A Novel Classification and Evaluation Algorithm for Blend Vegetable Oils

Blend vegetable oils supply our daily nutrition. A judge of quality guides us to choose appropriate blend vegetable oils. The blend oil market has the problem of mislabeling and ambiguity of ingredients proportion. A novel classification and evaluation algorithm for blend vegetable oils is proposed to standardize the blend oil markets. After double times of fluorescence intensity values of blend vegetable oils, the algorithm gets the summation of an excitation-emission-matrix along the direction of excitation wavelength (or the direction of emission wavelength) over the region of the characteristic spectra which means an area with higher fluorescence intensity values or an area different from others and then gets the envelope and calculates its statistical characteristic values. Take the statistical characteristic values to do partial least squares (PLS) regression to the values of classification and evaluation. At last symbolic results are presented. The algorithm offers a way of standard of blend vegetable oils using judge of classification and evaluation of blend vegetable oils. It is useful to build a health blend vegetable oils market.