Use of In-Situ Visible and Near-Infrared Spectroscopy for Non-invasive Discrimination of Spirulina Platensis

• Published in: 2009 International Conference on Computational Intelligence and Security Vol. 1; pp. 330 - 334
• Main Authors: Di Wu, Tianyun Ma, Pengcheng Nie, Zhiping Wang, Zhengjun Qiu, Yong He
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2009
• Subjects: Calibration; Condition monitoring; Educational institutions; genetic algorithms and partial least square (GA-PLS); Helium; Infrared spectra; Input variables; Projection algorithms; Reflectivity; Spectroscopy; Spirulina platensis; Successive projections algorithm (SPA); Uninformation variable elimination (UVE); Visible and near infrared (Vis-NIR) spectroscopy; Wavelength measurement
• ISBN: 1424454115; 9781424454112
• DOI: 10.1109/CIS.2009.277

This paper evaluated the feasibility of using visible and near infrared (Vis-NIR) spectroscopy for the non-invasive discrimination of Spirulina platensis. The reflectance spectra of Spirulina platensis culture medium were measured. Full-spectrum obtained an 86.69% correct answer rate (CAR) for the discrimination of twelve species. Several spectral wavelength variable selection algorithms were operated. A hybrid variable selection algorithm of uninformation variable elimination (UVE) and successive projections algorithm (SPA) obtained the best result of 87.22% of CAR for the prediction set than other methods, including SPA, UVE and UVE-genetic algorithms(GA)-partial least squares(PLS). These results show the possibility for the non-invasive discrimination of Spirulina platensis using Vis-NIR spectroscopy, and UVE-SPA is a good spectral variable selection algorithm. It is necessary to operate UVE before SPA, which can both reduce the calculation time and increase the model' s performance.