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Tibaduiza D, Anaya M, Gómez J, Sarmiento J, Perez M, Lara C, Ruiz J, Osorio N, Rodriguez K, Hernandez I, Sanchez C. Electronic Tongues and Noses: A General Overview. BIOSENSORS 2024; 14:190. [PMID: 38667183 PMCID: PMC11048215 DOI: 10.3390/bios14040190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/28/2024]
Abstract
As technology advances, electronic tongues and noses are becoming increasingly important in various industries. These devices can accurately detect and identify different substances and gases based on their chemical composition. This can be incredibly useful in fields such as environmental monitoring and industrial food applications, where the quality and safety of products or ecosystems should be ensured through a precise analysis. Traditionally, this task is performed by an expert panel or by using laboratory tests but sometimes becomes a bottleneck because of time and other human factors that can be solved with technologies such as the provided by electronic tongue and nose devices. Additionally, these devices can be used in medical diagnosis, quality monitoring, and even in the automotive industry to detect gas leaks. The possibilities are endless, and as these technologies continue to improve, they will undoubtedly play an increasingly important role in improving our lives and ensuring our safety. Because of the multiple applications and developments in this field in the last years, this work will present an overview of the electronic tongues and noses from the point of view of the approaches developed and the methodologies used in the data analysis and steps to this aim. In the same manner, this work shows some of the applications that can be found in the use of these devices and ends with some conclusions about the current state of these technologies.
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Affiliation(s)
- Diego Tibaduiza
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Maribel Anaya
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Johan Gómez
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Juan Sarmiento
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Maria Perez
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Cristhian Lara
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Johan Ruiz
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Nicolas Osorio
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Katerin Rodriguez
- Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Bogotá 111321, Colombia;
| | - Isaac Hernandez
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
| | - Carlos Sanchez
- Departamento de Ingeniería Eléctrica y Electrónica, Universidad Nacional de Colombia, Bogotá 111321, Colombia; (M.A.); (J.G.); (J.S.); (M.P.); (C.L.); (J.R.); (N.O.); (I.H.); (C.S.)
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Fodor M, Jókai Z, Matkovits A, Benes E. Assessment of Maturity of Plum Samples Using Fourier Transform Near-Infrared Technique Combined with Chemometric Methods. Foods 2023; 12:3059. [PMID: 37628058 PMCID: PMC10453540 DOI: 10.3390/foods12163059] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/13/2023] [Accepted: 08/14/2023] [Indexed: 08/27/2023] Open
Abstract
The FT-NIR technique was used for rapid and non-destructive determination of plum ripeness. The dry matter (DM), titratable acidity (TA), total soluble solids (TSS) and calculated maturity index (MI: TSS/TA) were used as reference values. The PLS correlations were validated via five-fold cross-validation (RMSECV for different parameters: DM: 0.66%, w/w; TA = 0.07%, w/w; TSS = 0.72%, w/w; MI = 1.39) and test set validation (RMSEP for different parameters: DM: 0.65%, w/w TA = 0.07%, w/w; TSS = 0.61%, w/w; MI = 1.50). Different classification algorithms were performed for TA, TSS and MI. Linear, quadratic and Mahalanobis discriminant analysis (LDA, QDA, MDA) were found to be the best sample detection methods. The accuracy of the classification methods was 100% for all investigated parameters and cultivars.
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Affiliation(s)
- Marietta Fodor
- Department of Food and Analytical Chemistry, Institute of Food Science, Hungarian University of Agriculture and Life Sciences, Villányi út 29–43, 1118 Budapest, Hungary; (Z.J.); (A.M.); (E.B.)
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Chu X, Zhang K, Wei H, Ma Z, Fu H, Miao P, Jiang H, Liu H. A Vis/NIR spectra-based approach for identifying bananas infected with Colletotrichum musae. FRONTIERS IN PLANT SCIENCE 2023; 14:1180203. [PMID: 37332705 PMCID: PMC10272841 DOI: 10.3389/fpls.2023.1180203] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 05/09/2023] [Indexed: 06/20/2023]
Abstract
Introduction Anthracnose of banana caused by Colletotrichum species is one of the most serious post-harvest diseases, which can cause significant yield losses. Clarifying the infection mechanism of the fungi using non-destructive methods is crucial for timely discriminating infected bananas and taking preventive and control measures. Methods This study presented an approach for tracking growth and identifying different infection stages of the C. musae in bananas using Vis/NIR spectroscopy. A total of 330 banana reflectance spectra were collected over ten consecutive days after inoculation, with a sampling rate of 24 h. The four-class and five-class discriminant patterns were designed to examine the capability of NIR spectra in discriminating bananas infected at different levels (control, acceptable, moldy, and highly moldy), and different time at early stage (control and days 1-4). Three traditional feature extraction methods, i.e. PC loading coefficient (PCA), competitive adaptive reweighted sampling (CARS) and successive projections algorithm (SPA), combining with two machine learning methods, i.e. partial least squares discriminant analysis (PLSDA) and support vector machine (SVM), were employed to build discriminant models. One-dimensional convolutional neural network (1D-CNN) without manually extracted feature parameters was also introduced for comparison. Results The PCA-SVM and·SPA-SVM models had good performance with identification accuracies of 93.98% and 91.57%, 94.47% and 89.47% in validation sets for the four- and five-class patterns, respectively. While the 1D-CNN models performed the best, achieving an accuracy of 95.18% and 97.37% for identifying infected bananas at different levels and time, respectively. Discussion These results indicate the feasibility of identifying banana fruit infected with C. musae using Vis/NIR spectra, and the resolution can be accurate to one day.
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Affiliation(s)
- Xuan Chu
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Kun Zhang
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Hongyu Wei
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Zhiyu Ma
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Han Fu
- College of Engineering, South China Agricultural University, Guangzhou, China
| | - Pu Miao
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
| | - Hongzhe Jiang
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China
| | - Hongli Liu
- College of Mechanical and Electrical Engineering, Zhongkai University of Agriculture and Engineering, Guangzhou, China
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Osmólska E, Stoma M, Starek-Wójcicka A. Juice Quality Evaluation with Multisensor Systems-A Review. SENSORS (BASEL, SWITZERLAND) 2023; 23:4824. [PMID: 37430738 DOI: 10.3390/s23104824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 05/10/2023] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.
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Affiliation(s)
- Emilia Osmólska
- Department of Power Engineering and Transportation, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
| | - Monika Stoma
- Department of Power Engineering and Transportation, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
| | - Agnieszka Starek-Wójcicka
- Department of Biological Bases of Food and Feed Technologies, Faculty of Production Engineering, University of Life Sciences in Lublin, 20-612 Lublin, Poland
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Szabo G, Vitalis F, Horvath-Mezofi Z, Gob M, Aguinaga Bosquez JP, Gillay Z, Zsom T, Nguyen LLP, Hitka G, Kovacs Z, Friedrich L. Application of Near Infrared Spectroscopy to Monitor the Quality Change of Sour Cherry Stored under Modified Atmosphere Conditions. SENSORS (BASEL, SWITZERLAND) 2023; 23:479. [PMID: 36617077 PMCID: PMC9824794 DOI: 10.3390/s23010479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
Determining and applying ‘good’ postharvest and quality control practices for otherwise highly sensitive fruits, such as sour cherry, is critical, as they serve as excellent media for a wide variety of microbial contaminants. The objective of this research was to report two series of experiments on the modified atmosphere storage (MAP) of sour cherries (Prunus cerasus L. var. Kántorjánosi, Újfehértói fürtös). Firstly, the significant effect of different washing pre-treatments on various quality indices was examined (i.e., headspace gas composition, weight loss, decay rate, color, firmness, soluble solid content, total plate count) in MAP-packed fruits. Subsequently, the applicability of near infrared (NIR) spectroscopy combined with chemometrics was investigated to detect the effect of various storage conditions (packed as control or MAP, stored at 3 or 5 °C) on sour cherries of different perceived ripeness. Significant differences were found for oxygen concentration when two perforations were applied on the packages of ‘Kántorjánosi’ (p < 0.01); weight loss when ‘Kánorjánosi’ (p < 0.001) and ‘Újfehértói fürtös’ (p < 0.01) were packed in MAP; SSC when ‘Újfehértói fürtös’ samples were ozone-treated (p < 0.05); and total plate count when ‘Kántorjánosi’ samples were ozone-treated (p < 0.01). The difference spectra reflected the high variability in the samples, and the detectable effects of different packaging. Based on the investigations with the soft independent modelling of class analogies (SIMCA), different packaging and storage resulted in significant differences in most of the cases even on the first storage day, which in many cases increased by the end of storage. The soft independent modelling of class analogies proved to be suitable for classification with apparent error rates between 0 and 0.5 during prediction regardless of ripeness. The research findings suggest the further correlation of NIR spectroscopic and reference parameters to support postharvest handling and fast quality control.
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Affiliation(s)
- Gergo Szabo
- Department of Postharvest, Commerce, Supply Chain and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Flora Vitalis
- Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Zsuzsanna Horvath-Mezofi
- Department of Postharvest, Commerce, Supply Chain and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Monika Gob
- Department of Postharvest, Commerce, Supply Chain and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Juan Pablo Aguinaga Bosquez
- Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Zoltan Gillay
- Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Tamás Zsom
- Department of Postharvest, Commerce, Supply Chain and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Lien Le Phuong Nguyen
- Department of Livestock Product and Preservation Technology, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Geza Hitka
- Department of Postharvest, Commerce, Supply Chain and Sensory Science, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Zoltan Kovacs
- Department of Food Measurement and Process Control, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
| | - Laszlo Friedrich
- Department of Livestock Product and Preservation Technology, Institute of Food Science and Technology, Hungarian University of Agriculture and Life Sciences (MATE), H-1118 Budapest, Hungary
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Chen Y, Chen J, Chen R, Xiao L, Wu X, Hu L, Li Z, Wang Y, Zhu M, Liu Z, Xiao Y. Comparison of the Fungal Community, Chemical Composition, Antioxidant Activity, and Taste Characteristics of Fu Brick Tea in Different Regions of China. Front Nutr 2022; 9:900138. [PMID: 35656159 PMCID: PMC9152283 DOI: 10.3389/fnut.2022.900138] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 04/26/2022] [Indexed: 12/12/2022] Open
Abstract
In this study, the fungal community structure, metabolites, antioxidant ability, and taste characteristics of five Fu brick tea (FBT) from different regions of China were determined and compared. A total of 69 operational taxonomic units (OTUs) were identified and assigned into 5 phyla and 27 genera, with Eurotium as the predominant genus in all samples. Hunan (HN) sample had the strongest fungal diversity and richness, followed by Guangxi (GX) sample, and Zhejiang (ZJ) sample had the lowest. GX sample had higher amounts of gallic acid (GA), total catechins, gallocatechin (GC), and epicatechin gallate (ECG) as well as antioxidant activity than the other samples. The levels of total phenolics, total flavonoids, epigallocatechin (EGC), catechin, epicatechin (EC), thearubigins (TRs), and theaflavins (TFs) were the highest in the ZJ sample. Guizhou (GZ) and Shaanxi (SX) samples contained the highest contents of epigallocatechin gallate (EGCG) and gallocatechin gallate (GCG), respectively. Total phenolics, GA, EC, CG, and TFs were positively associated with most of fungal genera. Total phenolic content (TPC), total flavonoid content (TFC), and most of catechins contributed to the antioxidant activities of FBT. HN sample had the strongest sourness and sweetness, ZJ sample had the strongest saltiness, SX sample had the strongest umami, and GZ sample had the strongest astringency, which was ascribed to the varied metabolites. This work reveals that FBT in different regions vary greatly in fungal community, metabolites, antioxidant activity, and taste characteristics, and provides new insight into the quality characteristics formation of FBT in different regions.
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Affiliation(s)
- Yulian Chen
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
- College of Animal Science and Technology, Hunan Agricultural University, Changsha, China
| | - Jiaxu Chen
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
- Longping Branch Graduate School, Hunan University, Changsha, China
| | - Ruyang Chen
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Leike Xiao
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Xing Wu
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Lin Hu
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Zongjun Li
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Yuanliang Wang
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
| | - Mingzhi Zhu
- Key Laboratory of Ministry of Education for Tea Science, College of Horticulture, Hunan Agricultural University, Changsha, China
- National Research Center of Engineering Technology for Utilization of Botanical Functional Ingredients, Hunan Agricultural University, Changsha, China
- *Correspondence: Mingzhi Zhu,
| | - Zhonghua Liu
- Key Laboratory of Ministry of Education for Tea Science, College of Horticulture, Hunan Agricultural University, Changsha, China
- National Research Center of Engineering Technology for Utilization of Botanical Functional Ingredients, Hunan Agricultural University, Changsha, China
| | - Yu Xiao
- College of Food Science and Technology, Hunan Agricultural University, Changsha, China
- Key Laboratory of Ministry of Education for Tea Science, College of Horticulture, Hunan Agricultural University, Changsha, China
- Yu Xiao, ,
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