UniPhen "PIWI" -high-resolution simulation of the phenological development of 13 fungus-tolerant cultivars based on broad observation data set from Central Europe

Due to their high potential for fungicide reduction, fungus-tolerant “PIWI” cultivars are increasingly gaining interest in European viticulture. This investigation aimed (i) to obtain phenological observation datasets of PIWI cultivars across a broad set of European locations, (ii) to apply the temperature sum based “UniPhen” model allowing for a precise simulation of the phenological development at all BCCH stages between bud swelling and berries ripe for harvest and (iii) to discuss the potential implementations in applied viticulture as well as in viticultural climate change impact research. Four consecutive years of complete data sets of phenological observations originating from eight locations in Central Europe for 13 PIWI and 3 traditional cultivars were used to apply the UniPhen model using a cumulative degree day approach with three temperature thresholds (lower threshold: 10 °C; upper threshold: 20 °C; heat threshold: 30 °C). Muscaris showed the thermal-temporally earliest budburst, while Solaris was earliest in beginning of flowering and harvest ripeness. The latest budburst and the latest beginning of flowering in PIWI cultivars were observed in Pinotin, while harvest ripeness was reached latest by Calardis blanc. The average normalised standard deviation (SD15 °C) over all stages, locations and cultivars was 5.5, corresponding to 5.5 days at 15 °C, with the lowest SD15 °C values around budburst and flowering stages. The highest SD15 °C values were observed in the bunch closure and post-veraison stages. UniPhen “PIWI” enables a precise simulation of all 31 BBCH stages between the beginning of the bud swell (01) and berries being ripe for harvest (89) for 13 fungus-tolerant cultivars and can be extended to additional cultivars. The model can be applied (i) as a bioclimatic indicator describing the suitability of a location/region for the cultivation of specific cultivars under present and future climate conditions, (ii) for the simulation of cultivar-specific phases of highest susceptibility for fungal diseases and, indirectly, the timing of fungicide treatments as well as (iii) for the classification of the relative late frost risk depending on the thermal-temporal precocity of budburst. This knowledge helps to lower the barrier to growing PIWI cultivars and helps to pave the way for a more sustainable, climate change-resilient viticulture.