title: Measurement of non-sugar solids content in Chinese rice wine using near infrared spectroscopy combined with an efficient characteristic variables selection algorithm.
abstract: 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 (Rc) in calibration set and similarly tested by mean square error of prediction (RMSEP) and correlation coefficient (Rp) 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: Rc=0.95 and RMSEC=1.12 in the calibration set, Rp=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.
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Qin
authors.initials: Q
authors.lastname: Ouyang
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China.
authors.forename: Jiewen
authors.initials: J
authors.lastname: Zhao
authors.affiliation: School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China. Electronic address: qschen@ujs.edu.cn.
authors.forename: Quansheng
authors.initials: Q
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D002241:Carbohydrates / Q000032:analysis*; D005504:Food Analysis / Q000379:methods*; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D012275:Oryza / Q000737:chemistry*; D019265:Spectroscopy, Near-Infrared / Q000379:methods*; D014920:Wine / Q000032:analysis*
chemical_list: D002241:Carbohydrates
keywords: Chinese rice wine; Competitive adaptive reweighted sampling; Near infrared spectroscopy; Non-sugar solids; Synergy interval partial least square