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Independent component analysis (ICA) is a blind source signal processing technique that separates the source signal from the mixed signal. ICA makes great progress in researches and applications in the field of spectroscopy. This review summed up the principles and theoretical foundations of ICA algorithm in spectral analysis, the commonly used and advanced ICA algorithms, and the strategies for determining the optimal number of independent components. Then the progress of researches and applications of ICA combined with other chemometric method for quantitative resolution in spectroscopy technique recently, including infrared, Raman, fluorescence, UV -visible and nuclear magnetic resonance spectroscopy were reviewed. The possible problems concerning ICA in the analysis of practical complex system were discussed and corresponding solutions were proposed, and the research trends and development futures of ICA in the field of quantitative analysis were also prospected. The review can provide a basis and reference for the selection and use of quantitative analytical strategies in the complex mixtures.