Following up the development of wheat kernel by multispectral imaging

FOLLOWING UP THE DEVELOPMENT OF WHEAT KERNEL BY MULTISPECTRAL IMAGING B. JAILLAIS1 AND D. BERTRAND2 1. INRA

BIA, NANTES, FRANCE. 2. DATA_FRAME, NANTES, FRANCE.

1

Phenodays 2012

INRA AND DATA_FRAME INRA, CEPIA division BIA Unit

BIBS Platform

MS

Microscopy

CHEMOTYPING Analysis of polysaccharides Sophie Le Gall, Poster n째9

NMR

PHENO CHEM

PHENOTYPING Analysis of internal structure of seeds Phenodays 2012

Data_frame Consulting in Chemometrics 2

WHEN HARVESTING? • Wheat is mature • Kernel is well filled • Yellow color of kernel At the right time!

• Depends of area of cultivation, climate, cultivar…

New tool to characterise changes in wheat kernel!

Phenodays 2012

3

GREEN TO YELLOW SPIKE? Changes : •Grain growth •Molecular and morphological changes inside •Grain filling •Change of colour about 20 DAA •Accumulation of carotenoids •Far-red fluorescence from chlorophyll decreasing •Blue-green fluorescence from hydroxycinnamic acids decreasing

Phenodays 2012

4

ENDOSPERM DEVELOPMENT Phase 1 : Formation of the first endosperm nucleus Phase 2 : Cellularization of the layer of endosperm cells lining the embryo sac Phase 3 : Completion of meristemic activity Phase 4 : Attainment of maximum dry weight Phase 5 : Harvest ripeness Phase 1

Phase 2

Phase 3

Phase 4

Phase 5

Adapted from Evers (1970)

Embryo and endosperm increase in mass and volume (all phases) Parenchymatous pericarp degenerates from center to the outside (P2, P3) Endosperm enlargement (P2, P3) Accumulation of storage components (P4) Drying (P5) Phenodays 2012

5

OBJECTIVE • Application of multivariate imaging to study the state of physiological maturity of a wheat kernel HOW? • By using 8 wavelengths to characterise tissues • By obtaining RGB images for each wavelength • By merging all the RGB images for one sample • By processing pixel-vectors of spectral responses

Phenodays 2012

6

MATERIALS and METHODS

Phenodays 2012

7

SAMPLE COLLECTION • Cultivar : Récital • Grown under controlled conditions (INRA Rennes)

• 10 kernels per each development time • 14 Development times (in DAA) : 4

5

6

8

11

14

15

16

17

18

21

24

25

28

Phenodays 2012

8

SAMPLE PREPARATION Estimated time : 10 s

Phenodays 2012

9

MUWI (MUltiWay Imager) NIR 950 nm

CCD colour camera (+ cooling device)

NIR 875 nm

microscope

Red Green

Black box

Blue

4x 8-leds Blocks

UV 400 nm UV 370 nm

Sample

UV 360 nm

8 lightning conditions x 3 RGB channels = 24 image-plans for each sample

Phenodays 2012

10

EXPOSURE TIME VS WAVELENGTH • Exposure time required to obtain well-exposed images varies with wavelength • Imaging device requires the possibility to address different values of time • For the same aperture, needed time is : • About 7s for UV lights • Between 0.02 and 0.1 s for Visible lights • About 0.02s for infrared lights Estimated time : 30 s Phenodays 2012

11

IMAGES IN FALSE COLOURS IR875red

IR875gre

IR875blu

UV360re d

UV360gre

UV360blu

gre enred

gree ngre

gree nblu

re d re d

red gre

re d blu

UV400re d

UV400gre

UV400blu

IR950red

IR950gre

IR950blu

blue re d

blue gre

blue blu

UV370re d

UV370gre

UV370blu

Phenodays 2012

12

DATA PREPROCESSING Unfolded Image Cube

Image 位

z=24

p

IR 950 n

IR 875 Red

z

Green Blue p

UV 360 UV 370

Image Cube

n

UV 400 Unfolding of multivariate image : Each pixel is an individual caracterised by a vector of Phenodays 2012 24 intensities (i.e. spectral responses)

nxp

13

IMAGE PCA Unfolded Image Cube

Scores

z=24

Refolded Scores z=10

p PC1 n PC2

PCA

Refolding

PC3 PC4 PC5 PC6 PC7 PC8

nxp

nxp

Phenodays 2012

14

IMAGES FROM PCA Channe l #1

Channe l #2

50 100

50

PC1

100

150

150

200

200

250

250

300

300

350

350

400

400

450

450

500

500

100

200

300 400 Channe l #3

500

600

700

50 100

PC2

100

200

300 400 Channe l #4

500

600

700

200

300

500

600

700

50

PC3

100

150

150

200

200

250

250

300

300

350

350

400

400

450

450

500

500 100

200

300

400

500

600

700

Phenodays 2012

PC4

100

400

15

SEGMENTATION s e uil > 0

x 10

-4

4 X: 217 Y: 199 Inde x: 0.0002628 RGB: 1, 0.0625, 0

X: 530 Y: 204 Inde x: -7.801e -005 RGB: 1, 1, 0

2 0 -2 -4 -6

X: 300 Y: 430 Inde x: 0.0003858 RGB: 0.75, 0, 0

-8 -10

s euil > 0.0002

> « Red » pixels Estimated time : 2 mn

> « Yellow » pixels s euil > 0.0003

> « Dark red » pixels Phenodays 2012

16

RESULTS

Phenodays 2012

17

SEQUENCE of RGB IMAGES UV 360nm

5 DAA

6 DAA

8 DAA

15 DAA

18 DAA

28 DAA

Phenodays 2012

18

SEQUENCE of RGB IMAGES UV 400nm

5 DAA

6 DAA

8 DAA

15 DAA

18 DAA

28 DAA

Phenodays 2012

19

EVOLUTION OF PC1 SCORE-IMAGE

4 DAA

6 DAA

11 DAA

14 DAA

16 DAA

18 DAA

25 DAA

28 DAA

Phenodays 2012

20

THEORY/EXPERIMENT

Grain growth

Grain filling

Anthesis

Grain drying Days

4 DAA

6 DAA

11 DAA Phenodays 2012

21 DAA

28 DAA 21

EVOLUTION OF NUMBER OF PIXELS

Each point is the mean of the 10 kernels at the same time

Phenodays 2012

22

CONCLUSIONS

Phenodays 2012

23

CONCLUSIONS (1)

The MUWI system makes it possible to quantify the degree of maturity of wheat kernels.

4 DAA

6 DAA

11 DAA

14 DAA

16 DAA

Phenodays 2012

18 DAA

25 DAA

28 DAA

24

CONCLUSIONS (2) • Rapid (about 3 mn/sample), simple, robust, low-cost method • No need to human inspection • No limit for image processing only for sample presentation : bottleneck of phenotyping • It’s possible to increase the throughput of analysis by development of robot • Extraction of parameters (shape, colour, texture) from multispectral images is easy chemometrics processing Phenodays 2012

25

THANK YOU FOR YOUR ATTENTION !

AUTOMATE PHOTO

PhenoDays 2012

27