1
|
Bechynska K, Sedlak J, Uttl L, Kosek V, Vackova P, Kocourek V, Hajslova J. Metabolomics on Apple ( Malus domestica) Cuticle-Search for Authenticity Markers. Foods 2024; 13:1308. [PMID: 38731678 PMCID: PMC11083494 DOI: 10.3390/foods13091308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 04/17/2024] [Accepted: 04/21/2024] [Indexed: 05/13/2024] Open
Abstract
The profile of secondary metabolites present in the apple cuticular layer is not only characteristic of a particular apple cultivar; it also dynamically reflects various external factors in the growing environment. In this study, the possibility of authenticating apple samples by analyzing their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. A total of 274 authentic apple samples from four cultivars harvested in the Czech Republic and Poland between 2020 and 2022 were analyzed. The complex data generated, processed using univariate and multivariate statistical methods, enabled the building of classification models to distinguish apple cultivars as well as their geographical origin. The models showed very good performance in discriminating Czech and Polish samples for three out of four cultivars: "Gala", "Golden Delicious" and "Idared". Moreover, the validity of the models was tested over several harvest seasons. In addition to metabolites of the triterpene biosynthetic pathway, the diagnostic markers were mainly wax esters. "Jonagold", which is known to be susceptible to mutations, was the only cultivar for which an unambiguous classification of geographical origin was not possible.
Collapse
Affiliation(s)
- Kamila Bechynska
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| | - Jiri Sedlak
- Reserach and Breeding Institute of Pomology Holovousy, Holovousy 129, 50801 Holovousy, Czech Republic;
| | - Leos Uttl
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| | - Vit Kosek
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| | - Petra Vackova
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| | - Vladimir Kocourek
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| | - Jana Hajslova
- Department of Food Analysis and Nutrition, University of Chemistry and Technology, Technicka 3, 16628 Prague 6, Czech Republic; (K.B.); (L.U.); (V.K.); (P.V.); (V.K.)
| |
Collapse
|
2
|
Asadi M, Ghasemnezhad M, Bakhshipour A, Olfati JA, Mirjalili MH. Predicting the quality attributes related to geographical growing regions in red-fleshed kiwifruit by data fusion of electronic nose and computer vision systems. BMC PLANT BIOLOGY 2024; 24:13. [PMID: 38163882 PMCID: PMC10759769 DOI: 10.1186/s12870-023-04661-6] [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: 05/27/2023] [Accepted: 12/04/2023] [Indexed: 01/03/2024]
Abstract
The ability of a data fusion system composed of a computer vision system (CVS) and an electronic nose (e-nose) was evaluated to predict key physiochemical attributes and distinguish red-fleshed kiwifruit produced in three distinct regions in northern Iran. Color and morphological features from whole and middle-cut kiwifruits, along with the maximum responses of the 13 metal oxide semiconductor (MOS) sensors of an e-nose system, were used as inputs to the data fusion system. Principal component analysis (PCA) revealed that the first two principal components (PCs) extracted from the e-nose features could effectively differentiate kiwifruit samples from different regions. The PCA-SVM algorithm achieved a 93.33% classification rate for kiwifruits from three regions based on data from individual e-nose and CVS. Data fusion increased the classification rate of the SVM model to 100% and improved the performance of Support Vector Regression (SVR) for predicting physiochemical indices of kiwifruits compared to individual systems. The data fusion-based PCA-SVR models achieved validation R2 values ranging from 90.17% for the Brix-Acid Ratio (BAR) to 98.57% for pH prediction. These results demonstrate the high potential of fusing artificial visual and olfactory systems for quality monitoring and identifying the geographical growing regions of kiwifruits.
Collapse
Affiliation(s)
- Mojdeh Asadi
- Department of Horticultural Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | - Mahmood Ghasemnezhad
- Department of Horticultural Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran.
| | - Adel Bakhshipour
- Department of Biosystems Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran.
| | - Jamal-Ali Olfati
- Department of Horticultural Sciences, Faculty of Agricultural Sciences, University of Guilan, Rasht, Iran
| | - Mohammad Hossein Mirjalili
- Department of Agriculture, Medicinal Plants and Drugs Research Institute, Shahid Beheshti University, Tehran, Iran
| |
Collapse
|
3
|
Lu L, Hu Z, Hu X, Li D, Tian S. Electronic tongue and electronic nose for food quality and safety. Food Res Int 2022; 162:112214. [DOI: 10.1016/j.foodres.2022.112214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 11/02/2022] [Accepted: 11/15/2022] [Indexed: 11/18/2022]
|
4
|
Li X, Wang B, Yi C, Gong W. Gas sensing technology for meat quality assessment: A review. J FOOD PROCESS ENG 2022. [DOI: 10.1111/jfpe.14055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Xinxing Li
- Beijing Laboratory of Food Quality and Safety China Agricultural University Beijing China
- Nanchang Institute of Technology Nanchang China
| | - Biao Wang
- Beijing Laboratory of Food Quality and Safety China Agricultural University Beijing China
| | - Chen Yi
- Changchun Urban Planning & Research Center Changchun China
| | - Weiwei Gong
- China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute Beijing China
| |
Collapse
|
5
|
Determining the Geographical Origin of Fuji Apple from China by Multivariate Analysis Based on Soluble Sugars, Organic Acids, and Stable Isotopes. J FOOD QUALITY 2022. [DOI: 10.1155/2022/5415257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The aim of this study was to explore the regional characteristics of soluble sugars, organic acids, and stable isotopes (δ2H, δ18O, and δ13C) in Fuji apple and the viability of tracing the geographical origin. Totally, 181 Fuji apple samples from 2017 and 2018 from three main apple production regions in China, Bohai Bay (BHB), Loess Plateau (LP), and Northwest region (NW) were collected. The parameters of soluble sugars, organic acids, and stable isotopes in samples were analyzed with HPLC, IC, and IRMS, respectively. The results of regional difference analysis, multiway variance analysis, and correlation analysis indicated that sorbitol (Sor), glucose (Glu), fructose (Fru), sucrose (Sucr), δ2H, and δ13C can be used to distinguish the samples from the three regions. Stepwise linear discriminant analysis (SLDA) showed that the correct discriminant rate of samples from the advantageous production areas of apples in China (BHB and LP) was 82.2%, and the most effective indexes were Glu, Fru, Sucr, and δ2H. Moreover, satisfactory classification can be achieved in samples from BHB and NW, with a correct classification rate of 90.0%, and Sor, Glu, and Fru were included in the discrimination model. Furthermore, the validity of the discriminant model was verified by the prediction set. The study also found that organic acids were not suitable to distinguish the apple samples from the three regions. In addition, soluble sugars and stable isotopes could not effectively distinguish LP and NW samples, which was also the reason that the samples from the three main apple production regions could not be distinguished well.
Collapse
|
6
|
Ng PC, Ahmad Ruslan NAS, Chin LX, Ahmad M, Abu Hanifah S, Abdullah Z, Khor SM. Recent advances in halal food authentication: Challenges and strategies. J Food Sci 2021; 87:8-35. [PMID: 34954819 DOI: 10.1111/1750-3841.15998] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 10/12/2021] [Accepted: 11/02/2021] [Indexed: 11/28/2022]
Abstract
Increasing public awareness of food quality and safety has prompted a rapid increase in food authentication of halal food, which covers the production method, technical processing, identification of undeclared components, and species substitution in halal food products. This urges for extensive research into analytical methods to obtain accurate and reliable results for monitoring and controlling the authenticity of halal food. Nonetheless, authentication of halal food is often challenging because of the complex nature of food and the increasing number of food adulterants that cause detection difficulties. This review provides a comprehensive and impartial overview of recent studies on the analytical techniques used in the analysis of halal food authenticity (from 1980 to the present, but there has been no significant trend in the choice of techniques for authentication of halal food during this period). Additionally, this review highlights the classification of different methodologies based on validity measures that provide valuable information for future developments in advanced technology. In addition, methodological developments, and novel emerging techniques as well as their implementations have been explored in the evaluation of halal food authentication. This includes food categories that require halal authentication, illustrating the advantages and disadvantages as well as shortcomings during the use of all approaches in the halal food industry.
Collapse
Affiliation(s)
- Pei Chi Ng
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | | | - Ling Xuan Chin
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Musa Ahmad
- Chemical Technology Program, Faculty of Science and Technology, Universiti Sains Islam Malaysia, Bandar Baru Nilai, Malaysia
| | - Sharina Abu Hanifah
- Department of Chemical Sciences, Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Zanariah Abdullah
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Sook Mei Khor
- Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| |
Collapse
|
7
|
Martínez Gila DM, Sanmartin C, Navarro Soto J, Mencarelli F, Gómez Ortega J, Gámez García J. Classification of olive fruits and oils based on their fatty acid ethyl esters content using electronic nose technology. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2021. [DOI: 10.1007/s11694-021-01103-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
|
8
|
Yang Y, Rong Y, Liu F, Jiang Y, Deng Y, Dong C, Yuan H. Rapid characterization of the volatile profiles in Pu-erh tea by gas phase electronic nose and microchamber/thermal extractor combined with TD-GC-MS. J Food Sci 2021; 86:2358-2373. [PMID: 33929725 DOI: 10.1111/1750-3841.15723] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 02/24/2021] [Accepted: 03/16/2021] [Indexed: 11/30/2022]
Abstract
Aroma plays an important role in the quality of Pu-erh tea. However, the quality evaluation of Pu-erh tea aroma is heavily relied on the experience of sensory evaluation, and the theoretical research is relatively scarce. In the present work, the volatile compounds in Pu-erh tea were characterized by using gas phase electronic nose (e-nose) and microchamber/thermal extractor (µ-CTE) combined with thermal desorption coupled to gas chromatography-mass spectrometry (TD-GC-MS). A satisfactory discrimination model (R2 Y = 0.95, Q2 = 0.807) was obtained by using orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor fingerprint of different brands of Pu-erh tea. In addition, based on the double criterion of multivariate analysis with VIP >1.0 and univariate analysis with p ≤ 0.001, 39 volatile components were identified to contribute greatly to the discrimination of five brands of Pu-erh tea. The results suggested that gas phase e-nose and µ-CTE combined with TD-GC/MS were simple, rapid techniques to characterize the volatile compounds in Pu-erh tea and were allowed to effectively distinguish different brands of Pu-erh tea, which would provide an important reference on the quality assessment of Pu-erh tea. PRACTICAL APPLICATION: This work demonstrates that the volatile compounds in Pu-erh tea are simply and rapidly characterized by using µ-CTE/TD-GC/MS and gas phase e-nose, allowing to effectively distinguish different brands of Pu-erh tea, which can provide an important reference for the quality assessment and authentication of Pu-erh tea.
Collapse
Affiliation(s)
- Yanqin Yang
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Yuting Rong
- Yunnan Shuangjiang Mengku Tea Co., Ltd., Lincang, China
| | - Fuqiao Liu
- Yunnan Shuangjiang Mengku Tea Co., Ltd., Lincang, China
| | - Yongwen Jiang
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Yuliang Deng
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Chunwang Dong
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| | - Haibo Yuan
- Key Laboratory of Tea Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China
| |
Collapse
|
9
|
Xu L, Xu Z, Liao X. A review of fruit juice authenticity assessments: Targeted and untargeted analyses. Crit Rev Food Sci Nutr 2021; 62:6081-6102. [PMID: 33683157 DOI: 10.1080/10408398.2021.1895713] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Fruit juices are becoming more and more popular in the whole world. However, the increasing fruit juice fraud cases are undermining the healthy development of fruit juice industry. Fruit juice authenticity represents an important food quality and safety parameter. Many techniques have been applied in fruit juices authenticity assessment. The purpose of this review is to provide a research overview of the targeted and untargeted analyses of fruit authentication, and a method selection guide for fruit juice authenticity assessment. Targeted markers, such as stable isotopes, phenolics, carbohydrates, organic acids, volatile components, DNAs, amino acids and proteins, as well as carotenoids, will be discussed. And untargeted techniques, including liquid/gas chromatography-mass spectrometer, nuclear magnetic resonance, infrared spectroscopy, inductively-coupled plasma-mass spectrometry/optical emission spectrometer, fluorescence spectra, electronic sensors and others, will be reviewed. The emerging untargeted for novel targeted marker analysis will be also summarized.
Collapse
Affiliation(s)
- Lei Xu
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Beijing, China.,College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.,Beijing Key Laboratory for Food Nonthermal Processing, Key Lab of Fruit and Vegetable Processing, Ministry of Agriculture and Rural Affairs, Beijing, China
| | - Zhenzhen Xu
- Institute of Quality Standard & Testing Technology for Agro-Products, Key Laboratory of Agro-food Safety and Quality, Ministry of Agriculture and Rural Affairs, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xiaojun Liao
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China.,Beijing Key Laboratory for Food Nonthermal Processing, Key Lab of Fruit and Vegetable Processing, Ministry of Agriculture and Rural Affairs, Beijing, China
| |
Collapse
|
10
|
Aouadi B, Zaukuu JLZ, Vitális F, Bodor Z, Fehér O, Gillay Z, Bazar G, Kovacs Z. Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5479. [PMID: 32987908 PMCID: PMC7583984 DOI: 10.3390/s20195479] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 09/15/2020] [Accepted: 09/21/2020] [Indexed: 01/28/2023]
Abstract
Amid today's stringent regulations and rising consumer awareness, failing to meet quality standards often results in health and financial compromises. In the lookout for solutions, the food industry has seen a surge in high-performing systems all along the production chain. By virtue of their wide-range designs, speed, and real-time data processing, the electronic tongue (E-tongue), electronic nose (E-nose), and near infrared (NIR) spectroscopy have been at the forefront of quality control technologies. The instruments have been used to fingerprint food properties and to control food production from farm-to-fork. Coupled with advanced chemometric tools, these high-throughput yet cost-effective tools have shifted the focus away from lengthy and laborious conventional methods. This special issue paper focuses on the historical overview of the instruments and their role in food quality measurements based on defined food matrices from the Codex General Standards. The instruments have been used to detect, classify, and predict adulteration of dairy products, sweeteners, beverages, fruits and vegetables, meat, and fish products. Multiple physico-chemical and sensory parameters of these foods have also been predicted with the instruments in combination with chemometrics. Their inherent potential for speedy, affordable, and reliable measurements makes them a perfect choice for food control. The high sensitivity of the instruments can sometimes be generally challenging due to the influence of environmental conditions, but mathematical correction techniques exist to combat these challenges.
Collapse
Affiliation(s)
- Balkis Aouadi
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| | - John-Lewis Zinia Zaukuu
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| | - Flora Vitális
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| | - Zsanett Bodor
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| | - Orsolya Fehér
- Institute of Agribusiness, Faculty of Economics and Social Sciences, Szent István University, H-2100 Gödöllő, Hungary;
| | - Zoltan Gillay
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| | - George Bazar
- Department of Nutritional Science and Production Technology, Faculty of Agricultural and Environmental Sciences, Szent István University, H-7400 Kaposvár, Hungary;
- ADEXGO Kft., H-8230 Balatonfüred, Hungary
| | - Zoltan Kovacs
- Department of Measurement and Process Control, Faculty of Food Science, Szent István University, H-1118 Budapest, Hungary; (B.A.); (J.-L.Z.Z.); (F.V.); (Z.B.); (Z.G.)
| |
Collapse
|
11
|
Zhou L, Zhang C, Qiu Z, He Y. Information fusion of emerging non-destructive analytical techniques for food quality authentication: A survey. Trends Analyt Chem 2020. [DOI: 10.1016/j.trac.2020.115901] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
|
12
|
Bonah E, Huang X, Yi R, Aheto JH, Osae R, Golly M. Electronic nose classification and differentiation of bacterial foodborne pathogens based on support vector machine optimized with particle swarm optimization algorithm. J FOOD PROCESS ENG 2019. [DOI: 10.1111/jfpe.13236] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Ernest Bonah
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
- Food and Drugs AuthorityLaboratory Services Department Cantonments Accra Ghana
| | - Xingyi Huang
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
| | - Ren Yi
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
- School of Smart AgricultureSuzhou Polytechnic Institute of Agriculture Suzhou PR China
| | - Joshua H. Aheto
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
| | - Richard Osae
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
| | - Moses Golly
- School of Food and Biological EngineeringJiangsu University Zhenjiang Jiangsu PR China
| |
Collapse
|
13
|
Using Machine Learning and Multi-Element Analysis to Evaluate the Authenticity of Organic and Conventional Vegetables. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01597-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
|
14
|
Li Z, Yuan Y, Yue T, Meng J. Detection of 5‐
HMF
in apple juice with artificial sensing systems. Int J Food Sci Technol 2019. [DOI: 10.1111/ijfs.14178] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Zhao Li
- College of Food Science and Engineering Northwest A&F University Yangling Shaanxi 712100 China
- Laboratory of Quality & Safety Risk Assessment for Agro‐Products (Yangling) Ministry of Agriculture Yangling Shaanxi 712100 China
- National Engineering Research Center of Agriculture Integration Test (Yangling) Yangling Shaanxi 712100 China
| | - Yahong Yuan
- College of Food Science and Engineering Northwest A&F University Yangling Shaanxi 712100 China
- Laboratory of Quality & Safety Risk Assessment for Agro‐Products (Yangling) Ministry of Agriculture Yangling Shaanxi 712100 China
- National Engineering Research Center of Agriculture Integration Test (Yangling) Yangling Shaanxi 712100 China
| | - Tianli Yue
- College of Food Science and Engineering Northwest A&F University Yangling Shaanxi 712100 China
- Laboratory of Quality & Safety Risk Assessment for Agro‐Products (Yangling) Ministry of Agriculture Yangling Shaanxi 712100 China
- National Engineering Research Center of Agriculture Integration Test (Yangling) Yangling Shaanxi 712100 China
| | - Jianghong Meng
- College of Food Science and Engineering Northwest A&F University Yangling Shaanxi 712100 China
| |
Collapse
|
15
|
Electronic Nose in Combination with Chemometrics for Characterization of Geographical Origin and Agronomic Practices of Table Grape. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01458-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
|
16
|
Esteki M, Regueiro J, Simal-Gándara J. Tackling Fraudsters with Global Strategies to Expose Fraud in the Food Chain. Compr Rev Food Sci Food Saf 2019; 18:425-440. [PMID: 33336950 DOI: 10.1111/1541-4337.12419] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 11/24/2018] [Accepted: 12/02/2018] [Indexed: 12/30/2022]
Abstract
Deliberate adulteration of food products is as old as food processing and production systems. Food adulteration is occurring increasingly often today. With globalization and complex distribution systems, adulteration may have a far-reaching impact and even adverse consequences on well-being. The means of the international community to confront and solve food fraud today are scattered and largely ineffective. A collective approach is needed to identify all stakeholders in the food supply chain, certify and qualify them, exclude those failing to meet applicable standards, and track food in a real time. This review provides some background into the drivers of fraudulent practices (economically motivated adulteration, food-industry perspectives, and consumers' perceptions of fraud) and discusses a wide range of the currently available technologies for detecting food adulteration followed by multivariate pattern recognition tools. Food chain integrity policies are discussed. Future directions in research, concerned not only with food adulterers but also with food safety and climate change, may be useful for researchers in developing interdisciplinary approaches to contemporary problems.
Collapse
Affiliation(s)
- M Esteki
- Dept. of Chemistry, Univ. of Zanjan, Zanjan, 45195-313, Iran
| | - J Regueiro
- Nutrition and Bromatology Group, Dept. of Analytical and Food Chemistry, Food Science and Technology Faculty, Univ. of Vigo - Ourense Campus, E-32004, Ourense, Spain
| | - J Simal-Gándara
- Nutrition and Bromatology Group, Dept. of Analytical and Food Chemistry, Food Science and Technology Faculty, Univ. of Vigo - Ourense Campus, E-32004, Ourense, Spain
| |
Collapse
|
17
|
|
18
|
Gas-Sensor Drift Counteraction with Adaptive Active Learning for an Electronic Nose. SENSORS 2018; 18:s18114028. [PMID: 30463202 PMCID: PMC6263697 DOI: 10.3390/s18114028] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 11/08/2018] [Accepted: 11/12/2018] [Indexed: 11/24/2022]
Abstract
Gas sensors are the key components of an electronic nose (E-nose) in violated odour analysis. Gas-sensor drift is a kind of physical change on a sensor surface once an E-nose works. The perturbation of gas-sensor responses caused by drift would deteriorate the performance of the E-nose system over time. In this study, we intend to explore a suitable approach to deal with the drift effect in an online situation. Considering that the conventional drift calibration is difficult to implement online, we use active learning (AL) to provide reliable labels for online instances. Common AL learning methods tend to select and label instances with low confidence or massive information. Although this action clarifies the ambiguity near the classification boundary, it is inadequate under the influence of gas-sensor drift. We still need the samples away from the classification plane to represent drift variations comprehensively in the entire data space. Thus, a novel drift counteraction method named AL on adaptive confidence rule (AL-ACR) is proposed to deal with online drift data dynamically. By contrast with conventional AL methods selecting instances near the classification boundary of a certain category, AL-ACR collects instances distributed evenly in different categories. This action implements on an adjustable rule according to the outputs of classifiers. Compared with other reference methods, we adopt two drift databases of E-noses to evaluate the performance of the proposed method. The experimental results indicate that the AL-ACR reaches higher accuracy than references on two E-nose databases, respectively. Furthermore, the impact of the labelling number is discussed to show the trend of performance for the AL-type methods. Additionally, we define the labelling efficiency index (LEI) to assess the contribution of certain labelling numerically. According to the results of LEI, we believe AL-ACR can achieve the best effect with the lowest cost among the AL-type methods in this work.
Collapse
|