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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.