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A fundamental problem for any food industry, particularly one that deals with processing of a natural agricultural commodity, like Black Tea, is the relationship between perceived quality by human against the presence of natural bio-chemical compounds in the produce. Black Tea is characterized by four principal quality attributes; namely: a) appearance, b) aroma, c) taste and d) flavour. Estimation, characterization and quantification of aroma and appearance of Black Tea have been an unmet challenge of the tea scientists for very long. On one hand, methodologies for estimation of such perceived quality being human-dependent, difficulties like subjectivity, non-repeatability and lack of reproducibility create huge problem towards any efforts of standardization of Black Tea quality. On the other hand, besides high cost, sample preparation complexities and non-availability of expert manpower make chemical analysis methods anchored on chromatographic techniques cumbersome and, most importantly, unsuitable for online deployment. So, an emergent need for some physical, fast and low cost methodology for measurement of physical quality attributes, like smell and appearance, is felt by one and all in the domain of food processing industries, in general and Black Tea Manufacturing Industries in India in particular. The ENOVISION system underpins this very problem for the Black Tea Manufacturing/Blending Industries and proposes a pragmatic methodology for measurement of aroma and appearance of Black Tea by fusion of advanced sensor technologies, backed up with intelligent self-learning type software algorithms. The methodologies developed are physical, fast, objective, inexpensive and affordably deployable in Black Tea Industries. The Electronic Nose based aroma indices, innovated through sustained experimentations in Black Tea Fermentation Process, enable online smell monitoring and detection of optimum fermentation time for producing best flavor components in the manufactured Black Tea. The neural network based self-learning type of computational models built into the E-Nose Software System permit fast declaration of quality scores of finished Black Tea, coherent with the organoleptic appraisals of the Tea Tasters. The Electronic Vision system, on the other hand, monitors the colour change during tea fermentation process online to predict the same optimal Fermentation Time. Other appearance parameters, like granular gradation and fibre content of manufactured Black Tea, or colour characterization of tea liquors and infusion, are also built into in the same E-Vision system. The entire system is software driven, field-customisable and requires minimum operator intervention. It is also fully autonomous while measuring Quality of Black Tea in a physical, reliable and affordable manner. The system is presently in pilot deployment phase in few Tea Industries in India and Kenya. The ENV technology being a core technology, it is anticipated that multi-dimensional applications in food & beverage sector, agricultural produces etc. would blossom in days to come. This novel application of electronics and information technology with multiple applications potential possesses immense scope of up scaling and commercialization.

What we deliver

A product named ENOVISION, which is an Integrated version of Electronic Nose & Vision System for quality measurement of Black Tea along with the software solution loaded in a desktop PC or laptop. The developed product will be used in the following applications: 1. Online fermentation process control. 2. Tea Tasting. Target Group: 1. Tea Industries 2. Tea Tasting, broking and auction centres. 3. Tea research Laboratories 4. Educational Institutes.

Whom we deliver

1. Tea Industries 2. Tea Quality Control Laboratories 3. Research Organizations/ Educational Institutes etc.

How is the project unique?

The product is novel and unique in following aspects. a) Such system has been developed and deployed with the users (tea industries) for the first time in India as well as in world perspective too. b) The system attempts to quantify quality of agricultural produce like tea for the first time in rapid and real time manner. As of date, there is no gadget known to have these attributes. c) The system is user-friendly and anybody and everybody with very basic computer awareness may use the system. d) The system is affordable and need minimum maintenance. e) The innovation quantifies quality parameters of tea which were otherwise estimated through human sensory panel. This may open up new global standards of tea.


Center For Development Of Advanced Computing (C-DAC), Kolkata
Dr. Nabarun Bhattacharyya, Associate Director, C-DAC (K)
Plot E2/1, Block-GP, Sector-V, Bidhannagar, Saltlake, Kolkata-700091, West Bengal, – 700091 India
URL/Website –

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