Chemometric Models for the Quantitative Descriptive Sensory Properties of Green Tea ( Camellia sinensis L.) Using Fourie
- PDF / 940,425 Bytes
- 9 Pages / 595.276 x 790.866 pts Page_size
- 100 Downloads / 192 Views
Chemometric Models for the Quantitative Descriptive Sensory Properties of Green Tea (Camellia sinensis L.) Using Fourier Transform Near Infrared (FT-NIR) Spectroscopy Hui Jiang & Quansheng Chen
Received: 15 March 2014 / Accepted: 21 August 2014 # Springer Science+Business Media New York 2014
Abstract Multivariable models based on chemometric analyses of the tea infusion sensory data and FT-NIR spectra of 70 “Biluochun” green tea (Camellia sinensis L.) samples were generated aiming to predict the scores of sensory attributes of green tea. Modified BP_AdaBoost algorithm was used to develop the models. The synergy interval partial least square (siPLS) algorithm was applied to select the wavenumbers for the prediction model of sensory properties in order to take only significant spectral intervals into account. Some parameters were optimized by cross-validation in model calibrations. Experimental results showed that the optimal BP_AdaBoost model was achieved with four principal components (PCs), when 184 variables in the combination of four spectral intervals [3 17 19 21] were selected by siPLS. The predicted precision of the best model obtained were as follows: the root mean square error of cross-validation (RMSECV) was 5.0305 and the correlation coefficient (Rc) was 0.8554 in the calibration set; the root mean square error of prediction (RMSEP) was 6.0807, the correlation coefficient (Rp) was 0.7717, and the ratio performance deviation (RPD) was 1.59 in the prediction set. Finally, the BP_AdaBoost model revealed its superior performance when compared with back propagation neural network (BPNN) model. The overall results demonstrate that FT-NIR spectroscopy technique can be successfully used in the evaluation of sensory quality of green tea, and BP_AdaBoost algorithm shows its superiority in model calibration.
H. Jiang (*) School of Electrical and Information Engineering, Jiangsu University, Zhenjiang 212013, People’s Republic of China e-mail: [email protected] Q. Chen (*) School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, People’s Republic of China e-mail: [email protected]
Keywords FT-NIR spectroscopy . Synergy interval partial least squares . Modified BP_AdaBoost . Green tea . Sensory analysis
Introduction Green tea is one of the most popular beverages consumed in the world, which is of great interest due to its beneficial medicinal properties (Chen et al. 2008). There are substantial amounts of polyphenols, caffeine, aroma-forming substance, and other compounds existing in green tea that have unique biological activities and health benefits, such as anti-cancer, anti-oxidation, anti-senescence, and protection against cardiovascular disease (Fujiki et al. 2001; Nakachi et al. 2000; Jian et al. 2004). In recent years, the production and consumption of the green tea, especially the famous green tea “Biluochun”, have increased greatly in China. Therefore, the quality evaluation for green tea has extremely been important in commercial trade. The taste of tea infusion is the inf
Data Loading...
