1
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Mori S, Hall CR, Bradley SJ, Smith TA. Multidimensional fluorescence spectroscopy of wine using synchronous excitation/emission matrices and time-resolved fluorescence interferometric detection. Methods Appl Fluoresc 2024; 12:045001. [PMID: 39019074 DOI: 10.1088/2050-6120/ad64a9] [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: 04/04/2024] [Accepted: 07/17/2024] [Indexed: 07/19/2024]
Abstract
Wines are complex mixtures of chemical compounds with broad and overlapping absorption and emission spectral features in the UV and visible spectral regions, making them challenging to study with conventional optical spectroscopic techniques. Multidimensional fluorescence spectroscopies correlate fluorescence spectra with other degrees of freedom, and have proven useful for studying complex molecular systems, offering a pathway for the analysis of wines utilising their inherent fluorescence. Here we employ steady-state excitation-emission matrix (EEM) and time-resolved fluorescence spectral measurements to investigate representative commercial white and red wine samples and a fluorescent 'model' wine base. Combining these multidimensional measurement methods provides information on the emission characteristics of the components that wines contain. This investigation illustrates the potential for multidimensional fluorescence techniques as diagnostic tools for the wine industry.
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Affiliation(s)
- Sakuya Mori
- School of Chemistry, University of Melbourne, 3010, Victoria, Australia
- ARC Centre of Excellence in Exciton Science, University of Melbourne, 3010, Victoria, Australia
| | - Christopher R Hall
- School of Chemistry, University of Melbourne, 3010, Victoria, Australia
- ARC Centre of Excellence in Exciton Science, University of Melbourne, 3010, Victoria, Australia
| | - Siobhan J Bradley
- School of Chemistry, University of Melbourne, 3010, Victoria, Australia
- ARC Centre of Excellence in Exciton Science, University of Melbourne, 3010, Victoria, Australia
| | - Trevor A Smith
- School of Chemistry, University of Melbourne, 3010, Victoria, Australia
- ARC Centre of Excellence in Exciton Science, University of Melbourne, 3010, Victoria, Australia
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2
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Zhu Y, Gu M, Su Y, Li Z, Xiao Z, Lu F, Han C. Recent advances in spoilage mechanisms and preservation technologies in beef quality: A review. Meat Sci 2024; 213:109481. [PMID: 38461675 DOI: 10.1016/j.meatsci.2024.109481] [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: 11/20/2023] [Revised: 03/04/2024] [Accepted: 03/05/2024] [Indexed: 03/12/2024]
Abstract
Beef is a popular meat product that can spoil and lose quality during postharvest handling and storage. This review examines different preservation methods for beef, from conventional techniques like low-temperature preservation, irradiation, vacuum packing, and chemical preservatives, to novel approaches like bacteriocin, essential oil, and non-thermal technologies. It also discusses how these methods work and affect beef quality. The review shows that beef spoilage is mainly due to enzymatic and microbial activities that impact beef freshness, texture, and quality. Although traditional preservation methods can extend beef shelf life, they have some drawbacks and limitations. Therefore, innovative preservation methods have been created and tested to improve beef quality and safety. These methods have promising results and potential applications in the beef industry. However, more research is needed to overcome the challenges and barriers for their commercialization. This review gives a comprehensive and critical overview of the current and emerging preservation methods for beef and their implications for the beef supply chain.
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Affiliation(s)
- Yiqun Zhu
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China
| | - Mengqing Gu
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China
| | - Yuhan Su
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China
| | - Zhe Li
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China; Shenyang Key Laboratory of Grain and Oil Deep Processing, Shenyang, Liaoning 110034, China
| | - Zhigang Xiao
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China; Shenyang Key Laboratory of Grain and Oil Deep Processing, Shenyang, Liaoning 110034, China
| | - Fei Lu
- College of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning 110034, China; Shenyang Key Laboratory of Grain and Oil Deep Processing, Shenyang, Liaoning 110034, China.
| | - Chunyang Han
- Guangxi Key Laboratory of Health Care Food Science and Technology, Hezhou, Guangxi 542899, China.
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3
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Liu H, Zhu L, Ji Z, Zhang M, Yang X. Porphyrin fluorescence imaging for real-time monitoring and visualization of the freshness of beef stored at different temperatures. Food Chem 2024; 442:138420. [PMID: 38237294 DOI: 10.1016/j.foodchem.2024.138420] [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: 07/13/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 02/15/2024]
Abstract
This study presents a novel fluorescence imaging method for the real-time monitoring of beef quality deterioration and freshness. The fluorescence property of porphyrin in the form of heme can be used to characterize quality changes in beef during storage. Therefore, a fluorescence imaging system with an excitation light source of 440 nm and a CCD camera with a specific wavelength filter of 595 nm was constructed, and the porphyrin fluorescence images of beef samples stored at different temperatures were then collected. The quantitative model for predicting the microbial freshness indicator (TVC) of beef was built with the support vector machine regression (SVR) algorithm and produced satisfactory results with Rc2 and Rp2 of 0.858 and 0.812, respectively. The classification model based on the support vector machine (SVM) algorithm classified beef freshness into "fresh" and "spoiled", with calibration and prediction accuracy of 100 % and 90.9 %, respectively.
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Affiliation(s)
- Huan Liu
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China; Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
| | - Lei Zhu
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
| | - Zengtao Ji
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China; Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China
| | - Min Zhang
- Academy of Agricultural Planning and Engineering, Ministry of Agriculture and Rural Affairs, Beijing 100125, China.
| | - Xinting Yang
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China; National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China; National Engineering Laboratory for Agri-product Quality Traceability, Beijing 100097, China; Key Laboratory of Cold Chain Logistics Technology for Agro-product, Ministry of Agriculture and Rural Affairs, Beijing 100097, China.
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4
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Hong SJ, Riahi Z, Shin GH, Kim JT. Development of innovative active packaging films using gelatin/pullulan-based composites incorporated with cinnamon essential oil-loaded metal-organic frameworks for meat preservation. Int J Biol Macromol 2024; 267:131606. [PMID: 38631566 DOI: 10.1016/j.ijbiomac.2024.131606] [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: 11/08/2023] [Revised: 02/28/2024] [Accepted: 04/12/2024] [Indexed: 04/19/2024]
Abstract
This study aimed to investigate the effect of cinnamon essential oil (CEO)-loaded metal-organic frameworks (CEO@MOF) on the properties of gelatin/pullulan (Gel/Pull)-based composite films (Gel/Pull-based films). The incorporation of CEO@MOF into Gel/Pull-based films demonstrated significant antimicrobial activity against S. aureus, S. enterica, E. coli, and L. monocytogenes. Additionally, CEO@MOF integrated film exhibited a 98.16 % ABTS radical scavenging, with no significant change in the mechanical properties of the neat Gel/Pull film. The UV blocking efficiency of the composite films increased significantly from 81.38 to 99.56 % at 280 nm with the addition of 3 wt% CEO@MOF. Additionally, Gel/Pull/CEO@MOF films effectively extended the shelf life of meat preserved at 4 °C by reducing moisture loss by 3.35 %, maintaining the pH within the threshold limit (6.2), and inhibiting bacterial growth by 99.9 %. These results propose that CEO@MOF has significant potential as an effective additive in active packaging to improve shelf life and food safety.
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Affiliation(s)
- Su Jung Hong
- Department of Food and Nutrition, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Zohreh Riahi
- Department of Food and Nutrition, Kyung Hee University, Seoul 02447, Republic of Korea; BioNanocomposite Research Center, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Gye Hwa Shin
- Department of Food and Nutrition, Kunsan National University, Gunsan 54150, Republic of Korea.
| | - Jun Tae Kim
- Department of Food and Nutrition, Kyung Hee University, Seoul 02447, Republic of Korea; BioNanocomposite Research Center, Kyung Hee University, Seoul 02447, Republic of Korea.
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5
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Leng D, Ren X, Liu L, Zhang D, Zhang N, Ju H, Wei Q. A self-powered photoelectrochemical biosensing platform for H-FABP monitoring mediated by CsPbBr 3@COF-V. Biosens Bioelectron 2023; 241:115710. [PMID: 37769486 DOI: 10.1016/j.bios.2023.115710] [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: 06/25/2023] [Revised: 09/08/2023] [Accepted: 09/22/2023] [Indexed: 10/03/2023]
Abstract
Advanced bioelectronic detection based on the integration of modern optical electronics and biological systems has a broad prospect. The strategy of cathode signal amplification in self-powered photoelectrochemical (PEC) immunosensors with excellent performance is rarely reported in the field of immune analysis. Herein, the work demonstrates a self-powered PEC biosensor formed with BiOI photocathode and WO3/SnS2/ZnS photoanode, and CsPbBr3@COF-V was used as the photocathode signal quenching source for the quantitative monitoring of heart fatty acid binding protein (H-FABP). The high efficiency and stable self-powered biosensor formed not only provides continuous and powerful photocurrent response for bioanalysis through reasonable stepped band structure, but also effectively eliminates the interference of reducing substances. The quenching source CsPbBr3@COF-V greatly affects the photocurrent response due to steric hindrance, weak conductivity, competition with the substrate for dissolved oxygen and excitation light source. And the intervention of this key factor achieves multiple signal amplification effect and opens up an innovative vision for self-powered PEC immunosensor. Taking H-FABP as a representative analyte, the proposed signal amplification self-powered photoelectrochemical presents a broad linear range from 0.0005 to 150 ng/mL with the detection limit of 0.19 pg/mL.
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Affiliation(s)
- Dongquan Leng
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China
| | - Xiang Ren
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China
| | - Lei Liu
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China
| | - Daopeng Zhang
- School of Chemistry and Chemical Engineering, Shandong University of Technology, Zibo, 255049, PR China
| | - Nuo Zhang
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China; School of Chemistry and Chemical Engineering, Shandong University of Technology, Zibo, 255049, PR China.
| | - Huangxian Ju
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China; State Key Laboratory of Analytical Chemistry for Life Science, Department of Chemistry, Nanjing University, Nanjing, 210023, PR China
| | - Qin Wei
- Collaborative Innovation Center for Green Chemical Manufacturing and Accurate Detection, Key Laboratory of Interfacial Reaction & Sensing Analysis in Universities of Shandong, School of Chemistry and Chemical Engineering, University of Jinan, Jinan, 250022, PR China; Department of Chemistry, Sungkyunkwan University, Suwon, 16419, Republic of Korea.
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Zhao J, Ni Y, Tan L, Zhang W, Zhou H, Xu B. Recent advances in meat freshness "magnifier": fluorescence sensing. Crit Rev Food Sci Nutr 2023:1-17. [PMID: 37555377 DOI: 10.1080/10408398.2023.2241553] [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: 08/10/2023]
Abstract
To address the serious waste of meat resources and food safety problems caused by the decrease in meat freshness due to the action of microorganisms and enzymes, a low-cost, time-saving and high-efficiency freshness monitoring method is urgently needed. Fluorescence sensing could act as a "magnifier" for meat freshness monitoring due to its ability to sense characteristic signal produced by meat spoilage. Here, the magnification mechanism of meat freshness via sensing the water activity, adenosine triphosphate, hydrogen ion, total volatile basic nitrogen, hydrogen sulfide, bioamines was comprehensively analyzed. The existing "magnifier" forms including paper chips, films, labels, arrays, probes, and hydrogels as well as the application in livestock, poultry and aquatic meat freshness monitoring were reviewed. Future research directions involving innovation of principles, visualization and quantification capabilities for various meats freshness were provided. By critically evaluating the potential and limitations, efficient and reliable meat freshness monitoring strategies wish to be developed for the post-epidemic era.
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Affiliation(s)
- Jinsong Zhao
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
| | - Yongsheng Ni
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
| | - Lijun Tan
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
| | - Wendi Zhang
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
| | - Hui Zhou
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
| | - Baocai Xu
- School of Food and Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
- Engineering Research Center of Bio-Process of Ministry of Education, School of Food & Biological Engineering, Hefei University of Technology, Hefei, Anhui Province, China
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7
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Liu ZX, Tang SH, Wang Y, Tan J, Jiang ZT. Rapid, simultaneous and non-destructive determination of multiple adulterants in Panax notoginseng powder by front-face total synchronous fluorescence spectroscopy. Fitoterapia 2023; 166:105469. [PMID: 36907229 DOI: 10.1016/j.fitote.2023.105469] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 02/16/2023] [Accepted: 03/06/2023] [Indexed: 03/13/2023]
Abstract
The authentication of traditional herbal medicines in powder form is of great significance, as they are always of high values but vulnerable to adulteration. Based on the distinct fluorescence of protein tryptophan, phenolic acids and flavonoids, front-face synchronous fluorescence spectroscopy (FFSFS) was applied for the fast and non-invasive authentication of Panax notoginseng powder (PP) adulterated with the powder of rhizoma curcumae (CP), maize flour (MF) and whole wheat flour (WF). For either single or multiple adulterants in the range of 5-40% w/w, prediction models were built based on the combination of unfolded total synchronous fluorescence spectra and partial least square (PLS) regression, and were validated by both five-fold cross-validation and external validation. The constructed PLS2 models simultaneously predicted the contents of multiple adulterants in PP and gave suitable results, with most of the determination coefficients of prediction (Rp2) >0.9, the root mean square error of prediction (RMSEP) no >4% and residual predictive deviation (RPD) >2. The limits of detections (LODs) were 12.0, 9.1 and 7.6% for CP, MF and WF, respectively. All the relative prediction errors for simulated blind samples were between -22% and + 23%. FFSFS offers a novel alternative to the authentication of powdered herbal plants.
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Affiliation(s)
- Zhao-Xi Liu
- Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China
| | - Shu-Hua Tang
- Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China
| | - Ying Wang
- Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China
| | - Jin Tan
- Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China.
| | - Zi-Tao Jiang
- Tianjin International Joint Research & Development Center of Food Science and Engineering, Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, China; School of Food Engineering, Tianjin Tianshi College, Tianjin 301700, China.
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8
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Li X, Cai M, Li M, Wei X, Liu Z, Wang J, Jia K, Han Y. Combining Vis-NIR and NIR hyperspectral imaging techniques with a data fusion strategy for the rapid qualitative evaluation of multiple qualities in chicken. Food Control 2023. [DOI: 10.1016/j.foodcont.2022.109416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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9
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Assessment of the Effect of Cold Atmospheric Plasma (CAP) on the Hairtail ( Trichiurus lepturus) Quality under Cold Storage Conditions. Foods 2022; 11:foods11223683. [PMID: 36429278 PMCID: PMC9689270 DOI: 10.3390/foods11223683] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 11/10/2022] [Accepted: 11/13/2022] [Indexed: 11/19/2022] Open
Abstract
Cold Atmospheric Plasma (CAP) is a novel non-thermal preservation method that extends the shelf-life of food. Therefore, this study investigated the effect of CAP on the quality parameters of hairtail (Trichiurus lepturus) during cold storage conditions (at 4 °C and RH range 45−55%). For that reason, different quality parameters including the total bacteria count (TBC), total volatile basic nitrogen (TVB-N), pH, thiobarbituric acid reacting substances value (TBARS), color, texture, and sensory evaluation have been measured. The hairtail was exposed to CAP at 50 kV voltage for 2, 3, 4, and 5 min. The results showed that the samples treated with CAP at 50 kV for 5 min had significantly lower (p < 0.05) TBC (7.04 ± 0.26 log CFU/g) compared with the control sample (8.69 ± 0.06 log CFU/g). Similar results were found concerning TVB-N, which strongly decreased in the treated samples (16.63 ± 0.03 mg N/100 g) in comparison with the control sample (22.79 ± 0.03 mg N/100 g). In addition, the CAP-treated samples had lower (p < 0.05) changes in color than those of the control group. With reference to the sensory evaluation, the shelf-life of CAP-treated samples (at 50 kV for 5 min) was longer than the untreated samples by about 6 days. These results led us to the conclusion that CAP can effectively delay spoilage and deterioration, slow the rise in pH, and maintain the sensory attributes of hairtail during cold storage conditions.
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Shao W, Hou S, Jia W, Zheng Y. Rapid Non-Destructive Analysis of Food Nutrient Content Using Swin-Nutrition. Foods 2022; 11:3429. [PMID: 36360043 PMCID: PMC9656370 DOI: 10.3390/foods11213429] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/11/2022] [Accepted: 10/25/2022] [Indexed: 09/10/2023] Open
Abstract
Food non-destructive detection technology (NDDT) is a powerful impetus to the development of food safety and quality. One of the essential tasks of food quality regulation is the non-destructive detection of the food's nutrient content. However, existing food nutrient NDDT performs poorly in terms of efficiency and accuracy, which hinders their widespread application in daily meals. Therefore, this paper proposed an end-to-end food nutrition non-destructive detection method, named Swin-Nutrition, which combined deep learning and NDDT to evaluate the nutrient content of food. The method aimed to fully capture the feature information from the food images and thus accurately estimate the nutrient content. Swin-Nutrition resorted to Swin Transformer, the feature fusion module (FFM), and the nutrient prediction module to evaluate nutrient content. In particular, Swin Transformer acted as the backbone network for feature extraction of food images, and FFM was used to obtain the discriminative feature representation to improve the accuracy of prediction. The experimental results on the Nutrition5k dataset demonstrated the effectiveness and efficiency of our proposed method. Specifically, the mean value of the percentage mean absolute error (PMAE) for calories, mass, fat, carbohydrate, and protein were only 15.3%, 12.5%, 22.1%, 20.8%, and 15.4%, respectively. We hope that our simple and effective method will provide a solid foundation for the research of food NDDT.
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Affiliation(s)
| | - Sujuan Hou
- School of Information Science and Engineering, Shandong Normal University, Jinan 250358, China
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11
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Luo X, Sun Q, Yang T, He K, Tang X. Nondestructive determination of common indicators of beef for freshness assessment using airflow-three dimensional (3D) machine vision technique and machine learning. J FOOD ENG 2022. [DOI: 10.1016/j.jfoodeng.2022.111305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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12
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Identification of Four Chicken Breeds by Hyperspectral Imaging Combined with Chemometrics. Processes (Basel) 2022. [DOI: 10.3390/pr10081484] [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 current study aims to explore the potential of the combination of hyperspectral imaging and chemometrics in the rapid identification of four chicken breeds. The hyperspectral data of four chicken breeds were collected in the range of 400–900 nm. Five pretreatment methods were used to pretreat the original spectra. The important characteristic wavelength variables were extracted by random frog (RF), successive projection algorithm (SPA), and competitive adaptive reweighted sampling (CARS) algorithms. The classification models were established by using support vector machine (SVM), k-nearest neighbor (KNN), and partial least squares-discriminant analysis (PLS-DA). The results showed that the mean normalization pretreatment method was preferable, and overall classification accuracy of SVM-based models was higher than that of KNN-based and PLS-DA-based models. The correct classification rate (CCR) of the full-spectrum SVM model (Full-SVM) could reach 96.25%. The SPA method extracted 13 important wavelengths, and the SVM model based on SPA (SPA-SVM) achieved 90% CCR. This study can provide a theoretical reference for the discriminant analysis of chicken breeds.
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13
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Li J, Zhang N, Yang X, Yang X, Wang Z, Liu H. RhB@MOF-5 Composite Film as a Fluorescence Sensor for Detection of Chilled Pork Freshness. BIOSENSORS 2022; 12:bios12070544. [PMID: 35884347 PMCID: PMC9313163 DOI: 10.3390/bios12070544] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/13/2022] [Accepted: 07/18/2022] [Indexed: 01/14/2023]
Abstract
This study presents a novel composite thin film based on rhodamine B encapsulated into MOF-5 (Metal Organic Frameworks) as a fluorescence sensor for the real-time detection of the freshness of chilled pork. The composite film can adsorb and respond to the volatile amines produced by the quality deterioration of pork during storage at 4 °C, with the fluorescence intensity of RhB decreasing over time. The quantitative model used for predicting the freshness indicator (total volatile base nitrogen) of pork was built using the fluorescence spectra (excited at 340 nm) of the RhB@MOF-5 composite film combined with the partial least squares (PLS) algorithm, providing Rc2 and Rp2 values of 0.908 and 0.821 and RMSEC (root mean square error of calibration) and RMSEP (root mean square error of prediction) values of 3.435 mg/100 g and 3.647 mg/100 g, respectively. The qualitative model established by the partial least squares discriminant analysis (PLS-DA) algorithm was able to accurately classify pork samples as fresh, acceptable or spoiled, and the accuracy was 86.67%.
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Affiliation(s)
- Jingyi Li
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (J.L.); (X.Y.)
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China;
- National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing 100097, China
| | - Ning Zhang
- Beijing Key Laboratory of Flavor Chemistry, Beijing Technology and Business University (BTBU), Beijing 100048, China;
| | - Xin Yang
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (J.L.); (X.Y.)
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China;
- National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing 100097, China
| | - Xinting Yang
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China;
- National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing 100097, China
| | - Zengli Wang
- College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (J.L.); (X.Y.)
- Correspondence: (Z.W.); (H.L.); Tel.: +86-10-62737066 (Z.W.); +86-10-51503630 (H.L.)
| | - Huan Liu
- Research Center of Information Technology, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China;
- National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China
- National Engineering Laboratory for Agri-Product Quality Traceability, Beijing 100097, China
- Correspondence: (Z.W.); (H.L.); Tel.: +86-10-62737066 (Z.W.); +86-10-51503630 (H.L.)
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14
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Liu H, Zhu W, Luo N, Ji Z, Yang X. A novel method for real-time prediction of the shelf life of pork at different storage temperatures using front-face fluorescence excitation-emission matrices. Food Chem 2022; 398:133795. [DOI: 10.1016/j.foodchem.2022.133795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 07/07/2022] [Accepted: 07/24/2022] [Indexed: 11/28/2022]
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15
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Zhuang Q, Peng Y, Yang D, Wang Y, Zhao R, Chao K, Guo Q. Detection of frozen pork freshness by fluorescence hyperspectral image. J FOOD ENG 2022. [DOI: 10.1016/j.jfoodeng.2021.110840] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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16
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Xue SS, Tan J, Xie JY, Li MF. Rapid, simultaneous and non-destructive determination of maize flour and soybean flour adulterated in quinoa flour by front-face synchronous fluorescence spectroscopy. Food Control 2021. [DOI: 10.1016/j.foodcont.2021.108329] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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17
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Tao H, Hu Q, Wu Y, Han P, Liang X. Evaluation of antibacterial protein with antioxidant activity from
Rahnella
aquatilis
L103 and its effect on beef during refrigerated storage. Int J Food Sci Technol 2021. [DOI: 10.1111/ijfs.14996] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Huan‐yu Tao
- Faculty of Agriculture and Food Kunming University of Science and Technology Kunming Yunnan650500China
| | - Qin Hu
- Department of Diabetes The First Affiliated Hospital Kunming Medical University Kunming Yunnan650500China
| | - Yi Wu
- Faculty of Agriculture and Food Kunming University of Science and Technology Kunming Yunnan650500China
| | - Peng Han
- Faculty of Agriculture and Food Kunming University of Science and Technology Kunming Yunnan650500China
| | - Xiaobo Liang
- Faculty of Agriculture and Food Kunming University of Science and Technology Kunming Yunnan650500China
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18
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Tan J, Li MF, Li R, Jiang ZT, Tang SH, Wang Y. Front-face synchronous fluorescence spectroscopy for rapid and non-destructive determination of free capsanthin, the predominant carotenoid in chili (Capsicum annuum L.) powders based on aggregation-induced emission. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2021; 255:119696. [PMID: 33774412 DOI: 10.1016/j.saa.2021.119696] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2020] [Revised: 02/12/2021] [Accepted: 03/08/2021] [Indexed: 06/12/2023]
Abstract
Capsanthin is the major natural carotenoid pigment in red chili pepper possessing important bioactivity. Its conventional determination method is high performance liquid chromatography (HPLC) with complex and tedious sample pretreatment. In this study, synchronous front-face fluorescence spectroscopy (FFFS) was applied for the fast and non-invasive detection of free capsanthin in chili powders. Although capsanthin was only weak fluorescent in solution state, it showed strong fluorescence in two separated regions in front-face geometry which could also be clearly observed in chili powders. The mechanisms of these emissions are revealed to be aggregation-induced emission (AIE) and J-aggregate formation (JAF). The free capsanthin in 85 chili powder samples were determined by HPLC as in the range of 0.6-3.0 mg/g. The total synchronous FFFS spectra of these samples were scanned. Simple first-order models were built by partial least square regression (PLSR), and were validated by 5-fold cross-validation and external validation. The coefficients of determination (R2) were higher than 0.9, and the root mean square errors (RMSE) were less than 0.2 mg/g. The relative error of prediction (REP) was 9.9%, and the residual predictive deviation (RPD) was 3.7. The method was applied for the estimation of free capsanthin in several real-world samples with satisfactory analytical results. The average relative error to HPLC reference values was -11.8%.
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Affiliation(s)
- Jin Tan
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
| | - Ming-Fen Li
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
| | - Rong Li
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
| | - Zi-Tao Jiang
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
| | - Shu-Hua Tang
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
| | - Ying Wang
- Tianjin Key Laboratory of Food Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin 300134, People's Republic of China.
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19
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Khaled AY, Parrish CA, Adedeji A. Emerging nondestructive approaches for meat quality and safety evaluation-A review. Compr Rev Food Sci Food Saf 2021; 20:3438-3463. [PMID: 34151512 DOI: 10.1111/1541-4337.12781] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 03/29/2021] [Accepted: 05/11/2021] [Indexed: 11/28/2022]
Abstract
Meat is one of the most consumed agro-products because it contains proteins, minerals, and essential vitamins, all of which play critical roles in the human diet and health. Meat is a perishable food product because of its high moisture content, and as such there are concerns about its quality, stability, and safety. There are two widely used methods for monitoring meat quality attributes: subjective sensory evaluation and chemical/instrumentation tests. However, these methods are labor-intensive, time-consuming, and destructive. To overcome the shortfalls of these conventional approaches, several researchers have developed fast and nondestructive techniques. Recently, electronic nose (e-nose), computer vision (CV), spectroscopy, hyperspectral imaging (HSI), and multispectral imaging (MSI) technologies have been explored as nondestructive methods in meat quality and safety evaluation. However, most of the studies on the application of these novel technologies are still in the preliminary stages and are carried out in isolation, often without comprehensive information on the most suitable approach. This lack of cohesive information on the strength and shortcomings of each technique could impact their application and commercialization for the detection of important meat attributes such as pH, marbling, or microbial spoilage. Here, we provide a comprehensive review of recent nondestructive technologies (e-nose, CV, spectroscopy, HSI, and MSI), as well as their applications and limitations in the detection and evaluation of meat quality and safety issues, such as contamination, adulteration, and quality classification. A discussion is also included on the challenges and future outlooks of the respective technologies and their various applications.
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Affiliation(s)
- Alfadhl Y Khaled
- Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, Kentucky, USA
| | - Chadwick A Parrish
- Department of Electrical and Computer Engineering, University of Kentucky, Lexington, Kentucky, USA
| | - Akinbode Adedeji
- Department of Biosystems and Agricultural Engineering, University of Kentucky, Lexington, Kentucky, USA
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20
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Botosoa EP, Chèné C, Karoui R. Front Face Fluorescence Spectroscopy Combined with PLS‐DA Allows to Monitor Chemical Changes of Edible Vegetable Oils during Storage at 60 °C. EUR J LIPID SCI TECH 2021. [DOI: 10.1002/ejlt.202000088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Eliot Patrick Botosoa
- Univ. Artois, EA 7394, ICV‐Institut Charles VIOLLETTE Lens F‐62300 France
- INRA, USC 1281 Lille F‐59000 France
- Ulco F‐62200 Boulogne‐sur‐Mer France
- Univ. Lille Lille F‐59000 France
- YNCREA Lille F‐59000 France
| | | | - Romdhane Karoui
- Univ. Artois, EA 7394, ICV‐Institut Charles VIOLLETTE Lens F‐62300 France
- INRA, USC 1281 Lille F‐59000 France
- Ulco F‐62200 Boulogne‐sur‐Mer France
- Univ. Lille Lille F‐59000 France
- YNCREA Lille F‐59000 France
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21
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Bekhit AEDA, Giteru SG, Holman BWB, Hopkins DL. Total volatile basic nitrogen and trimethylamine in muscle foods: Potential formation pathways and effects on human health. Compr Rev Food Sci Food Saf 2021; 20:3620-3666. [PMID: 34056832 DOI: 10.1111/1541-4337.12764] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 03/30/2021] [Accepted: 04/02/2021] [Indexed: 12/18/2022]
Abstract
The use of total volatile basic nitrogen (TVB-N) as a quality parameter for fish is rapidly growing to include other types of meat. Investigations of meat quality have recently focused on TVB-N as an index of freshness, but little is known on the biochemical pathways involved in its generation. Furthermore, TVB-N and methylated amines have been reported to exert deterimental health effects, but the relationship between these compounds and human health has not been critically reviewed. Here, literature on the formative pathways of TVB-N has been reviewed in depth. The association of methylated amines and human health has been critically evaluated. Interventions to mitigate the effects of TVB-N on human health are discussed. TVB-N levels in meat can be influenced by the diet of an animal, which calls for careful consideration when using TVB-N thresholds for regulatory purposes. Bacterial contamination and temperature abuse contribute to significant levels of post-mortem TVB-N increases. Therefore, controlling spoilage factors through a good level of hygiene during processing and preservation techniques may contribute to a substantial reduction of TVB-N. Trimethylamine (TMA) constitutes a significant part of TVB-N. TMA and trimethylamine oxide (TMA-N-O) have been related to the pathogenesis of noncommunicable diseases, including atherosclerosis, cancers, and diabetes. Proposed methods for mitigation of TMA and TMA-N-O accumulation are discussed, which include a reduction in their daily dietary intake, control of internal production pathways by targeting gut microbiota, and inhibition of flavin monooxygenase 3 enzymes. The levels of TMA and TMA-N-O have significant health effects, and this should, therefore, be considered when evaluating meat quality and acceptability. Agreed international values for TVB-N and TMA in meat products are required. The role of feed, gut microbiota, and translocation of methylated amines to muscles in farmed animals requires further investigation.
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Affiliation(s)
| | - Stephen G Giteru
- Department of Food Science, University of Otago, Dunedin, New Zealand.,Food & Bio-based Products, AgResearch Limited, Tennent Drive, Palmerston North, 4410, New Zealand
| | - Benjamin W B Holman
- Centre for Red Meat and Sheep Development, NSW Department of Primary Industries, Cowra, New South Wales, Australia
| | - David L Hopkins
- Centre for Red Meat and Sheep Development, NSW Department of Primary Industries, Cowra, New South Wales, Australia
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22
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Bekhit AEDA, Holman BW, Giteru SG, Hopkins DL. Total volatile basic nitrogen (TVB-N) and its role in meat spoilage: A review. Trends Food Sci Technol 2021. [DOI: 10.1016/j.tifs.2021.01.006] [Citation(s) in RCA: 131] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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