Non-destructive determination of total polyphenols content and classification of storage periods of Iron Buddha tea using multispectral imaging system

Total polyphenols is a primary quality indicator in tea which is consumed worldwide. The feasibility of using near infrared reflectance (NIR) spectroscopy (800–2500 nm) and multispectral imaging (MSI) system (405–970 nm) for prediction of total polyphenols contents (TPC) of Iron Buddha tea was investigated in this study. The results revealed that the predictive model by MSI using partial least squares (PLS) analysis for tea leaves was considered to be the best in non-destructive and rapid determination of TPC. Besides, the ability of MSI to classify tea leaves based on storage period (year of 2004, 2007, 2011, 2012 and 2013) was tested and the classification accuracies of 95.0% and 97.5% were achieved using LS-SVM and BPNN models, respectively. These overall results suggested that MSI together with suitable analysis model is a promising technology for rapid and non-destructive determination of TPC and classification of storage periods in tea leaves.