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Fakhlaei R, Babadi AA, Sun C, Ariffin NM, Khatib A, Selamat J, Xiaobo Z. Application, challenges and future prospects of recent nondestructive techniques based on the electromagnetic spectrum in food quality and safety. Food Chem 2024; 441:138402. [PMID: 38218155 DOI: 10.1016/j.foodchem.2024.138402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/26/2023] [Accepted: 01/06/2024] [Indexed: 01/15/2024]
Abstract
Safety and quality aspects of food products have always been critical issues for the food production and processing industries. Since conventional quality measurements are laborious, time-consuming, and expensive, it is vital to develop new, fast, non-invasive, cost-effective, and direct techniques to eliminate those challenges. Recently, non-destructive techniques have been applied in the food sector to improve the quality and safety of foodstuffs. The aim of this review is an effort to list non-destructive techniques (X-ray, computer tomography, ultraviolet-visible spectroscopy, hyperspectral imaging, infrared, Raman, terahertz, nuclear magnetic resonance, magnetic resonance imaging, and ultrasound imaging) based on the electromagnetic spectrum and discuss their principle and application in the food sector. This review provides an in-depth assessment of the different non-destructive techniques used for the quality and safety analysis of foodstuffs. We also discussed comprehensively about advantages, disadvantages, challenges, and opportunities for the application of each technique and recommended some solutions and developments for future trends.
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Affiliation(s)
- Rafieh Fakhlaei
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
| | - Arman Amani Babadi
- School of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, China
| | - Chunjun Sun
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; International Joint Research Laboratory of Intelligent Agriculture and Agri-products Processing, Jiangsu University, Zhenjiang 212013, China
| | - Naziruddin Mat Ariffin
- Department of Food Science, Faculty of Food Science and Technology, University Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Alfi Khatib
- Pharmacognosy Research Group, Department of Pharmaceutical Chemistry, Kulliyyah of Pharmacy, International Islamic University Malaysia, Kuantan 25200, Pahang Darul Makmur, Malaysia; Faculty of Pharmacy, Airlangga University, Surabaya 60155, Indonesia
| | - Jinap Selamat
- Food Safety and Food Integrity (FOSFI), Institute of Tropical Agriculture and Food Security, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
| | - Zou Xiaobo
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China.
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2
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Stocco G, Gómez-Mascaraque LG, Deshwal GK, Sanchez JC, Molle A, Pizzamiglio V, Berzaghi P, Gergov G, Cipolat-Gotet C. Exploring the use of NIR and Raman spectroscopy for the prediction of quality traits in PDO cheeses. Front Nutr 2024; 11:1327301. [PMID: 38379551 PMCID: PMC10876835 DOI: 10.3389/fnut.2024.1327301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 01/04/2024] [Indexed: 02/22/2024] Open
Abstract
The aims of this proof of principle study were to compare two different chemometric approaches using a Bayesian method, Partial Least Square (PLS) and PLS-discriminant analysis (DA), for the prediction of the chemical composition and texture properties of the Grana Padano (GP) and Parmigiano Reggiano (PR) PDO cheeses by using NIR and Raman spectra and quantify their ability to distinguish between the two PDO and among their ripening periods. For each dairy chain consortium, 9 cheese samples from 3 dairy industries were collected for a total of 18 cheese samples. Three seasoning times were chosen for each dairy industry: 12, 20, and 36 months for GP and 12, 24, and 36 months for PR. A portable NIR instrument (spectral range: 950-1,650 nm) was used on 3 selected spots on the paste of each cheese sample, for a total of 54 spectra collected. An Alpha300 R confocal Raman microscope was used to collect 10 individual spectra for each cheese sample in each spot for a total of 540 Raman spectra collected. After the detection of eventual outliers, the spectra were also concatenated together (NIR + Raman). All the cheese samples were assessed in terms of chemical composition and texture properties following the official reference methods. A Bayesian approach and PLS-DA were applied to the NIR, Raman, and fused spectra to predict the PDO type and seasoning time. The PLS-DA reached the best performances, with 100% correctly identified PDO type using Raman only. The fusion of the data improved the results in 60% of the cases with the Bayesian and of 40% with the PLS-DA approach. A Bayesian approach and a PLS procedure were applied to the NIR, Raman, and fused spectra to predict the chemical composition of the cheese samples and their texture properties. In this case, the best performance in validation was reached with the Bayesian method on Raman spectra for fat (R2VAL = 0.74). The fusion of the data was not always helpful in improving the prediction accuracy. Given the limitations associated with our sample set, future studies will expand the sample size and incorporate diverse PDO cheeses.
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Affiliation(s)
- Giorgia Stocco
- Department of Veterinary Science, University of Parma, Parma, Italy
| | - Laura G. Gómez-Mascaraque
- Department of Food Chemistry and Technology, Teagasc Food Research Centre Moorepark, Fermoy, Ireland
| | - Gaurav Kr Deshwal
- Department of Food Chemistry and Technology, Teagasc Food Research Centre Moorepark, Fermoy, Ireland
| | | | - Arnaud Molle
- Department of Veterinary Science, University of Parma, Parma, Italy
| | | | - Paolo Berzaghi
- Department of Animal Medicine, Production and Health, University of Padova, Padova, Italy
| | - Georgi Gergov
- Institute of Chemical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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3
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Cardin M, Mounier J, Coton E, Cardazzo B, Perini M, Bertoldi D, Pianezze S, Segato S, Di Camillo B, Cappellato M, Coton M, Carraro L, Currò S, Lucchini R, Mohammadpour H, Novelli E. Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling. Food Res Int 2024; 178:113975. [PMID: 38309918 DOI: 10.1016/j.foodres.2024.113975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/29/2023] [Accepted: 01/03/2024] [Indexed: 02/05/2024]
Abstract
Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.
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Affiliation(s)
- Marco Cardin
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy; Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Écologie Microbienne, F-29280 Plouzané, France
| | - Jérôme Mounier
- Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Écologie Microbienne, F-29280 Plouzané, France
| | - Emmanuel Coton
- Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Écologie Microbienne, F-29280 Plouzané, France
| | - Barbara Cardazzo
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy
| | - Matteo Perini
- Centro Trasferimento Tecnologico, Fondazione Edmund Mach, Via E. Mach, 1, 38098 San Michele all'Adige, Italy
| | - Daniela Bertoldi
- Centro Trasferimento Tecnologico, Fondazione Edmund Mach, Via E. Mach, 1, 38098 San Michele all'Adige, Italy
| | - Silvia Pianezze
- Centro Trasferimento Tecnologico, Fondazione Edmund Mach, Via E. Mach, 1, 38098 San Michele all'Adige, Italy
| | - Severino Segato
- Department of Animal Medicine, Production and Health, University of Padova, Viale Università 16, 35020 Legnaro, PD, Italy
| | - Barbara Di Camillo
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy; Department of Information Engineering, University of Padova, Via Gradenigo 6/b, 35131 Padova, Italy
| | - Marco Cappellato
- Department of Information Engineering, University of Padova, Via Gradenigo 6/b, 35131 Padova, Italy
| | - Monika Coton
- Univ Brest, INRAE, Laboratoire Universitaire de Biodiversité et Écologie Microbienne, F-29280 Plouzané, France
| | - Lisa Carraro
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy
| | - Sarah Currò
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy
| | - Rosaria Lucchini
- Italian Health Authority and Research Organization for Animal Health and Food Safety (Istituto zooprofilattico sperimentale delle Venezie), Viale Università 10, 35020 Legnaro, PD, Italy
| | - Hooriyeh Mohammadpour
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy
| | - Enrico Novelli
- Department of Comparative Biomedicine and Food Science, University of Padova, Viale Università 16, 35020, Legnaro, PD, Italy.
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4
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Beltrán Sanahuja A, Pesci de Almeida R, Igler Marí KA, Lamadrid MC, Valdés García A, Nadal ES. Sensory Attributes and Instrumental Chemical Parameters of Commercial Spanish Cured Ewes' Milk Cheeses: Insights into Cheese Quality Figures. Foods 2023; 13:127. [PMID: 38201155 PMCID: PMC10778908 DOI: 10.3390/foods13010127] [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: 11/22/2023] [Revised: 12/18/2023] [Accepted: 12/26/2023] [Indexed: 01/12/2024] Open
Abstract
The external appearance of some of the Protected Designation of Origin (PDO) cured cheeses is similar to other cheese samples made in Spain: 1 kg and 2.5-3 kg formats, cylindrical, and with or without a pleita mark on the surface. In this work, commercial cured ewe's milk cheese samples with a similar external appearance were analyzed, including five PDO and five non-PDO samples. The parameters analyzed were color, texture, pH, humidity, water activity, and the volatile profile. Additionally, a descriptive and consumer-sensory analysis of the cheese samples was carried out. Statistical analysis of the results showed that luminosity, color coordinates a* and b*, percentage of deformation, humidity, water activity, and acid contents were significantly higher in non-PDO cheese samples. The breaking force, maximum force, and the content of esters were significantly higher in those cheese samples with PDO. In addition, PDO cheese samples showed higher scores for all attributes evaluated by consumers, except for color. These results suggest that PDO cheeses are placed on the market with a higher degree of ripening than non-PDO ones and that consequently they are more positively valued by consumers.
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Affiliation(s)
- Ana Beltrán Sanahuja
- Department of Analytical Chemistry, Nutrition and Food Sciences, P.O. Box 99, 03080 Alicante, Spain; (A.B.S.); (R.P.d.A.)
| | - Rafaela Pesci de Almeida
- Department of Analytical Chemistry, Nutrition and Food Sciences, P.O. Box 99, 03080 Alicante, Spain; (A.B.S.); (R.P.d.A.)
| | - Kilian-Anja Igler Marí
- Centro de Investigación e Innovación Agroalimentaria y Agroambiental (CIAGRO-UMH), Miguel Hernández University, Carretera de Beniel, km 3.2, Orihuela, 03312 Alicante, Spain; (K.-A.I.M.); (M.C.L.); (E.S.N.)
| | - Marina Cano Lamadrid
- Centro de Investigación e Innovación Agroalimentaria y Agroambiental (CIAGRO-UMH), Miguel Hernández University, Carretera de Beniel, km 3.2, Orihuela, 03312 Alicante, Spain; (K.-A.I.M.); (M.C.L.); (E.S.N.)
| | - Arantzazu Valdés García
- Department of Analytical Chemistry, Nutrition and Food Sciences, P.O. Box 99, 03080 Alicante, Spain; (A.B.S.); (R.P.d.A.)
| | - Esther Sendra Nadal
- Centro de Investigación e Innovación Agroalimentaria y Agroambiental (CIAGRO-UMH), Miguel Hernández University, Carretera de Beniel, km 3.2, Orihuela, 03312 Alicante, Spain; (K.-A.I.M.); (M.C.L.); (E.S.N.)
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5
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Dewantier GR, Torley PJ, Blanch EW. Identifying Chemical Differences in Cheddar Cheese Based on Maturity Level and Manufacturer Using Vibrational Spectroscopy and Chemometrics. Molecules 2023; 28:8051. [PMID: 38138541 PMCID: PMC10745544 DOI: 10.3390/molecules28248051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Revised: 12/03/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Cheese is a nutritious dairy product and a valuable commodity. Internationally, cheddar cheese is produced and consumed in large quantities, and it is the main cheese variety that is exported from Australia. Despite its importance, the analytical methods to that are used to determine cheese quality rely on traditional approaches that require time, are invasive, and which involve potentially hazardous chemicals. In contrast, spectroscopic techniques can rapidly provide molecular information and are non-destructive, fast, and chemical-free methods. Combined with partner recognition methods (chemometrics), they can identify small changes in the composition or condition of cheeses. In this work, we combined FTIR and Raman spectroscopies with principal component analysis (PCA) to investigate the effects of aging in commercial cheddar cheeses. Changes in the amide I and II bands were the main spectral characteristics responsible for classifying commercial cheddar cheeses based on the ripening time and manufacturer using FTIR, and bands from lipids, including β'-polymorph of fat crystals, were more clearly determined through changes in the Raman spectra.
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Affiliation(s)
- Gerson R. Dewantier
- Applied Chemistry and Environmental Science, School of Science, Royal Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia;
| | - Peter J. Torley
- Biosciences and Food Technology, School of Science, Royal Melbourne Institute of Technology University, Bundoora, VIC 3083, Australia;
| | - Ewan W. Blanch
- Applied Chemistry and Environmental Science, School of Science, Royal Melbourne Institute of Technology University, Melbourne, VIC 3001, Australia;
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6
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Reis MM, Dixit Y, Carr A, Tu C, Palevich F, Gupta T, Reis MG. Hyperspectral imaging through vacuum packaging for monitoring cheese biochemical transformation caused by Clostridium metabolism. Food Res Int 2023; 169:112866. [PMID: 37254314 DOI: 10.1016/j.foodres.2023.112866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 04/15/2023] [Accepted: 04/18/2023] [Indexed: 06/01/2023]
Abstract
This study developed a novel method for monitoring cheese contamination with Clostridium spores non-invasively using hyperspectral imaging (HSI). The ability of HSI to quantify Clostridium metabolites was investigated with control cheese and cheese manufactured with milk contaminated with Clostridium tyrobutyricum, Clostridium butyricum and Clostridium sporogenes. Microbial count, HSI and SPME-GC-MS data were obtained over 10 weeks of storage. The developed method using HSI successfully quantified butyric acid (R2 = 0.91, RPD = 3.38) a major compound of Clostridium metabolism in cheese. This study creates a new venue to monitor the spatial and temporal development of late blowing defect (LBD) in cheese using fast and non-invasive measurement.
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Affiliation(s)
- Marlon M Reis
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand.
| | - Yash Dixit
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
| | - Alistair Carr
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
| | - Christine Tu
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
| | - Faith Palevich
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
| | - Tanushree Gupta
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
| | - Mariza G Reis
- AgResearch, Te Ohu Rangahau Kai, Palmerston North 4474, New Zealand
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7
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Atik DS, Huppertz T. Melting of natural cheese: A review. Int Dairy J 2023. [DOI: 10.1016/j.idairyj.2023.105648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
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8
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Atanassova S, Yorgov D, Veleva P, Stoyanchev T, Zlatev Z. Cheese quality assessment by use of near-infrared spectroscopy. BIO WEB OF CONFERENCES 2023. [DOI: 10.1051/bioconf/20235802007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2023] Open
Abstract
Dairy products are worldwide spread and have great commercial importance. Rapid and reliable analysis of cheese would be highly desirable both for the manufacturers and consumers. The results of experiments, related to the application of near-infrared spectroscopy for cheese quality estimation will be presented. Several kinds of Bulgarian white brine cheese - natural from cow milk, imitation products with vegetable oil, and cheese with different water content were investigated. Fatty acids composition of samples was determined by using gas chromatography and moisture content by the oven-dry method. Spectra of all tested samples were obtained with a scanning NIRQuest 512 (Ocean Optics, Inc.) instrument in the range of 900-1700 nm using a reflection fiber-optics probe. PLS models were developed for quantitative determination and SIMCA for classification. The misclassification rate of the SIMCA model for discrimination of natural cheese and imitation products with vegetable oil was 2.9%. Quantitative determination of water content based on NIR spectra showed high accuracy, Models for classification of cheese samples into 3 groups according to water content achieved 5.64% misclassification rate for the independent test set. Results showed the potential of near-infrared spectroscopy as a non-destructive and rapid screening tool for assessing cheese quality and detecting adulteration.
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9
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Hassoun A, Jagtap S, Garcia-Garcia G, Trollman H, Pateiro M, Lorenzo JM, Trif M, Rusu AV, Aadil RM, Šimat V, Cropotova J, Câmara JS. Food quality 4.0: From traditional approaches to digitalized automated analysis. J FOOD ENG 2023. [DOI: 10.1016/j.jfoodeng.2022.111216] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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10
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Holroyd SE, Nickless E, Watkinson P. Raman and mid‐infrared spectroscopy to assess changes in Cheddar cheese with maturation. INT J DAIRY TECHNOL 2022. [DOI: 10.1111/1471-0307.12929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Stephen E Holroyd
- Fonterra Research and Development Centre Private Bag 11 029 Palmerston North 4442 New Zealand
| | - Elizabeth Nickless
- Fonterra Research and Development Centre Private Bag 11 029 Palmerston North 4442 New Zealand
| | - Philip Watkinson
- Fonterra Research and Development Centre Private Bag 11 029 Palmerston North 4442 New Zealand
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11
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Borba A, Gómez-Zavaglia A. Infrared spectroscopy: an underexploited analytical tool for assessing physico-chemical properties of food products and processing. Curr Opin Food Sci 2022. [DOI: 10.1016/j.cofs.2022.100953] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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12
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Lourenco A, Handschuh S, Fenelon M, Gómez-Mascaraque LG. X-ray computerized microtomography and confocal Raman microscopy as complementary techniques to conventional imaging tools for the microstructural characterization of Cheddar cheese. J Dairy Sci 2022; 105:9387-9403. [DOI: 10.3168/jds.2022-22048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/17/2022] [Indexed: 11/07/2022]
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13
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Abstract
Food quality and safety are the essential hot issues of social concern. In recent years, there has been a growing demand for real-time food information, and non-destructive testing is gradually replacing traditional manual sensory testing and chemical analysis methods with lagging and destructive effects and has strong potential for application in the food supply chain. With the maturity and development of computer science and spectroscopic techniques, machine learning and hyperspectral imaging (HSI) have been widely demonstrated as efficient detection techniques that can be applied to rapidly evaluate sensory characteristics and quality attributes of food products nondestructively and efficiently. This paper first briefly described the basic concepts of hyperspectral imaging and machine learning, including the imaging process of HSI, the type of algorithms contained in machine learning, and the data processing flow. Secondly, this paper provided an objective and comprehensive overview of the current applications of machine learning and HSI in the food supply chain for sorting, packaging, transportation, storage, and sales, based on the state-of-art literature from 2017 to 2022. Finally, the potential of the technology is further discussed to provide optimized ideas for practical application.
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14
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Manzoor MF, Hussain A, Naumovski N, Ranjha MMAN, Ahmad N, Karrar E, Xu B, Ibrahim SA. A Narrative Review of Recent Advances in Rapid Assessment of Anthocyanins in Agricultural and Food Products. Front Nutr 2022; 9:901342. [PMID: 35928834 PMCID: PMC9343702 DOI: 10.3389/fnut.2022.901342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/31/2022] [Indexed: 01/10/2023] Open
Abstract
Anthocyanins (ACNs) are plant polyphenols that have received increased attention recently mainly due to their potential health benefits and applications as functional food ingredients. This has also created an interest in the development and validation of several non-destructive techniques of ACN assessments in several food samples. Non-destructive and conventional techniques play an important role in the assessment of ACNs in agricultural and food products. Although conventional methods appear to be more accurate and specific in their analysis, they are also associated with higher costs, the destruction of samples, time-consuming, and require specialized laboratory equipment. In this review article, we present the latest findings relating to the use of several spectroscopic techniques (fluorescence, Raman, Nuclear magnetic resonance spectroscopy, Fourier-transform infrared spectroscopy, and near-infrared spectroscopy), hyperspectral imaging, chemometric-based machine learning, and artificial intelligence applications for assessing the ACN content in agricultural and food products. Furthermore, we also propose technical and future advancements of the established techniques with the need for further developments and technique amalgamations.
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Affiliation(s)
| | - Abid Hussain
- Department of Agriculture and Food Technology, Faculty of Life Science, Karakoram International University, Gilgit-Baltistan, Pakistan
| | - Nenad Naumovski
- School of Rehabilitation and Exercise Science, Faculty of Health, University of Canberra, Canberra, ACT, Australia
- Functional Foods and Nutrition Research (FFNR) Laboratory, University of Canberra, Bruce, ACT, Australia
| | | | - Nazir Ahmad
- Department of Nutritional Sciences, Faculty of Medical Sciences, Government College University Faisalabad, Faisalabad, Pakistan
| | - Emad Karrar
- State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, China
| | - Bin Xu
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang, China
- *Correspondence: Bin Xu
| | - Salam A. Ibrahim
- Food Microbiology and Biotechnology Laboratory, North Carolina Agricultural and Technical State University, Greensboro, NC, United States
- Salam A. Ibrahim
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15
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Chawanji A, Holroyd SE, Nickless E. Raman confocal microscopy to assess changes in cheddar cheese during maturation. INT J DAIRY TECHNOL 2022. [DOI: 10.1111/1471-0307.12897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Abraham Chawanji
- Fonterra Research and Development Centre PO Box 11 029 Palmerston North 4442 New Zealand
| | - Stephen E Holroyd
- Fonterra Research and Development Centre PO Box 11 029 Palmerston North 4442 New Zealand
| | - Elizabeth Nickless
- Fonterra Research and Development Centre PO Box 11 029 Palmerston North 4442 New Zealand
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16
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Hebling E Tavares JP, da Silva Medeiros ML, Barbin DF. Near-infrared techniques for fraud detection in dairy products: A review. J Food Sci 2022; 87:1943-1960. [PMID: 35362099 DOI: 10.1111/1750-3841.16143] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 03/09/2022] [Accepted: 03/16/2022] [Indexed: 01/14/2023]
Abstract
The dairy products sector is an important part of the food industry, and their consumption is expected to grow in the next 10 years. Therefore, the authentication of these products in a faster and precise way is required for the sake of public health. This review proposes the use of near-infrared techniques for the detection of food fraud in dairy products as they are faster, nondestructive, environmentally friendly, do not require sample preparation, and allow multiconstituent analysis. First, we have described frequent forms of food fraud in dairy products and the application of traditional techniques for their detection, highlighting gaps and counterproductive characteristics for the actual global food chain, as longer sample preparation time and use of reagents. Then, the application of near-infrared spectroscopy and hyperspectral imaging for the detection of food fraud mainly in cheese, butter, and yogurt are described. As these techniques depend on model development, the coverage of different dairy products by the literature will promote the identification of food fraud in a faster and reliable way.
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Affiliation(s)
| | | | - Douglas Fernandes Barbin
- Department of Food Engineering, School of Food Engineering, University of Campinas, Campinas, Brazil
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17
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Abstract
Microscopy is often used to assist the development of cheese products, but manufacturers can benefit from a much broader application of these techniques to assess structure formation during processing and structural changes during storage. Microscopy can be used to benchmark processes, optimize process variables, and identify critical control points for process control. Microscopy can also assist the reverse engineering of desired product properties and help troubleshoot production problems to improve cheese quality. This approach can be extended using quantitative analysis, which enables further comparisons between structural features and functional measures used within industry, such as cheese meltability, shreddability, and stretchability, potentially allowing prediction and control of these properties. This review covers advances in the analysis of cheese microstructure, including new techniques, and outlines how these can be applied to understand and improve cheese manufacture.
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Affiliation(s)
- Lydia Ong
- Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia; .,Dairy Innovation Hub, Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria, Australia
| | - Xu Li
- Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia;
| | - Adabelle Ong
- Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia; .,Dairy Innovation Hub, Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria, Australia
| | - Sally L Gras
- Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia; .,Dairy Innovation Hub, Department of Chemical Engineering, The University of Melbourne, Parkville, Victoria, Australia
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18
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Silva LKR, Santos LS, Ferrão SPB. Application of infrared spectroscopic techniques to cheese authentication: A review. INT J DAIRY TECHNOL 2022. [DOI: 10.1111/1471-0307.12859] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Larissa K R Silva
- Center for Biological and Health Sciences Federal University of Western Bahia Campus Universitário Barreiras Bahia CEP 47810‐047Brazil
| | - Leandro S Santos
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga Bahia CEP 45700‐000 Brazil
| | - Sibelli P B Ferrão
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga Bahia CEP 45700‐000 Brazil
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19
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Bittante G, Patel N, Cecchinato A, Berzaghi P. Invited review: A comprehensive review of visible and near-infrared spectroscopy for predicting the chemical composition of cheese. J Dairy Sci 2022; 105:1817-1836. [PMID: 34998561 DOI: 10.3168/jds.2021-20640] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 09/26/2021] [Indexed: 11/19/2022]
Abstract
Substantial research has been carried out on rapid, nondestructive, and inexpensive techniques for predicting cheese composition using spectroscopy in the visible and near-infrared radiation range. Moreover, in recent years, new portable and handheld spectrometers have been used to predict chemical composition from spectra captured directly on the cheese surface in dairies, storage facilities, and food plants, removing the need to collect, transport, and process cheese samples. For this review, we selected 71 papers (mainly dealing with prediction of the chemical composition of cheese) and summarized their results, focusing our attention on the major sources of variation in prediction accuracy related to cheese variability, spectrometer and spectra characteristics, and chemometrics techniques. The average coefficient of determination obtained from the validation samples ranged from 86 to 90% for predicting the moisture, fat, and protein contents of cheese, but was lower for predicting NaCl content and cheese pH (79 and 56%, respectively). There was wide variability with respect to all traits in the results of the various studies (standard deviation: 9-30%). This review draws attention to the need for more robust equations for predicting cheese composition in different situations; the calibration data set should consist of representative cheese samples to avoid bias due to an overly specific field of application and ensure the results are not biased for a particular category of cheese. Different spectrometers have different accuracies, which do not seem to depend on the spectrum extension. Furthermore, specific areas of the spectrum-the visible, infrared-A, or infrared-B range-may yield similar results to broad-range spectra; this is because several signals related to cheese composition are distributed along the spectrum. Small, portable instruments have been shown to be viable alternatives to large bench-top instruments. Last, chemometrics (spectra pre-treatment and prediction models) play an important role, especially with regard to difficult-to-predict traits. A proper, fully independent, validation strategy is essential to avoid overoptimistic results.
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Affiliation(s)
- Giovanni Bittante
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy
| | - Nageshvar Patel
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy
| | - Alessio Cecchinato
- Department of Agronomy, Food, Natural resources, Animals and Environment (DAFNAE) University of Padova (Padua), 35020 Legnaro, Italy.
| | - Paolo Berzaghi
- Department of Animal Medicine, Production and Health (MAPS), University of Padova (Padua), 35020 Legnaro, Italy
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20
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Calvini R, Michelini S, Pizzamiglio V, Foca G, Ulrici A. Evaluation of the effect of factors related to preparation and composition of grated Parmigiano Reggiano cheese using NIR hyperspectral imaging. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108412] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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21
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Sen M. Food Chemistry: Role of Additives, Preservatives, and Adulteration. Food Chem 2021. [DOI: 10.1002/9781119792130.ch1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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22
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Gopalakrishnan K, Sharma A, Emanuel N, Prabhakar PK, Kumar R. Sensors for Non‐Destructive Quality Evaluation of Food. Food Chem 2021. [DOI: 10.1002/9781119792130.ch13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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23
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Pardo-Botello R, Chamizo-Calero F, Monago-Maraña O, Rodríguez-Corchado R, de la Torre-Carreras R, Galeano-Díaz T. Evaluation of Hydrophilic and Lipophilic Antioxidant Capacity in Spanish Tomato Paste: Usefulness of Front-Face Total Fluorescence Signal Combined with Parafac. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02175-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
AbstractThe hydrophilic and lipophilic antioxidant activities due to the main bioactive components present in Spanish tomato paste samples were studied, using standardized and fluorescent methods. After extraction, phenolic antioxidants (Folin-Ciocalteu method) and total antioxidant activity (TEAC assay) were evaluated, examining differences between hydrophilic and lipophilic extracts corresponding to different samples. Total fluorescence spectra of extracts (excitation-emission matrices, EEMs) were recorded in the front-face mode at two different ranges: 210–300 nm/310–390 nm, and 295–350 nm/380–480 nm, for excitation and emission, respectively, in the hydrophilic extracts. In the lipophilic extracts, the first range was 230–283 nm/290–340 nm, while the second range was 315–383 nm/390–500 nm for excitation and emission, respectively. EEMs from a set of 22 samples were analyzed by the second-order multivariate technique Parallel Factor Analysis (PARAFAC). Tentative assignation of the different components to the various fluorophores of tomato was tried, based on literature. Correlation between the antioxidant activity and score values retrieved for different components in PARAFAC model was obtained. The possibility of using EEMs-PARAFAC to evaluate antioxidant activity of hydrophilic and lipophilic compounds in these samples was examined, obtaining good results in accordance with the Folin-Ciocalteu and TEAC assays.
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24
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A quick look to the use of time domain nuclear magnetic resonance relaxometry and magnetic resonance imaging for food quality applications. Curr Opin Food Sci 2021. [DOI: 10.1016/j.cofs.2021.03.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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25
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Al‐Hilphy AR, Ali HI, Al‐IEssa SA, Lorenzo JM, Barba FJ, Gavahian M. Refractance window (RW) concentration of milk‐Part II: Computer vision approach for optimizing microbial and sensory qualities. J FOOD PROCESS PRES 2021. [DOI: 10.1111/jfpp.15702] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Asaad R. Al‐Hilphy
- Department of Food Science, College of Agriculture University of Basrah Basrah Iraq
| | - Haider I. Ali
- Department of Food Science, College of Agriculture University of Basrah Basrah Iraq
| | - Sajedah A. Al‐IEssa
- Department of Food Science, College of Agriculture University of Basrah Basrah Iraq
| | - José M. Lorenzo
- Centro Tecnológico de la Carne de Galicia San Cibrao das Viñas Spain
- Área de Tecnología de los Alimentos, Facultad de Ciencias de Ourense Universidad de Vigo Ourense Spain
| | - Francisco J. Barba
- Preventive Medicine and Public Health, Food Science, Toxicology and Forensic Medicine Department, Nutrition and Food Science Area Universitat de València València Spain
| | - Mohsen Gavahian
- Department of Food Science National Pingtung University of Science and Technology Pingtung Taiwan, ROC
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26
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Ren Y, Lin X, Lei T, Sun DW. Recent developments in vibrational spectral analyses for dynamically assessing and monitoring food dehydration processes. Crit Rev Food Sci Nutr 2021; 62:4267-4293. [PMID: 34275402 DOI: 10.1080/10408398.2021.1947773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Dehydration is one of the most widely used food processing techniques, which is sophisticated in nature. Rapid and accurate prediction of dehydration performance and its effects on product quality is still a difficult task. Traditional analytical methods for evaluating food dehydration processes are laborious, time-consuming and destructive, and they are not suitable for online applications. On the other hand, vibrational spectral techniques coupled with chemometrics have emerged as a rapid and noninvasive tool with excellent potential for online evaluation and control of the dehydration process to improve final dried food quality. In the current review, the fundamental of food dehydration and five types of vibrational spectral techniques, and spectral data processing methods are introduced. Critical overtones bands related to dehydration attributes in the near-infrared (NIR) region and the state-of-the-art applications of vibrational spectral analyses in evaluating food quality attributes as affected by dehydration processes are summarized. Research investigations since 2010 on using vibrational spectral technologies combined with chemometrics to continuously monitor food quality attributes during dehydration processes are also covered in this review.
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Affiliation(s)
- Yuqiao Ren
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, University College Dublin (UCD), National University of Ireland, Belfield, Dublin 4, Ireland
| | - Xiaohui Lin
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, University College Dublin (UCD), National University of Ireland, Belfield, Dublin 4, Ireland
| | - Tong Lei
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, University College Dublin (UCD), National University of Ireland, Belfield, Dublin 4, Ireland
| | - Da-Wen Sun
- Food Refrigeration and Computerized Food Technology (FRCFT), School of Biosystems and Food Engineering, Agriculture & Food Science Centre, University College Dublin (UCD), National University of Ireland, Belfield, Dublin 4, Ireland
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27
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Özdoğan G, Lin X, Sun DW. Rapid and noninvasive sensory analyses of food products by hyperspectral imaging: Recent application developments. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.02.044] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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28
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Application of Spectroscopic Techniques to Evaluate Heat Treatments in Milk and Dairy Products: an Overview of the Last Decade. FOOD BIOPROCESS TECH 2021. [DOI: 10.1007/s11947-021-02607-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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29
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Silva LKR, Jesus JC, Onelli RRV, Conceição DG, Santos LS, Ferrão SPB. Discriminating Coalho cheese by origin through near and middle infrared spectroscopy and analytical measures. Discrimination of Coalho cheese origin. INT J DAIRY TECHNOL 2021. [DOI: 10.1111/1471-0307.12767] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Larissa K R Silva
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
- Center for Biological and Health Sciences Federal University of Western Bahia Campus Universitário Barreiras BahiaCEP 47810‐047Brazil
| | - Josane C Jesus
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
| | - Rebeca R V Onelli
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
| | - Daniele G Conceição
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
| | - Leandro S Santos
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
| | - Sibelli P B Ferrão
- Program in Food Engineering and Science State University of Bahia Southwest Campus Universitário Itapetinga BahiaCEP 45700‐000Brazil
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30
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Farrugia J, Griffin S, Valdramidis VP, Camilleri K, Falzon O. Principal component analysis of hyperspectral data for early detection of mould in cheeselets. Curr Res Food Sci 2021; 4:18-27. [PMID: 33554131 PMCID: PMC7859297 DOI: 10.1016/j.crfs.2020.12.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 12/27/2020] [Accepted: 12/31/2020] [Indexed: 11/27/2022] Open
Abstract
The application of non-destructive process analytical technologies in the area of food science got a lot of attention the past years. In this work we used hyperspectral imaging to detect mould on milk agar and cheese. Principal component analysis is applied to hyperspectral data to localise and visualise mycelia on the samples' surface. It is also shown that the PCA loadings obtained from a set of training samples can be applied to hyperspectral data from new test samples to detect the presence of mould on these. For both the agar and cheeselets, the first three principal components contained more than 99 % of the total variance. The spatial projection of the second principal component highlights the presence of mould on cheeselets. The proposed analysis methods can be adopted in industry to detect mould on cheeselets at an early stage and with further testing this application may also be extended to other food products.
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Affiliation(s)
- Jessica Farrugia
- Centre for Biomedical Cybernetics, University of Malta, Msida, Malta
| | - Sholeem Griffin
- Centre for Biomedical Cybernetics, University of Malta, Msida, Malta.,Department of Food Sciences and Nutrition, University of Malta, Msida, Malta.,Centre of Molecular Medicine and Biobanking, University of Malta, Msida, Malta
| | - Vasilis P Valdramidis
- Department of Food Sciences and Nutrition, University of Malta, Msida, Malta.,Centre of Molecular Medicine and Biobanking, University of Malta, Msida, Malta
| | - Kenneth Camilleri
- Centre for Biomedical Cybernetics, University of Malta, Msida, Malta.,Department of Systems & Control Engineering, Faculty of Engineering, University of Malta, Msida, Malta
| | - Owen Falzon
- Centre for Biomedical Cybernetics, University of Malta, Msida, Malta
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31
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Kõrge K, Šeme H, Bajić M, Likozar B, Novak U. Reduction in Spoilage Microbiota and Cyclopiazonic Acid Mycotoxin with Chestnut Extract Enriched Chitosan Packaging: Stability of Inoculated Gouda Cheese. Foods 2020; 9:E1645. [PMID: 33187311 PMCID: PMC7697305 DOI: 10.3390/foods9111645] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Revised: 11/07/2020] [Accepted: 11/09/2020] [Indexed: 12/16/2022] Open
Abstract
Active chitosan-based films, blended with fibrous chestnut (Castanea sativa Mill.) tannin-rich extract were used to pack Gouda cheese that has been contaminated with spoilage microflora Pseudomonas fluorescens, Escherichia coli, and fungi Penicillium commune. A comprehensive experimental plan including active chitosan-based films with (i) chestnut extract (CE), (ii) tannic acid (TA), and (iii) without additives was applied to evaluate the film's effect on induced microbiological spoilage reduction and chemical indices of commercial Gouda cheese during 37 days while stored at 4 °C and 25 °C, respectively. The cheese underwent microbiology analysis and chemical assessments of ultra-high-performance liquid chromatography (UHPLC) (cyclopiazonic acid), pH, and moisture content. The biopackaging used for packing cheese was characterized by mechanical properties before food packaging and analyzed with the same chemical analysis. The cheese microbiology showed that the bacterial counts were most efficiently decreased by the film without additives. However, active films with CE and TA were more effective as they did not break down around the cheese and showed protective properties against mycotoxin, moisture loss, and pH changes. Films themselves, when next to high-fat content food, changed their pH to less acidic, acted as absorbers, and degraded without plant-derived additives.
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Affiliation(s)
- Kristi Kõrge
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia; (K.K.); (M.B.); (B.L.)
- Department of Chemistry and Biotechnology, Tallinn University of Technology, Akadeemia tee 15, 12618 Tallinn, Estonia
| | - Helena Šeme
- Acies Bio d.o.o., Tehnološki park 21, 1000 Ljubljana, Slovenia;
| | - Marijan Bajić
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia; (K.K.); (M.B.); (B.L.)
| | - Blaž Likozar
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia; (K.K.); (M.B.); (B.L.)
| | - Uroš Novak
- Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia; (K.K.); (M.B.); (B.L.)
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32
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Lin X, Sun DW. Recent developments in vibrational spectroscopic techniques for tea quality and safety analyses. Trends Food Sci Technol 2020. [DOI: 10.1016/j.tifs.2020.06.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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33
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Boukria O, El Hadrami EM, Boudalia S, Safarov J, Leriche F, Aït-Kaddour A. The Effect of Mixing Milk of Different Species on Chemical, Physicochemical, and Sensory Features of Cheeses: A Review. Foods 2020; 9:E1309. [PMID: 32957530 PMCID: PMC7555713 DOI: 10.3390/foods9091309] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Revised: 09/12/2020] [Accepted: 09/14/2020] [Indexed: 01/29/2023] Open
Abstract
The yield and quality of cheese are associated with the composition, physicochemical, sensory, rheological, and microbiological properties of milk and with the technology applied to the milk before and/or during cheese processing. This review describes the most important research on cheeses obtained from processing mixtures of different milk species and discusses the effect of milk mixtures (i.e., species and mixture ratios) on composition, physicochemical, sensory, rheological, and microbiological properties of cheeses. More specifically, the present review paper will gather and focus only on studies that have provided a clear comparison between cheeses produced from a mixture of two milk species to cheeses produced from only one species.
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Affiliation(s)
- Oumayma Boukria
- Applied Organic Chemistry Laboratory, Sciences and Techniques Faculty, Sidi Mohamed Ben Abedallah University, BP 2202 Route d’Immouzer, Fez 30050, Morocco; (O.B.); (E.M.E.H.)
| | - El Mestafa El Hadrami
- Applied Organic Chemistry Laboratory, Sciences and Techniques Faculty, Sidi Mohamed Ben Abedallah University, BP 2202 Route d’Immouzer, Fez 30050, Morocco; (O.B.); (E.M.E.H.)
| | - Sofiane Boudalia
- Laboratoire de Biologie, Département d’Écologie et Génie de l’Environnement, Faculté des Sciences de la Nature et de la Vie & Sciences de la Terre et l’Univers, Université 8 Mai 1945 Guelma, BP 401, Guelma 24000, Algeria;
| | - Jasur Safarov
- Department of Food Engineering, Faculty of Mechanical Building, Tashkent State Technical University Named after Islam Karimov, University str. 2, Tashkent 100095, Uzbekistan;
| | - Françoise Leriche
- Université Clermont Auvergne, INRA, VetAgro Sup, UMRF, F-63370 Lempdes, France;
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34
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Classification of Hyperspectral In Vivo Brain Tissue Based on Linear Unmixing. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10165686] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Hyperspectral imaging is a multidimensional optical technique with the potential of providing fast and accurate tissue classification. The main challenge is the adequate processing of the multidimensional information usually linked to long processing times and significant computational costs, which require expensive hardware. In this study, we address the problem of tissue classification for intraoperative hyperspectral images of in vivo brain tissue. For this goal, two methodologies are introduced that rely on a blind linear unmixing (BLU) scheme for practical tissue classification. Both methodologies identify the characteristic end-members related to the studied tissue classes by BLU from a training dataset and classify the pixels by a minimum distance approach. The proposed methodologies are compared with a machine learning method based on a supervised support vector machine (SVM) classifier. The methodologies based on BLU achieve speedup factors of ~459× and ~429× compared to the SVM scheme, while keeping constant and even slightly improving the classification performance.
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35
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González-Martín MI, Vivar-Quintana AM, Revilla I, Salvador-Esteban J. The determination of fatty acids in cheeses of variable composition (cow, ewe's, and goat) by means of near infrared spectroscopy. Microchem J 2020. [DOI: 10.1016/j.microc.2020.104854] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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36
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A novel NIR spectral calibration method: Sparse coefficients wavelength selection and regression (SCWR). Anal Chim Acta 2020; 1110:169-180. [DOI: 10.1016/j.aca.2020.03.007] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 03/03/2020] [Accepted: 03/04/2020] [Indexed: 11/19/2022]
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37
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Rapid Methods for Assessing Food Safety and Quality. Foods 2020; 9:foods9040533. [PMID: 32340291 PMCID: PMC7230918 DOI: 10.3390/foods9040533] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 04/16/2020] [Indexed: 11/17/2022] Open
Abstract
Food safety represents a central issue for the global food chain and a daily concern for all people. Contaminated food by physical, biological or chemical hazards can harm consumers, increasing demand for health services, government expenditure on public health and other social costs. The quality assurance programs are based on the continuous monitoring of raw matter, production process, storage and distribution of the end products, including the purpose for which they are intended. Such programs represent an important objective for food producers, not only for the potential risk to human health, but also for the economic losses to which they can be subjected. The development and use of rapid analytical methods able to identify the main failures in food production can benefit food companies by saving time and costs for the good and fast control of products through the entire food chain.
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38
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Rodriguez-Saona L, Aykas DP, Borba KR, Urtubia A. Miniaturization of optical sensors and their potential for high-throughput screening of foods. Curr Opin Food Sci 2020. [DOI: 10.1016/j.cofs.2020.04.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
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39
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Nastaj M, Terpiłowski K, Sołowiej BG. The effect of native and polymerised whey protein isolate addition on surface and microstructural properties of processed cheeses and their meltability determined by Turbiscan. Int J Food Sci Technol 2020. [DOI: 10.1111/ijfs.14471] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Maciej Nastaj
- Department of Milk Technology and Hydrocolloids Faculty of Food Sciences and Biotechnology University of Life Sciences in Lublin Skromna 8 20‐704 Lublin Poland
| | - Konrad Terpiłowski
- Department of Physical Chemistry‐Interfacial Phenomena Maria Curie Skłodowska University M. Curie Skłodowska Sq. 3 20‐031 Lublin Poland
| | - Bartosz G. Sołowiej
- Department of Milk Technology and Hydrocolloids Faculty of Food Sciences and Biotechnology University of Life Sciences in Lublin Skromna 8 20‐704 Lublin Poland
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40
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Priyashantha H, Höjer A, Saedén KH, Lundh Å, Johansson M, Bernes G, Geladi P, Hetta M. Use of near-infrared hyperspectral (NIR-HS) imaging to visualize and model the maturity of long-ripening hard cheeses. J FOOD ENG 2020. [DOI: 10.1016/j.jfoodeng.2019.109687] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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