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Zhang J, Wei Z, Lu T, Qi X, Xie L, Vincenzetti S, Polidori P, Li L, Liu G. The Research Field of Meat Preservation: A Scientometric and Visualization Analysis Based on the Web of Science. Foods 2023; 12:4239. [PMID: 38231689 DOI: 10.3390/foods12234239] [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: 10/22/2023] [Revised: 11/14/2023] [Accepted: 11/20/2023] [Indexed: 01/19/2024] Open
Abstract
Meat plays a significant role in human diets, providing a rich source of high-quality protein. With advancements in technology, research in the field of meat preservation has been undergoing dynamic evolution. To gain insights into the development of this discipline, the study conducted an analysis and knowledge structure mapping of 1672 papers related to meat preservation research within the Web of Science Core Collection (WOSCC) spanning from 2001 to 2023. And using software tools such as VOSviewer 1.6.18 and CiteSpace 5.8.R3c allowed for the convenient analysis of the literature by strictly following the software operation manuals. Moreover, the knowledge structure of research in the field of meat preservation was synthesized within the framework of "basic research-technological application-integration of technology with fundamental research," aligning with the research content. Co-cited literature analysis indicated that meat preservation research could be further categorized into seven collections, as well as highlighting the prominent role of the antibacterial and antioxidant properties of plant essential oils in ongoing research. Subsequently, the future research direction and focus of the meat preservation field were predicted and prospected. The findings of this study could offer valuable assistance to researchers in swiftly comprehending the discipline's development and identifying prominent research areas, thus providing valuable guidance for shaping research topics.
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Affiliation(s)
- Jingjing Zhang
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione 93, 62024 Matelica, MC, Italy
| | - Zixiang Wei
- Key Laboratory of Industrial Fermentation Microbiology, College of Biotechnology, Tianjin University of Science and Technology, Tianjin 300222, China
| | - Ting Lu
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
| | - Xingzhen Qi
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
| | - Lan Xie
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
| | - Silvia Vincenzetti
- School of Biosciences and Veterinary Medicine, University of Camerino, Via Circonvallazione 93, 62024 Matelica, MC, Italy
| | - Paolo Polidori
- School of Pharmacy, University of Camerino, Via Gentile da Varano, 62032 Camerino, MC, Italy
| | - Lanjie Li
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
- Office of International Programs, Liaocheng University, Liaocheng 252000, China
| | - Guiqin Liu
- Shandong Engineering Technology Research Center for Efficient Breeding and Ecological Feeding of Black Donkey, College of Agronomy and Agricultural Engineering, Liaocheng University, Liaocheng 252000, China
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Liu P, Zhang L, Li Y, Feng H, Zhang X, Zhang M. rGO-PDMS Flexible Sensors Enabled Survival Decision System for Live Oysters. SENSORS (BASEL, SWITZERLAND) 2023; 23:1308. [PMID: 36772351 PMCID: PMC9919715 DOI: 10.3390/s23031308] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
The shell-closing strength (SCS) of oysters is the main parameter for physiological activities. The aim of this study was to evaluate the applicability of SCS as an indicator of live oyster health. This study developed a flexible pressure sensor system with polydimethylsiloxane (PDMS) as the substrate and reduced graphene oxide (rGO) as the sensitive layer to monitor SCS in live oysters (rGO-PDMS). In the experiment, oysters of superior, medium and inferior grades were selected as research objects, and the change characteristics of SCS were monitored at 4 °C and 25 °C. At the same time, the time series model was used to predict the survival rate of live oyster on the basis of changes in their SCS characteristics. The survival times of superior, medium and inferior oysters at 4 °C and 25 °C were 31/25/18 days and 12/10/7 days, respectively, and the best prediction accuracies for survival rate were 89.32%/82.17%/79.19%. The results indicate that SCS is a key physiological indicator of oyster survival. The dynamic monitoring of oyster vitality by means of flexible pressure sensors is an important means of improving oyster survival rate. Superior oysters have a higher survival rate in low-temperature environments, and our method can provide effective and reliable survival prediction and management for the oyster industry.
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Affiliation(s)
| | | | | | | | - Xiaoshuan Zhang
- Correspondence: (X.Z.); (M.Z.); Tel.: +86-133-6639-6640 (X.Z.); +86-158-0106-2668 (M.Z.)
| | - Mengjie Zhang
- Correspondence: (X.Z.); (M.Z.); Tel.: +86-133-6639-6640 (X.Z.); +86-158-0106-2668 (M.Z.)
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Guan B, Wang F, Jiang H, Zhou M, Lin H. Preparation of Mesoporous Silica Nanosphere-Doped Color-Sensitive Materials and Application in Monitoring the TVB-N of Oysters. Foods 2022; 11:foods11060817. [PMID: 35327241 PMCID: PMC8947737 DOI: 10.3390/foods11060817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 03/10/2022] [Accepted: 03/11/2022] [Indexed: 02/01/2023] Open
Abstract
In this work, a new colorimetric sensor based on mesoporous silica nanosphere-modified color-sensitive materials was established for application in monitoring the total volatile basic nitrogen (TVB-N) of oysters. Firstly, mesoporous silica nanospheres (MSNs) were synthesized based on the improved Stober method, then the color-sensitive materials were doped with MSNs. The “before image” and the “after image” of the colorimetric senor array, which was composed of nanocolorimetric-sensitive materials by a charge-coupled device (CCD) camera were then collected. The different values of the before and after image were analyzed by principal component analysis (PCA). Moreover, the error back-propagation artificial neural network (BP-ANN) was used to quantitatively predict the TVB-N values of the oysters. The correlation coefficient of the colorimetric sensor array after being doped with MSNs was greatly improved; the Rc and Rp of BP-ANN were 0.9971 and 0.9628, respectively when the principal components (PCs) were 10. Finally, a paired sample t-test was used to verify the accuracy and applicability of the BP-ANN model. The result shows that the colorimetric-sensitive materials doped with MSNs could improve the sensitivity of the colorimetric sensor array, and this research provides a fast and accurate method to detect the TVB-N values in oysters.
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Affiliation(s)
- Binbin Guan
- Nantong Food and Drug Supervision and Inspection Center, Nantong 226400, China; (B.G.); (M.Z.)
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; (F.W.); (H.J.)
| | - Fuyun Wang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; (F.W.); (H.J.)
| | - Hao Jiang
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; (F.W.); (H.J.)
| | - Mi Zhou
- Nantong Food and Drug Supervision and Inspection Center, Nantong 226400, China; (B.G.); (M.Z.)
| | - Hao Lin
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, China; (F.W.); (H.J.)
- Correspondence:
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