Modelling of weather parameters to predict russet on ‘Golden Delicious’ apple

Abstract

Russet on ‘Golden Delicious’ apple (Malus × domestica Borkh.) fruit is a physiological disorder that causes major economic losses to growers. Large variations occur in the severity of russet from one year to another. In Girona (Spain), good correlations were found between the annual severity of russet at harvest and several weather parameters measured shortly after full bloom. A specific statistical methodology for the analysis of compositional data (CoDa) was used to establish these correlations. The most important factor was the percentage of time at relative humidity values > 55% from 30 – 34 d after full bloom (DAFB), which yielded a high correlation (R = 0.80). The percentage of rainy days from 0 – 34 DAFB was also positively correlated with the severity of russet (R = 0.80). Ordinal logit regression models that included these two climatic variables strongly predicted a low, moderate, or high annual severity of russet. Understanding the effects of weather on russet, and developing predictive models may help to manage the marketing of this apple variety which is prone to russet in some areas of cultivation