Determination Of Fermentation Level Of Keemun Black Tea By Near Infrared Spectrum Technology

Keemun black tea,referred as black tea,is a kind of traditional Congou black tea in China.Fermentation is the key process in the manufacturing of the Congou black tea,which is essentially the series of biochemical reactions concentrated on the enzymatic oxidation of tea,and it forms the unique characters of this tea.The quality of tea will be degraded by either over-fermentation or under-fermentation.In the practice,the sensory elements such as the aroma and the color are the main indicators for the level of fermentation.They are not only based on the human physiological senses and experience but also in the lack of quantitative indicators.And the subjective determination due to different factors,e.g.,gender and mood,requires a long-term learning and training for the adjudicator.Thus,a rapid and accurate supervising method for the fermentation of black tea is urgently needed in the processing.Near infrared spectroscopy?NIRS?can achieved determination and pattern recognition analysis of mulit-component content,and it is nondestructive,real-time monitoring than chemical analytical methods.In recent years,the need for scientific and reliable screen methods of authenticity and species identification has enhanced the application of NIRS for level control in the agriculture,pharmaceuticaland food industry.In order to find out a scientific and accuracy method to define optimum fermentation during the processing fermentation of black tea.So we explored the relation ship between the NIR spectra and the fermentation level of Keemun black tea,which is build model to estimate black tea fermentation level by NIRS.The main results of the dissertation involve:?1?Near infrared spectroscopy?NIRS?combined with contents of catechins build the models for estimating fermentation level of Keemun black tea.The optimized quantified model is filtered out by comparing different models which are from the spectral preprocessing,the principal components factors?PCs?and the characteristic wavelength selection.Experimental results showed that the original spectra data were preprocessdby the Standard Normal Variate Transformation?SNVT?method.And the model of NIRS with the contents of a catechins combined with Synergy Interval Partial Least squares?Si-PLS?was established.The correlation coefficients and the cross validation root mean square error are treated as the efficient indexes for evaluating models.The results showed that the optimal prediction model of amino acids by Si-PLS contained20 spectral intervals combined with 3subintervals and 10 principal component factors.The correlation coefficient and the root mean square error of the calibration set were 0.9401 and 1.22,respectively;the correlation coefficient and the root mean square error of the prediction set were 0.9379 and 2.16,respectively.?2?The model for predict fermentation level of the Keemun black tea was established using NIRS combined with contents of amino acids.The original spectra data were processed by the Standard Normal Variate Transformation?SNVT?method.And the model of NIRS with the contents of amino acids combined with Si-PLS was established in this study.Experimental results showed the optimal prediction model of catechins by Si-PLS contained 20 spectral intervals combined with 4subintervals and 9 principal component factors.The correlation coefficient and the root mean square error of the calibration set were0.9558 and 1.768,respectively;the correlation coefficient and the root mean square error of the prediction set were0.9495 and2.16,respectively.?3?NIRS combined with the image processing was employed for building the model to predict fermentation level of Keemun black tea.The leaves pictures of different fermented quality were collected and transformed into color digital information values?RGB forms?.And the model of NIRS with the contents of R-value,?R+G?-value and?R/B?-value combined with Partial Least squares?PLS?was established in this study.The results showed that the prediction is model of?R+G?-value,the correlation coefficient and the root mean square error of the calibration set were0.8559 and 4.8,respectively;the correlation coefficient and the root mean square error of the prediction set were0.8425and6.5,respectively.The results indicated that could be efficiently employed to discriminate black tea from different fermentation quality.However,R-value and?R/B?-value could not be achieved to estimate black tea fermentation level.?4?NIRS combined with Partial Least Squares-Discriminant Analysis,?PLS-DA?method was employed to build estimate the models to predict fermentation level of Keemun black tea.The effects on the spectral region,the spectral preprocessing methods and PCs to results were discussed.The results showed that the optimal number of PLS-DA factors were 9,the spectral ranges was 6503.92-5299.65cm^-1,and spectral preprocessingmethod was SNVT for the best identification model.Identification accuracy rate of the model was up to 93.96% for known samples from the correlation set.this technique could therefore be achieved to estimate black tea fermentation level.