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Yu Y, Chen W, Zhang H, Liu R, Li C. Discrimination among Fresh, Frozen-Stored and Frozen-Thawed Beef Cuts by Hyperspectral Imaging. Foods 2024; 13:973. [PMID: 38611279 PMCID: PMC11011688 DOI: 10.3390/foods13070973] [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: 02/15/2024] [Revised: 03/14/2024] [Accepted: 03/19/2024] [Indexed: 04/14/2024] Open
Abstract
The detection of the storage state of frozen meat, especially meat frozen-thawed several times, has always been important for food safety inspections. Hyperspectral imaging (HSI) is widely applied to detect the freshness and quality of meat or meat products. This study investigated the feasibility of the low-cost HSI system, combined with the chemometrics method, to classify beef cuts among fresh (F), frozen-stored (F-S), frozen-thawed three times (F-T-3) and frozen-thawed five times (F-T-5). A compact, low-cost HSI system was designed and calibrated for beef sample measurement. The classification model was developed for meat analysis with a method to distinguish fat and muscle, a CARS algorithm to extract the optimal wavelength subset and three classifiers to identify each beef cut among different freezing processes. The results demonstrated that classification models based on feature variables extracted from differentiated tissue spectra achieved better performances, with ACCs of 92.75% for PLS-DA, 97.83% for SVM and 95.03% for BP-ANN. A visualization map was proposed to provide detailed information about the changes in freshness of beef cuts after freeze-thawing. Furthermore, this study demonstrated the potential of implementing a reasonably priced HSI system in the food industry.
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Affiliation(s)
- Yuewen Yu
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China; (Y.Y.); (W.C.); (H.Z.)
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Wenliang Chen
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China; (Y.Y.); (W.C.); (H.Z.)
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Hanwen Zhang
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China; (Y.Y.); (W.C.); (H.Z.)
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Rong Liu
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Chenxi Li
- State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China; (Y.Y.); (W.C.); (H.Z.)
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Čandek-Potokar M, Lebret B, Gispert M, Font-I-Furnols M. Challenges and future perspectives for the European grading of pig carcasses - A quality view. Meat Sci 2024; 208:109390. [PMID: 37977057 DOI: 10.1016/j.meatsci.2023.109390] [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: 04/30/2023] [Revised: 11/03/2023] [Accepted: 11/05/2023] [Indexed: 11/19/2023]
Abstract
This study sought to evaluate pig carcass grading, describing the existing approaches and definitions, and highlighting the vision for overall quality grading. In particular, the current state of pig carcass grading in the European Union (SEUROP system), its weaknesses, and the challenges to achieve more uniformity and harmonization across member states were described, and a broader understanding of pig carcass value, which includes a vision for the inclusion of meat quality aspects in the grading, was discussed. Finally, the noninvasive methods for the on-line evaluation of pig carcass and meat quality (hereafter referred to as pork quality), and the conditions for their application were discussed. As the way pigs are raised (especially in terms of animal welfare and environmental impact), and more importantly, their perception of pork quality, is becoming increasingly important to consumers, the ideal grading of pigs should comprise pork quality aspects. As a result, a forward-looking "overall quality" approach to pork grading was proposed herein, in which grading systems would be based on the shared vision for pork quality (carcass and meat quality) among stakeholders in the pig industry and driven by consumer expectations with respect to the product. Emerging new technologies provide the technical foundation for such perspective; however, integrating all knowledge and technologies for their practical application to an "overall quality" grading approach is a major challenge. Nonetheless, such approach aligns with the recent vision of Industry 5.0, i.e. a model for the next level of industrialization that is human-centric, resilient, and sustainable.
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Affiliation(s)
- Marjeta Čandek-Potokar
- Agricultural Institute of Slovenia (KIS), Hacquetova ulica 17, 1000 Ljubljana, Slovenia.
| | | | - Marina Gispert
- IRTA-Food Quality and Technology, Finca Camps i Armet, E-17121 Monells, Girona, Spain
| | - Maria Font-I-Furnols
- IRTA-Food Quality and Technology, Finca Camps i Armet, E-17121 Monells, Girona, Spain
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Jiménez A, Rufo M, Paniagua JM, González-Mohino A, Antequera T, Perez-Palacios T. Acoustic Characterization Study of Beef Loins Using Ultrasonic Transducers. SENSORS (BASEL, SWITZERLAND) 2023; 23:9564. [PMID: 38067937 PMCID: PMC10708575 DOI: 10.3390/s23239564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/18/2023]
Abstract
The objective of this study was to non-destructively characterize samples of fresh beef loin by low-intensity ultrasound inspection at various frequencies and to correlate the acoustic parameters of these inspections with quality parameters. In this regard, ultrasonic parameters such as ultrasound pulse velocity (UPV) and variables related to attenuation and frequency components obtained from fast Fourier transform (FFT) were considered. For this, pulsed ultrasonic signal transducers with a frequency of 0.5 and 1.0 MHz were used. Acoustic parameters and those obtained through traditional instrumental analyses (physicochemical and texture) underwent a Pearson correlation analysis. The acoustic determinations revealed numerous significant correlations with the rest of the studied parameters. The results demonstrate that ultrasonic inspection has the ability to characterize samples with a non-destructive nature, and likewise, this methodology can be postulated as a promising predictive tool for determining quality parameters in beef loin samples.
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Affiliation(s)
- Antonio Jiménez
- Department of Applied Physics, School of Technology, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (A.J.); (M.R.)
| | - Montaña Rufo
- Department of Applied Physics, School of Technology, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (A.J.); (M.R.)
| | - Jesús M. Paniagua
- Department of Applied Physics, School of Technology, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (A.J.); (M.R.)
| | - Alberto González-Mohino
- Department of Food Technology, Faculty of Veterinary, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (T.A.); (T.P.-P.)
| | - Teresa Antequera
- Department of Food Technology, Faculty of Veterinary, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (T.A.); (T.P.-P.)
| | - Trinidad Perez-Palacios
- Department of Food Technology, Faculty of Veterinary, Research Institute of Meat and Meat Product, Universidad de Extremadura, Avenida de la Universidad s/n, 10003 Cáceres, Spain; (T.A.); (T.P.-P.)
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Ghidini S, De Luca S, Rinaldi E, Zanardi E, Ianieri A, Guadagno F, Alborali GL, Meemken D, Conter M, Varrà MO. Comparing Visual-Only and Visual-Palpation Post-Mortem Lung Scoring Systems in Slaughtering Pigs. Animals (Basel) 2023; 13:2419. [PMID: 37570228 PMCID: PMC10417645 DOI: 10.3390/ani13152419] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 07/19/2023] [Accepted: 07/25/2023] [Indexed: 08/13/2023] Open
Abstract
Respiratory diseases continue to pose significant challenges in pig production, and the assessment of lung lesions at the abattoir can provide valuable data for epidemiological investigations and disease surveillance. The evaluation of lung lesions at slaughter is a relatively simple, fast, and straightforward process but variations arising from different abattoirs, observers, and scoring methods can introduce uncertainty; moreover, the presence of multiple scoring systems complicates the comparisons of different studies, and currently, there are limited studies that compare these systems among each other. The objective of this study was to compare validated, simplified, and standardized schemes for assessing surface-related lung lesions in slaughtered pigs and analyze their reliability under field conditions. This study was conducted in a high-throughput abattoir in Italy, where two different scoring methods (Madec and Blaha) were benchmarked using 637 plucks. Statistical analysis revealed a good agreement between the two methods when severe or medium lesions were observed; however, their ability to accurately identify healthy lungs and minor injuries diverged significantly. These findings demonstrate that the Blaha method is more suitable for routine surveillance of swine respiratory diseases, whereas the Madec method can give more detailed and reliable results for the respiratory and welfare status of the animals at the farm level.
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Affiliation(s)
- Sergio Ghidini
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
| | - Silvio De Luca
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
| | - Elena Rinaldi
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
| | - Emanuela Zanardi
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
| | - Adriana Ianieri
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
| | - Federica Guadagno
- Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia-Romagna-Headquarters, Via A. Bianchi, 9, 25124 Brescia, Italy; (F.G.); (G.L.A.)
| | - Giovanni Loris Alborali
- Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia-Romagna-Headquarters, Via A. Bianchi, 9, 25124 Brescia, Italy; (F.G.); (G.L.A.)
| | - Diana Meemken
- Department of Veterinary Medicine, Institute of Food Safety and Food Hygiene, Freie Universität Berlin, 14163 Berlin, Germany;
| | - Mauro Conter
- Department of Veterinary Science, University of Parma, Via del Taglio 10, 43126 Parma, Italy
| | - Maria Olga Varrà
- Department of Food and Drug, University of Parma, Via del Taglio 10, 43126 Parma, Italy; (S.G.); (S.D.L.); (E.R.); (E.Z.); (A.I.); (M.O.V.)
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Lin DY, Yu CY, Ku CA, Chung CK. Design, Fabrication, and Applications of SERS Substrates for Food Safety Detection: Review. MICROMACHINES 2023; 14:1343. [PMID: 37512654 PMCID: PMC10385374 DOI: 10.3390/mi14071343] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 06/25/2023] [Accepted: 06/28/2023] [Indexed: 07/30/2023]
Abstract
Sustainable and safe food is an important issue worldwide, and it depends on cost-effective analysis tools with good sensitivity and reality. However, traditional standard chemical methods of food safety detection, such as high-performance liquid chromatography (HPLC), gas chromatography (GC), and tandem mass spectrometry (MS), have the disadvantages of high cost and long testing time. Those disadvantages have prevented people from obtaining sufficient risk information to confirm the safety of their products. In addition, food safety testing, such as the bioassay method, often results in false positives or false negatives due to little rigor preprocessing of samples. So far, food safety analysis currently relies on the enzyme-linked immunosorbent assay (ELISA), polymerase chain reaction (PCR), HPLC, GC, UV-visible spectrophotometry, and MS, all of which require significant time to train qualified food safety testing laboratory operators. These factors have hindered the development of rapid food safety monitoring systems, especially in remote areas or areas with a relative lack of testing resources. Surface-enhanced Raman spectroscopy (SERS) has emerged as one of the tools of choice for food safety testing that can overcome these dilemmas over the past decades. SERS offers advantages over chromatographic mass spectrometry analysis due to its portability, non-destructive nature, and lower cost implications. However, as it currently stands, Raman spectroscopy is a supplemental tool in chemical analysis, reinforcing and enhancing the completeness and coverage of the food safety analysis system. SERS combines portability with non-destructive and cheaper detection costs to gain an advantage over chromatographic mass spectrometry analysis. SERS has encountered many challenges in moving toward regulatory applications in food safety, such as quantitative accuracy, poor reproducibility, and instability of large molecule detection. As a result, the reality of SERS, as a screening tool for regulatory announcements worldwide, is still uncommon. In this review article, we have compiled the current designs and fabrications of SERS substrates for food safety detection to unify all the requirements and the opportunities to overcome these challenges. This review is expected to improve the interest in the sensing field of SERS and facilitate the SERS applications in food safety detection in the future.
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Affiliation(s)
- Ding-Yan Lin
- Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Chung-Yu Yu
- Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Chin-An Ku
- Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan
| | - Chen-Kuei Chung
- Department of Mechanical Engineering, National Cheng Kung University, Tainan 701, Taiwan
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Putri LA, Rahman I, Puspita M, Hidayat SN, Dharmawan AB, Rianjanu A, Wibirama S, Roto R, Triyana K, Wasisto HS. Rapid analysis of meat floss origin using a supervised machine learning-based electronic nose towards food authentication. NPJ Sci Food 2023; 7:31. [PMID: 37328497 DOI: 10.1038/s41538-023-00205-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Accepted: 05/26/2023] [Indexed: 06/18/2023] Open
Abstract
Authentication of meat floss origin has been highly critical for its consumers due to existing potential risks of having allergic diseases or religion perspective related to pork-containing foods. Herein, we developed and assessed a compact portable electronic nose (e-nose) comprising gas sensor array and supervised machine learning with a window time slicing method to sniff and to classify different meat floss products. We evaluated four different supervised learning methods for data classification (i.e., linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbors (k-NN), and random forest (RF)). Among them, an LDA model equipped with five-window-extracted feature yielded the highest accuracy values of >99% for both validation and testing data in discriminating beef, chicken, and pork flosses. The obtained e-nose results were correlated and confirmed with the spectral data from Fourier-transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) measurements. We found that beef and chicken had similar compound groups (i.e., hydrocarbons and alcohol). Meanwhile, aldehyde compounds (e.g., dodecanal and 9-octadecanal) were found to be dominant in pork products. Based on its performance evaluation, the developed e-nose system shows promising results in food authenticity testing, which paves the way for ubiquitously detecting deception and food fraud attempts.
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Affiliation(s)
- Linda Ardita Putri
- PT Nanosense Instrument Indonesia, Yogyakarta, 55167, Indonesia
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta, 55281, Indonesia
| | - Iman Rahman
- PT Nanosense Instrument Indonesia, Yogyakarta, 55167, Indonesia
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta, 55281, Indonesia
| | - Mayumi Puspita
- PT Nanosense Instrument Indonesia, Yogyakarta, 55167, Indonesia
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta, 55281, Indonesia
- Indonesian Oil Palm Research Institute, Jalan Taman Kencana No 1, Bogor, 16128, Indonesia
| | | | - Agus Budi Dharmawan
- PT Nanosense Instrument Indonesia, Yogyakarta, 55167, Indonesia
- Faculty of Information Technology, Universitas Tarumanagara, Jl. Letjen S. Parman No. 1, Jakarta, 11440, Indonesia
| | - Aditya Rianjanu
- Department of Materials Engineering, Institut Teknologi Sumatera, Terusan Ryacudu, Way Hui, Jati Agung, Lampung, 35365, Indonesia
| | - Sunu Wibirama
- Department of Electrical and Information Engineering, Universitas Gadjah Mada, Jl. Grafika 2, Yogyakarta, 55281, Indonesia
| | - Roto Roto
- Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta, 55281, Indonesia
| | - Kuwat Triyana
- Department of Physics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara PO Box BLS 21, Yogyakarta, 55281, Indonesia.
- Institute of Halal Industry and System (IHIS), Universitas Gadjah Mada, Sekip Utara, Yogyakarta, 55281, Indonesia.
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