Instrumental testing of tea by combining the responses of electronic nose and tongue

Banerjee, Rajib; Tudu, Bipan; Shaw, Laxmi; Jana, Arun; Bhattacharyya, Nabarun; Bandyopadhyay, Rajib

doi:10.1016/j.jfoodeng.2011.12.037

Cited by 124 publications

(32 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The entire transient response for each sensor is considered for analysis. The electronic nose and tongue sensors used in this work are described in detail in [9,10].The experimental conditions used for electronic nose and tongue is given in [4].…”

Section: Experimentationmentioning

confidence: 99%

“…Like human taster simultaneous utilization of aroma and taste sense will give better discrimination and that is already applied in several areas [1][2][3]. Authors have reported the research work on tea quality analysis based on fusion of these two sensor responses using neural network [4].Here we have attempted to fuse two sensory responses and analyzed using three different classifiers. The fusion techniques attempted in this work is based on fuzzy logic and neural network.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fusion of Electronic Nose and Tongue Response Using Fuzzy based Approach for Black Tea Classification

Banerjee

Modak

Mondal

et al. 2013

Procedia Technology

Self Cite

View full text Add to dashboard Cite

Automation for tea quality estimation is a challenging task and with the advent of electronic nose and electronic tongue systems this problem becomes quite addressable by instrumental means. Electronic nose judges tea sample based on aroma of the sample and based on taste tea quality can be classified using electronic tongue. For estimation of flavour of tea rather the overall quality of tea can be estimated if these two sensory responses can be fused. In this work, we have attempted to fuse these two sensory features using fuzzy fusion technique. A general fuzzy rule base is developed from the transient datasets obtained from electronic nose and tongue separately. The fuzzy system model can give accurate prediction with much simpler model than neural network. But both the system has certain advantages. In order to develop better classifier fuzzy neural network (FNN) model is also developed. Moreover the model works with transient responses and no data compression technique is employed. It is found that the combined sensor signature regarding tea quality estimation is quiet improved compared to individual sensor systems for all three classifiers and among these FNN is the best suited model for tea classification.

show abstract

Section: Experimentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fusion of Electronic Nose and Tongue Response Using Fuzzy based Approach for Black Tea Classification

Banerjee

Modak

Mondal

et al. 2013

Procedia Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…A combination of the nose and tongue was also found to markedly improve classification properties (Deisingh et al, 2004). Recently, Banerjee et al (2012) showed that the integration of e-nose and e-tongue systems improved the classification accuracy in tea quality assessment.…”

Section: Multisensory Flavour Perception As Distinct Of Eating Hedonicsmentioning

confidence: 98%

Challenges in relating concentrations of aromas and tastes with flavor features of foods

Regueiro

Negreira

Simal‐Gándara

2015

Critical Reviews in Food Science and Nutrition

View full text Add to dashboard Cite

Flavor sensations in food are highly influenced by the aroma and taste compounds. Reviewing the extensive literature of recent years in this field has shown that the reconstitution of flavor based on aroma and taste compounds poses numerous problems. These are of different nature and include among others (a) chemical transformations among these compounds, (b) changes in the concentrations of the compounds responsible for the perceived flavor, (c) interactions among the chemical compounds that enhance or reduce a specific flavor sensation, and finally, (d) the complexity of the different food matrices and its influence in the flavor perception. Another difficulty that flavor scientists must face is how to properly model and visualize the complex relationships existing between the chemical composition of foods and the flavor perception. These problems have repercussions on the reconstitution of the flavor signature of food based on the natural concentrations of its key aroma and taste compounds. Therefore, the main aim of this review is to deal with all these issues to propose potential solutions for a robust transformation in a science-based quality approach.

show abstract

“…These hybrid systems provide better discrimination and classification of samples than separated electronic tongue or electronic nose. In recent years, more and more hybrid systems were studied, especially in food industry [12][13][14]. Considering both taste and odor are natural properties of food, we believe combination of electronic nose with electronic tongue could provide sufficient information of food only if suitable methods for model recognition are used.…”

Section: Bioinspired Smell and Taste Hybrid Systemmentioning

confidence: 99%

Future Trends of Bioinspired Smell and Taste Sensors

Wang

Zhuang

Zou

et al. 2015

Bioinspired Smell and Taste Sensors

View full text Add to dashboard Cite

Anosmia and ageusia are both harmful to the quality of life. However, the common view of anosmia and ageusia as trivial can make it more difficult for a patient to receive the same types of medical aid as someone who has lost other senses, such as sight or hearing. In order to achieve those goals, electronic noses and electronic tongue should be designed to mimic human's sense rather than outputting electrical parameters only. Unfortunately, most commercial electronic noses (PEN3, zNose) detect volatile compounds in samples [1]. But for human beings, our nose can determine whether the sample is fragrant or not instead of determining what compounds are in the sample.For human beings, the sense of taste consists of five basic tastes including sourness, saltiness, umami, bitterness, and sweetness [2]. When tasting a food or beverage, a human perceives each type of taste on sensory organs called taste buds on the tongue. Taste buds are composed of approximately 50-100 cells. Many kinds of gustatory receptors present in gustatory cells. Each gustatory receptor receives multiple chemical substances constituting a single taste. Namely, gustatory receptors exhibit semi-selectivity rather than rigid and high selectivity. While those researches on the molecular and cellular biology of taste reception has been

show abstract

Instrumental testing of tea by combining the responses of electronic nose and tongue

Cited by 124 publications

References 30 publications

Fusion of Electronic Nose and Tongue Response Using Fuzzy based Approach for Black Tea Classification

Fusion of Electronic Nose and Tongue Response Using Fuzzy based Approach for Black Tea Classification

Challenges in relating concentrations of aromas and tastes with flavor features of foods

Future Trends of Bioinspired Smell and Taste Sensors

Contact Info

Product

Resources

About