Now More Than 600 Customers Worldwide
Since World-First e-Tongue 1993 Launch
Since Insent launched its world-first e-Tongue (electronic ‘tongue’) taste sensor in 1993, more than 600 business customers worldwide now use this product.
- Taste Evaluation Correlated with Human Gustatory Sensation: Using our patented technology, customers can access digital taste information captured by our high-sensitivity and high-selectivity sensors for the five basic tastes and astringency.
- High Data Reproducibility: High repeatability and reproducibility are achieved by automatically cleaning and checking the response of sensors after measuring each sample.
- Initial Taste and Aftertaste: Both the first impression (initial taste) and time-dependent aftertaste can be obtained for umami, bitterness and astringency, without multivariate analysis.
- Objective Taste Scale: An objective and universal taste intensity for a control sample is captured based on the Weber-Fechner Law using our proprietary algorithm.
Unique Biomimetic Membrane
These proprietary lipid and polymer membranes mimic living organisms.
Five Basic Tastes and Astringency
The bitter, sour, salty, umami, sweet tastes and astringency can be evaluated and correlated with intensity.
Equivalent to or Better than Human Taste Sensitivity
The taste-sensor sensitivity is designed to match human thresholds, and the response covers the human dynamic range (ranging from 1 to 10 times threshold)
High Basic-Taste Selectivity
Like antigen/antibody reactions, selectivity is not a one-to-one relation, but is instead like the ‘global selectivity’ similar to other human receptors.
Insent’s e-Tongue taste sensor is a biomimetic technology inspired by the structure and function of biological membranes. A single biological taste receptor can capture the same taste attribute, such as bitterness, for multiple chemicals. Our patented lipid/polymer membrane generates a voltage that changes according to the interaction with a specific taste attribute. The membrane response characteristics are adjusted by changing the types of membrane lipid and plasticizing agents as well as the ratio of multiple lipid types with selective responses to specific tastes (e.g., separate membranes that each respond specifically to bitterness, astringency, etc.).
[Reference]
[Collaborations]
Unique Aftertaste Measurement
Both initial taste and aftertaste can be captured from molecules adsorbed on the membranes.
Repeatability and Reproducibility
Reproducible test results are obtained by performing a cleaning process before and after every sample measurement.
Automatic Measurement
The system automates all measurement procedures after the operator manually sets the solutions.
Sensor and Protocol Selection
The standard set of sensors and test protocols can be customized for the test purpose.
The taste sensor outputs the change in potential relative to the membrane potential of a tasteless reference solution (e.g., Ag/AgCl saturated KCl solution of reference electrode). To perform electrochemically stable measurements, the reference-electrode electrolyte is a solution of 30 mM KCl and 0.3 mM tartaric acid.
The taste sensor evaluates two types of taste: initial, which is the perceived taste when food first enters the mouth, and aftertaste, which is the taste persisting in the mouth after swallowing the food. First, the initial taste is measured as the difference in the potential of the sample liquid versus the potential of the reference solution* as zero. Then, the sensors are lightly washed, and the aftertaste is measured as difference in potential versus the reference solution.
*Reference solution: a nearly tasteless solution of 30 mM KCl and 0.3 mM tartaric acid used to mimic human saliva.
Universal Taste Scale
Automatic transform from raw data to taste intensity like a measure based on Weber-fechner’s law.
Six Initial Tastes and Three Aftertastes
Sourness, saltiness, bitterness, astringency, umami, and sweetness are measured as initial tastes, while bitterness, astringency and umami are measured as aftertastes as well as initial tastes.
"Tastelessness" and Intensity
The results show which tastes have no perceivable intensity (tastelessness) and the strength or weakness compared to a target.
Instant Data Analysis
A new application supports on-the-fly analysis with one-click display of results.
The taste sensor is a chemical sensor that attempts to approximate the taste intensity perceived by people. According to the Weber-Fechner Law, for moderate stimuli, the intensity of the human sensory response (E) is proportional to the logarithm of the intensity of the stimulus (R). This can be expressed as:
$E=ClogR$
where C is a constant. The taste-sensor response is also proportional to the logarithmic value of the taste sample concentration, so the value of the taste sensor response approximates the human taste sensation.
Used Insent TS-5000Z to test and compare different roast degrees of taste by Coffee Classificador (no. 09001130)
- The digitized taste provides an objective gauge offering the following business advantages.
- Presents accurate image of taste to consumers and supports marketing
- Provides accurate images of taste to help educate inexperienced professionals
- Supports advanced quality assurance without well-trained sensory testers or expensive analytical instruments
- Leads to quick and precise product development by better data collection and better understanding of clients/consumers
For more applications by customers, refer to Publications. Note that Insent assumes no liability for the contents of third-party publications.
Private brands of instant coffee were purchased from TESCO, Sainsbury’s, Maxwell House, Morrisons, M&S, Waitrose, The Co-operative Food, ASDA, Carrefour, Intermarché, ALDI and LIDL
NESCAFÉ GOLD was used as the control and the origin of the chart. All coffees were brewed as described on the label.
Objective taste data can answer questions such as:
- How the coffee trend has changed since 2016?
- Which flavor do customers prefer by region, age, and gender (by integrating with point of sales data)?
- How to match the product taste to the target taste?
- How to communicate effectively with customers?
For more applications by customers, refer to Publications. Note that Insent assumes no liability for the contents of third-party publications.
This result is for shredded cabbage stored for 28 days in refrigerated freshness-preservation bags with different functions/performance. It shows the different functions/performance result as different taste changes. Digital taste data can help quick product development without wasting limited resources.
Measurement Procedure:
- Remove two outer leaves of cabbage and shred into strips.
- Store about 80 g of shredded cabbage in each freshness-preservation bag, seal, and refrigerate.
- Each day, put weighed amount of shredded cabbage from bag in food processor.
- Add deionized water at ratio of twice weight of cabbage.
- Liquidize in food processor for 1 minute.
- Centrifuge at 3000 rpm for 10 minutes.
- Freeze and store supernatant.
- Thaw supernatant under running water on day of measurement.
For more applications by customers, refer to Publications. Note that Insent assumes no liability for the contents of third-party publications.
This result shows bitterness masking when four types of cyclodextrin are mixed with cetirizine hydrochloride. The high correlation between the x-axis sensory test results and the y-axis sensor output shows that the taste sensor detects bitterness masking.
Measurement
Preparation solvent: 10 mM potassium chloride
Cetirizine hydrochloride: 5 mM
Added cyclodextrin: 20 mM
Sensor: AN0
Analysis method: Simple regression analysis
For more applications by customers, refer to Publications. Note that Insent assumes no liability for the contents of third-party publications.
For more applications by customers, refer to Publications.
Note that Insent assumes no liability for the contents of third-party publications.
Product development / renovation
– Screening ingredients
– Reformulating products with alternative ingredients (cost reduction)
– Matching products/targeting product taste
– Masking bitterness/adding palatants
– Formulating health products/nursing-care meals
Market assessment
– Linking market insights to commercial data
– Obtaining product taste insights
Consumer/customer engagement
– Demonstrating quality/taste profile
Quality control
– Maintaining product quality during production (identifying non-conforming product)
– Comparing batch-to-batch
– Evaluating customer complaints
– Validating/supporting taste panel
– Assessing shelf life
| Taste Sensing System TS-5000Z | Number of sample | 10 (max. 14 depends on measurement procedure) |
| Required sample volume | 70mL (min. 35 mL depends on the nature of sample) | |
| Weight | 26kg | |
| Dimension (W x D x H) | 470mm × 530mm × 510mm | |
| CPU | SH-4A | |
| OS (enbedded) | SuperH Linux | |
| Memory | 64MB | |
| Simple Web server | thttpd | |
| Taste sensor | Response mechanism | Membrane potential measurement (potentiometric measurement) |
| Sensor type | Artificial lipid/polymer membrane | |
| Measurement object | Drinks, solids, drugs, etc. (in case of solids, preliminary liquefaction is required) | |
| Ceramic reference electrode | Liquid juction | Single junction through ceramic |
| Temperature sensor | Response mechanism | Impedance measurement using platinum resistance thermometer |
| Sensor head | Pin jack type | Inner and outer sensor attachments |
| Management server computer | CPU | Pentium 4, 2.0GHz or higher |
| Harddisk | 160GB or more | |
| Memory | 1GB or more | |
| OS | Linux | |
| DBMS | PostgreSQL | |
| Web server | apache + Tomcat | |
| Analysis application | Analysis function | Data search, data processing function, correction processing, statistical analysis, graphing tool, etc. |
For the specifications of SA402B, please contact us.
| Taste information | Sensor | Characteristic | Target example | |
| Initial taste (relative value) | Saltiness | CT0 | Saltiness evoked by dietary salts | Seasoning, soup |
| Sourness | CA0 | sourness produced by citric acid and tartaric acid | Beer, coffee | |
| Umami | AAE | Umami (saboriness) by amino acids and nucleic acids | Soup, meat, seasoning | |
| Acidic bitterness | C00 | Bitterness derived by bitter substances found in foodstuffs and beverages, but can alsobe perceived richness with its concentration being low | Beer, coffee | |
| Astringency | AE1 | Pungent taste by astringent taste materials | Tea | |
| Sweetness | GL1 | Sweetness produced by sugars and sugar alcohols | Sweets, drink | |
| Aftertaste (CPA value) | Bitter aftertaste (acidic) | C00 | Aftertaste by bitter taste materials | Beer, coffee |
| Astringent aftertaste | AE1 | Aftertaste by astringent taste materials | Tea | |
| Umami aftertaste | AAE | Richness, also called “continuity” evoked by umami sabstances | Soup, meat, seasoning | |
| Bitter aftertaste (basic) | AN0 | Bitteness of medicines | Basic drugs (such as quinine hydrochloride, famotidine) | |
| Aftertaste from hydrochloride salts | BT0 | Bitterness of medicines | Hydrochloride drugs |
If you have any questions, we are happy to help you.
Feel free to ask one-on-one online meeting with one of our experts for discussing your individual solutions.
Insent | Intelligent Sensor Technology, Inc.
5-1-1 Onna, Atsugi City, Kanagawa Prefecture 243-0032 Japan
Phone: +81 46-296-6609
Email: info@insentjp.com
