|Ferguson, John -|
|Mills, Lynn -|
|Grove, Gary -|
|Keller, Markus -|
Submitted to: Annals Of Botany
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 26, 2010
Publication Date: August 1, 2011
Citation: Ferguson, J.C., Tarara, J.M., Mills, L.J., Grove, G.G., Keller, M. 2011. Dynamic thermal-time model of cold hardiness for dormant grapevine buds. Annals Of Botany. 107:389-396. Interpretive Summary: Winter injury costs grape growers in terms of frost protection measures, lost production, and labor for vineyard retraining. Accurate predictions of the cold-hardiness of dormant grapevines are important for growers to maximize the efficiency of their frost protection measures and minimize potential winter injury. Current methods of estimating cold-hardiness rely on weekly- or twice-weekly collection of samples from dormant grapevines followed by assessment with sophisticated freezer systems that are available only in scientific laboratories. We used a database of these laboratory-generated cold-hardiness values to correlate the cold-hardiness threshold of the dormant vines with air temperature in the vineyard during one, two, or three days prior to sample collection. A model was produced that can be posted to publicly-accessible agricultural weather networks for growers to obtain web-based, daily predictions of the low temperature at which they might expect their vineyards to suffer significant winter injury.
Technical Abstract: Grapevine (Vitis spp.) cold hardiness varies dynamically throughout the dormant season, primarily in response to changes in temperature. We describe development and possible uses of a discrete-dynamic model of bud cold hardiness for three Vitis genotypes. Iterative methods were used to optimize and evaluate model parameters by minimizing the root mean square error between observed and predicted bud hardiness, using up to 22 years of low-temperature exotherm data. Three grape cultivars were studied: Cabernet Sauvignon, Chardonnay (both V. vinifera), and Concord (V. labruscana). The model uses time steps of 1 d along with the measured daily mean air temperature to calculate the change in bud hardiness, which is then added to the hardiness from the previous day. Cultivar-dependent thermal time thresholds determine whether buds acclimate (gain hardiness) or de-acclimate (lose hardiness). The parameterized model predicted bud hardiness for Cabernet Sauvignon and Chardonnay with an r2 = 0.89 and for Concord with an r2 = 0.82. Thermal time thresholds and (de-)acclimation rates changed between the early and late dormant season and were cultivar-dependent but independent of each other. The timing of these changes also was unique for each cultivar. Concord achieved the greatest mid-winter hardiness but had the highest deacclimation rate, which resulted in rapid loss of hardiness in spring. Cabernet Sauvignon was least hardy, yet maintained its hardiness latest as a result of late transition to eco-dormancy, high threshold temperature required to induce deacclimation, and low deacclimation rate. We developed a robust model of grapevine bud cold hardiness that will aid in the anticipation of and response to potential injury from fluctuations in winter temperature and from extreme cold events. The model parameters that produce the best fit also permit insight into dynamic differences in hardiness among genotypes.