Disease monitoring in wheatthrough remotely sensed data

Perla Chávez-Dulanto1

Pawan K. Singh1

Christian Yarlequé2

Matthew P. Reynolds1

1CIMMYT, Mexico2CIP, Peru

p.chavez@cgiar.org

Justification

Conventional visual fieldmonitoring: stress is detectedafter significant damage hasoccurred and yield reduced.

Pests and diseases pressureincreased due to climatechange.

Disease monitoring through remotely sensed data

Stresses can be detected before symptomsdevelopment

Early disease monitoring through remotely sensed data

Approach and advantage

Reducing environmental risks andfootprint of farming by reducing useof agrichemicals.

Target application (local and extend)of pesticides.

Breeding purposes: identification ofresilient genotypes.

Non-destructive and large-scaleapplicable approach.

Boosting competitiveness throughmore efficient practices (e.g.improved management of inputs).

1) Ground-based assessment

2) Air-borne assessment

3) Space-borne assessment

SVI Name CalculationNDVI Normalized difference vegetation index (RNIR-Rred)/(RNIR+Rred)SRa Simple ratio R800/R680

NPQI Normalized pheophytinization index (R415-R435)/(R415+R435)PRI Photochemical reflectance index (R531-R570)/(R531+R570)WI1 Water index 1 R900/R970

WI2 Water index 2 R900/R950

Spectral vegetation indices (SVIs) calculated from the hyperspectral reflectance data of thewheat genotypes under study did not show reliable results

Early disease monitoring through hyperspectral remotely sensed data

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Wavelenght (nm)

Ref

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Blue Green Red NIR

Method 1 : Physiology and Statistics (Chavez et al., 2009)

Ref

lect

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(%) ∫f(x) dx

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Method 2 : Physics, Physiology and Statistics (Chavez et al., 2010)

Fractal dimensions and formalism of the time series hyperspectral data

Decision tree for classification of fungal disease severity of wheat with hyperspectral timeseries data

Three main diseases evaluated:

• Spot blotch → Agua Fria

• Tan spot → El Batán

• Septoria tritici blotch → Toluca

0.8 m wide

1 2 3

SEPTORIA TRITICI BLOTCH - TolucaGenotype AUDPC Index3m PhysioStat PhyStat AUDPC Index3m

Met1+Met2 Met1 Met2 Rank Rank

CROC_1/AE.SQUARROSA (205)//BORL95/3/2*MILAN131.07 I 0.47 I 25588 A 0.955 G 1 1

MURGA 139.71 H 0.49 H 30022 A 0.708 A 2 2

FINSI/METSO 218.93 G 0.54 G 23896 A 0.919 F 3 3

6B662 237.66 F 0.55 F 28227 A 0.858 D 4 4

GLENLEA 250.62 E 0.56 E 31360 A 0.748 B 5 5

CATBIRD 259.26 D 0.58 D 20345 A 1.024 H 6 6

ERIK 381.69 C 0.66 C 29257 A 0.87 E 7 8

ND-495 393.21 B 0.66 C 30350 A 0.83 C 8 7

HUIRIVIS #1 445.06 A 0.71 B 19691 A 1.048 I 9 9

KACHU #1 445.06 A 0.83 A 20036 A 1.187 J 10 10r 2 wi th AUDPC 1.00 0.95 0.35 0.52 0.99

SPOT BLOTCH - AguaFriaGenotype AUDPC Index3m Phys ioStat PhyStat AUDPC Index3m

Met1+Met2 Met1 Met2 Rank RankMURGA 58.23 J 0.62 I 23817 DE 2.59 C 1 1CHIRYA.3 60.08 I 0.62 I 21145 F 3.01 G 2 2CATBIRD 124.69 F 0.65 H 27001 AB 3.00 F 5 3CROC_1/AE.SQUARROSA (205)//BORL95/3/2*MILAN61.73 H 0.66 G 25151 CD 3.44 J 3 4KACHU #1 113.99 G 0.68 F 27988 A 3.19 I 4 5FINSI/METSO 133.54 E 0.69 E 22261 EF 2.67 D 6 6

HUIRIVIS #1 158.64 D 0.72 D 23880 DE 2.58 B 7 7

FRANCOLIN #1 231.69 C 0.73 C 26642 ABC 3.16 H 8 8

CIANO T 79 391.77 B 0.75 B 25325 BCD 2.91 E 9 9

SONALIKA 643.83 A 0.78 A 28389 A 2.42 A 10 10r 2 with AUDPC 1.00 0.85 0.53 0.46 0.96

Same level ofsensitivity like

AUDPC todiscriminatesusceptible/

resistantgenotypes

TAN SPOT - El BatanGenotype AUDPC Index3m Phys ioStat PhyStat AUDPC Index3m

Met1+Met2 Met1 Met2 Rank RankCROC_1/AE.SQUARROSA (205)//BORL95/3/2*MILAN115.23 J 0.66 H 34824 C 2.75 E 1 1MURGA 122.43 I 0.67 G 35934 B 2.57 H 2 26B662 270.78 H 0.68 F 28178 G 3.29 A 3 3CATBIRD 292.39 G 0.69 E 37926 A 2.27 I 4 4HUIRIVIS #1 325.51 F 0.70 D 30195 F 2.67 G 5 5FINSI/METSO 328.40 E 0.71 C 34093 D 3.17 B 6 7KACHU #1 335.60 D 0.70 D 31912 E 2.73 F 7 6ERIK 371.60 C 0.71 C 27127 H 2.73 F 8 8GLENLEA 427.78 B 0.76 B 23147 I 3.03 D 9 9ND-495 488.27 A 0.81 A 20738 J 3.09 C 10 10r 2 with AUDPC 1.00 0.89 0.77 0.37 0.99

Pictures from CIMMYT Toluca 06/09/2012

Healthy Diseased

Yellow Rust Detection:

Merging both methods: 94% matching with conventional visual monitoring.

Discrimination between susceptible and resistant cultivars: Resilience level amonggenotypes.

Early disease detection through hyperspectral remotely sensed data :Yellow rust pilot trial (isolines) – Chavez P., Yahyaoui A., Singh P.K. et al.

Fusarium Head Bligth (FHB) : El Batan (in progress)

Images from El Batan, 2013

Thanks for your attention