Modeling Northern Highbush Blueberry Cold Hardiness for the Pacific Northwest

Abstract

Freezing temperatures in fall, winter, and spring can cause damage to multiple perennial fruit crops including northern highbush blueberry (Vaccinium corymbosum). Predictive modeling for lethal temperatures allows producers to make informed decisions about freeze mitigation practices but is lacking for northern highbush blueberry grown in the Pacific Northwest. If buds are hardier than air temperatures, unnecessary use of propane heaters and/or wind machines is costly. In contrast, use of heaters and/or wind machines during freezing, damaging temperatures can minimize crop damage and potential yield loss. The objective of this study was to model cold hardiness across multiple cultivars of northern highbush blueberry grown in various regions in Washington, USA, and to generate predictive cold hardiness models that producers in the Pacific Northwest could use to inform freeze mitigation. Multiple years of experimental cold hardiness data were collected on four cultivars of northern highbush blueberry grown in western and eastern Washington, USA. Freeze chambers were used to reduce bud temperatures systematically, after which buds were dissected and bud survival was assessed. A generalized linear mixed model with a binomial response and logit link was fit to each cultivar to characterize the relationship between bud survival, freezer temperature, recent air temperatures, and growing degree days from fall acclimation to late winter/spring deacclimation. Model simulation was performed to obtain marginal-scale lethal temperature estimates. Model error estimation was performed using cross validation. Results show cultivar-specific cold hardiness models can be generated, and model development and use can help growers make more informed decisions regarding freeze protection that also minimizes costly applications of freeze protection when unnecessary. Furthermore, such models can be adapted to other blueberry growing regions and cultivars experiencing similar climactic conditions.

Keywords

• bayesian
• control adjustment
• freeze damage
• generalized linear mixed model