PT - JOURNAL ARTICLE AU - Zapata, Diana AU - Salazar-Gutierrez, Melba AU - Chaves, Bernardo AU - Keller, Markus AU - Hoogenboom, Gerrit TI - Predicting Key Phenological Stages for 17 Grapevine Cultivars (<em>Vitis vinifera</em> L.) AID - 10.5344/ajev.2016.15077 DP - 2017 Jan 01 TA - American Journal of Enology and Viticulture PG - 60--72 VI - 68 IP - 1 4099 - http://www.ajevonline.org/content/68/1/60.short 4100 - http://www.ajevonline.org/content/68/1/60.full SO - Am J Enol Vitic.2017 Jan 01; 68 AB - Weather conditions have a significant impact on crops, and temperature is one of the main factors that controls plant development. Thermal time models based on temperature have been applied to predict the development of many species. To implement these models, determination of an appropriate base temperature (Tb) is required to characterize the differences among developmental stages and cultivars. The goal of this study was to determine the unique Tb and degree-days (DD) to predict budbreak, bloom, and veraison for 17 cultivars. Tb’s were estimated with the minimum variance method using phenological data collected over 23 years in Prosser, WA. Tb increased throughout grapevine development and ranged from 6.1 to 8.4°C for budbreak, from 7.2 to 10.5°C for bloom, and from 9.4 to 12.8°C for veraison. Starting DD accumulation on 1 Jan and using the Tb’s estimated for each cultivar, the duration to budbreak ranged from 78 to 180 DD, from budbreak to bloom ranged from 240 to 372 DD, and from bloom to veraison ranged from 556 to 800 DD. Errors in prediction varied between 4.8 and 7.8 days to budbreak, between 1.9 and 5.5 days to bloom, and between 7.1 and 12.4 days to veraison. Based on the errors in prediction, models that used an estimated Tb specific for a phenological stage performed better than models that had a fixed Tb of 0 and 10°C. The estimated thermal time parameters provide a simple approach for characterizing differences among cultivars and assist growers and industry in implementing management practices through simple decision support tools based on thermal time models.