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19 pages, 16285 KiB

Open AccessArticle

Sub-Terahertz Imaging-Based Real-Time Non-Destructive Inspection System for Estimating Water Activity and Foreign Matter Depth in Seaweed

by Dong-Hoon Kwak, Ho-Won Yun, Jong-Hun Lee, Young-Duk Kim and Doo-Hyun Choi

Sensors 2024, 24(23), 7599; https://doi.org/10.3390/s24237599 - 28 Nov 2024

Viewed by 230

Abstract

As the importance of hygiene and safety management in food manufacturing has been increasingly emphasized, research on non-destructive and non-contact inspection technologies has become more active. This study proposes a real-time and non-destructive food inspection system with sub-terahertz waves which penetrates non-conducting materials [...] Read more.

As the importance of hygiene and safety management in food manufacturing has been increasingly emphasized, research on non-destructive and non-contact inspection technologies has become more active. This study proposes a real-time and non-destructive food inspection system with sub-terahertz waves which penetrates non-conducting materials by using a frequency of 0.1 THz. The proposed system detects not only the presence of foreign matter, but also the degree of depth to which it is mixed in foods. In addition, the system estimates water activity levels, which serves as the basis for assessing the freshness of seaweed by analyzing the transmittance of signals within the sub-terahertz image. The system employs YOLOv8n, which is one of the newest lightweight object detection models. This lightweight model utilizes the feature pyramid network (FPN) to effectively detect objects of various sizes while maintaining a fast processing speed and high performance. In particular, to validate the performance in real manufacturing facilities, we implemented a hardware platform, which accurately inspects seaweed products while cooperating with a conveyor device moving at a speed of 45 cm/s. For the validation of the estimation performance against various water activities and the degree of depth of foreign matter, we gathered and annotated a total of 9659 sub-terahertz images and optimized the learning model. The final results show that the precision rate is 0.91, recall rate is 0.95, F1-score is 0.93, and mAP is 0.97, respectively. Overall, the proposed system demonstrates an excellent performance in the detection of foreign matter and in freshness estimation, and can be applied in several applications regarding food safety. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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19 pages, 4487 KiB

Open AccessArticle

A Simple Microwave Imaging System for Food Product Inspection through a Symmetry-Based Microwave Imaging Approach

by Gennaro Bellizzi, Alessio Buzzin, Lorenzo Crocco, Antonio Mastrandrea, Noemi Zeni, Sabrina Zumbo and Marta Cavagnaro

Sensors 2024, 24(1), 99; https://doi.org/10.3390/s24010099 - 24 Dec 2023

Cited by 3 | Viewed by 1586

Abstract

In the food industry, there is a growing demand for cost-effective methods for the inline inspection of food items able to non-invasively detect small foreign bodies that may have contaminated the product during the production process. Microwave imaging may be a valid alternative [...] Read more.

In the food industry, there is a growing demand for cost-effective methods for the inline inspection of food items able to non-invasively detect small foreign bodies that may have contaminated the product during the production process. Microwave imaging may be a valid alternative to the existing technologies, thanks to its inherently low-cost and its capability of sensing low-density contaminants. In this paper, a simple microwave imaging system specifically designed to enable the inspection of a large variety of food products is presented. The system consists of two circularly loaded antipodal Vivaldi antennas with a very large operative band, from 1 to 15 GHz, thus allowing a suitable spatial resolution for different food products, from mostly fatty to high water-content foods. The antennas are arranged in such a way as to collect a signal that can be used to exploit a recently proposed real-time microwave imaging strategy, leveraging the inherent symmetries that usually characterize food items. The system is experimentally characterized, and the achieved results compare favorably with the design specifications and numerical simulations. Relying on these positive results, the first experimental proof of the effectiveness of the entire system is presented confirming its efficacy. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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17 pages, 6542 KiB

Open AccessArticle

3D Printed Fused Deposition Modeling (FDM) Capillaries for Chemiresistive Gas Sensors

by Martin Adamek, Jiri Mlcek, Nela Skowronkova, Magdalena Zvonkova, Miroslav Jasso, Anna Adamkova, Josef Skacel, Iva Buresova, Romana Sebestikova, Martina Cernekova and Martina Buckova

Sensors 2023, 23(15), 6817; https://doi.org/10.3390/s23156817 - 31 Jul 2023

Cited by 3 | Viewed by 1563

Abstract

This paper discusses the possible use of 3D fused deposition modeling (FDM) to fabricate capillaries for low-cost chemiresistive gas sensors that are often used in various applications. The disadvantage of these sensors is low selectivity, but 3D printed FDM capillaries have the potential [...] Read more.

This paper discusses the possible use of 3D fused deposition modeling (FDM) to fabricate capillaries for low-cost chemiresistive gas sensors that are often used in various applications. The disadvantage of these sensors is low selectivity, but 3D printed FDM capillaries have the potential to increase their selectivity. Capillaries with 1, 2 and 3 tiers with a length of 1.5 m, 3.1 m and 4.7 m were designed and manufactured. Food and goods available in the general trade network were used as samples (alcohol, seafood, chicken thigh meat, acetone-free nail polish remover and gas from a gas lighter) were also tested. The “Vodka” sample was used as a standard for determining the effect of capillary parameters on the output signal of the MiCS6814 sensor. The results show the shift of individual parts of the signal in time depending on the parameters of the capillary and the carrier air flow. A three-tier capillary was chosen for the comparison of gas samples with each other. The graphs show the differences between individual samples, not only in the height of the output signal but also in its time characteristic. The tested 3D printed FDM capillaries thus made it possible to characterize the output response by also using an inexpensive chemiresistive gas sensor in the time domain. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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11 pages, 1414 KiB

Open AccessArticle

A Novel Equipment-Free Paper-Based Fluorometric Method for the Analytical Determination of Quinine in Soft Drink Samples

by Vasiliki C. Tsaftari, Maria Tarara, Paraskevas D. Tzanavaras and George Z. Tsogas

Sensors 2023, 23(11), 5153; https://doi.org/10.3390/s23115153 - 28 May 2023

Cited by 4 | Viewed by 2321

Abstract

A simple, equipment-free, direct fluorometric method, employing paper-based analytical devices (PADs) as sensors, for the selective determination of quinine (QN) is described herein. The suggested analytical method exploits the fluorescence emission of QN without any chemical reaction after the appropriate pH adjustment with [...] Read more.

A simple, equipment-free, direct fluorometric method, employing paper-based analytical devices (PADs) as sensors, for the selective determination of quinine (QN) is described herein. The suggested analytical method exploits the fluorescence emission of QN without any chemical reaction after the appropriate pH adjustment with nitric acid, at room temperature, on the surface of a paper device with the application of a UV lamp at 365 nm. The devices crafted had a low cost and were manufactured with chromatographic paper and wax barriers, and the analytical protocol followed was extremely easy for the analyst and required no laboratory instrumentation. According to the methodology, the user must place the sample on the detection area of the paper and read with a smartphone the fluorescence emitted by the QN molecules. Many chemical parameters were optimized, and a study of interfering ions present in soft drink samples was carried out. Additionally, the chemical stability of these paper devices was considered in various maintenance conditions with good results. The detection limit calculated as 3.3 S/N was 3.6 mg L⁻¹, and the precision of the method was satisfactory, being from 3.1% (intra-day) to 8.8% (inter-day). Soft drink samples were successfully analyzed and compared with a fluorescence method. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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12 pages, 1728 KiB

Open AccessArticle

Field-Deployable Determinations of Peroxide Index and Total Phenolic Content in Olive Oil Using a Promising Portable Sensor System

by Marco Grossi, Alessandra Bendini, Enrico Valli and Tullia Gallina Toschi

Sensors 2023, 23(11), 5002; https://doi.org/10.3390/s23115002 - 23 May 2023

Cited by 2 | Viewed by 1374

Abstract

Useful information about the oxidative stability of a virgin olive oil in terms of oxidation products and antioxidant compounds can be obtained by analyzing the peroxide index (PI) and total phenolic content (TPC), respectively. These quality parameters are usually determined in a chemical [...] Read more.

Useful information about the oxidative stability of a virgin olive oil in terms of oxidation products and antioxidant compounds can be obtained by analyzing the peroxide index (PI) and total phenolic content (TPC), respectively. These quality parameters are usually determined in a chemical laboratory using expensive equipment, toxic solvents, and well-trained personnel. This paper presents a novel portable sensor system for in the field and rapid determination of PI and TPC that is particularly suited in the case of small production environments that cannot afford an internal laboratory for quality control analysis. The system is small, can be powered by both USB ports and batteries, is easy to operate, and integrates a Bluetooth module for wireless data transmission. It estimates the PI and TPC in olive oil from the measurement of the optical attenuation of an emulsion between a reagent and the sample under test. The system has been tested on a set of 12 olive oil samples (eight for calibration and four for validation), and the results have shown how the considered parameters can be estimated with good accuracy. The maximum deviation from the results obtained with the reference analytical techniques is 4.7 meq O₂/kg in the case of PI and 45.3 ppm in the case of TPC for the calibration set, while it is 14.8 meq O₂/kg in the case of PI and 55 ppm in the case of TPC for the validation set. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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17 pages, 5586 KiB

Open AccessArticle

Microbiological Quality Estimation of Meat Using Deep CNNs on Embedded Hardware Systems

by Dimitrios Kolosov, Lemonia-Christina Fengou, Jens Michael Carstensen, Nette Schultz, George-John Nychas and Iosif Mporas

Sensors 2023, 23(9), 4233; https://doi.org/10.3390/s23094233 - 24 Apr 2023

Cited by 3 | Viewed by 2477

Abstract

Spectroscopic sensor imaging of food samples meta-processed by deep machine learning models can be used to assess the quality of the sample. This article presents an architecture for estimating microbial populations in meat samples using multispectral imaging and deep convolutional neural networks. The [...] Read more.

Spectroscopic sensor imaging of food samples meta-processed by deep machine learning models can be used to assess the quality of the sample. This article presents an architecture for estimating microbial populations in meat samples using multispectral imaging and deep convolutional neural networks. The deep learning models operate on embedded platforms and not offline on a separate computer or a cloud server. Different storage conditions of the meat samples were used, and various deep learning models and embedded platforms were evaluated. In addition, the hardware boards were evaluated in terms of latency, throughput, efficiency and value on different data pre-processing and imaging-type setups. The experimental results showed the advantage of the XavierNX platform in terms of latency and throughput and the advantage of Nano and RP4 in terms of efficiency and value, respectively. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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19 pages, 4815 KiB

Open AccessArticle

An Affordable NIR Spectroscopic System for Fraud Detection in Olive Oil

by Candela Melendreras, Ana Soldado, José M. Costa-Fernández, Alberto López, Marta Valledor, Juan Carlos Campo and Francisco Ferrero

Sensors 2023, 23(3), 1728; https://doi.org/10.3390/s23031728 - 3 Feb 2023

Cited by 14 | Viewed by 3461

Abstract

Adulterations of olive oil are performed by adding seed oils to this high-quality product, which are cheaper than olive oils. Food safety controls have been established by the European Union to avoid these episodes. Most of these methodologies require expensive equipment, time-consuming procedures, [...] Read more.

Adulterations of olive oil are performed by adding seed oils to this high-quality product, which are cheaper than olive oils. Food safety controls have been established by the European Union to avoid these episodes. Most of these methodologies require expensive equipment, time-consuming procedures, and expert personnel to execute. Near-infrared spectroscopy (NIRS) technology has many applications in the food processing industry. It analyzes food safety and quality parameters along the food chain. Using principal component analysis (PCA), the differences and similarities between olive oil and seed oils (sesame, sunflower, and flax oil) have been evaluated. To quantify the percentage of adulterated seed oil in olive oils, partial least squares (PLS) have been employed. A total of 96 samples of olive oil adulterated with seed oils were prepared. These samples were used to build a spectra library covering various mixtures containing seed oils and olive oil contents. Eighteen chemometric models were developed by combining the first and second derivatives with Standard Normal Variable (SNV) for scatter correction to classify and quantify seed oil adulteration and percentage. The results obtained for all seed oils show excellent coefficients of determination for calibration higher than 0.80. Because the instrumental aspects are not generally sufficiently addressed in the articles, we include a specific section on some key aspects of developing a high-performance and cost-effective NIR spectroscopy solution for fraud detection in olive oil. First, spectroscopy architectures are introduced, especially the Texas Instruments Digital Light Processing (DLP) technology for spectroscopy that has been used in this work. These results demonstrate that the portable prototype can be used as an effective tool to detect food fraud in liquid samples. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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Review

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24 pages, 369 KiB

Open AccessReview

The Need for Machines for the Nondestructive Quality Assessment of Potatoes with the Use of Artificial Intelligence Methods and Imaging Techniques

by Marek Danielak, Krzysztof Przybył and Krzysztof Koszela

Sensors 2023, 23(4), 1787; https://doi.org/10.3390/s23041787 - 5 Feb 2023

Cited by 4 | Viewed by 3032

Abstract

This article describes chemical and physical parameters, including their role in the storage, trade, and processing of potatoes, as well as their nutritional properties and health benefits resulting from their consumption. An analysis of the share of losses occurring during the production process [...] Read more.

This article describes chemical and physical parameters, including their role in the storage, trade, and processing of potatoes, as well as their nutritional properties and health benefits resulting from their consumption. An analysis of the share of losses occurring during the production process is presented. The methods and applications used in recent years to estimate the physical and chemical parameters of potatoes during their storage and processing, which determine the quality of potatoes, are presented. The potential of the technologies used to classify the quality of potatoes, mechanical and ultrasonic, and image processing and analysis using vision systems, as well as their use in applications with artificial intelligence, are discussed. Full article

(This article belongs to the Special Issue Innovative Sensors and Embedded Sensor Systems for Food Analysis)

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