Practical Use Of Nir In The Feed And Food Industry

��

NIR Seminar – Campden – October 14th 2009

Giovanni Campolongo

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I Italian Near Infrared Symphosium

2004 Lodi

• Limo •Fiber Optic on the Ham•Baby Food Plasmon (Heinz Group)

12th International Conference on Near-infrared Spectroscopy

2005 Auckland

• On-line Maillard reaction monitoring for food additives production (caramel)


VII CISETA2005 Cernobbio

• Ice cream mixtures

II Italian Near Infrared Symphosium2006

Ferrara

• Inorganic Integrators• Pectin• SO2• Proteolysis index in P.D.O. Cheeses

13th International Conference on Near-infrared Spectroscopy

2007 Umeå

• Cous cous• Vanilline• Wheat flour rheological paramethers

III Italian Near Infrared Symphosium

2008 Lazise

• On-line polymerization process• Licopen content in Tomatoes• Barilla FT-NIR Network for Flour monitoring

�! �" �� " # �� $ ��

Lab & R&D

• University• State agencies for control• Private Labs


INDUSTRY

NEEDS • Raw material control • Monitoring production processes• Fianl products quality control

TECHNOLOGY PRODUCERS

• Analytical systems

% ��# �� &�� ' �� ! �' ��


# ��

BARILLA

DIFFERENT PRODUCTS

DIFFERENT RAW MATERIALS

Wheat Flours

Industrialbread

Quality 1

Quality 2


BARILLA BAKERY

bread

Snacks

Quality 2

Quality 3

Quality 4

Quality 5

Quality up to 12

Cakes

( ) � �� * �� " % �� '

TARGET: Assess Quality of incoming Wheat Flour batches

• Identify Parameters to check• Identify an Analytical System able to perform quickly such

checking• Define sampling methods• Collect samples and verify

12 different Wheat Flour Qualities considered


12 different Wheat Flour Qualities considered 8 – 100 – 106 – 108 – 110 – 114 – 120 – 141 – 144 – 158 – 164 –

175…

• Samples collected starting from March 2007

• Samples collected from different suppliers all over Italy

�� '

CHEMICAL PARAMETERS REFERENCE METHODS

Farinographic

RHEOLOGICAL PARAMETERS

MoistureProtein ContentFalling Number

UNI reference Methods

Brabender Farinograph


Farinographic Baking Absorption

Alveographic WP/L

Chopin Alveograph

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• 3 Sub-samples for each incoming Flour Batch (3 spectra measurment for each batch)• Each spectra as average of 64 scans having a rotating petri dish system• Samples Temperature: 20 � 5�C

Spectra acquisition by diffuse reflectance using an FT-NIR SpectrometerWavelenght range 4000 – 10000 cm-1


Data management• NIRCal Chemometeric software to develop quantitative calibration models with Evaluation Set Tecnique

Chemometric software NIRCal 5.0

% ��# �� '

PEDRIGNANO BARILLA HEADQUARTER

MASTER UNIT Spectra Libraries Main Database

Sample’s spectraMeasurements

reports

CalibrationsSupport


Spectra Libraries Main DatabaseDevelopement of Quantitative Calibrations

ClientPicenengo

(Local database)

ClientNovara(Local database) ClientCastiglione

(Local database)ClientRubbiano

(Local database)

ClientAscoli(Local database)

ClientMelfi(Local database)

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Checking incoming raw materials chemical composition Why NIR?


Checking chemical composition of finished formulations

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Raw materials are paid according to chemical

composition

Example: Soy Flour according to protein content

Check every batch supplied means to pay the correct price


To produce according to the declared composition by having

an instant monitoringFinished products

PlusTo obtain the same chemical

composition they could be used different and new raw materials,

maybe cheaper

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WHEAT GLUTEN AND MELAMINE


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Original SpectraAll Spectra

Wavelengths

Re

fle

cta

nc

e

40005000600070008000900010000

0.2

0.4

0.6

0.8

NIR

Ca

l : C

usc

us

_S

em

ola

to_

Fa

rin

a_

Um

idita

23

11

06

26

/04

/20

07

10

.34

.43

Ad

min

istr

ato

r

Calibration SpectraValidation Spectra

��


Samples Method Range R C-set/V-set SEP SEC

Umidità 210 PLS 10.00 - 16.09 0.99 / 0.99 0.12 0.12

Proteine 144 PLS 11.02 - 14.03 0.97 / 0.97 0.16 0.15

Ceneri 210 PLS 0.69 - 1.35 0.94 / 0.93 0.20 0.22

Wavelengths40005000600070008000900010000

NIR

Ca

l : C

usc

us

_S

em

ola

to_

Fa

rin

a_

Um

idita

23

11

06

26

/04

/20

07

10

.34

.43

Ad

min

istr

ato

r

��

/ �� '

Original Property / Predicted PropertyAll Spectra

True Property lactose

Pre

dic

ted

Pro

per

ty la

cto

se

3.0 3.5 4.0 4.5 5.0 5.53.5

4.0

4.5

5.0

5.5

NIR

Cal

: L

atti

ero

case

ario

onl

ine-

aggi

orna

to2.

nir

Lact

ose

- im

plem

ente

d2

23/0

5/20

05 9

.25.

39 c

amg

V a l i d a t i o n S p e c tra f (x )= 0 .6 5 2 3 x + 1 . 7 1 3 7 r= 0 .7 7 7 8 3 8C a l i b ra t i o n S p e c t ra f (x )= 0 . 6 5 5 3 x + 1 .6 9 9 3 r= 0 . 8 0 9 5 2 3

P ro p e rty Ou t l i e r S p e c t raV a l i d a t i o n S p e c traC a l i b ra t i o n S p e c t ra

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True Property fat A

Pre

dict

ed

Pro

pert

y fa

t A

0 2 4 6

0

2

4

6

NIR

Cal

: L

atti

ero

case

ario

onl

ine-

aggi

orna

to2.

nir

Fat

A -

im

plem

ente

d2

23/0

5/20

05 8

.49.

25 c

amg

V a l i d a t i o n S p e c t ra f (x )= 0 . 9 8 8 9 x + 0 . 0 2 4 3 r= 0 .9 9 3 5 8 8Ca l i b ra t i o n S p e c t ra f (x )= 0 . 9 8 8 2 x + 0 .0 3 6 3 r= 0 . 9 9 4 1 0 7V a l i d a t i o n S p e c t raCa l i b ra t i o n S p e c t ra

��


Property(%)

C-Set SEE (SEC)

V-Set SEE (SEP)

C-Set Regression Coefficient

V-Set Regression Coefficient

Fat 0.17 0.17 0.99 0.99

Protein 0.17 0.16 0.85 0.86

Dry matter 0.31 0.31 0.98 0.98

Lactose 0.16 0.17 0.81 0.78

/ ��$��

Olive grinding Olive paste

Gramolatura

EstrazioneHusk WaterExtractionExtraction

Solvent


EstrazioneHusk

Separation

Filtration

Extraction

Extra-virgin Olive oil

Husk Oil

Water

/ ��$��

Spectrometer FT-NIR NIRFlex N500

• 2 acquisition each sample• Every acquisition is tha average of 64 scan with rotating petri dish (total time< 1min)• Temperature 20°C


PARAMETR Standard errorSEP [%] Range samples

Moisture 0.8 34.8 – 71.7 240

Fat 0.9 15.8 – 31.1 200

Samples from different geograpical regions 2007

Predicted Property vs. Original PropertyAll Spectra

Original Property Moisture

Pre

dic

ted

Pro

pe

rty

Mo

istu

re

40 50 60 7030

40

50

60

70

NIR

Ca

l :

co

py

of

Mo

istu

re,

0.8

05

0,

1-6

./6

, 4

60

0-1

00

00

. 2

4/0

4/2

00

8 1

4.3

0.4

9 A

dm

inis

tra

tor

Calibration Spectra f(x)=0.9873x+0.7300 r=0.9937 r2=0.9873 Sdev(x-y)=0.8254 BIAS(x-y)= 0 range(x)=34.8 .. 71.73 n=342Validation Spectra f(x)=1.0032x-0.1181 r=0.9920 r2=0.9840 Sdev(x-y)=0.8178 BIAS(x-y)=-0.0647 range(x)=41.8 .. 70.97 n=133Calibration SpectraValidation Spectra

��


Original Property Moisture

Pre

dic

ted

Pro

pe

rty

Mo

istu

re

40 50 60 7030

40

50

60

70

NIR

Ca

l :

co

py

of

Mo

istu

re,

0.8

05

0,

1-6

./6

, 4

60

0-1

00

00

. 2

4/0

4/2

00

8 1

4.3

0.4

9 A

dm

inis

tra

tor

Calibration Spectra f(x)=0.9873x+0.7300 r=0.9937 r2=0.9873 Sdev(x-y)=0.8254 BIAS(x-y)= 0 range(x)=34.8 .. 71.73 n=342Validation Spectra f(x)=1.0032x-0.1181 r=0.9920 r2=0.9840 Sdev(x-y)=0.8178 BIAS(x-y)=-0.0647 range(x)=41.8 .. 70.97 n=133Calibration SpectraValidation Spectra

��

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Diffuse reflectance


PARAMETR Standard error SEP [%] Range Samples

Moisture 1.8 24.7 – 70.7 170

Fat 0.3 1.0 – 12.1 180

Samples from different geograpical regions


Original Property Fat

Pre

dic

ted

Pro

pe

rty

Fa

t

0 2 4 6 8 10 120

2

4

6

8

10

12

NIR

Ca

l :

SV

_G

ras

si_

23

04

08

23

/04

/20

08

12

.17

.37

Ad

min

istr

ato

rCalibration Spectra f(x)=0.9621x+0.1741 r=0.9809 r2=0.9621 Sdev(x-y)=0.3836 BIAS(x-y)= 0 range(x)= 1 .. 12.1 n=296Validation Spectra f(x)=0.9366x+0.3830 r=0.9729 r2=0.9466 Sdev(x-y)=0.3878 BIAS(x-y)=-0.09397 range(x)= 2 .. 8.7 n=84Calibration SpectraValidation Spectra

��


Original Property Fat

Pre

dic

ted

Pro

pe

rty

Fa

t

0 2 4 6 8 10 120

2

4

6

8

10

12

NIR

Ca

l :

SV

_G

ras

si_

23

04

08

23

/04

/20

08

12

.17

.37

Ad

min

istr

ato

rCalibration Spectra f(x)=0.9621x+0.1741 r=0.9809 r2=0.9621 Sdev(x-y)=0.3836 BIAS(x-y)= 0 range(x)= 1 .. 12.1 n=296Validation Spectra f(x)=0.9366x+0.3830 r=0.9729 r2=0.9466 Sdev(x-y)=0.3878 BIAS(x-y)=-0.09397 range(x)= 2 .. 8.7 n=84Calibration SpectraValidation Spectra

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+ �� 0��

Olive Grinding Olive paste

Gramolatura

Fat content= 23.4%


EstrazioneHusk WaterExtractionFat content= 6.6%

Constant monitoring of plant yield

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Customization according to the needs of a specific industry

General calibrations developed thanks to refernce lab


PARAMETRO Standard error SEP [%] Range samples

Moisture 1.3 41.8 – 67.7 120

Fat 0.18 2.00 – 8.00 120


Original Property Grassi

Pre

dict

ed P

rope

rty

Gra

ssi

2 4 6 8

2

4

6

8

NIR

Cal

: Sa

nse

verg

ini g

rass

i <8%

121

207

13/0

5/20

08 1

3.56

.38

Adm

inis

trato

r

Calibration Spectra f(x)=0.9709x+0.1267 r=0.9854 r2=0.9709 Sdev(x-y)=0.2279 BIAS(x-y)= 0 range(x)= 2 .. 8 n=181Validation Spectra f(x)=0.9876x+0.0605 r=0.9915 r2=0.9831 Sdev(x-y)=0.1812 BIAS(x-y)=-0.006503 range(x)=2.49 .. 7.4 n=58

User SpectraCalibration SpectraValidation Spectra

��


Original Property Grassi

Pre

dict

ed P

rope

rty

Gra

ssi

2 4 6 8

2

4

6

8

NIR

Cal

: Sa

nse

verg

ini g

rass

i <8%

121

207

13/0

5/20

08 1

3.56

.38

Adm

inis

trato

r

Calibration Spectra f(x)=0.9709x+0.1267 r=0.9854 r2=0.9709 Sdev(x-y)=0.2279 BIAS(x-y)= 0 range(x)= 2 .. 8 n=181Validation Spectra f(x)=0.9876x+0.0605 r=0.9915 r2=0.9831 Sdev(x-y)=0.1812 BIAS(x-y)=-0.006503 range(x)=2.49 .. 7.4 n=58

User SpectraCalibration SpectraValidation Spectra

��

Higher measurement accuracy

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Transflettanza

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Spettrometro FT-NIR NIRLab N200

PARAMETER Standard error SEP [%] Range Samples

Solvents 0.06 0.02 – 1.03 105

Impurities 0.07 0.02 – 0.99 105


True Property Impurezze

Pre

dict

ed P

rope

rty

Impu

rezz

e

0.00 0.25 0.50 0.75 1.00 1.25

0.00

0.25

0.50

0.75

1.00

NIR

Cal

: ad

riaol

i - b

asse

con

cent

razi

on im

pure

zze.

nir i

mpu

rezz

e ba

sse

conc

netra

zion

i 030

7 13

/05/

2008

14.

25.5

6 ca

mg

Validation Spectra f(x)=0.9227x+0.0132 r=0.975797Calibration Spectra f(x)=0.9487x+0.0229 r=0.974025

Property Outlier SpectraValidation SpectraCalibration SpectraUser Spectra

��


True Property Impurezze

Pre

dict

ed P

rope

rty

Impu

rezz

e

0.00 0.25 0.50 0.75 1.00 1.25

0.00

0.25

0.50

0.75

1.00

NIR

Cal

: ad

riaol

i - b

asse

con

cent

razi

on im

pure

zze.

nir i

mpu

rezz

e ba

sse

conc

netra

zion

i 030

7 13

/05/

2008

14.

25.5

6 ca

mg

Validation Spectra f(x)=0.9227x+0.0132 r=0.975797Calibration Spectra f(x)=0.9487x+0.0229 r=0.974025

Property Outlier SpectraValidation SpectraCalibration SpectraUser Spectra

��

�2� 2/ 2�( ) ��$ �� $��

Istituto ZooprofilatticoSperimentale della Lombardia

e dell'Emilia Romagna

Spettrometro FT-NIR NIRFlex N-500 with

liquids cell


Parameters for olive oil quality evaluation

Acidity

Perox.

K232 K270�K

Tocoferol

Polifenol


Original Property Olio Acidità

Pre

dict

ed P

rope

rty

Olio

Aci

dità

-0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

NIR

Cal

: O

lio o

liva

acid

ità 1

4/05

/200

8 9.

25.4

3 Ad

min

istra

tor

Calibration Spectra f(x)=0.9959x+0.0021 r=0.9979 r2=0.9959 Sdev(x-y)=0.0400 BIAS(x-y)= 0 range(x)=0.01 .. 2.97 n=150Validation Spectra f(x)=0.9887x+0.0130 r=0.9918 r2=0.9837 Sdev(x-y)=0.0452 BIAS(x-y)=-0.008318 range(x)=0.04 .. 1.795 n=75Calibration SpectraValidation Spectra

��


Original Property Olio Acidità

Pre

dict

ed P

rope

rty

Olio

Aci

dità

-0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

NIR

Cal

: O

lio o

liva

acid

ità 1

4/05

/200

8 9.

25.4

3 Ad

min

istra

tor

Calibration Spectra f(x)=0.9959x+0.0021 r=0.9979 r2=0.9959 Sdev(x-y)=0.0400 BIAS(x-y)= 0 range(x)=0.01 .. 2.97 n=150Validation Spectra f(x)=0.9887x+0.0130 r=0.9918 r2=0.9837 Sdev(x-y)=0.0452 BIAS(x-y)=-0.008318 range(x)=0.04 .. 1.795 n=75Calibration SpectraValidation Spectra

��

Standard

�2� 2/ 2�( ) ��$ �� $��

Istituto ZooprofilatticoSperimentale della Lombardia

e dell'Emilia Romagna


Scores vs. ScoresAll Spectra

PC 1

PC

2

-0.2 -0.1 -0.0 0.1 0.2 0.3

-0.2

-0.1

-0.0

0.1

0.2

NIR

Cal

: O

lio o

liva

acid

ità 1

4/05

/200

8 9.

26.5

7 A

dmin

istra

tor

��

Scores vs. ScoresAll Spectra

PC 1

PC

2

-0.2 -0.1 -0.0 0.1 0.2 0.3

-0.2

-0.1

-0.0

0.1

0.2

NIR

Cal

: O

lio o

liva

acid

ità 1

4/05

/200

8 9.

26.5

7 A

dmin

istra

tor

��

PARAMETErStandard

error SEP

Coeff.Reg. R Range N. Spt.

(cp. X 3)

Acidity 0.04 0.99 0.01 – 2.97 228

Peroxidenum.

1.8 0.97 3.2 – 43.4 237

K232 0.12 0.98 1.99 – 5.27 237

k270 0.06 0.97 0.08 – 1.49 237

�K 0.0002 0.95 0.0001 –0.0555 237

Polifenol 30 0.70 139 - 300 93

Tocoferol 21 0.95 7 - 282 129

/ ��$��) ��$��

Dipartimento di Chimica e tecnologie Farmaceutiche e Alimentari - Univ. Genova

Application of differenet multi-variate analysis techiniques to identify the

geograpichal origin of olive oil


200 samples of olive oil

“Near infrared spectroscopy and classmodelling techniques for thegeographical authentication of Ligurianextra virgin olive oil”Journal of Near Infrared Spectroscopy,November 2007

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Dry matterProteinFatParameter


15.40 –19.906.80 – 8.401.40 – 5.30Range

0.290.210.16SEP

0.330.210.16SEC

0.950.790.98R V-SET

0.960.860.99R C-Set

ncl, logdg1, nleds2Pretreatments

PLSPLSPLSMethod

968897Samples

matterProteinFatParameter

Pretreated spectra for “fat content”

�� ! �! � �� ! ��


Pre

dict

ed P

rope

rty

Fat

0 2 4 60

2

4

6

NIR

Cal

: cop

y of

Om

ogen

izza

to g

rass

i 0409

06 0

7/0

9/20

06

17.2

3.0

4 bu

chi

Calibration Spectra f(x)=0.9887x+0.0421 r=0.994357 range(x)=1.32-6.32 Sdev(x-y)=0.1134 BIAS(x-y)=1.35324e-014 n=108Validation Spectra f(x)=0.9756x+0.0837 r=0.994598 range(x)=1.49-6.03 Sdev(x-y)=0.1096 BIAS(x-y)=0.00778034 n=52Calibration SpectraValidation Spectra


Original Property Fat0 2 4 6

NIR

Cal

: cop

y of

Om

ogen

izza

to g

rass

i 0409

06 0

7/0

9/20

06

17.2

3.0

4 bu

chi

��

Measurement time = 15 sec.

ParameterFat[%]

Samples 80

Regres. C-set 0.99

Regres. V-set 0.99

SEE C-set 0.11

SEP V-set 0.11

Range 1.32 - 6.32

6 ��' �� + �� 7��


PARAMETHERSProteinTotal fat

Saturated Fatty AcidUnsaturated Fatty Acid

Lactose

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Predicted Property vs. Original PropertyUser Spectra

Original Property proteolisi TCA 12%

Pre

dic

ted

Pro

per

ty p

rote

olis

i TC

A 1

2%

0 5 10 15 20 25

0

5

10

15

20

NIR

Cal

: R

agu

san

o p

rote

olis

i TC

A 1

2% 2

5060

6 1

3/05

/200

7 2

3.5

8.49

Adm

inis

trat

orCalibration Spectra f(x)=0.9300x+0.5710 r=0.964346 range(x)=0.43-22.04 Sdev(x-y)=1.1547 BIAS(x-y)=8.82512e-015 n=1207Validation Spectra f(x)=0.9472x+0.4541 r=0.963864 range(x)=0.63-20.02 Sdev(x-y)=1.1610 BIAS(x-y)=-0.0124169 n=597

User SpectraCalibration SpectraValidation SpectraProperty Outlier Spectra

��

Predicted Property vs. Original PropertyUser Spectra

Original Property proteolisi TCA 12%

Pre

dic

ted

Pro

per

ty p

rote

olis

i TC

A 1

2%

0 5 10 15 20 25

0

5

10

15

20

NIR

Cal

: R

agu

san

o p

rote

olis

i TC

A 1

2% 2

5060

6 1

3/05

/200

7 2

3.5

8.49

Adm

inis

trat

orCalibration Spectra f(x)=0.9300x+0.5710 r=0.964346 range(x)=0.43-22.04 Sdev(x-y)=1.1547 BIAS(x-y)=8.82512e-015 n=1207Validation Spectra f(x)=0.9472x+0.4541 r=0.963864 range(x)=0.63-20.02 Sdev(x-y)=1.1610 BIAS(x-y)=-0.0124169 n=597

User SpectraCalibration SpectraValidation SpectraProperty Outlier Spectra

��

Parameter Samples Samples Range [%] R SEC/SEP [%]

Soluble nitrogen TCA 12%

C-set 408 0.11 – 6.84 0.96 0.31

V-Set 197 0.12 – 15.67 0.96 0.30

Proteolysis index TCA

12%

C-set 408 0.43 – 22.04 0.96 1.15

V-Set 197 0.63 – 20.02 0.96 1.16

�� - � ��


Only one calibration for each parameter

Fat SEP = 0.4%

Protein SEP = 0.10%

Dry matterSEP = 0.41%

DIFFERENT MIXTURES OF ICE-CREAMS

MilkVanillaCremeYogurt

Chcocolate

/ �� ! �� * � ��

Spectrometer FT-NIR Buchi Nirflex N-419


Pre

dic

ted

Pro

per

ty A

sso

rbim

ento

a 6

10

0.50

NIR

Cal

: B

S11

1.n

ir A

SB

610

- n

ew 0

.92*

11/

03/2

005

14.4

8.06

ferg

Validation Spectra f(x)=0.9389x+0.0292 r=0.968015Calibration Spectra f(x)=0.9497x+0.0220 r=0.974547Validation SpectraCalibration Spectra


Pre

dic

ted

Pro

per

ty A

sso

rbim

ento

a 6

10

0.50

NIR

Cal

: B

S11

1.n

ir A

SB

610

- n

ew 0

.92*

11/

03/2

005

14.4

8.06

ferg

Validation Spectra f(x)=0.9389x+0.0292 r=0.968015Calibration Spectra f(x)=0.9497x+0.0220 r=0.974547Validation SpectraCalibration Spectra


True Property Assorbimento a 610

Pre

dic

ted

Pro

per

ty A

sso

rbim

ento

a 6

10

0.30 0.35 0.40 0.45 0.500.25

0.30

0.35

0.40

0.45

NIR

Cal

: B

S11

1.n

ir A

SB

610

- n

ew 0

.92*

11/

03/2

005

14.4

8.06

ferg

�� True Property Assorbimento a 610

Pre

dic

ted

Pro

per

ty A

sso

rbim

ento

a 6

10

0.30 0.35 0.40 0.45 0.500.25

0.30

0.35

0.40

0.45

NIR

Cal

: B

S11

1.n

ir A

SB

610

- n

ew 0

.92*

11/

03/2

005

14.4

8.06

ferg

��


1/cm

Tra

nsm

itta

nce

5000 6000 7000 8000 9000

0.0

0.2

0.4

0.6

0.8

NIR

Cal

: B

S11

1.ni

r A

SB

610

- n

ew

0.9

2*

11

/03

/200

5 1

4.5

1.44

ferg

��


1/cm

Tra

nsm

itta

nce

5000 6000 7000 8000 9000

0.0

0.2

0.4

0.6

0.8

NIR

Cal

: B

S11

1.ni

r A

SB

610

- n

ew

0.9

2*

11

/03

/200

5 1

4.5

1.44

ferg

��

Reading at a 610nm0.009/0.0100.97/0.960.275-0.52765610nm

0.04/0.040.98/0.970.325-1.133125550mn

SEC/ SEPR C-Set/ V-SetRangeSamplesParameter

��

Parameter NaHCO3 CaHPO4 CaCO3 MgO

Camp. 107 107 64 64

R C-Set 0.99 0.99 0.99 0.99

R V-Set 0.99 0.98 0.99 0.99

SEC 1.1 1.7 2.0 1.8

SEP 1.0 1.8 2.0 1.8

San Marco Plant

State University of Parma

Büchi

+

+


NaHCo3 CaHPO4

��

PARAMETERS

Moisture

CONSTANT MONITORING OF PRODUCTION

PROCESS

Analisi dei campioni tal


MoistureEsterification ratioGalacturonic Acid content

OPTIMIZATION OF PRODUCTION

PROCESS

PRODUCT WITH HIGHER QUALITY

Analisi dei campioni tal quali in uscita dalla produzione

Una sola scansione tutti i parametri contemporanemante

�� " ��


PARAMETER SEC SEP C-set r V-set r C-slope V-slope

Moisture 1.09 1.08 0.88 0.78 0.77 0.78

NaCl 0.29 0.50 0.92 0.62 0.85 0.71

Protein 0.99 0.97 0.82 0.80 0.68 0.66

N(TCA) 0.70 0.70 0.83 0.78 0.68 0.67

Proteolysisindex

1.88 1.82 0.79 0.72 0.63 0.62

* / 9 �� :


Regressione con set di validazione.

�� ! �� - � ��$�� ; ��% �� <<


P r e d ic te d P r o p e r ty v s . O r ig in a l P r o p e r tyAl l S p e c tra

O r ig in a l P ro pe r ty V a n illina

Pred

icte

d Pr

oper

ty V

anill

ina

1 2 3

1

2

3

NIRC

al :

Vani

llina

quan

titativ

a 14

0507

14/

05/2

007

22.4

6.48 A

dmin

istra

tor

C a l i b ra t i o n S p e c t ra f (x )= 0 .9 5 5 6 x+ 0 .0 7 6 5 r= 0 .9 7 7 5 3 5 ra n g e (x)= 0 .6 4 2 -3 .4 9 9 S d e v(x-y)= 0 .1 1 7 7 B IA S (x-y)= -1 .6 3 5 7 3 e -0 1 5 n = 6 0V a l i d a t i o n S p e c t ra f (x )= 0 .9 5 2 7 x+ 0 .0 9 3 1 r= 0 .9 5 8 9 9 1 ra n g e (x)= 0 .7 7 6 -2 .3 4 5 S d e v(x-y)= 0 .1 2 1 1 B IA S (x-y)= -0 .0 1 3 4 0 9 5 n = 2 8C a l i b ra t i o n S p e c t raV a l i d a t i o n S p e c t ra

��

P r e d ic te d P r o p e r ty v s . O r ig in a l P r o p e r tyAl l S p e c tra

O r ig in a l P ro pe r ty V a n illina

Pred

icte

d Pr

oper

ty V

anill

ina

1 2 3

1

2

3

NIRC

al :

Vani

llina

quan

titativ

a 14

0507

14/

05/2

007

22.4

6.48 A

dmin

istra

tor

C a l i b ra t i o n S p e c t ra f (x )= 0 .9 5 5 6 x+ 0 .0 7 6 5 r= 0 .9 7 7 5 3 5 ra n g e (x)= 0 .6 4 2 -3 .4 9 9 S d e v(x-y)= 0 .1 1 7 7 B IA S (x-y)= -1 .6 3 5 7 3 e -0 1 5 n = 6 0V a l i d a t i o n S p e c t ra f (x )= 0 .9 5 2 7 x+ 0 .0 9 3 1 r= 0 .9 5 8 9 9 1 ra n g e (x)= 0 .7 7 6 -2 .3 4 5 S d e v(x-y)= 0 .1 2 1 1 B IA S (x-y)= -0 .0 1 3 4 0 9 5 n = 2 8C a l i b ra t i o n S p e c t raV a l i d a t i o n S p e c t ra

��

0.120.970.64 – 3.5060C-setVanillin

0.120.960.77 – 2.3428V-Set

SEC/SEP [%]R

Range[%]SpectraSetParameter

�� , ��

Transflectance analysis of samples of honey as it is


/ �� = ��' ��

Batch Product No. of samples Target (% alcohol)

1 Whiskey 1 12 40

2 Whiskey 2 14 40

3 Whiskey 2 15 40

4 Whiskey 2 4 40

5 Whiskey 1 15 43


Full Calibration Range(40% and 43% alcohol)

True Property Density OnlineP

redi

cted

Pro

pert

y D

ensi

ty O

nlin

e40 41 42 43

40

41

42

43Validation Spectra f(x)=1.0016x-0.0694 r=0.999919Calibration Spectra f(x)=0.9998x+0.0080 r=0.999903Validation SpectraCalibration Spectra

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Documents

Practical Use Of Nir In The Feed And Food Industry