  This paper presents a new approach of applying partial least squares method
combined with a physical principle based dominant factor. The characteristic
line intensity of the specific element was taken to build up the dominant
factor to reflect the major elemental concentration and partial least squares
(PLS) approach was then applied to further improve the model accuracy. The
deviation evolution of characteristic line intensity from the ideal condition
was depicted and according to the deviation understanding, efforts were taken
to model the non-linear self-absorption and inter-element interference effects
to improve the accuracy of dominant factor model. With a dominant factor to
carry the main quantitative information, the novel multivariate model combines
advantages of both the conventional univariate and PLS models and partially
avoids the overuse of the unrelated noise in the spectrum for PLS application.
The dominant factor makes the combination model more robust over a wide
concentration range and PLS application improves the model accuracy for samples
with matrices within the calibration sample set. Results show that RMSEP of the
final dominant factor based PLS model decreased to 2.33% from 5.25% when using
the conventional PLS approach with full spectral information. Furthermore, with
the development in understanding the physics of the laser-induced plasma, there
is potential to easily improve the accuracy of the dominant factor model as
well as the proposed novel multivariate model.
