scholarly journals Development of a Dual MOS Electronic Nose/Camera System for Improving Fruit Ripeness Classification

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3256 ◽  
Author(s):  
Li-Ying Chen ◽  
Cheng-Chun Wu ◽  
Ting-I. Chou ◽  
Shih-Wen Chiu ◽  
Kea-Tiong Tang
Keyword(s):  
Electronic Nose ◽  
Quality Evaluation ◽  
Camera System ◽  
Camera Systems ◽  
Class Separability ◽  
Peel Color ◽  
Fruit Maturity ◽  
Volatile Organic ◽  
Non Destructive

Electronic nose (E-nose) systems have become popular in food and fruit quality evaluation because of their rapid and repeatable availability and robustness. In this paper, we propose an E-nose system that has potential as a non-destructive system for monitoring variation in the volatile organic compounds produced by fruit during the maturing process. In addition to the E-nose system, we also propose a camera system to monitor the peel color of fruit as another feature for identification. By incorporating E-nose and camera systems together, we propose a non-destructive solution for fruit maturity monitoring. The dual E-nose/camera system presents the best Fisher class separability measure and shows a perfect classification of the four maturity stages of a banana: Unripe, half-ripe, fully ripe, and overripe.

scholarly journals Non-Destructive Detection of Damaged Strawberries after Impact Based on Analyzing Volatile Organic Compounds

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 427
Author(s):  
Yang Cao ◽  
Yuchen Zhang ◽  
Menghua Lin ◽  
Di Wu ◽  
Kunsong Chen
Keyword(s):  
Gas Chromatography ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Impact Damage ◽  
Mechanical Damage ◽  
Mechanical Force ◽  
Occurrence Time ◽  
Volatile Organic ◽  
Non Destructive

Strawberries are susceptible to mechanical damage. The detection of damaged strawberries by their volatile organic compounds (VOCs) can avoid the deficiencies of manual observation and spectral imaging technologies that cannot detect packaged fruits. In the present study, the detection of strawberries with impact damage is investigated using electronic nose (e-nose) technology. The results show that the e-nose technology can be used to detect strawberries that have suffered impact damage. The best model for detecting the extent of impact damage had a residual predictive deviation (RPD) value of 2.730, and the correct rate of the best model for identifying the damaged strawberries was 97.5%. However, the accuracy of the prediction of the occurrence time of impact was poor, and the RPD value of the best model was only 1.969. In addition, the gas chromatography–mass spectrophotometry analysis further shows that the VOCs of the strawberries changed after suffering impact damage, which was the reason why the e-nose technology could detect the damaged fruit. The above results show that the mechanical force of impact caused changes in the VOCs of strawberries and that it is possible to detect strawberries that have suffered impact damage using e-nose technology.

Quality Evaluation of Dairy Products Based on Electronic Nose

2013 ◽  
Vol 475-476 ◽  
pp. 524-527
Author(s):  
Xiu Ying Ma ◽  
Yun Xiang Liu ◽  
Wan Jun Yu
Keyword(s):  
Quality Control ◽  
Signal Processing ◽  
Electronic Nose ◽  
Dairy Products ◽  
Quality Evaluation ◽  
Flavor Quality ◽  
Signal Processing Methods ◽  
Electronic Nose System

The construction of Electronic Nose system and associated signal processing methods were introduced .Then special references to applications to dairy products, such as the classification of different milk, the milk with different shelf-lives, flavor quality evaluation, antibiotics resedues detection and quality control were discussed. The results show that the quality of dairy products can be evaluated effectively using Electronic Nose system. The development trends of Electronic Nose are presented.

Electronic Nose: A Non-destructive Technology to Screen Tomato Fruit with Internal Bruising

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 489c-489
Author(s):  
Celso L. Moretti ◽  
Steven A. Sargent ◽  
Rolf Puschmann
Keyword(s):  
Electronic Nose ◽  
Mahalanobis Distance ◽  
Tomato Fruit ◽  
System Stability ◽  
Linear Discriminant ◽  
Polymer Sensors ◽  
Ripe Stage ◽  
Multivariate Discriminant ◽  
Non Destructive

Tomato (Lycopersicon esculentum Mill) fruit, cv. Solar Set, were harvested at the mature-green stage and gassed with 100 mg·kg–1 of ethylene at 20 °C. At the breaker stage, fruit were held by vacuum to avoid fruit rotation and dropped from a 40 cm height on a metallic, solid, smooth surface. Following impact, fruit were stored at 20 °C and 85% to 95% relative humidity until table-ripe stage. Bruised and unbruised fruit were then placed individually inside the electronic nose-sampling vessel and the 12 conducting polymer sensors were lowered into the vessel and exposed to the volatile given off by the fruit. Data were analyzed employing multivariate discriminant analysis (MVDA), which maximizes the variance between treatments. The degree of dissimilarity was defined using the Mahalanobis distance and posterior probabilities were calculated to accurate re-classification of cases. The differences found between bruised and unbruised fruit were highly significant (P < 0.0041). The Mahalanobis distance between groupings (28.19 units) was a dramatic indicative of the differences between the two treatments. The re-classification of bruised and unbruised fruit using a single linear discriminant function was highly accurate, being 1.0 for both bruised and unbruised fruit. The electronic nose proved to be a useful tool to nondestructively identify and classify tomato fruit exposed to harmful postharvest practices such as mechanical injuries. However, there are still some factors that must be investigated, including system stability and the development of specific sensors for specific commodities.

Discriminative detection of volatile organic compounds using an electronic nose based on TiO2 hybrid nanostructures

2021 ◽  
pp. 130124
Author(s):  
Patrick P. Conti ◽  
Rafaela S. Andre ◽  
Luiza A. Mercante ◽  
Lucas Fugikawa-Santos ◽  
Daniel S. Correa
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Hybrid Nanostructures ◽  
Volatile Organic

scholarly journals Paperboard Coating Detection Based on Full-Stokes Imaging Polarimetry

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 208
Author(s):  
Javier Brugés Martelo ◽  
Jan Lundgren ◽  
Mattias Andersson
Keyword(s):  
Food Packaging ◽  
Imaging Systems ◽  
Gaussian Kernel ◽  
Support Vector ◽  
Camera System ◽  
Distance Correlation ◽  
Imaging Polarimetry ◽  
Packaging Industry ◽  
Thickness Variations

The manufacturing of high-quality extruded low-density polyethylene (PE) paperboard intended for the food packaging industry relies on manual, intrusive, and destructive off-line inspection by the process operators to assess the overall quality and functionality of the product. Defects such as cracks, pinholes, and local thickness variations in the coating can occur at any location in the reel, affecting the sealable property of the product. To detect these defects locally, imaging systems must discriminate between the substrate and the coating. We propose an active full-Stokes imaging polarimetry for the classification of the PE-coated paperboard and its substrate (before applying the PE coating) from industrially manufactured samples. The optical system is based on vertically polarized illumination and a novel full-Stokes imaging polarimetry camera system. From the various parameters obtained by polarimetry measurements, we propose implementing feature selection based on the distance correlation statistical method and, subsequently, the implementation of a support vector machine algorithm that uses a nonlinear Gaussian kernel function. Our implementation achieves 99.74% classification accuracy. An imaging polarimetry system with high spatial resolution and pixel-wise metrological characteristics to provide polarization information, capable of material classification, can be used for in-process control of manufacturing coated paperboard.

scholarly journals Feasibility of Using VIS/NIR Spectroscopy and Multivariate Analysis for Pesticide Residue Detection in Tomatoes

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 196
Author(s):  
Araz Soltani Nazarloo ◽  
Vali Rasooli Sharabiani ◽  
Yousef Abbaspour Gilandeh ◽  
Ebrahim Taghinezhad ◽  
Mariusz Szymanek ◽  
...  
Keyword(s):  
Near Infrared ◽  
Cross Validation ◽  
Low Cost ◽  
Moving Average ◽  
Nir Spectroscopy ◽  
Control Treatment ◽  
Residue Detection ◽  
Non Destructive ◽  
Reflective Spectroscopy

The purpose of this work was to investigate the detection of the pesticide residual (profenofos) in tomatoes by using visible/near-infrared spectroscopy. Therefore, the experiments were performed on 180 tomato samples with different percentages of profenofos pesticide (higher and lower values than the maximum residual limit (MRL)) as compared to the control (no pesticide). VIS/near infrared (NIR) spectral data from pesticide solution and non-pesticide tomato samples (used as control treatment) impregnated with different concentrations of pesticide in the range of 400 to 1050 nm were recorded by a spectrometer. For classification of tomatoes with pesticide content at lower and higher levels of MRL as healthy and unhealthy samples, we used different spectral pre-processing methods with partial least squares discriminant analysis (PLS-DA) models. The Smoothing Moving Average pre-processing method with the standard error of cross validation (SECV) = 4.2767 was selected as the best model for this study. In addition, in the calibration and prediction sets, the percentages of total correctly classified samples were 90 and 91.66%, respectively. Therefore, it can be concluded that reflective spectroscopy (VIS/NIR) can be used as a non-destructive, low-cost, and rapid technique to control the health of tomatoes impregnated with profenofos pesticide.

scholarly journals Non-Invasive Method to Detect Infection with Mycobacterium tuberculosis Complex in Wild Boar by Measurement of Volatile Organic Compounds Obtained from Feces with an Electronic Nose System

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 584
Author(s):  
Kelvin de Jesús Beleño-Sáenz ◽  
Juan Martín Cáceres-Tarazona ◽  
Pauline Nol ◽  
Aylen Lisset Jaimes-Mogollón ◽  
Oscar Eduardo Gualdrón-Guerrero ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Wild Boar ◽  
Organic Compounds ◽  
Electronic Nose ◽  
Bovine Tuberculosis ◽  
Human Beings ◽  
Non Invasive ◽  
Testing Phase ◽  
Volatile Organic ◽  
Electronic Nose System

More effective methods to detect bovine tuberculosis, caused by Mycobacterium bovis, in wildlife, is of paramount importance for preventing disease spread to other wild animals, livestock, and human beings. In this study, we analyzed the volatile organic compounds emitted by fecal samples collected from free-ranging wild boar captured in Doñana National Park, Spain, with an electronic nose system based on organically-functionalized gold nanoparticles. The animals were separated by the age group for performing the analysis. Adult (>24 months) and sub-adult (12–24 months) animals were anesthetized before sample collection, whereas the juvenile (<12 months) animals were manually restrained while collecting the sample. Good accuracy was obtained for the adult and sub-adult classification models: 100% during the training phase and 88.9% during the testing phase for the adult animals, and 100% during both the training and testing phase for the sub-adult animals, respectively. The results obtained could be important for the further development of a non-invasive and less expensive detection method of bovine tuberculosis in wildlife populations.

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