Foliar symptoms of Esca as a sign of vine mortality: A binary logistic regression approach

Foliar symptoms of Esca as a signal of vine mortality: a binary logistic regression approach—the study aims to evaluate how temporal dynamics influence vine mortality in plants that have previously shown symptoms of Esca. Esca is a complex of trunk diseases caused by various wood-infecting fungi, including Phaeomoniella chlamydospore, Phaeoacremonium aleophilum, and Fomitiporia mediterranea. The situation with Esca disease in our country, every year
is variable and depends from variety, climate changes and conditions, and measurement for grapevine protection. For
this research, Vranec black grapevine variety was observed, at an experimental field in Smilica, Kavadarci, Republic of
North Macedonia. Our initial assumption was to monitor the progress of the Esca disease in vines that displayed
interveinal necrosis on their leaves. Due to the inconsistency and fluctuation of foliar symptoms at vines over several years, it is necessary to use a binary logistic regression analysis using IBM SPSS software to analyze and predict the percentage of vine deaths. A binary logistic regression model was chosen because the dependent variable distinguishes between chronic and acute forms of Esca disease, with values coded as 0 and 1. Esca disease is associated with the development of internal wood necroses, which are chronic and acute and discussed in the context of these findings.