2011
DOI: 10.1127/0941-2948/2011/0247
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Must quality estimation based on climate data in the Upper Moselle region

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Cited by 5 publications
(2 citation statements)
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“…Alternatively, models relating macroclimate to local climate parameters are used to statistically downscale (Hewitson et al ., ) climate model outputs before applying models of the relationship between local climate and viticulture (Santos et al ., ). Statistical models have been applied to measure climate change impacts on yield (Santos et al ., ), grapevine pathogens (Francesca et al ., ; Calonnec et al ., ), and various measures of harvest quality from vintage ratings (Jones et al ., ; Moriondo et al ., ) and harvest prices (Webb et al ., ) to sugar content (Urhausen et al ., ; Neumann & Matzarakis, ) and other physicochemical properties of berries (Barnuud et al ., ). Dynamic, or process‐based, crop growth models have been widely used for measuring climate impacts on annual crops (Rötter & van de Geijn, ; Rosenzweig et al ., ) but have been less often applied to studies on viticulture. Dynamic models of grapevine growth range from growing season, field‐scale simulation models primarily used as decision‐support and forecasting tools, to functional models offering insight into specific plant physiological processes (Moriondo et al ., ). Several of the most widely used crop growth models have been applied to assess impacts of, and adaptation to, future climate projections.…”
Section: Measuring Climate Change Impacts On Viticulturementioning
confidence: 99%
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“…Alternatively, models relating macroclimate to local climate parameters are used to statistically downscale (Hewitson et al ., ) climate model outputs before applying models of the relationship between local climate and viticulture (Santos et al ., ). Statistical models have been applied to measure climate change impacts on yield (Santos et al ., ), grapevine pathogens (Francesca et al ., ; Calonnec et al ., ), and various measures of harvest quality from vintage ratings (Jones et al ., ; Moriondo et al ., ) and harvest prices (Webb et al ., ) to sugar content (Urhausen et al ., ; Neumann & Matzarakis, ) and other physicochemical properties of berries (Barnuud et al ., ). Dynamic, or process‐based, crop growth models have been widely used for measuring climate impacts on annual crops (Rötter & van de Geijn, ; Rosenzweig et al ., ) but have been less often applied to studies on viticulture. Dynamic models of grapevine growth range from growing season, field‐scale simulation models primarily used as decision‐support and forecasting tools, to functional models offering insight into specific plant physiological processes (Moriondo et al ., ). Several of the most widely used crop growth models have been applied to assess impacts of, and adaptation to, future climate projections.…”
Section: Measuring Climate Change Impacts On Viticulturementioning
confidence: 99%
“…Alternatively, models relating macroclimate to local climate parameters are used to statistically downscale (Hewitson et al, 2014) climate model outputs before applying models of the relationship between local climate and viticulture (Santos et al, 2011). Statistical models have been applied to measure climate change impacts on yield (Santos et al, 2011), grapevine pathogens (Francesca et al, 2006;Calonnec et al, 2008), and various measures of harvest quality from vintage ratings Moriondo et al, 2011) and harvest prices (Webb et al, 2008) to sugar content (Urhausen et al, 2011;Neumann & Matzarakis, 2014) and other physicochemical properties of berries (Barnuud et al, 2014). 3.…”
Section: Biophysical Modelling Approachesmentioning
confidence: 99%