Practical application
In this paper, a hierarchical approach was proposed for the
detection and quantification of adulteration of sesame oils using
gas chromatography and multivariate data analysis. The detection
model was developed by support vector machine algorithm, and
the quantification model was constructed using partial least square
method. All the above models can achieve satisfactory results,
implying that the proposed approach is an efficient tool for the
problem of adulterated sesame oils.