EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 35 / No 1 (2020) Ciência Téc. Vitiv., 35 1 (2020) 16-29 References
Open Access
Issue
Ciência Téc. Vitiv.
Volume 35, Number 1, 2020
Page(s) 16 - 29
DOI https://doi.org/10.1051/ctv/20203501016
Published online 08 June 2020
  • Allen R., 2015. Reference evapotranspiration calculator (Ref-ET). Available at: http://extension.uidaho.edu/kimberly/2013/04/ref-etreference-evapotranspiration-calculator/ (accessed on 2.06.2017). [Google Scholar]
  • Bindi M., Fibbi L., Gozzini B., Orlandini S., Miglietta F., 1996. Modelling the impact of future climate scenarios on yield and yield variability of grapevine. Clim. Res., 7, 213–224. [CrossRef] [Google Scholar]
  • Bisson L.F., Waterhouse A.L., Ebeler S.E., Walker M.A., Lapsley J.T., 2002. The present and future of the international wine industry. Nature, 418, 696–669. [PubMed] [Google Scholar]
  • Bock A., Sparks T.H., Estrella N., Menzel A., 2013. Climateinduced changes in grapevine yield and must sugar content in Franconia (Germany) between 1805 and 2010. PloS one, 8, e69015. [CrossRef] [PubMed] [Google Scholar]
  • Bonnefoy C., Quenol H., Bonnardot V., Barbeau G., Madelin M., Planchon O., Neethling E., 2013. Temporal and spatial analyses of temperature in a French wine-producing area: the Loire Valley. Int. J. Climatol., 33, 1849–1862. [Google Scholar]
  • Cardell M.F., Amengual A., Romero R., 2019. Future effects of climate change on the suitability of wine grape production across Europe. Reg. Environ. Change, 19, 2299–2310. [Google Scholar]
  • Clingeleffer P., Dunn G., Krstic M., Martin S., 2001. Crop development, crop estimation and crop control to secure quality and production of major wine grape varieties: A national approach. Technical report, Australian Grape and Wine Authority. CSH 96/1, 136. [Google Scholar]
  • Cola G., Mariani L., Salinari F., Civardi S., Bernizzoni F., Gatti M., Poni S., 2014. Description and testing of a weather-based model for predicting phenology, canopy development and source-sink balance in Vitis vinifera L. cv. Barbera. Agric. For. Meteorol., 184, 117–136. [Google Scholar]
  • Cunha M., Abreu I., Pinto P., Castro R., 2003. Airborne pollen samples for early-season estimates of wine production in a Mediterranean climate of Northern Portugal. Am J. Enol. Vitic., 54, 189–194. [Google Scholar]
  • Cunha M., Marçal A.R.S., Silva L., 2010. Very early prediction of wine yield based on satellite data from vegetation. Int. J. Remote Sens., 31, 3125–3142. [Google Scholar]
  • Cunha M., Ribeiro H., Abreu I., 2016. Pollen-based predictive modelling of wine production: application to an arid region. Eur. J. Agron., 73, 42–54. [Google Scholar]
  • Cunha M., Richter C., 2012. Measuring the impact of temperature changes on the wine production in the Douro Region using the short time Fourier transform. Int. J. Biometeorol., 56, 357–370. [CrossRef] [PubMed] [Google Scholar]
  • Cunha M., Richter C., 2014. A time-frequency analysis on the impact of climate variability on semi-natural mountain meadows. IEEE Trans. Geosci. Remote Sensing, 52, 6156–6164. [CrossRef] [Google Scholar]
  • Cunha M., Richter C., 2016. The impact of climate change on the winegrape vineyards of the Portuguese Douro region. Clim. Change, 138, 239–251. [Google Scholar]
  • CVRVV, 2018. Dados estatísticos sobre a produção de vinho na Região dos Vinhos Verdes. Comissão de Viticultura da Região dos Vinhos Verdes. Available at: http://portal.vinhoverde.pt/pt/estatisticas (accessed on 9.12.2018). [Google Scholar]
  • Esteves M.A., Orgaz M.D.M., 2001. The influence of climatic variability on the quality of wine. Int. J. Biometeorol., 45, 13–21. [CrossRef] [PubMed] [Google Scholar]
  • EU-CMO, 2019. Common market organisation (CMO), the wine market. Available at: https://ec.europa.eu/agriculture/wine_en (accessed on 17.05.2019). [Google Scholar]
  • Fraga H., Malheiro A.C., Moutinho-Pereira J., Santos J.A., 2014. Climate factors driving wine production in the Portuguese Minho region. Agric. For. Meteorol., 185, 26–36. [Google Scholar]
  • Fraga H., Santos J.A., 2017. Daily prediction of seasonal grapevine production in the Douro wine region based on favourable meteorological conditions. Aust. J. Grape Wine Res., 23, 296–304. [Google Scholar]
  • Fraga H., Santos J.A., Malheiro A.C., Oliveira A.A., Moutinho-Pereira J., Jones G.V., 2016. Climatic suitability of Portuguese grapevine varieties and climate change adaptation. Int. J. Climatol., 36, 1–12. [Google Scholar]
  • Giorgi F., Lionello P., 2008. Climate change projections for the Mediterranean region. Glob. Planet Change, 63, 90–104. [CrossRef] [Google Scholar]
  • Gouriéroux C., Holly A., Monfort A., 1982. Likelihood ratio test, Wald Test, and Kuhn-Tucker test in linear models with inequality constraints on the regression parameters. Econometrica, 50, 63–80. [Google Scholar]
  • Gouveia C., Liberato M.L.R., Da Câmara C.C., Trigo R.M., Ramos M., 2011. Modelling past and future wine production in the Portuguese Douro Valley. Clim. Res., 48, 349–362. [CrossRef] [Google Scholar]
  • Guilpart N., Metay A., Gary C., 2014. Grapevine bud fertility and number of berries per bunch are determined by water and nitrogen stress around flowering in the previous year. Eur. J. Agron., 54, 9–20. [Google Scholar]
  • Hannah L., Roehrdanz P.R., Ikegami M., Shepard A.V., Shaw M.R., Tabor G., Zhi L., Marquet P.A., Hijmans R.J., 2013. Climate change, wine, and conservation. PNAS, 110, 6907–6912. [CrossRef] [Google Scholar]
  • Hargreaves G., Samani Z., 1985. Reference crop evapotranspiration from temperature. Appl. Eng. Agric., 1, 96–99. [Google Scholar]
  • Hughes A.H., Richter C., 2003a. Learning and monetary policy in a spectral analysis representation. computational intelligence in economics and finance. In: Computational Intelligence in Economics and Finance. 91–103. Wang P., Chen. S.-H. (eds.). Springer Verlag, Berlin. [Google Scholar]
  • Hughes A.H., Richter C., 2006. Measuring the degree of convergence among European business cycles. Comput. Econ., 27, 229–259. [CrossRef] [Google Scholar]
  • IPCC, 2007. Climate change (2007). Fourth assessment report of the intergovernmental panel on climate change. 939 p. Cambridge University Press, New York. [Google Scholar]
  • IVDP, 2018. Dados estatísticos sobre a produção de vinho do Douro e Porto na Região Demarcada do Douro. Instituto dos Vinhos do Douro e Porto. Available at: http://www.ivdp.pt/statistics (accessed on 29.08.2018). [Google Scholar]
  • IVV, 2018. Dados estatísticos sobre a produção de vinho em Portugal. Instituto da Vinha e do Vinho. Available at: http://portal.vinhoverde.pt/pt/estatisticas (accessed on 9.12.2018). [Google Scholar]
  • Johnson L., Pierce L., Michaelis A., Scholasch T., Nemani, R., 2006. Remote sensing and water balance modeling in California drip-irrigated vineyards. In: ASCE World Environmental & Water Resources. Omaha, Nebraska, United States. [Google Scholar]
  • Jones G.V., 2007. Climate Changes and the global wine industry. In: 13th Australian wine industry technical Conference. Adelaide, Australia. [Google Scholar]
  • Jones G.V., 2012. A climate assessment for the Douro wine region: an examination of the past, present, and future climate conditions for wine production. Associação para o Desenvolvimento da Viticultura Duriense, 67. Available at: http://www.advid.pt/imagens/outros/1368437718350.pdf (accessed on 21.08.2017). [Google Scholar]
  • Jones G.V., Davis R.E., 2000. Climate influences on grapevine phenology, grape composition, and wine production and quality for Bordeaux, France. Am J. Enol.Vitic., 51, 249–261. [Google Scholar]
  • Lobell D., Cahill K., Field., 2007. Historical effects of temperature and precipitation on California crop yields. Clim. Change, 81, 187–203. [Google Scholar]
  • Lorenzo M.N., Taboada J.J., Lorenzo J.F., Ramos A.M., 2013. Influence of climate on grape production and wine quality in the Rías Baixas, north-western Spain. Reg. Environ. Change, 13, 887–896. [Google Scholar]
  • Martins A., Mestre S., Gonçalves E., 1998. Estabilidade do rendimento de clones de videira (in portuguese). In: 4º Simpósio de Vitivinicultura do Alentejo, Évora, Portugal. [Google Scholar]
  • Maxwell J.T., Ficklin D.L., Harley G.L., Jones G.V., 2016. Projecting future winegrape yields using a combination of Vitis vinifera L. growth rings and soil moisture simulations, Northern California, USA. Aust. J. Grape Wine Res., 22, 73–80. [Google Scholar]
  • May P., 2004. Flowering and fruitset in grapevines. Lythrum Press, Adelaide. [Google Scholar]
  • Maybeck P., 1979. Stochastic models, estimation, and control. Vol 1, 424 p. Academic Press, New York. [Google Scholar]
  • Moriondo M., Jones G.V., Bois B., Dibari C., Ferrise R., Trombi G., Bindi M., 2013. Projected shifts of wine regions in response to climate change. Clim. Change, 119, 825–839. [Google Scholar]
  • Mosedale J.R., Abernethy K.E., Smart R.E., Wilson R.J., Maclean I.M.D., 2016. Climate change impacts and adaptive strategies: lessons from the grapevine. Globl Change Biol., 22, 3814–3828. [CrossRef] [PubMed] [Google Scholar]
  • Peterson T.C., Easterling D.R., Karl T.R., Groisman P., Nicholls N., Plummer N., Torok S., Auer I., Boehm R., Gullett D., Vincent L., Heino R., Tuomenvirta H., Mestre O., Szentimrey T., Salinger J., Førland E.J., Hanssen-Bauer I., Alexandersson H., Jones P., Parker D., 1998. Homogeneity adjustments of in situ atmospheric climate data: a review. Int. J. Climatol., 18, 1493–1517. [Google Scholar]
  • Pierce L., Nemani R., Johnson L., 2015. VSIM - Vineyard Soil Irrigation Model – release 3/1/06 - User Guide. Available at: http://geo.arc.nasa.gov/sge/vintage/vsim_050103_guide.pdf (assessed on 29.01.2015). [Google Scholar]
  • Ploberger W., Krämer W., Kontrus K., 1989. A new test for structural stability in the linear regression model. J. Econom., 40, 307–318. [Google Scholar]
  • Quiroga S., Iglesias A., 2009. A comparison of the climate risks of cereal, citrus, grapevine and olive production in Spain. Agric.Syst., 101, 91–100. [CrossRef] [Google Scholar]
  • Ramakrishna R.N., Michael A.W., Daniel R.C., Gregory V.J., Steven W.R., Joseph C.C., David L.P., 2001. Asymmetric warming over coastal California and its impact on the premium wine industry. Clim. Res., 19, 25–34. [CrossRef] [EDP Sciences] [Google Scholar]
  • Reis M.P., Ribeiro H., Abreu I., Eiras-Dias J., Mota T., Cunha M., 2018. Predicting the flowering date of Portuguese grapevine varieties using temperature-based phenological models: a multi-site approach. J. Agric. Sci., 156, 865–876. [Google Scholar]
  • Santos J.A., Grätsch S.D., Karremann M.K., Jones G.V., Pinto J.G., 2013. Ensemble projections for wine production in the Douro Valley of Portugal. Clim. Change, 117, 211–225. [Google Scholar]
  • Santos J.A., Malheiro A.C., Karremann M.K., Pinto J.G., 2011. Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions. Int. J. Biometeorol., 55, 119–131 [CrossRef] [PubMed] [Google Scholar]
  • Teslić N., Vujadinović M., Ruml M., Ricci A., Vuković A., Parpinello G.P., Versari A., 2019. Future climatic suitability of the Emilia-Romagna (Italy) region for grape production. Reg. Environ. Change, 19, 599–614. [CrossRef] [Google Scholar]
  • Valdés-Gómez H., Gary C., Cartolaro P., Lolas-Caneo M., Calonnec A., 2011. Powdery mildew development is positively influenced by grapevine vegetative growth induced by different soil management strategies. Crop Prot., 30, 1168–1177. [Google Scholar]
  • Vasconcelos M.C., Greven M., Winefield C.S., Trought M.C.T., Raw V., 2009. The Flowering process of Vitis vinifera: A review. Am J. Enol.Vitic., 60, 411–434. [Google Scholar]
  • Wells C., 1996. The Kalman Filter in Finance. 171 p. Kluwer Academic Publishers, Dordrecht. [Google Scholar]
  • Ye T., Nie J., Wang J., Shi P., Wang Z., 2015. Performance of detrending models of crop yield risk assessment: evaluation on real and hypothetical yield data. Stoch. Environ. Res. and Risk Assess., 29, 109–117. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.