Search

This document provides a list of scientific articles related to various topics in 3D food printing, sustainable food production, and the use of biomaterials in 3D printing. The articles cover a wide range of subjects, including the development of emulsions for 3D printing, the use of plant-based proteins in meat analogs, and the exploration of functional plant-based seafood. These articles offer valuable insights into the latest research and advancements in these areas, making them a useful resource for library patrons conducting research on these topics. [Extracted from the article]

With the developing technology, methods for determining the quality of food products by fast, easy, cheap, and reliable methods are preferred. Fast techniques have many advantages over traditional methods in terms of usability in determining the quality and safety of food products. Furthermore, they also have significant advantages because they can be used in a variety of issues such as predicting the quality, shelf life, and risk evaluations of food products in mathematical models, which have become increasingly popular in recent years. Developing fast methods and the advantages of using constantly developing mathematical methods together with these methods in all sectors, especially food and marine food products, will increase their preferences in the future as well as today. The fuzzy logic approach is one of these recommended mathematical methodologies. Therefore, on the importance of subject the usage of fuzzy logic model, their applications on food and marine food products and the latest studies on this subject were included in this review. In the future, it is expected that upgraded versions of the fuzzy logic method will eventually replace the fuzzy logic versions currently in use. [ABSTRACT FROM AUTHOR]

The statistical methods have many benefits in acquiring results in a variety of areas such as the optimization the conditions of processing, estimating the shelf life of food products, predicting the bacteria growth on foods, and also predicting the risk formation of chemicals and pathogenic bacteria on food products. The Artificial Neural Network (ANN) model is just one of many mathematical models used today, and its applications in many areas of food and aquatic products will be enhanced in the future. In addition, in the near future, the most appropriate ANN model will be determined by combining the data produced with advanced processing technologies or obtained from food products and different models for each type of food product, and relible predictions can be made for the future. In the lights of the importance of the subject in this review; the meaning, importance, types, formulations of the ANN models were explained. Additionally, the usages of the ANN models not only in aquaculture and fisheries studies, but also the usages of the ANN models for evaluation of safety assessments of the processing technologies of fishery products were highlighted. Moreover, the usages of the ANN models for determining the freshness and shelf life of fishery products were reviewed. It is expected that future development of various mathematical models, as well as studies to adapt the use of these models together, will benefit the aquaculture, fisheries, food and seafood processing industries. [ABSTRACT FROM AUTHOR]

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The frozen-thawed squid rings were marinated by using different formulations of the mineral water and lemon juice at different times at 4°C. Analyses of microbe counts (total mesophilic bacteria (TMB), total psychrotrophic bacteria, lactic acid bacteria, yeast-mould, Enterobactericeae, coliform, fecal coliform, E.coli, S.aureus, Vibrio spp.), pH and sensory factors were conducted during the marination process. Increasing the fraction of lemon juice in the marinade solution resulted in a decrease in the number of TMB and a lower squid ring pH. Increasing the fraction of lemon juice in the marinade solution increased the growth of lactic acid bacteria. Faecal coliform, E.coli, S.aureus and Vibrio spp. were not observed in any of the marinated or non-marinated samples. Response Surface Methodology (RSM) was used to optimise the marination conditions, including the content of the marination liquid (lemon juice+mineral water), the marination time (1,3,6,12,24,48,72 h) and the pH. The recommended optimal conditions for marinating frozen-thawed squid rings at 4°C are as follows: 41.2 ml lemon juice+61.7 ml mineral water/100 g squid rings, pH 4.4, 1 h marination time. Additionally, Good agreement was found between the experimental values and those estimated from the RSM model for the pH (r² =0.89), total mesophilic bacteria count (R² =0.93) and lactic acid bacteria count (r² =0.84). Given the desirable sensory qualities of the resulting squid rings, these optimal marination conditions can be evaluated in the seafood-processing industry. [ABSTRACT FROM AUTHOR]

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, grey and regression models were developed to estimate the aerobic plate bacteria development on frozen squid rings during the thawing process. The regression model was found to be suitable for predicting the microbiological growth on frozen squid rings during the thawing process for different temperatures and times (R2 adj = 0.918). This model allowed predictions to be made based on time, temperature and treatment factors. The other model developed for the data in this study was grey modeling, which is also used to predict the total aerobic bacteria growth on frozen squid rings during the thawing process. The GM (1,1) model allowed modeling that could only be based on time. Therefore, a comparison of the groups was not possible with the GM (1,1) model, compared to the regression modeling technique. However, the grey model appeared to be a good alternative when there was little data and time-dependent measurements were made. The proposed modeling techniques are be useful for predicting the total aerobic bacteria growth on frozen squid rings during the thawing process because they are economical and timesaving. [ABSTRACT FROM AUTHOR]

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Ürünleri Dergisi is the property of Ege Journal of Fisheries & Aquatic Sciences (EgeJFAS) / Su Urunleri Dergisi and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)