CHEMOMETRICS ASSISTED UV-SPECTROPHOTOMETRIC ...

1.3. Multivariate methods
There are various chemometric or multivariate methods. All these methods commonly share
the basic principle in multivariate analysis. They are used to resolve the problem in analyzing
multi component mixture by allowing rapid and simultaneous determination of each
component in the mixture. The accuracy and precision is achieved without prior separation of
the components. This implies that these methods are time and cost effective. This will be
asserted more as follows:
The resolution of multi component preparations is often a complex analytical problem since
combined substances may have different chemical structures but similar properties, like
chromatographic behaviour and UV spectra. Multivariate calibration is a useful tool in
analysis of multi component mixture because it allows the rapid and simultaneous
determination of each component in the mixture with minimum sample preparation,
responsible accuracy and precision and without the need of lengthy separation [35].
Although various methods are there in application, three of them will be treated here for the
convenience of the study.
1.3.1. Classical least squares regression analysis (CLS)
CLS is one of the traditional regression algorithms, that depends on the Beer Lambert law
with assistance of close tools mixtures of components with overlapping spectra will be
resolved. Beer’s law describes the relationship between two variables, the spectral response
(A) and the constituent concentration (c), and two constants, the intercept (a) and the
regression coefficient (b)
A λ 1 = CaKa λ 1+CbKb λ 1 ...........................................[3]
According to beer’s law absorbance of multiple constituent at a given wave length is additive.
A λ 2 = CaKa λ 2+CbKb λ 2......................................... [4]
A λ 1 = CaKa1+CbKb1…..CnKn λ1+E λ1.................... [5]
A λ 2 = CaKa2+CbKb2+…..CnKn λ1+E λ2................. [6]
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