Preemptive identification of optimum fermentation time for black tea using electronic nose

Abstract

During black tea manufacturing, tealeaves pass through the fermentation process, when the grassy smell is transformed into a floral smell. Optimum fermentation is extremely crucial in deciding the final quality of finished tea and it is very important to terminate the fermentation process at the right time. Present day industry practice for monitoring of fermentation is purely subjective and is carried out by experienced personnel. In this paper, a study has been made on real-time smell monitoring of black tea during the fermentation process using electronic nose as well as prediction of the correct fermentation time. The study has been implemented in two steps. First, for prediction of optimum fermentation time, five different time-delay neural networks (TDNNs), named as multiple-time-delay neural networks (m-TDNN), have been used. During the second study, we have investigated the possibility of existence of different smell stages during the fermentation runs of black tea processing using self-organizing map (SOM), and then used three TDNNs for different smell stages. The results show excellent promise for the instrument to be used by the industry.