Skip to main content

Table 3 Results for the pre-symptomatic detection of Esca leaf symptoms

From: Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards

   VNIR SWIR
   2017 2018 2017 2018
Modeling CA (%) 62 ± 2 79 ± 2 74 ± 1 86 ± 2
TPR (%) 63 ± 2 83 ± 4 78 ± 5 87 ± 4
FPR (%) 35 ± 1 28 ± 3 32 ± 5 21 ± 4
Application per plant CA (%) 73 81 79 91
TPR (%) 69 100 75 100
FPR (%) 26 20 21 9
  1. For modeling, all pixels were evaluated not considering spatial scales. Developed models were then applied on plant scale using all leaves for majority voting
  2. CA  classification accuracy, TPR  true-positive rate, FPR false-positive rate.
\