Pedro M. K. A.,Ferreira M. M. C., "Simultaneuosly Calibrating Solids, Sugars and Acidity of Tomato Products Using PLS2 and NIR Spectroscopy". Águas de Lindóia, SP, Brazil, 10-15/09/2006: 10th International Conference on Chemometrics in Analytical Chemistry (CAC-2006, CAC-X), Book of Abstracts (2006) OP35. Oral 035.
10th International Conference on Chemometrics in Analytical Chemistry OP35
Simultaneously Calibration
Solids, Sugars and Acidity of Tomato
Products Using PLS2 and
NIR Spectroscopy
André M. K. Pedro*1 and Márcia M. C. Ferreira2 andre.k.pedro@unilever.com
1Unilever Brasil
Ltda, Av. Invernada 401, Valinhos (SP), 13271-450, Brazil, 2Universidade
Estadual de
Campinas (UNICAMP), Chemistry
Institute, Physical Chemistry Department, Campinas (SP), 13083-970
Caixa Postal 6154, Brazil
Keywords: Fourier filter,
multivariate calibration, tomato quality
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The purpose
of this work is to develop a robust calibration model
for determining, simultaneously and
non-destructively,
relevant quality parameters in processed tomato products,
namely total and soluble
solids, total acidity and
sugars. These are key quality parameters once they
largely determine sensorial
profile and consumer acceptance
of tomato products.
Forty-two
samples of tomato concentrate products with total solids
content ranging from 6.9 to 35.9%
were collected from
Latin America, the US and Europe. Three spectra
of each sample were acquired in
the 4000
to 10000 cm-1 region
using a Büchi NIRLab N-200 spectrometer
with a MSC-100 diffuse
reflectance cell.
Total solids were determined by oven-drying
under vacuum (70º, ~150 mmHg abs.
pressure) until constant
weight. Soluble solids were determined using a Metrohm 702 automatic titrator
and
NaOH 0.1 mol L-1
Merck standard solution. Sugars were quantified by HPLC using an
Shimatzu refractive
index detector, a
Shodex NH2P-50 4E column and
Shodex NH2P-50G column-guard.
Mobile phase was
acetonitrile:water (75:25),
isocratic, 1 mLmin-1.
Simultaneous
Partial Least Squares (PLS2)1,2
was used to build the calibration models.
Original
spectra were
pre-processed by applying a 50-points mean smoother,
followed by multiplicative signal
correction (MSC)1-3.
Alternatively, a Fourier filter with Gaussian convolution function was
applied, followed
by MSC and
first- or second-derivatives according
to Savitsky and Golay4.
Seven samples were
separated for
external validation and the others were used in
the calibrations. The optimum number of
factors was determined by
leave-one-out cross validation1,2.
Comparisons between different models were
performed through RMSEP
and rval1,2. PLS1
models were built for comparison as well1,2.
Results
have shown that PLS2 gave models with
better prediction abilities and/or with
a smaller
number of factors than PLS1.
The best pre-processing strategy was mean smoothing followed
by MSC;
despite the
Fourier filter followed by MSC giving quite similar results,
it is a more complex approach. The
RMSEP for each
property was: total solids, 0.6294; soluble solids,
0.6755; total acidity, 0.2189; total
sugar, 1.9648;
glucose, 0.5365 and fructose, 0.8802. The final model
required only 4 factors, much less
than PLS1 models previously
reported5.
As conclusion,
PLS2 gave a good model for predicting the levels of important properties
of concentrate
tomato products.
Despite its usage not being widely
reported in the literature, this application clearly
shows the advantages
of PLS2 over PLS1 for some applications,
as a better and simpler model was
obtained.
Acknowledgement.
The authors would like to thank Colin Haine, Unilever's Head of the
Tomato Global
Technology Centre, and his
team, for providing the samples for this study.
__________________________________________________________________________________________________________________________
References
1Martens H.; Naes
T. Multivariate Calibration (2nd edn), vol. 1. Wiley: Chichester, UK, 1989.
2Beebe K. R.;
Pell R. J.; Sheasholtz M.B. Chemometrics: a Practical Guide, Wiley: New
Yourk, US, 1998.
3Isakson T.;
Naes T. Appl. Spectrosc. 1988, 42, 1273-1286.
4Savstsky A.;
Golay M. Anal. Chem. 1964, 36, 1627.
5Ferreira M.M.C.,
Pedro A.M.K. Anal. Chem. 2005, 77, 2505-2511.