Electronic nose based on partition column integrated with gas sensor for fruit identification and classification

Radi,; Ciptohadijoyo, Sunarto; Litananda, Wahyu Satria; Rivai, Muhammad; Purnomo, Mauridhi Hery

doi:10.1016/j.compag.2015.11.013

Cited by 51 publications

(16 citation statements)

References 10 publications

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“…The e-nose is an electronic instrument that has the ability to emulate the human nose in detecting smells. This tool can be used in many fields, for example in biomedicine for detecting diabetes [1][2][3], in the foodindustry [4][5][6], for environmental monitoring [7], in agriculture [8], for detecting mixtures of food ingredients [9,10], and detecting the methane gas content of chili [11]. An e-nose consists of a nonselective chemical gas sensor array to capture and transform smell into electric signals or sensor responses.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Threshold using Pearson Correlation for Selecting Features of Electronic Nose Signals

Sabilla¹,

Sarno²,

Triyana³

2019

IJIES

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This research studied the use of sensors in an electronic-nose (e-nose) system to select the most efficient features to detect three classes of data signals. The data signals were collected from sensors that were assembled specifically for recognition of meat types. The development of e-noses has been the subject of many researches. However, researchers tend to install multiple sensors without optimizing their utilization, leading to higher costs. This research proposes three significant contributions to optimize the number of sensors to be used in e-noses, i.e. (i) tuning the threshold of the correlation coefficient; (ii) obtaining significant features by determining the optimal threshold of independent features; (iii) optimizing efficiency by considering the significant features and the accuracy of the results. The proposed efficiency method suggested that the number of sensors in the system could be reduced from 10 to 5. The optimal threshold suggested that 12 out of 20 features were correlated to each other. The highest accuracy obtained in this research was 92% for three classes of meats.

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Section: Introductionmentioning

confidence: 99%

Optimizing Threshold using Pearson Correlation for Selecting Features of Electronic Nose Signals

Sabilla¹,

Sarno²,

Triyana³

2019

IJIES

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“…At present, the assessment of rice quality mainly depends on sensory evaluation, routine physical, and chemical tests (Sung, Kim, Kim, & Kim, 2014). Sensory evaluation which employs human nose to evaluate the flavor of rice is not objective and largely depends on the discretion of panelist (Radi, Litananda, Rivai, & Purnomo, 2016); compared to physical and chemical tests that are laborious and time-consuming. Olfactory visualization is a novel and portable electronic nose system which is based on the colorimetric sensor array (CSA) and available for real-time monitoring (Krishnan et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Discrimination of aged rice using colorimetric sensor array combined with volatile organic compounds

Hao

Song

et al. 2019

J Food Process Engineering

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This article studied the distribution of volatile organic compounds (VOCs) expose to colorimetric sensors array on stored rice. COMSOL Multiphysics software was utilized to simulate the flow field in reaction chambers, where arc baffle with different curvature in different position were employed for optimization. It was observed that the velocity field was the most uniform when the curvature of baffle was 3.3 and the vertical distance from the front end of the baffle to the inlet was 1.5 cm. The research results revealed that color changes of the sensors exposed to the same VOCs in the designed chamber were more uniform than that of free volatilization chamber. Fresh and aged rice samples were 100% correctly identified by principal components analysis when the designed chamber was used, while the recognition percentage was 90% using the free volatilization chamber. Practical applications This work presents a nondestructive method for the discrimination of aged rice. The data and figures presented clearly suggest the optimized chamber can extremely improve the reaction between volatile organic compounds and colorimetric sensor array. When the optimized reaction chamber was performed to detect the fresh and aged rice, all of the samples were discriminated successfully. This research results supports a potential way for fast, nondestructive detection of freshness in rice industry.

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“…By presenting many different odorants to the sensor array, a database is built up. This database of odorants with each odorant unique characteristics is used to train an intelligent classification system, such as Neural Networks [11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Two Dimensional Electronic Nose for Vehicular Central Locking System (E-Nose-V)

Iskandarani¹

2019

IJACSA

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A new approach to vehicle security is proposed, tried, tested. The designed and tested system comprises an odor detection system (E-Nose) that sends signals corresponding to selected odors to the smart vehicle Electronic Control Unit (ECU), which is interfaced to a smart system with neural networks. The signal is interpreted in time and space, whereby a certain ordered number of samples should be obtained before the vehicle functions are unlocked. Correlation of rise and decay times and amplitudes of the signal is carried out to ensure security. The proposed system is highly secured and could be further developed to become a vital and integrated part of Intelligent Transportation Systems (ITS) through the addition of driver's body odor smell as an extra measure of security and in cases of accidents to auto call emergency services with driver identification and some diagnostics. Such system can be utilized in smart cities.

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Electronic nose based on partition column integrated with gas sensor for fruit identification and classification

Cited by 51 publications

References 10 publications

Optimizing Threshold using Pearson Correlation for Selecting Features of Electronic Nose Signals

Optimizing Threshold using Pearson Correlation for Selecting Features of Electronic Nose Signals

Discrimination of aged rice using colorimetric sensor array combined with volatile organic compounds

Two Dimensional Electronic Nose for Vehicular Central Locking System (E-Nose-V)

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