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Assessment of the spatial variability of anthocyanins in grapes using a fluorescence sensor: relationships with vine vigour and yield

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Abstract

The use of new, rapid and non-invasive sensors in the field allows the collection of many observations which are necessary to assess the spatial variability of berry composition. The aim of this work was to study the spatial variability in anthocyanin content in grapes and to quantify its relationship with the vigour and yield in a commercial vineyard. The study was conducted in a Tempranillo (Vitis vinifera L.) vineyard (Navarra, Spain). A new, hand-held, non-destructive fluorescence-based proximal sensor was used for monitoring the anthocyanin content in grapes at veraison and harvest. Yield, vine vigour, spectral (normalized difference vegetation index and plant cell density) and chlorophyll (SPAD and simple chlorophyll fluorescence ratio) parameters were measured. Yield variability within the vineyard was the largest of all the parameters. Fluorescence-based anthocyanin indices were less variable at harvest than at veraison. The vigour parameters (main shoot length, total shoot length and shoot pruning weight) were positively correlated to yield; the chlorophyll and the spectral indices were negatively correlated with berry anthocyanin production. The correlations between vigour, yield and anthocyanin content in grapes varied substantially in time and space across the vineyard.

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Abbreviations

ANTH_RG:

Anthocyanin fluorescence index

FERARI:

Fluorescence excitation ratio anthocyanin relative index

MSL:

Main shoot length

NDVI:

Normalized difference vegetation index

PCD:

Plant cell density

SFR:

Simple chlorophyll fluorescence ratio

SPW:

Shoot pruning weight

TSL:

Total shoot length

References

  • Agati, G., Meyer, S., Matteini, P., & Cerovic, Z. G. (2007). Assessment of anthocyanins in grape (Vitis vinifera L.) berries using a non-invasive chlorophyll fluorescence method. Journal of Agriculture and Food Chemistry, 55, 1053–1061.

    Article  CAS  Google Scholar 

  • Arnó, J., Martínez-Casanovas, J., Ribes-Dasi, M., & Rosell, J. R. (2009). Review. Precision viticulture. Research topics, challenges and opportunities in site-specific vineyard management. Spanish Journal Agriculture Research, 7, 779–790.

    Google Scholar 

  • Baluja, J., Diago, M. P., Rocchi, L., Ochagavia, H., & Tardaguila, J. (2011). Using a fluorescence proximal sensor to study the spatial variability of grape phenols in a Tempranillo vineyard. In J. V. Stafford (Ed.), Proceedings of the 8th European Conference on Precision Agriculture (pp. 577–584). Prague: Czech University of Life Sciences.

    Google Scholar 

  • Ben Ghozlen, N., Cerovic, Z. G., Germain, C., Toutain, S., & Latouche, G. (2010a). Non-destructive optical monitoring of grape maturation by proximal sensing. Sensors, 10, 10040–10068.

    Article  PubMed  Google Scholar 

  • Ben Ghozlen, N., Moise, N., Latouche, G., Martninon, V., Mercier, L., Besancon, E., et al. (2010b). Assessment of grapevine maturity using a new portable sensor: Non-destructive quantification of anthocyanins. Journal International des Sciences de la Vigne et du Vin, 44, 1–8.

    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: Managing vineyard variability for improved quality outcomes. In A. G. Reynolds (Ed.), Managing wine quality (Vol. one, pp. 445–480)., Viticulture and wine quality Cambridge: Woodhead Publishing.

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  • Bramley, R. G. V., & Lamb, D. W. (2010). Making sense of vineyard variability in Australia. In R. Ortega & A. Esser (Eds.), Precision viticulture. Proceedings of an international symposium held as part of the IX Congreso Latinoamericano de Viticultura y Enologia (pp. 35–54). Santiago: Centro de Agricultura de Precisión, Pontificia Universidad Católica de Chile.

    Google Scholar 

  • Bramley, R. G. V., Le Moigne, M., Evain, S., Ouzman, J., Florin, L., Fadaili, E. M., et al. (2011a). On-the-go sensing of grape berry anthocyanins during commercial harvest: Development and prospect. Australian Journal of Grape and Wine Research, 17, 316–326.

    Article  CAS  Google Scholar 

  • Bramley, R. G. V., Ouzman, J., & Thornton, C. (2011b). Selective harvest is a feasible and profitable strategy even when grape and wine production is geared towards large fermentation volumes. Australian Journal of Grape and Wine Research, 17, 298–305.

    Article  CAS  Google Scholar 

  • Bramley, R. G. V., Trought, M. C. T., & Praat, J. P. (2011c). Vineyard variability in Marlborough, New Zealand: Characterizing variation in vineyard performance and options for the implementation of Precision Viticulture. Australian Journal of Grape and Wine Research, 17, 83–89.

    Google Scholar 

  • Cambardella, C. A., Moorman, T. B., Novak, J. M., Parkin, T. B., Karlen, D. L., Truko, R. F., et al. (1994). Field-scale variability of soil properties in central Iowa soils. Soil Science Society of America Journal, 58, 1501–1511.

    Article  Google Scholar 

  • Cerovic, Z. G., Goutouly, J. P., Hilbert, G., Destrac-Irvine, A., Martinon, V., & Moise, N. (2009). Mapping winegrape quality attributes using portable fluorescence-based sensors. In S. Best (Ed.), Frutic 09 (pp. 301–310). Conception, Chile: Progap INIA.

    Google Scholar 

  • Cerovic, Z. G., Moise, N., Agati, G., Latouche, G., Ben Ghozlen, N., & Meyer, S. (2008). New portable optical sensors for the assessment of winegrape phenolic maturity based on berry fluorescence. Journal of Food Composition and Analysis, 21, 650–654.

    Article  CAS  Google Scholar 

  • Cortell, J. M., Halbleib, M., Gallagher, A. V., Righetti, T., & Kennedy, J. A. (2005). Influence of vine vigor on grape (Vitis vinifera L. cv. Pinot Noir) and wine proanthocyanidins. Journal of Agriculture and Food Chemistry, 53, 5798–5808.

    Article  CAS  Google Scholar 

  • Cortell, J. M., Halbleib, M., Gallagher, A. V., Righetti, T., & Kennedy, J. A. (2007). Influence of vine vigor on grape (Vitis vinifera L. cv. Pinot Noir) anthocyanins. 1. Anthocyanin concentration and composition in fruit. Journal of Agriculture and Food Chemistry, 55, 6575–6584.

    Article  CAS  Google Scholar 

  • Dobrowski, S. Z., Ustin, S. L., & Wolpert, J. A. (2003). Grapevine dormant pruning weight prediction using remotely sensed data. Australian Journal of Grape and Wine Research, 9, 177–182.

    Article  Google Scholar 

  • Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Chichester: Wiley.

    Google Scholar 

  • Gitelson, A., Buschmann, C., & Lichtenthaler, H. K. (1999). The chlorophyll fluorescence ratio F735/F700 as an accurate measure of the chlorophyll content in plants. Remote Sensing of Environment, 69, 296–302.

    Article  Google Scholar 

  • Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113–129.

    Article  Google Scholar 

  • Gray, J. D., Gibson, R. J., Coombe, B. G., Illand, P. G., & Pattison, S. J. (1997). Assessment of winegrape quality value in the vineyard—Survey of cv. Shiraz from South Australian vineyards in 1992. Australian Journal of Grape and Wine Research, 3, 109–116.

    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 

  • Han, S., Evans, R. G., Schneider, S. M., & Rawlins, S. L. (1996). Spatial variability of soil properties on two center-pivot irrigated fields. In P. C. Robert, R. H. Rust, & W. E. Larson (Eds.), Proceedings of the Third International Conference on Precision Agriculture (pp. 97–106). Madison: American Society of Agronomy, Crop Science Society of America, Soil Science Society of America.

    Google Scholar 

  • Iland, P., Bruer, N., Edwards, G., Weeks, S., & Wilkes, E. (2004). Chemical analysis of grapes and wine: techniques and concepts. Campbelltown: Patrick Iland wine promotions.

    Google Scholar 

  • Johnson, L. F. (2003). Temporal stability of an NDVI-LAI relationship in a Napa Valley vineyard. Australian Journal of Grape and Wine Research, 9, 96–101.

    Article  Google Scholar 

  • Johnstone, R. S. (1999). Vineyard variability – is it important? In R. J. Blair, A. N. Sas, P. F. Hayes, & P. B. Hoj (Eds.), Proceedings of the Tenth Australian Wine Industry Technical Conference (pp. 113–115). Sydney: Australian Wine Industry Technical Conference.

    Google Scholar 

  • Kennedy, J. A. (2010). Wine colour. In A. G. Reynolds (Ed.), Managing wine quality (Vol. one, pp. 73–104)., Viticulture and wine quality Cambridge: Woodhead Publishing.

    Chapter  Google Scholar 

  • Krstic, M., Moulds, G., Panagiopoulos, B., & West, S. (2003). Growing quality grapes to winery specifications: Quality measurement and management options for grape-growers. Adelaide: Winetitles.

    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 

  • Le Moigne, M., Florin, L., Rigaud, S., & Cerovic, Z. G. (2010). Anthocyanin assessment at grape reception in a winery using a fluorescence optical remote sensor. In: Macrowine 2010: Third International Symposium on macromolecules and secondary metabolites of grapevine and wine. (pp. 85). Torino, Italy.

  • Martinez-Casasnovas, J. A., & 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.

    Google Scholar 

  • Minasny, B., McBratney, A. B., & Whelan, B. M. (2005). VESPER version 1.62. Australian Centre for Precision Agriculture. http://www.usyd.edu.au/su/agric/acpa. Accessed 1 Dec 2011.

  • Panten, K., Bramley, R. G. V., Lark, R. M., & Bishop, T. F. A. (2010). Enhancing the value of field experimentation through whole-of-block designs. Precision Agriculture, 11, 198–213.

    Article  Google Scholar 

  • Proffit, T., Bramley, R. G. V., Lamb, D., & Winter, E. (2006). Precision Viticulture. A new era in vineyard management and wine production. Adelaide: Winetitles.

    Google Scholar 

  • Reynolds, A. G. (2010). Viticultural and vineyard management practices and their effects on grape and wine quality. In A. G. Reynolds (Ed.), Managing wine quality (Vol. one, pp. 365–444)., Viticulture and wine quality Cambridge: Woodhead Publishing.

    Chapter  Google Scholar 

  • Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W., & Harlan, J. C. (1974). Monitoring the vernal advancement and retrogradation (greenwave effect) of natural vegetation. III Final Report. Greenbelt: Texas A & M University.

    Google Scholar 

  • Saint-Cricq de Gaulejac, N., Vivas, N., & Glories, Y. (1998). Maturation phénolique: définition et contrôle. Revue Française d’enologie, 173, 22–25.

    CAS  Google Scholar 

  • Smart, R., & Robinson, M. (1991). Sunlight into the vine. A handbook for winegrape canopy management. Adelaide: Winetitles.

    Google Scholar 

  • Tardaguila, J., Baluja, J., Arpon, L., Balda, P., & Oliveira, M. T. (2011). Variations of soil properties affect the vegetative growth and yield components of Tempranillo grapevines. Precision Agriculture, 12, 762–773.

    Article  Google Scholar 

  • Tardaguila, J., & Martínez de Toda, F. (2008). Assessment of Tempranillo grapes quality in the vineyard by vitur score-sheet. Journal International des Sciences de la Vigne et du Vin, 42, 59–65.

    Google Scholar 

  • 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 

  • Trought, M. C. T., & Bramley, R. G. V. (2011). Vineyard variability in Marlborough, New Zealand: Characterising spatial and temporal changes in fruit composition and juice quality in the vineyard. Australian Journal of Grape and Wine Research, 17, 72–81.

    Article  Google Scholar 

  • Trought, M. C. T., Dixon, R., Mills, T., Greven, M., Agnew, R., Mauk, J. L., et al. (2008). The impact of differences in soil texture within a vineyard on vine vigour, vine earliness and juice composition. Journal International des Sciences de la Vigne et du Vin, 42, 67–72.

    CAS  Google Scholar 

  • Webster, R., & Oliver, M. A. (2007). Geostatistics for environmental scientists. Chichester: Wiley.

    Book  Google Scholar 

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Acknowledgments

We would like to thank Bodegas Pago de Larrainzar for their help in the field measurements and for the grapes supply. This work was jointly funded by Force-A and the University of La Rioja. Special gratefulness to Dr. Zoran Cerovic for his comments and suggestions.

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Authors and Affiliations

  1. Instituto de Ciencias de la Vid y del Vino, University of La Rioja, CSIC, Gobierno de La Rioja, 26006, Logroño, Spain

    J. Baluja, M. P. Diago & J. Tardaguila

  2. BioMedware, Inc., 3526W Liberty, Suite 100, Ann Arbor, MI, 48103, USA

    P. Goovaerts

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  1. J. Baluja
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  2. M. P. Diago
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  3. P. Goovaerts
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  4. J. Tardaguila
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Correspondence to J. Tardaguila.

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Baluja, J., Diago, M.P., Goovaerts, P. et al. Assessment of the spatial variability of anthocyanins in grapes using a fluorescence sensor: relationships with vine vigour and yield. Precision Agric 13, 457–472 (2012). https://doi.org/10.1007/s11119-012-9261-x

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