Skip to main content

Table 1 HTPP features selected through recursive feature elimination to predict YR Features marked in bold are unique to the timepoint

From: Predicting yellow rust in wheat breeding trials by proximal phenotyping and machine learning

Model trained on data collected on 2020-07-02

Model trained on data collected on 2020-07-09

Model feature

Average rank across all resamples

Standard deviation

Model feature

Average rank across all resamples

Standard deviation

PSRI

3.10

2.62

RGI

1.40

0.81

PRI2

3.27

2.35

GI

3.40

3.17

SIPI3

4.63

3.36

PSRI

4.87

2.76

PRI

5.43

4.12

NRI

5.87

4.12

REP_LE

5.53

3.34

Boochs2

6.87

2.49

RGI

5.77

1.89

DPI

7.00

4.17

BRI

10.77

4.44

REP_LE

8.63

4.12

SR9

14.00

6.72

SR10

10.30

4.23

Vogelmann3

17.10

6.82

PRI

12.30

4.69

PRI norm

17.53

9.55

PRI2

13.10

5.36

LRDSI2

18.87

10.83

Datt5

13.27

10.05

PRI (YR Zheng)

20.97

10.97

DWSI4

14.60

8.32

DD

22.07

16.16

CI

15.03

8.93

DPI

22.27

9.50

Vogelmann3

15.40

5.20

ARI

22.57

5.85

SPVI

17.07

8.66

mSR705

22.93

12.24

ARI2

19.43

6.52

SIPI2

25.63

14.27

PRI (YR Zheng)

20.07

6.76

mND705

25.67

14.20

Boochs

20.57

8.70

MTCI

25.77

15.49

NDVI3

21.43

9.62

SR7

26.77

15.03

PRI_norm

22.30

5.07

D1

27.23

12.15

NPQI

22.77

9.13

mSR

27.77

19.16

SR5

25.13

9.02

NIR Camera BNDVI

29.20

11.86

Carter5

28.33

10.49

mNDVI

31.27

15.72

RGB_Biomass

29.23

9.48

MSAVI

31.63

19.99

DD

30.43

16.17

SR8

32.23

13.74

EVI

32.97

10.13

SIPI

32.27

16.97

MCARI2

33.43

13.59

PhRI

32.30

12.07

NPCI

35.50

12.56

BGI

32.73

12.66

DDn

35.67

10.10

NDVI3

32.97

17.46

SRPI

35.67

11.28

OSAVI

33.13

15.26

ClAInt

36.07

13.96

ARI2

33.67

11.50

Sum_Dr2

36.17

15.92

DWSI4

33.80

17.01

Gitelson

36.63

11.03

mREIP

34.27

10.68

SIPI2

37.17

15.58

CI

36.47

12.66

mREIP

38.23

8.80

REP_Li

36.67

11.06

Datt3

38.47

13.72

MCARI2_OSAVI2

37.67

19.27

SR8

38.57

8.62

SAVI

38.07

15.66

mSR

38.60

16.38

Carter

38.17

13.72

SR9

38.87

11.15

SR10

38.47

13.58

MCARI2_OSAVI2

39.07

12.98

Gitelson

38.70

14.70

   

NPCI

39.60

14.79

   
  1. Variable names highlighted in bold letters denote predictors unqiuely selected through feature elimination at that timepoint