Journal
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
Volume 151, Issue -, Pages 280-285Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.saa.2015.06.071
Keywords
Chinese rice wine; Non-sugar solids; Near infrared spectroscopy; Synergy interval partial least square; Competitive adaptive reweighted sampling
Categories
Funding
- National Natural Science Foundation of China [31271875]
- China Postdoctoral Science Foundation [2015M571698]
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The non-sugar solids (NSS) content is one of the most important nutrition indicators of Chinese rice wine. This study proposed a rapid method for the measurement of NSS content in Chinese rice wine using near infrared (NIR) spectroscopy. We also systemically studied the efficient spectral variables selection algorithms that have to go through modeling. A new algorithm of synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was proposed for modeling. The performance of the final model was back-evaluated using root mean square error of calibration (RMSEC) and correlation coefficient (R-c) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (R-p) in prediction set. The optimum model by Si-CARS-PLS algorithm was achieved when 7 PLS factors and 18 variables were included, and the results were as follows: R-c = 0.95 and RMSEC = 1.12 in the calibration set, R-p = 0.95 and RMSEP = 1.22 in the prediction set. In addition, Si-CARS-PLS algorithm showed its superiority when compared with the commonly used algorithms in multivariate calibration. This work demonstrated that NIR spectroscopy technique combined with a suitable multivariate calibration algorithm has a high potential in rapid measurement of NSS content in Chinese rice wine. (C) 2015 Elsevier B.V. All rights reserved.
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