ArticleSensors (Basel, Switzerland)2020
Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Review of Applications of Cyclodextrins as Taste-Masking Excipients for Pharmaceutical Purposes.Molecules (Basel, Switzerland) · 2023Review
- Evaluating and forecasting the associated main flavor components in Baijiu (Chinese distilled spirits) with alcohol metabolism and hangover symptoms through mice acute withdrawal model.Food science & nutrition · 2023Article
- Review
- No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.Frontiers in pharmacology · 2022Article
- Application of Artificial Intelligence in Food Industry-a Guideline.Food engineering reviews · 2022Review
- Apple quality identification and classification by image processing based on convolutional neural networks.Scientific reports · 2021Article
- Challenges in using electronic tongue to study rasa of plants: I. Finding the right tool for the right job.Journal of Ayurveda and integrative medicineArticle
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human's descriptive language, making food detection technology a step closer to human perception.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.