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Doctoraatsverdediging
Menghui Zhang
Multivariate calibration
of the antioxidant capacity of green tea
The thesis describes the development of a rapid and
convenient method for the determination of the total antioxidant capacity
in green tea, using near-infrared (NIR)
spectroscopy and multivariate calibration. NIR is an indirect method and
a calibration model therefore needs to be constructed by relating the
NIR spectrum of green tea samples with the corresponding antioxidant capacity
values, which are measured by a reference method called "Trolox Equivalent
Antioxidant Capacity assay". The thesis focuses on two problems that
are often encountered in modelling. One is outlier detection. A new method
called "Robust principal components regression based on principal
sensitivity vectors" is proposed and its outlier detection ability
is investigated. The other problem is the selection of an adequate number
of components to be included in the partial least square model. A model
with a too small number of components may lead to bad prediction since
some relevant information is not included whereas a model with a too large
number of components may lead to the perfect fitting of the calibration
samples but poor prediction for new samples (overfitting). Two novel methods,
"Averaged partial least squares" and "Boosting partial
least squares", are proposed to solve this problem.
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