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“La spettroscopia di riflettanza risolta nel tempo (TRS): principi ed applicazioni”

Alessandro Torricelli

Winter School«Le tecniche spettroscopiche: strumenti innovativi applicati all’analisi dei settori

ambientale ed agro-alimentare –nuove sfide per il futuro»

28 January 2015, Milano

Politecnico di Milano (PoliMi)Teaching & Research University

PoliMi since 1863

1863 – 2013150 years

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150 years

EngineeringArchitectureDesign

Department of PhysicsPhotonics for Health, Food and Cultural Heritage

Head: Rinaldo CubedduStaff @PoliMi Antonio Pifferi

Paola TaroniAlessandro TorricelliGianluca ValentiniAndrea BassiDaniela ComelliCosimo D’AndreaDavide ContiniAlberto Dalla Mora

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Alberto Dalla Mora

Staff @ IFN-CNR Lorenzo SpinelliAustin NevinAndrea Farina

Post-Docs Ilaria BargigiaGiovanna QuartoRebecca ReMaristella VanoliLucia Zucchelli + PhD Students

+ Undergraduate Students+ Facilities (mechanic and electronic workshop)

Photonics for Health, Food and Cultural Heritage Research activities: overview

Health In vivo Tissue Spectroscopy Optical Mammography Tissue Oximetry and Functional Imaging of the Brain Fluorescence Lifetime Imaging in biology and medicine

Food nondestructive assessment of

internal defects by pulsed NIR

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Cultural Heritage Photoablation and Material Processing Fluorescence Spectroscopy and Imaging Multispectral Imaging and Colorimetry

internal defects by pulsed NIR nondestructive maturity

assessment at harvest

Photonics for Health, Food and Cultural Heritage Laboratories

Time-resolved systems mode-locking of dye, gas and solid state lasers time-correlated single-photon counting (TCSPC) time-gated imaging

Spectral-domain tunable laser sources broadband detectors

TEMPORAL⇒ fast!

SPECTRAL⇒ colored!

fNIRS Lab

NIRf Lab

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• functional near infrared spectroscopy - fNIRS Lab• diffuse spectroscopy - DiffS Lab• optical mammography - Mammot Lab• molecular imaging - Molim Lab• near infrared spectroscopy for food - NIRf Lab• imaging spectroscopy for cultural heritage - ARTIS Lab• ultras for biomedicine - UB Lab

Spatial-domain scanning systems or camera multi-channel systems

Temporal-domain fast acquisition rate

SPATIAL⇒ wide!

DiffS Lab

Mammot Lab

Fluo Lab

UB Lab

Molim Lab

ISCH Lab

Can light penetrate biological tissues?

Georges de La Tour (1593 – 1652)

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St Joseph, 1642, Louvre, Paris Thanks to Marco Ferrari (UnivAQ)

Light absorption in the NIRbiological tissue

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The therapeutic and diagnostic window

Light absorption in the NIRfruit

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Light propagation in diffusive media:absorption and scattering

clear diffusive

Scattering: related to tissue structure

Scattering coefficient:

Absorption: related to tissue components

Absorption coefficient:µa = 1/la (cm-1)

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Linout

aeII µ−=

Scattering coefficient:µs = 1/ls (cm-1)

( )Linout

saeII µµ +−=

interplay between absorption and scattering

Time-resolved Reflectance Spectroscopy (TRS)Basics

Intensity

Laser pulse

10-100 ps duration

Remitted pulse

log10I

µ’s

time

Effect of scattering

Changes in peak position!

Slope does not change

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µ’s , µa

ρtime (1-10 ns)

time

µa

time

log10IEffect of absorption

Changes in slopePeak position does not change

Conservation of energy in a small volume dV in a given direction Ω

(1) (3) (4) (5)

Light source

(2)

Radiative Transport Equation (RTE)

επ

+∫ )•′µ+µ−µ−∇•−=∂∂

4ssa dˆˆ(vvvˆv Ωnpnnn

t

nsss

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sPhotons outPhotons in

Photons scattered to another direction

Photons scattered from another direction (s’) to direction of interest (s)

dV

Light source

Photons absorbed

Radiative Transport Equation

Expansion methods

•PN approximation:

P0 = Diffusion Theory

P = Diffusing Wave

Stochastic methods

• Monte Carlo

Solutions of the RTE

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P1 = Diffusing Wave

P3 = …

Discretisation methods

• Discrete ordinates

• 2-flux or Kubelka-Munk

• Adding-double method

• Finite Element Method

Hybrid methods

• Paasschens (1997)

• Martelli (2008)

• Kienle (2011)

Infinite Semi-infinite

Slab Parallelepiped

Photon Diffusionsolutions for other geometries

2 layer

N layers

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Sphere Cylinder

F.Martelli et al. Photon migration through diffusive media:Theories and software (SPIE book, 2010)

inhomogeneity

Photon Diffusiontime-resolved reflectance

∑∞+

−∞=

−−

−×

−−

−=m

mm

mm

a

Dvt

zz

Dvt

zz

tDv

Dvtvt

tR4

exp4

exp)4(2

4exp

),(2

,4,4

2,3

,32/52/3

2

π

ρµρ

1.000laser pulseTRS datamodel

)=∂

)Φ∂+)Φµ+)Φ∇− tSt

tttD ,(

,(

v

1,(,( 0a

2 rr

rr

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0.001

0.010

0.100

0 1000 2000 3000 4000 5000

time (ps)

inte

nsity

(a.u

.)

µ’s , µa

ρ

Time Frequency

R(ρ,t)

t

R(ρ,ω)

t

ρ ρ

Time, Frequency, Space and Angle domain measurein diffusive media

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Time Frequency

AngleSpace

CW CWR(ρ)

ρ

R(θ)

θ

θρ

Laboratory set-up for broadband TRS

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Fully automated system

spectral range: 540 -1100 nm Pifferi et al., Review of Scientific Instrument 78, 053103 (2007)

Laboratory set-up for broadband TRS

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Fully automated system

spectral range: 540 -1100 nm Pifferi et al., Review of Scientific Instrument 78, 053103 (2007)

Optical characterisation of biological tissuesfemale breast

0,15

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0,25

0,30

abso

rptio

n co

effic

ient

(cm

-1)

HbO2 [43 uM]Hb [22 uM]Water [34%]Lipid [53%]

Σ= λελµ iicia

15

20

redu

ced

scat

terin

g (c

m-1

)

Empirical approximation to Mie theory

bcbnabxas −==≈

λλπµ r2'

Absorption spectrum and tissue constituents Scatteri ng spectrum and tissue structure

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0,00

0,05

0,10

0,15

600 650 700 750 800 850 900 950 1000

wavelength (nm)

abso

rptio

n co

effic

ient

(cm

Σ= λελµ iicia

Beer’s law

0

5

10

600 650 700 750 800 850 900 950 1000

wavelength (nm)re

duce

d sc

atte

ring

(cm

a ⇔ density of scatterers

b ⇔ equivalent size of scatterers

Breast Absorption spectra: Inter-subject variation

R3 PT-40 DC-29 EL-34 LT-23 FM-50 KE-31water 72% 48% 36% 31% 22% 12%lipids 5% 41% 35% 48% 66% 71%tHb/µM 15.3 25 11 20 16 15SO2 63% 75% 62% 73% 59% 81%

0.20

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0.40

abso

rptio

n (c

m-1

)

Fibrous Adipose

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0.00

0.05

0.10

0.15

0.20

600 650 700 750 800 850 900 950 1000 1050

wavelength (nm)

abso

rptio

n (c

m

BreastScattering spectra: Inter-subject variation

T PT-40 DC-29 EL-34 LT-23 FM-50 KE-31a 9.3 8.9 6.8 11.7 11.0 9.6b 2.0 1.4 2.0 0.7 0.7 0.7

15

20

25

redu

ced

scat

terin

g (c

m-1

)

µ’s = aλ-b

Density

Size

Fibrous Adipose

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0

5

10

600 650 700 750 800 850 900 950 1000 1050

wavelength (nm)

redu

ced

scat

terin

g (c

m

A.Pifferi et al., J. Biomed. Opt. 9:1143-1151, (2004)

Time-resolved optical mammograph

laser heads

905 nm

683 nm

785 nm

637 nm

driver

sync

coupler

930 nm

975 nm

1060 nm

variable attenuators

• Continuous movement:

• Laser driver: “Sepia” (PicoQuant)

• Repetition rate: 20 MHz

• Pulse duration: 180-400 ps

• Average incident power: 1-1.5 mW

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fiber bundle

AMP

TCSPC board

sync

NIR PMT

VIS PMT

sync

collimator

cut-off filter variable attenuators

optics

XY translation stage

personal computer

AMP

TCSPC board

• Continuous movement:stepping motors & Counter/Timer PC board

• Maximum scan area: 180 mm x 240 mm

• Step interval: 1 mm

• Measurement time: 25 ms per point

• Photomultipliers (Hamamatsu, KK):

VIS: R5900U-01-L16, 150 ps TTS, λ < 850 nm

NIR: H7422P-60, 450 ps TTS, λ < 1100 nm

• TCSPC board (SPC-134, Becker & Hickl):

4 independent channels

16 MHz max count rate

Optical MammographyOPTIMAMM Project FP5 (2000-2003)

Patient #47, oblique view

age: 36 ythickness = 5.7 cmLesion size = 3.0 cmLesion type = tumor

S02 tHb

R LR L

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52%-89% 17 - 91µM62%-95% 16 - 66µM

Type View Cases Detection rate FailuresCorrected

detection rate

Cancer 2 41 73% 80%1 9 89% 4 96%

0 6 11%

Cyst 2 59 72% 8 83%1 5 78% 3 90%

0 18 22%

Fibroadenoma 2 17 33% 2 39%1 5 43% 5 50%

0 29 57%Taroni et al., TRTC 4:527-537 (2005).

Clinical study (225 lesion)

Multi-channel time-domain system for functional nea r infrared spectroscopy (fNIRS)

µCHIP

delay

2x2 fused splitter

50%

50%

2x4 fusedsplitter

R1R2

R3R4

S9

S8

S1

sync

820 nm

690 nm

Laserdriver

variable ND

variable ND

1x9 fiber switch

1x9 fiber switch

clock

PicoQuantPDL800

PiezojenaF-SM19

OZOpticsVISNIR5050

µCHIP

delay

2x2 fused splitter

50%

50%

2x4 fusedsplitter

R1R2

R3R4

S9

S8

S1

sync

820 nm

690 nm

Laserdriver

variable ND

variable ND

1x9 fiber switch

1x9 fiber switch

clock

PicoQuantPDL800

PiezojenaF-SM19

OZOpticsVISNIR5050

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clock

µCHIPS16

4 anodesPMT-1

4 anodesPMT-2

4 anodesPMT-3

4 anodesPMT-4

4 chrouter-1

4 chrouter-2

4 chrouter-3

4 chrouter-4

8 champ-1

8 champ-2

F1

F16

TCSPC-1

TCSPC-2

TCSPC-3

TCSPC-4

HamamatsuR5900-20-M4

Becker & Hickl, SPC-134, HRT-41, HAFC-26

Microchip TechnologydsPIC30F6014

Contini et al. Opt Express14:5418-5432 (2006)

clock

µCHIPS16

4 anodesPMT-1

4 anodesPMT-2

4 anodesPMT-3

4 anodesPMT-4

4 chrouter-1

4 chrouter-2

4 chrouter-3

4 chrouter-4

8 champ-1

8 champ-2

F1

F16

TCSPC-1

TCSPC-2

TCSPC-3

TCSPC-4

HamamatsuR5900-20-M4

Becker & Hickl, SPC-134, HRT-41, HAFC-26

Microchip TechnologydsPIC30F6014

Contini et al. Opt Express14:5418-5432 (2006)

Can light penetrate biological tissues?

Georges de La Tour (1593 – 1652)

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St Joseph, 1642, Louvre, Paris Thanks to Marco Ferrari (UnivAQ)

Noninvasive imaging of brain function and disease b y pulsed near infrared light (nEUROPt FP7 2008-2012)

healthy ULD patientsA, D:O2Hb and HHb time-courses in themost reactive channel and thecorresponding GLM activationmaps.

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In collaboration with: I.Gilioli, S.Franceschetti, F. Panzica, E.Visani @ IRCCS Besta Milan, Italy

B, E:BOLD signal extracted from theactive cluster and fMRI maps.

An optical neuro-monitor of cerebral oxygen metabol ismand blood flow for neonatology (BabyLux ICT CIP 620 996)

• The BabyLux project aims to provide a

precise, accurate, and robust

integrated system to continuously

monitoring cerebral blood flow,

oxygen metabolism, and oxygenation

in critically ill newborn babies.

• The instrument must be easy to

operate by busy clinical staff and

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operate by busy clinical staff and

must be ready for integration into a

generic neonatal intensive care

environment.

• The proposed solution will integrate

two advanced photonic techniques:

time resolved near-infrared

spectroscopy (TRS) and diffuse

correlation spectroscopy (DCS).

Started on 1st January 20149 European partnersCoordinated by PoliMi

Photonics for Health Photonics for Food

H BC

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Photonics for Food @ PoliMiResearch activities

DIFFRUIT, EU FP4, 1996-1999 TRS APPLE, MAFF (UK), 2000 AGROTEC, MIUR (I), 2000-2002 CUSBO, LASERLAB, EU FP5+FP6+FP7, 2004-2014 INSIDEFOOD, EU FP7 2009-2013 TROPICO, Regione Lombardia (I), 2010-2012 3D Mosaic, EU ICT-AGRI, 2011-2013 USER-PA EU ICT-AGRI 2013-2016

Projects

Publications (2001-2013) >30 papers published on peer reviewed international journals >30 papers on international books and proceedings

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Collaborations

>30 papers on international books and proceedings >30 talks on international conferences

CRA-IAA, Milan (I), Paola Eccher-Zerbini , Anna Rizzolo, Maristella Vanoli, Maurizio Grassi Laimburg (I), Angelo Zanella Agricultural Research Organization, Bet Dagan (Israel), Susan Lurie, Victor Alchanitis Wageningen Universiteit (NL), Pol Tijskens, Olaf Van Kooten, Rob Schouten Planteforsk, Lofthus (N), Eivind Vangdal Potsdam (D), Manuela Zude-Sasse Leuven (B), Bart Nicolai, Bert Verlinden, Wouter Sayes, Pieter Verboven, Maarten Hertog UPM, ETSI Agronomos Madrid (E), Margarita Ruiz-Altisent, Constantino Valero Horiculture Research International, East Malling, (UK) - David Johnson, Colin Dover

Photonics for Food @ PoliMiMain applications

Non destructive optical characterisation of internal optical propertiesand correlation with quality parameters• Basic studies in apples, kiwifruits, nectarines, to matoes, …• Changes in optical properties during growth in Elst ar apples and Tophit plums• Texture in Jonagored apples, Braeburn apples and Pin k Lady apples during storage

Non destructive detection of internal disorders and defects• Browning in Granny Smith apples, Braeburn apples an d Conference pears• Watercore in Fuji apples

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• Watercore in Fuji apples• Mealiness in Braeburn apples and Jonagored apples• Chilling injuries in Jubileum plums and Morsiani nect arines

Non destructive assessment of fruit maturity at harvestand correlation with quality parameters• Basic studies in apples, kiwifruits, nectarines, pe aches, mangoes, …• Sensory attributes, aroma composition, ethylene pro duction Ambra nectarines• Softening prediction (based on biological age) in S pring Bright nectarines

and in Tommy Atkins mangoes

Optical characterization of foodsabsorption and scattering spectra

0.3

0.4

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abso

rptio

n (c

m-1

)

apple

kiwifruit

15

20

25

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spor

t sca

tterin

g (c

m-1

)

apple

kiwifruit

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0.0

0.1

0.2

650 700 750 800 850 900 950 1000

wavelength (nm)

abso

rptio

n (c

m

0

5

10

650 700 750 800 850 900 950 1000

wavelength (nm)

tran

spor

t sca

tterin

g (c

m

Cubeddu et al., Applied Optics 40:538-543 (2001)

8

10

12

14

16

tran

spor

t sca

tterin

g (c

m-1

)

Optical characterization of foodseffect of skin: Apple (cv. Golden Delicious)

0.04

0.06

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rptio

n (c

m-1

)

peeledintact

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0

2

4

6

600 625 650 675 700

wavelength (nm)

tran

spor

t sca

tterin

g (c

m

peeledintact

0.00

0.02

0.04

600 625 650 675 700

wavelength (nm)

abso

rptio

n (c

m

Optical characterization of foodseffect of skin: Mango (cv. Palmer)

Green skin

0

0.1

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500 550 600 650 700 750 800 850 900

abso

rptio

n (c

m-1

)

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scat

terin

g (c

m-1

)

0.0

0.5

1.0

1.5

abso

rban

ce

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Red skin

500 550 600 650 700 750 800 850 900

wavelength (nm)500 550 600 650 700 750 800 850 900

wavelength (nm)

0

0.1

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0.3

0.4

0.5

500 550 600 650 700 750 800 850 900

wavelength (nm)

abso

rptio

n (c

m-1

)

0

5

10

15

20

25

30

500 550 600 650 700 750 800 850 900

wavelength (nm)

scat

terin

g (c

m-1

)

0.0350 400 450 500 550 600 650 700 750

wavelength (nm)

0.0

0.5

1.0

1.5

350 400 450 500 550 600 650 700 750

wavelength (nm)

abso

rban

ce

Optical properties during growthAbsorption spectra

Plum Apple

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GrapefruitChlorophyll breakdown in plum and apple, almost no changes in grapefruit.

Optical properties during growthScattering spectra

Plum

Apple

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Grapefruit

Large changes during growth in the scattering properties for plum and grapefruit, minor changes for apple.

Optical propertiesEffect of layered structure in grapefruit

100

1000

10000

coun

ts (

ph)

IRF (a.u.)

DTOF_1.5cm

DTOF_2.5cm

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pulp

albedo

skin

1

10

0 1000 2000 3000 4000 5000 6000 7000 8000

coun

ts (

ph)

time (ps)

Shorter distance: early photons travel in the albedo, late photons in the pulpLonger distance: photon-path is mainly in the pulp

Nondestructive detection of internal defectsBrown heart in Conference pears

A0.06

0.08

0.10

abso

rptio

n (c

m-1

)

R3 (BH)

R3 (sound)

R3 (BH - sound)

µa (cm-1)@ 720 nm

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0.00

0.02

0.04

0.06

0.08

0.10A

H

G

F

E

D

C

B

0.00

0.02

0.04

710 730 750 770 790 810 830 850

wavelength (nm)

abso

rptio

n (c

m

µa (cm-1)@ 720 nm

Eccher Zerbini et al., Postharvest Biology and Technology 25:87-99 (2002)

Measurement campaignsNondestructive assessment of maturity at harvest

10

20

30

40

50

60

70

80

firm

ness

N

0.090.10.140.180.20.270.30.390.42overripe

ready-firmtransportable

dangerously hardnever ripe

ready-ripe

10

20

30

40

50

60

70

80

firm

ness

N

0.090.10.140.180.20.270.30.390.42overripe

ready-firmtransportable

dangerously hardnever ripe

ready-ripe

( ) minminmax

*minmax1

Fe

FFF

Ff ttFFk+

+

−=

∆+⋅−⋅

)

+−

=∆ β

µµ

α 1log*a

maxa,Ft

6

7

sens

ory

firm

ness

sco

re

.

5 6 13

spots with decay

overly soft spots

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0

10

0 2 4 6 8 10 12

days at 20°C after harvest

0

10

0 2 4 6 8 10 12

days at 20°C after harvest

0

1

2

3

4

5

overripe ready-ripe

ready-firm

trans-portable

danger.hard

neverripe

class of usability

sens

ory

firm

ness

sco

re

.

soft

softer

seems soft

very firm

firm

Eccher Zerbini et al., Postharvest Biology and Technology 39:223-232 (2006) Tijskens et al., Int. J. Postharvest Technology and Innovation, 1 (2), 178-188 (2006)

Tijskens et al., Postharvest Biology and Technology 45:204-213 (2007)Rizzolo et al., Biosystems Engineering (2009 in press)

TRS measurements:Absorption spectra: µ a

Day 0 Day 5

Maturity at harvest and shelf lifein Tommy Atkins mangoes

chlorophyll

carotenoids

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540 nm

650 nm

TRS measurements:Absorption spectra: µ a

Maturity at harvest and shelf lifein Tommy Atkins mangoes

chlorophyll carotenoids

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Chlorophyll-a and carotenoids estimation from TRSOpen problem: extinction coefficient for carotenoids in vivo

TRS set-up @PoliMi (Photonics for Food)

Laboratory based set-up (time sharing with Photonic s for Health):1) Broad band (450-1700 nm) TRS

ps supercontinuum laser, fast detectors, and TCSPC

2) fs laser + streak camera TRSoperative since September 2013

Transportable set -up

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Transportable set -up3) Dual-wavelength (670 nm, 780 nm) TRS

ps diode laser heads, metal channel dynode PMT, and TCSPC

4) Multi-wavelength (14 wavelengths in the 500-900 nm range) TRSps supercontinuum laser, hybrid PMT, and TCSPC

1) Broad band (450-1700 nm) TRS

ps white light laser

NKT Photonics SuperK Extreme

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Bassi et al., Opt Expr (2007)

Becker-HicklSPC130

MPD

Hybrid PMTNIR PMT1NIR PMT2

2) fs laser + Streak camera

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Hamamatsu Photonics

+++ temporal resolution+ sensitivity

http://sales.hamamatsu.com/en/products/system-division/ultra-fast/streak-systems.php

3) Dual-wavelength transportable system for TRS

laser heads

750 nm

670 nmdriver

fiber optic swtch

PMTampTCSPCsync

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filters and optics

Cubeddu et al., Appl Spectroscopy 55:1368-1374 (2001)Torricelli et al. Sens. & Instrumen. Food Qual. 2:82–89 (2008)

Laser source:

Supercontinuum fiber laser

− spectral range: 450-1600 nm

− power: 6 W

− frequency: 40 MHz

Wavelength selection:

Filter wheel

− spectral range: 540-900 nm

Detector:

Hybrid PMT

− no afterpulse

− time response: 250 ps

4) Multi-wavelength (500-900 nm range) transportable TRS

Supercontinuumlaser

grin fiber∅ =100μm

Large areadetector

Objective 10x Step-index fiber∅ =1mmSupercontinuum

laserSupercontinuum

lasergrin fiber∅ =100μm

Large areadetector

Large areadetector

Objective 10x Step-index fiber∅ =1mm

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TCSPCSYNC

CFD

Time resolution:

Time-Correlated Single-Photon Counting:

− high dynamic range

− suitable for faint signal

− time resolution: up to 1 ps

SY

NC

Filter wheelSample

Filter wheelFilter wheelSampleSample

Filter wheel

8 absorption nominal values:

0 : 0.07 : 0.49 cm-1 (label 1 -> 8)

4 reduced scattering nominal values:

5 : 5 : 20 cm-1 (label A -> D)

Robust calibrations….Solid phantoms: Epoxy based

Well established solutionabsorption

Scatt

erin

g

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New series: 2.5, 7.5, 12.5 17.5 cm-1 nominal reduced scattering

Development of a transportable TRS set-upfor measurements in the orchards

2x1 combiner

100um GIλ1PD

L d

riv

er

λ2

laser head

variable attenuator fiber bundle

1 mm POF GI

cfdSPAD

lens, IF filter, shutter

SPADlens,

IF filter, shutter

TCSPC board

cfdTCSPC board

Scheme of the TRS setup

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light source: pulsed diode laser (LDH series PicoQuant GmbH, Germany)detection: SPAD detectors (Excelitas Inc., Canada)acquisition: TCSPC board (Becker&Hickl GmbH, Germany)power supply: portable (gasoline), inverter technology (i20, Honda, Japan)

80 MHz sync

80 MHz sync

shutter

Development of a transportable TRS set-upfor measurements in the orchards

Photo of the TRS set-up

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Field trials 2014Preliminary results

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Field trials 2014Preliminary results

Absorption coefficient

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Chlorophyll absorption decreases during fruit growth(agreement with Seifert et al. Physiol Plantarum 2014)

Field trials 2014Preliminary results

Scattering coefficient

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Scattering decreases during fruit growth(agreement with Seifert et al. Physiol Plantarum 2014)

Evolution of TRS set-upTowards a smart photonic chip for TRS

Transportable>2013

Handheld>2016

Canopy>2018

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Reducing size and cost ...

Evolution of TRS set-upThe future is near …

fNIRS – brain response to finger tapping

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1 wavelength1 channelExternal power supply

Conclusion and future perspectives

• Time-resolved reflectance spectroscopy (TRS) naturally yieldsdiscrimination between light absorption (related to tissue constituents)and light scattering (related to tissue structure)

• Physical and mathematical models for TRS are available and allowquantitative data analysis for non destructive fruit quality assessment

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• We have demonstrated in the last years several applications of TRS inthe food sector, mainly at research level

• We are at the forefront of a new era where recent advances inphotonic technologies might allow TRS to bridge the gap betweenresearch and market (the development is mostly driven by thebiomedical sector)

Acknowledgements

• CNR-IFN, Milan (Italy) Lorenzo Spinelli

• Politecnico di Milano - Dipartimento di Fisica, Milan (Italy) Antonio Pifferi Davide Contini Alberto Dalla Mora

• CRA-IAA (ex IVTPA), Milan (Italy)

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• CRA-IAA (ex IVTPA), Milan (Italy) Anna Rizzolo Maristella Vanoli Maurizio Grassi (Paola Eccher Zerbini)