作者: Qin Ouyang , Jiewen Zhao , Quansheng Chen
DOI: 10.1016/J.SAA.2015.06.071
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摘要: Abstract The non-sugar solids (NSS) content is one of the most important nutrition indicators Chinese rice wine. This study proposed a rapid method for measurement NSS in wine using near infrared (NIR) spectroscopy. We also systemically studied efficient spectral variables selection algorithms that have to go through modeling. A new algorithm synergy interval partial least square with competitive adaptive reweighted sampling (Si-CARS-PLS) was performance final model back-evaluated root mean error calibration (RMSEC) and correlation coefficient (Rc) set similarly tested by prediction (RMSEP) (Rp) set. optimum Si-CARS-PLS achieved when 7 PLS factors 18 were included, results as follows: Rc = 0.95 RMSEC = 1.12 set, Rp = 0.95 RMSEP = 1.22 In addition, showed its superiority compared commonly used multivariate calibration. work demonstrated NIR spectroscopy technique combined suitable has high potential