XTERNAL CAVITY-QUANTUM CASCADE LASER SPECTROSCOPY … · JK acknowledges a Sara Borrell grant...
Transcript of XTERNAL CAVITY-QUANTUM CASCADE LASER SPECTROSCOPY … · JK acknowledges a Sara Borrell grant...
EXTERNAL CAVITY-QUANTUM CASCADE LASER SPECTROSCOPY AND CHEMOMETRICS FOR
PROTEIN ANALYSIS IN COW’S MILK
Julia Kuligowski1,2*, Andreas Schwaighofer2, Mirta R. Alcaráz2,3, Máximo Vento1,4, Bernhard Lendl2
1Neonatal Research Group, Health Research Institute La Fe, Valencia, Spain 2Institute for Chemical Technology and Analytics, Vienna University of Technology, Vienna, Austria
3Laboratorio de Desarrollo Analítico y Quimiometría, FBCB, Universidad Nacional del Litoral-CONICET, Santa Fe, Argentina 4Division of Neonatology, University & Polytechnic Hospital La Fe, Valencia, Spain
*e-mail: [email protected]
The authors acknowledge the Austrian Research Promotion Agency (FFG) within the K-project imPACts (contract no. 843546) for funding. JK acknowledges a Sara Borrell grant (CD12/00667) from Instituto Carlos III (Spanish Ministry of Economy and Competitiveness).
OBJECTIVE
CONCLUSIONS & OUTLOOK
The determination of total protein content in cow’s milk is a routine application of mid-infrared (IR) transmission spectroscopy. However, the quantitation of protein in this kind
of samples demands laborious and time consuming experimental work. We report an analytical method based on the direct spectroscopic determination of casein (Cas), α-
lactalbumin αLA and β-lactoglobulin βLG in cow milk samples.
1. An EC-QCL setup was applied for the determination of Cas, ɑLA and βLG.
2. The present method supports the direct analysis of samples without sample processing.
3. Background correction employing SBC is used for compensation of the milk matrix.
4. Quantification of proteins in off the shelf cow milk samples was carried out using PLS regression.
5. This high throughout method could potentially be employed as a standard tool for quality control of milk.
PARTIAL LEAST SQUARES REGRESSION MODELS FOR PROTEIN QUANTIFICATION
EC-QCL SETUP BACKGROUND CORRECTION
REFERENCES
1. M.R. Alcaráz, A. Schwaighofer, C. Kristament, G. Ramer, M. Brandstetter, H. Goicoechea, B. Lendl,
Anal Chem, 87, 6980-6987 (2015).
Grating angle
determines
emission
wavelength
Fourier Transform IR (FTIR) vs. EC-QCL Spectroscopy • Emission power: EC-QCL (mW) >> Globar (µW)
• Path length for acqueous solutions: FTIR <10 µm // EC-QCL 38 µm
• Flow-through measurements: not feasable (FTIR) // FIA system (EC-QCL)
• LOD: high protein concentration ~10 mg/ml (FTIR) // ~2.5 mg/ml (EC-QCL)
EC-QCL (Daylight Solutions)
1565 cm-1 – 1730 cm-1
Temp. stabilized
(Peltier-cooled)
EC-QCL Measurements [1] • No sample preparation
• Sample volume: 1 ml
• Acquisition time: 10 min
• Reference spectrum: H2O
Science Based Calibration (SBC) Single spectrum:
Set of spectra:
• Analyte signal: mean analyte spectrum ( ) ± standard dev. ( )
• Spectral noise: mean noise value ( ) ± covariance matrix ( )
If analyte concentration constant, after mean centering, spectra only contain information about the noise!
Concentration
Transposed analyte spectrum
Signal not derived from analyte
(Matrix, instrumental noise)
Pseudo-inverse of
covariance of spectral noise
Matrix components (e.g. sugar, fat) in milk modify background absorption
Variation in the sample’s water content
Background correction necessary
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-0.07
-0.06
-0.05
-0.04
-0.03
-0.02
Wavenumbers [cm-1
]
Ab
so
rba
nc
e [
AU
]
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0.1
0.15
0.2
0.25
Wavernumbers [cm-1
]
Ab
so
rba
nc
e [
AU
]
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-0.04
-0.02
0
0.02
0.04
0.06
0.08
Wavenumber [-1
]
Ab
so
rba
nc
e [
AU
]
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0.05
0.1
0.15
0.2
Wavenumbers [cm-1
]
Ab
so
rba
nc
e [
AU
]
1. Collect lactose spectrum 2. Collect spectra of protein
standard mixtures
3. Collect spectra of (spiked)
cow milk samples
4. Compute optimum b
vector (bopt)
5. Predict lactose concentration
(ypred) in milk spectra (xpred)
6. Subtraction of lactose
proportion from signal
Mean analyte
concentration
Mean noise
spectrum
Protein concentrations In commercially available milk
samples
• Cas: 24.5±1.4 mg mL-1
• αLA: 1.4±0.9 mg mL-1
• βLG: 2.4±0.2 mg mL-
Recoveries Spiked milk samples
• Cas: 95±8%
• αLA: 101±22%
• βLG: 99±4%
PLS models for protein
determination • Calibration set: spectra of
10 standard mixtures and
their concentrations
• Cross validation: Leave-
one-out
• Validation set: background
corrected spectra of
(spiked) milk samples
0 10 20 300
10
20
30
40
Measured Cas [mg/mL]Pre
dic
ted
Cas
[m
g/m
L]
Casein Preprocessing: Mean Center; Num. LVs: 4
RMSEC: 0.5; RMSECV: 1.3; RMSEP: 2.1
Bias: 0; CV Bias: -0.2
R2 Cal: 0.998; R2 CV: 0.990
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1
1.5
2
2.5
Wavenumber [cm-1]
VIP
Sc
ore
s f
or
Cas
2 4 6 8 10
0
5
10
Measured aLA [mg/mL]
Pre
dic
ted
aL
A [
mg
/mL
]
ɑLA Preprocessing: Mean Center; Num. LVs: 4
RMSEC: 0.3; RMSECV: 0.7; RMSEP: 0.7
Bias: 0; CV Bias: 0.03
R2 Cal: 0.990; R2 CV: 0.94
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1
1.5
2
2.5
Wavenumbers [cm-1]
VIP
Sc
ore
s f
or
aL
A
VIP Scores for Cas
Significance Threshold
Cas 20 mg/mL x 200
βLG Preprocessing: 1st Derivative (order: 3, window: 15 pt), Mean
Center; Num. LVs: 4
RMSEC: 0.10; RMSECV: 0.3; RMSEP: 0.20
Bias: 0; CV Bias: -0.0011
R2 Cal: 0.9990; R2 CV: 0.990
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2
3
4
Variable
VIP
Sc
ore
s f
or
Y 3
0 5 100
5
10
Measured bLG [mg/mL]
Pre
dic
ted
bL
G [
mg
/mL
]
VIP Scores for aLA
Significance Threshold
aLA 20 mg/mL x 200
Fit
1:1
Calibration
Test
VIP Scores for bLG
Significance Threshold
bLG 20 mg/mL x 200
Fit
1:1
Calibration
Test
Fit
1:1
Calibration
Test