical conductivity. Computers and Electronics in Agriculture, 46, 285–308.

    Article  Google Scholar 

  • Koundouras, S., Marinos, V., Gkoulioti, A., Kotseridis, Y., & Van Leeuwen, C. (2006). Influence of vineyard location and vine water status on fruit maturation of nonirrigated cv. Agiorgitiko (Vitis vinifera L.). Effects on wine phenolic and aroma components. Journal of Agricultural and Food Chemistry, 54, 5077–5086.

    Article  PubMed  CAS  Google Scholar 

  • Kuhn, J., Brenning, A., Wehrhan, M., Koszinski, S., & Sommer, M. (2009). Interpretation of electrical conductivity patterns by soil properties and geological maps for precision agriculture. Precision Agriculture, 10, 490–507.

    Article  Google Scholar 

  • Kyaw, T., Ferguson, R. B., Adamchuk, V. I., Marx, D. B., Tarkalson, D. D., & McCallister, D. L. (2008). Delineating site-specific management zones for pH-induced iron chlorosis. Precision Agriculture, 9, 71–84.

    Article  Google Scholar 

  • Lamb, D. W., Weedon, M. M., & Bramley, R. G. V. (2004). Using remote sensing to predict phenolics and colour at harvest in a Cabernet Sauvignon vineyard: Timing observations against vine phenology and optimising image resolution. Australian Journal of Grape and Wine Research, 10, 46–54.

    Article  CAS  Google Scholar 

  • Lark, R. M., & Stafford, J. V. (1997). Classification as a first step in the interpretation of temporal and spatial variation of crop yield. Annals of Applied Biology, 130, 111–121.

    Article  Google Scholar 

  • Liu, J., Pattey, E., Nolin, M. C., Miller, J. R., & Ka, O. (2008). Mapping within-field soil drainage using remote sensing. DEM and apparent soil electrical conductivity. Geoderma, 143, 261–272.

    Article  Google Scholar 

  • McCutcheon, M. C., Farahani, H. J., Stednick, J. D., Buchleiter, G. W., & Green, T. R. (2006). Effect of soil water on apparent soil electrical conductivity and texture relationships in a dryland field. Biosystems Engineering, 94(1), 19–32.

    Article  Google Scholar 

  • Molin, J. P., & Castro, C. N. (2008). Establishing management zones using soil electrical conductivity and other soil properties by the fuzzy clustering technique. Scientia Agricola, 65(6), 567–573.

    Article  CAS  Google Scholar 

  • Moral, F. J., Terrón, J. M., & Marques da Silva, J. R. (2010). Delineation of management zones using mobile measurements of soil apparent electrical conductivity and multivariate geostatistical techniques. Soil and Tillage Research, 106(2), 335–343.

    Article  Google Scholar 

  • Odeh, I. O. A., McBratney, A. B., & Chittleborough, D. J. (1992). Soil pattern recognition with fuzzy-c-means: Application to classification and soil–landform interrelationships. Soil Science Society of America Journal, 56, 505–516.

    Article  Google Scholar 

  • Ortega, R. A., Esser, A., & Santibanez, O. (2003). Spatial variability of wine grape yield and quality in Chilean vineyards: economic and environmental impacts. In J. V. Stafford & A. Werner (Eds.), Proceedings of the fourth European conference on precision agriculture (pp. 499–506). Wageningen: Wageningen Academic Publishers.

  • Ping, J. L., Green, C. J., Bronson, K. F., Zartman, R. E., & Dobermann, A. (2005). Delineating potential management zones for cotton based on yields and soil properties. Soil Science, 170(5), 371–385.

    Article  CAS  Google Scholar 

  • Schepers, A. R., Shanahan, J. F., Liebig, M. A., Schepers, J. S., Johnson, S. H., & Luchiari, A. (2004). Appropriateness of management zones for characterizing spatial variability of soil properties and irrigated corn yields across years. Agronomy Journal, 96, 195–203.

    Article  Google Scholar 

  • Shaner, D. L., Khosla, R., Brodahl, M. K., Buchleiter, G. W., & Farahani, H. J. (2008). How well does zone sampling based on soil electrical conductivity maps represent soil variability. Agronomy Journal, 100(5), 1472–1480.

    Article  Google Scholar 

  • Sheets, K. R., & Hendrickx, J. M. H. (1995). Noninvasive soil water content measurement using electromagnetic induction. Water Resources Research, 31(10), 2401–2409.

    Article  Google Scholar 

  • Smart, R. E. (1974). Photosynthesis by grapevine canopies. Journal of Applied Ecology, 11, 997–1006.

    Article  Google Scholar 

  • 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 

  • 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 

  • Sudduth, K. A., Drummond, S. T., & Kitchen, N. R. (2001). Accuracy issues in electromagnetic induction sensing of soil electrical conductivity for precision agriculture. Computers and Electronics in Agriculture, 31, 239–264.

    Article  Google Scholar 

  • Tagarakis, A., Liakos, V., Fountas, S., Koundouras, S., Aggelopoulou, K., & Gemtos, T. (2011). Management zones delineation using fuzzy clustering techniques in vines. In J. V. Stafford (Ed.), Proceedings of the 8th European conference on precision agriculture (pp.191–200). Wageningen: Wageningen Academic Publishers.

  • Tagarakis, A., Xatzinikos, A., Fountas, S., & Gemtos, T. (2006). Delineation of management zones in precision viticulture. In N. Dalezios, M. Salampasis, & S. Tzortzios (Eds.), Proceedings of the international conference HAICTA (information systems in sustainable agriculture, agroenvironment and food technology) (pp. 547–554). Greece: Volos.

    Google Scholar 

  • 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 

  • Tisseyre, B., Mazzoni, C., Ardoin, N., & Clipet, C. (2001). Yield and harvest quality measurement in precision viticulture—Application for a selective vintage. In G. Grenier & S. Blackmore (Eds.), Proceedings of the third European conference on precision agriculture (pp.133–138).

  • Tisseyre, B., Mazzoni, C., & Fonta, H. (2008). Within-field temporal stability of some parameters in viticulture: Potential toward a site specific management. Journal International des Sciences de la Vigne et du Vin, 42, 27–39.

    Google Scholar 

  • Vanden Heuvel, J. E., Leonardos, E. D., Proctor, J. T. A., Fisher, K. H., & Sullivan, J. A. (2002). Translocation and partitioning patterns of 14C photoassimilate from light- and shade- adapted shoots in greenhouse-grown ‘Chardonnay’ grapevines (Vitis vinifera L.). Journal of the American Society for Horticultural Science, 127, 912–918.

    Google Scholar 

  • Vina, A., Gitelson, A. A., Rundquist, D. C., Keydan, G., Leavitt, B., & Schepers, J. S. (2004). Monitoring maize (Zea mays L.) phenology with remote sensing. Agronomy Journal, 96, 1139–1147.

    Article  Google Scholar 

  • Wample, R. L., Mills, L., & Davenport, J. R. (1999). Use of precision farming practices in grape production. In P. Robert, R. H. Rust & W. E. Larson (Eds.), Proceedings of the IV international conference on precision agriculture (pp. 897–905). Minneapolis.

  • Yan, L., Zhou, S., Cifang, W., Hongyi, L., & Feng, L. (2007). Classification of management zones for precision farming in saline soil based on multi-data sources to characterize spatial variability of soil properties. Transactions of the Chinese Society of Agricultural Engineering, 23(8), 84–89.

    Google Scholar 

  • Zhang, X., Shi, L., Jia, X., Seielstad, G., & Helgason, C. (2010). Zone mapping application for precision-farming: a decision support tool for variable rate application. Precision Agriculture, 11, 103–114.

    Article  CAS  Google Scholar 

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Acknowledgments

This research was partially supported by the European Union FP7 Project SIRRIMED “Sustainable use of irrigation water in the Mediterranean Region”. Grant agreement No.: 245159. The authors would also like to thank Mr. Demitrios Timblalexis, grape grower, for supporting the research and managing the experimental vineyard. The authors would like to express our gratitude to the anonymous reviewers and especially the editor for substantially improving the initially submitted manuscript.

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Correspondence to A. Tagarakis.

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Tagarakis, A., Liakos, V., Fountas, S. et al. Management zones delineation using fuzzy clustering techniques in grapevines. Precision Agric 14, 18–39 (2013). https://doi.org/10.1007/s11119-012-9275-4

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