Abstract: Consensus modeling averages the results of multiple independent models to obtain a single prediction, which avoids the instability of a single model. Based on the philosophy of consensus modeling, a consensus partial least squares regression(cPLS) method was proposed and applied to building the quantitative model of NIR spectra of tobacco samples. Through an investigation of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of chlorine in tobacco samples. With repeated independent runs, cPLS model was found to be more robust and credible than PLS model. Furthermore, compared with PLS method, cPLS model gives more stable and accurate prediction results.

Key words: Consensus modeling, Partial least squares, Near-infrared spectroscopy, Tobacco sample, Quantitative analysis