Food freshness using electronic nose and its classification method: A review
01 Jan 2018-International journal of engineering and technology (Science Publishing Corporation Inc)-Vol. 7, pp 49-53
TL;DR: E-nose is discussed briefly about electronic nose, it’s principle of work and classification method and in order to classify food freshness.
Abstract: Generally, E-nose mimics human olfactory sense to detect and distinguish an odor or gasses or volatile organic compound from a few objects such as food, chemicals, explosive etc. Thus, E-nose can be used to measure gas emitted from food due to its ability to measure gas and odor. Principally, the E-nose operates by using a number of sensors to response to the odorant molecules (aroma). Each sensor will respond to their specific gas respectively. These sensors are a major part of the electronic nose to detect gas or odor contained in a volatile component. Information about the gas detected by sensors will be recorded and transmitted to the signal processing unit to perform the analysis of volatile organic compound (VOC) pattern and stored in the database classification, in order to determine the type of odor. Classification is a way to distinguish a mixture odor/aroma obtained from gas sensors in an electric signal form. In this paper, we discussed briefly about electronic nose, it’s principle of work and classification method and in order to classify food freshness.
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01 Nov 2019
TL;DR: The results from the combined approach produced an overall accuracy rate of 92%, thus, the electronic nose system is capable of sensing food gases and accurately determine spoilage inside the refrigerator.
Abstract: The study focuses on monitoring freshness and determining food spoilage inside the refrigerator. The objective is to design an electronic nose system that will be sensitive to the gases emitted by spoiled food samples namely banana, pechay, carrots and grapes operating in low level temperature particularly the refrigerator and then determine food spoilage using Principal Component Analysis – K Nearest Neighbors, however, it will not take any corrective actions. The system will gather readings from MQ gas sensors and will be subjected to PCA and KNN. PCA is implemented to minimize data and for feature projection represented in form of graphs. Whereas, KNN is applied for clusters formed by the PCA transformation to classify the grouping of the food. The results from the combined approach produced an overall accuracy rate of 92%, thus, the electronic nose system is capable of sensing food gases and accurately determine spoilage inside the refrigerator.
17 citations
TL;DR: In this paper, the authors discuss the individual challenges at each point in the production cycles and propose solutions to those, and discuss how to deal with the challenges of individual product design and production.
Abstract: Individualization is a common trend in many fields of production across the industries. Also in the food sector, significant changes can be observed. For many products, individual offerings towards the customer are meanwhile either mandatory or at least help to increase the sales and revenue. Somehow, individual product design and production contradicts scaling effects, which are especially important for food production. On the other hand, as digitalization is implemented in a fairly limited way in the food sector, currently great chances can be observed to build a unique selling proposition and consequently gain market share by implementing appropriate measures to enable a digital food factory. This is where the proposed idea comes into the game. The starting point is the idea to produce individually developed beer and ship it to the individual customer. The beer can be designed on a web page based on typical parameters, like beer type, bitterness, colour, or alcohol concentration. In an expert mode, individual beer creations may be thoughtful, allowing the creation of completely individual recipes (for sure, not guaranteeing the customer a perfect drinking experience). In any way, the data from the web page is directly fed to the brewing equipment in the brewing facility. There, using newly to be developed specialized machines, the individually ordered beer will be produced automatically. In this paper we discuss the individual challenges at each point in the production cycles and propose solutions to those.
2 citations
Cites background or methods from "Food freshness using electronic nos..."
...Enablers for this research is, e.g., the so called electronic nose (Di Natale et al., 2000; Haugen, 2001; Gorska-Horczyczak et al., 2016; Palmiro et al., 2017; Mohamed et al., 2018), which allows to digitalize the aforementioned human perceptions....
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...Electric noses and tongues are known (Haugen, 2001; Gorska-Horczyczak et al., 2016; Palmiro et al., 2017; Mohamed et al., 2018; Di Natale et al., 2000), while the processing of the data and the description of the perception is not trivial and not yet very well researched....
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01 Jan 2023
TL;DR: A dataset processing method for odor recognition using neural networks, which extracts the sensor multi-dimensional temperature information and high-dimensional time series information during the response process, successfully achieves 98.7% accuracy in chemical gas recognition and 95.8%" accuracy in food classification.
Abstract: In this paper, we propose a dataset processing method for odor recognition using neural networks, which extracts the sensor multi-dimensional temperature information and high-dimensional time series information during the response process. In this “sniffing” system, 4 different Micro-Electro-Mechanical System (MEMS) Metal-Oxide-Semiconductor (MOX) gas sensors are utilized, and 4 different heating voltages are applied to the sensor array. After classifying 6 chemical gases closely related to food at 3 different concentrations each, we introduced 10 kinds of food for classification. To construct an abstract odor factor map as a feature map of odor samples, we process each group of different relatively low-bandwidth sensor signals with smoothing spline, Gaussian window, etc. By Inputting the feature map into a specific convolutional neural network, we successfully achieve 98.7% accuracy in chemical gas recognition and 95.8% accuracy in food classification.
01 Jan 1987
TL;DR: In this paper, an analytical method and experimental results of identifying and quantifying smells using an electronic system composed of an integrated sensor and a microcomputer are described, where the microcomputer identifies the scent on the basis of similarities calculated by comparing standard patterns stored in the memory and a sample pattern developed by the integrated sensor.
Abstract: An analytical method and experimental results of identifying and quantifying smells using an electronic system composed of an integrated sensor and a microcomputer are described. The integrated sensor with six different elements on an alumina substrate was fabricated by using thick-film techniques. The elements are kept at around 400°C by a Pt heater mounted on the sensor back. Since each element was made from different semiconductor oxides, they possess different sensitivities to material odors and the integrated sensor can develop specific patterns corresponding to each odor as a histogram of conductance ratios for each element. The microcomputer identifies the scent on the basis of similarities calculated by comparing standard patterns stored in the memory and a sample pattern developed by the integrated sensor. The scent is then quantified by using the sensor element with the highest sensitivity to the smell identified. The experimental results show that smells can be successfully identified and quantified with the electronic System.
References
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TL;DR: An electronic nose constructed using semiconductor transducers and incorporating design features suggested by the proposal can reproducibly discriminate between a wide variety of odours, and its properties show that discrimination in an olfactory system could be achieved without the use of highly specific receptors.
Abstract: Olfaction exhibits both high sensitivity for odours and high discrimination between them. We suggest that to make fine discriminations between complex odorant mixtures containing varying ratios of odorants without the necessity for highly specialized peripheral receptors, the olfactory systems makes use of feature detection using broadly tuned receptor cells organized in a convergent neurone pathway. As a test of this hypothesis we have constructed an electronic nose using semiconductor transducers and incorporating design features suggested by our proposal. We report here that this device can reproducibly discriminate between a wide variety of odours, and its properties show that discrimination in an olfactory system could be achieved without the use of highly specific receptors.
1,309 citations
"Food freshness using electronic nos..." refers background in this paper
...Electronic nose is a sensor that was first developed in 1982 by [27], followed by [28, 29] in 1985 and 1987 at Hitachi in Japan....
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TL;DR: The human nose is still the primary instrument used to assess the smell or flavour of various industrial products today, despite considerable and sustained attempts to develop new electronic instrumentation capable of mimicking its remarkable ability as discussed by the authors.
Abstract: The human nose is still the primaryinstrument' used to assess the smell or flavour of various industrial products today, despite considerable and sustained attempts to develop new electronic instrumentation capable of mimicking its remarkable ability In this paper we review the research effort that has been carried out over the past 25 years or so to create an electronic nose Indoing so, we first provide a definition for the term electronic nose, and then discuss some of the technologies that have been explored in what is essentially an intelligent chemical array sensor systemwe summarize the applications of electronic noses to date and suggest where future applications may lie
1,079 citations
"Food freshness using electronic nos..." refers methods in this paper
...It is an electronic device that is intelligent of simulating human olfactory system [7], which contains an array of electrochemical sensors to detect and identify gases/odor and will classify through a kind of pattern recognition method....
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TL;DR: A substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic, and other items of everyday life is observed as discussed by the authors, which involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odours.
Abstract: ‘Electronic nose’ systems involve various types of electronic chemical gas sensors with partial specificity, as well as suitable statistical methods enabling the recognition of complex odours. As commercial instruments have become available, a substantial increase in research into the application of electronic noses in the evaluation of volatile compounds in food, cosmetic and other items of everyday life is observed. At present, the commercial gas sensor technologies comprise metal oxide semiconductors, metal oxide semiconductor field effect transistors, organic conducting polymers, and piezoelectric crystal sensors. Further sensors based on fibreoptic, electrochemical and bi-metal principles are still in the developmental stage. Statistical analysis techniques range from simple graphical evaluation to multivariate analysis such as artificial neural network and radial basis function. The introduction of electronic noses into the area of food is envisaged for quality control, process monitoring, freshness evaluation, shelf-life investigation and authenticity assessment. Considerable work has already been carried out on meat, grains, coffee, mushrooms, cheese, sugar, fish, beer and other beverages, as well as on the odour quality evaluation of food packaging material.
440 citations
"Food freshness using electronic nos..." refers methods in this paper
...There are several methods to classify data from E-nose as explained earlier such as classical computational techniques based on statistical and factorial analysis such as Principal Component Analysis (PCA), Corresponding Analysis (CA) and Generalized Canonical Analysis (GCA) [43]....
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TL;DR: This review covers quality control applications to food and beverages, including determination of freshness and identification of contaminants or adulteration in electronic noses that use metal oxide semi-conductors.
Abstract: Electronic noses (E-noses) use various types of electronic gas sensors that have partial specificity. This review focuses on commercial and experimental E-noses that use metal oxide semi-conductors. The review covers quality control applications to food and beverages, including determination of freshness and identification of contaminants or adulteration. Applications of E-noses to a wide range of foods and beverages are considered, including: meat, fish, grains, alcoholic drinks, non-alcoholic drinks, fruits, milk and dairy products, olive oils, nuts, fresh vegetables and eggs.
275 citations
"Food freshness using electronic nos..." refers background in this paper
...The sensor part is using the gas sensor to detect an odor which can be used a market ready product such as MOS transistors, QMB, CP, piezoelectric crystal, QCM [18-20] and there are some of researchers developed their own gas sensors [21- 23] for their research....
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...The sensor part is using the gas sensor to detect an odor which can be used a market ready product such as MOS transistors, QMB, CP, piezoelectric crystal, QCM [18-20] and there are some of researchers developed their own gas sensors [2123] for their research....
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TL;DR: In this article, the development of efficient CO 2 sensors that can intelligently monitor the gas concentration changes inside a food package and specific to food packaging applications is discussed. But, most of them are not versatile for food packaging application and suffers from limitations such as high equipment cost, bulkiness, and energy input requirement, including safety concerns.
252 citations
"Food freshness using electronic nos..." refers background in this paper
...Food can be classified as bad or good from the activity of microorganism in food that eventually will produce gas [24-25]....
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