Identification of paralytic shellfish poison producing algae based on three-dimensional fluorescence spectra and quaternion principal component analysis

In view of the problem of the paralytic shellfish poison producing algae on-line measurement and iden-tification, a new feature extraction method of paralytic shellfish poison producing algae measurement and identification based on quaternion principal component analysis (QPCA) is investigated. The three-dimensional (3D) fluorescence spectra of three common species of paralytic shellfish poison producing algae and eight species common of non paralytic shellfish poison producing algae are analyzed. The quaternion parallel representation model of algae three-dimensional fluorescence spectrum data is established, then the features of quaternion principal component is extracted to use as the input of k-nearest neighbor (KNN) classifier, and the identification of paralytic shellfish poison producing algae is realized by the three-dimensional fluorescence spectra coupled with quaternion principal component analysis. The results show that under the quaternion parallel representation model, the recognition accu-racy rate of multiplication feature, modulus feature and summation feature is 90%, 95% and 100% respec-tively. Compared with that of the principal component analysis feature extraction method, the recognition accuracy rate in pure samples by summation feature of quaternion principal component is improved by 10%. This study provides an experimental basis for the accurate monitoring technology of three-dimensional fluorescence spectrum of paralytic shellfish poison producing algae. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

A new feature extraction method based on quaternion principal component analysis is investigated to improve the identification accuracy of paralytic shellfish poison producing algae, providing an experimental basis for accurate monitoring technology of three-dimensional fluorescence spectrum.