caa a22 4500 606243151 CHVBK 20210128101323.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s11694-014-9214-3 doi (NATIONALLICENCE)springer-10.1007/s11694-014-9214-3 Improved partial least squares regression for rapid determination of reducing sugar of potato flours by near infrared spectroscopy and variable selection method [Elektronische Daten] [Xudong Sun, Xiaoling Dong] The feasibility of near infrared (NIR) spectroscopy coupled with variable selection methods for rapid determination of reducing sugar content in potato flours was investigated. Monte Carlo uninformative variable elimination (MCUVE), successive projections algorithm (SPA) and genetic algorithm (GA) were performed comparatively to choose characteristic variables associated with reducing sugar distributions. Eighty three and twenty seven samples were used to calibrate models and assess the performance of the models, respectively. Through comparing the performance of partial least squares regression models with new samples, the optimal models of reducing sugar was obtained with 12 selected variables by combination of MCUVEand SPA method. The correlation coefficient of prediction (r p ) and root mean square errors of prediction(RMSEP) were 0.981 and 0.243, respectively. The results suggest that NIR technique combining with MCUVE and SPA has significant potential to quantitatively analyze reducing sugar in potato flours; moreover, it could indicate the related spectral contributions. Springer Science+Business Media New York, 2014 Near infrared spectroscopy nationallicence Monte Carlo uninformative variable elimination nationallicence Successive projections algorithm nationallicence Reducing sugar nationallicence Potato nationallicence Sun Xudong School of Mechatronics Engineering, East China Jiaotong University, 330013, Nanchang, People's Republic of China aut Dong Xiaoling School of Foreign Langue, East China Jiaotong University, 330013, Nanchang, People's Republic of China aut Journal of Food Measurement and Characterization Springer US; http://www.springer-ny.com 9/1(2015-03-01), 95-103 2193-4126 9:1<95 2015 9 11694 https://doi.org/10.1007/s11694-014-9214-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s11694-014-9214-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Sun Xudong School of Mechatronics Engineering, East China Jiaotong University, 330013, Nanchang, People's Republic of China aut NATIONALLICENCE 700 1- Dong Xiaoling School of Foreign Langue, East China Jiaotong University, 330013, Nanchang, People's Republic of China aut NATIONALLICENCE 773 0- Journal of Food Measurement and Characterization Springer US; http://www.springer-ny.com 9/1(2015-03-01), 95-103 2193-4126 9:1<95 2015 9 11694