Direct, simultaneous quantification of ...

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ATR spectroscopy and chemometrics for rapid identification of superior, engineered β-fructofuranosidases. Kim M. Trollope, Heinrich Volschenk, Johann F.
Analytical and Bioanalytical Chemistry

Electronic Supplementary Material

Direct, simultaneous quantification of fructooligosaccharides by FT-MIR ATR spectroscopy and chemometrics for rapid identification of superior, engineered β-fructofuranosidases

Kim M. Trollope, Heinrich Volschenk, Johann F. Gӧrgens, Rasmus Bro, Hélène H. Nieuwoudt

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Fig. S1 Stacked tacked pure component powder FT-MIR FT MIR ATR spectra for fructose, glucose, sucrose, 11 kestose and nystose. Spectra were collected from 4000 to 550 cm−1. The ATR diamond exhibits broad bands in the 2700–1800 2700 cm-1 regions due to carbon bond absorption while hydrogen and nitrogen content is responsible for bands at 3100 cm-1 and 1500–1000 1500 cm-1, respectively [1] [1] Li-Chan Chan E, Chalmers JM, Griffiths P (2010) Applications of vibrational spectroscopy in food science: Volumes I and II: Analysis of food, drink and related materials. John Wiley & Sons, Chichester, UK

Table S1 Sample statistics of datasets used in PLS modelling Glucose

Fructose

Sucrose

1-Kestose estose

Nystose

Number of samples*

112 (8)

151 (5)

180 (9)

159 (8)

129 (7)

Number of batches

4

4

8

9

7

Concentration range (g/L)

53.0 .0 – 104.5

2.6 – 88.0

4.1 – 204.1

0 - 77.66

1.0 – 43.0

Mean (g/L) + SD

80.1 + 13.3

16.3 + 13.6

81.8 + 60.7

25.9 + 18.4

11.5 + 9.8

*Number of spiked samples is indicated in brackets SD Standard deviation

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Table S2 Results of applying interval selection in PLS modelling for glucose, fructose, sucrose, 1-kestose and nystose Validation statistics Sugar

Model

Calibration statistics

Fructose

Sucrose

1-Kestose

Nystose

50% data split

Percentage improvement in avg RMSEP

Variable selection

Number of latent variables

R2

RMSEC (g/L)

RMSECV (g/L)

RMSEP (g/L)

RMSEP (g/L)

%

None

5

0.854

4.6

5.2

5.5 + 0.2

6.1

0.00

a

forward iPLS

5

0.840

4.7

5.3

6.2 + 1.0

6.9

-13.2

b

reverse iPLS

6

0.829

4.8

5.5

7.3 + 1.1

6.6

-34.4

None

6

0.940

3.0

3.3

3.9 + 0.1

3.7

0.00

c

forward iPLS

8

0.973

2.0

2.3

2.2 + 0.4

2.8

44.0

d

reverse iPLS

6

0.940

3.1

3.3

3.2 + 0.4

4.3

17.5

None

6

0.944

13.8

14.4

13.6 + 0.9

15.3

0.00

e

forward iPLS

7

0.974

9.1

9.7

10.0 + 0.3

10.6

26.0

f

reverse iPLS

6

0.945

13.4

14.2

14.4 + 0.3

15.2

-6.4

None

6

0.819

7.2

7.8

8.4 + 0.8

7.8

0.0

g

forward iPLS

5

0.864

6.1

6.8

6.9 + 0.5

8.5

18.2

h

reverse iPLS

7

0.869

5.6

6.7

6.4 + 0.4

7.5

23.5

None

4

0.911

2.6

2.9

2.9 + 0.4

2.8

0.00

i

forward iPLS

4

0.940

2.2

2.4

2.6 + 0.4

2.2

11.6

j

reverse iPLS

6

0.945

2.0

2.3

2.7 + 0.3

2.7

7.8

Wavenumbers used (cm-1) Glucose

70% data split Average + SD

3996.461 901.135

3996.461 901.135

3996.461 901.135

3996.461 901.135

3996.461 901.135

Number samples –









112

151

180

159

129

of

SD Standard deviation (n = 3) R2 Coefficient of determination

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