Food safety considerations in the production of traditional fermented products : Japanese rice koji and miso
- Allwood, Joanne, Wakeling, Lara, Post, Laurie, Bean, David
- Authors: Allwood, Joanne , Wakeling, Lara , Post, Laurie , Bean, David
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Journal of Food Safety Vol. 43, no. 4 (2023), p.
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- Description: While established in Asia, rice koji and miso are fermented foods that are becoming more popular in western countries. They have been shown to contain a variety of microorganisms, consisting of bacteria, yeasts, and fungal species. Many contemporary miso varieties are not pasteurized as consumers are looking for more natural products, and/or have the desire to consume fermented foods containing live microorganisms. While correctly prepared fermented foods are rarely associated with food safety outbreaks, incidences have been recorded. On these occasions, pathogenic, or spoilage microorganisms were introduced into the products from external sources such as the raw material or the processing environment. Consequently, hygiene and fermentation conditions need to be carefully monitored to ensure food safety. Furthermore, many of the production steps during koji and miso manufacture do not fit into contemporary food safety guidelines for foods. Although pH is a required food safety hurdle for fermented foods, this does not apply to nonacidic foods such as koji or miso. This review focuses on control of microbial pathogens and discusses the processes of miso fermentation, and how fermentation of rice koji and miso fits with current food safety hurdles in western countries. © 2023 The Authors. Journal of Food Safety published by Wiley Periodicals LLC.
- Authors: Allwood, Joanne , Wakeling, Lara , Post, Laurie , Bean, David
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Journal of Food Safety Vol. 43, no. 4 (2023), p.
- Full Text:
- Reviewed:
- Description: While established in Asia, rice koji and miso are fermented foods that are becoming more popular in western countries. They have been shown to contain a variety of microorganisms, consisting of bacteria, yeasts, and fungal species. Many contemporary miso varieties are not pasteurized as consumers are looking for more natural products, and/or have the desire to consume fermented foods containing live microorganisms. While correctly prepared fermented foods are rarely associated with food safety outbreaks, incidences have been recorded. On these occasions, pathogenic, or spoilage microorganisms were introduced into the products from external sources such as the raw material or the processing environment. Consequently, hygiene and fermentation conditions need to be carefully monitored to ensure food safety. Furthermore, many of the production steps during koji and miso manufacture do not fit into contemporary food safety guidelines for foods. Although pH is a required food safety hurdle for fermented foods, this does not apply to nonacidic foods such as koji or miso. This review focuses on control of microbial pathogens and discusses the processes of miso fermentation, and how fermentation of rice koji and miso fits with current food safety hurdles in western countries. © 2023 The Authors. Journal of Food Safety published by Wiley Periodicals LLC.
MCSNet+ : enhanced convolutional neural network for detection and classification of tribolium and sitophilus sibling species in actual wheat storage environments
- Yang, Haiying, Li, Yanyu, Xin, Liyong, Teng, Shyh, Pang, Shaoning, Zhao, Huiyi, Cao, Yang, Zhou, Xiaoguang
- Authors: Yang, Haiying , Li, Yanyu , Xin, Liyong , Teng, Shyh , Pang, Shaoning , Zhao, Huiyi , Cao, Yang , Zhou, Xiaoguang
- Date: 2023
- Type: Text , Journal article
- Relation: Foods Vol. 12, no. 19 (2023), p.
- Full Text:
- Reviewed:
- Description: Insect pests like Tribolium and Sitophilus siblings are major threats to grain storage and processing, causing quality and quantity losses that endanger food security. These closely related species, having very similar morphological and biological characteristics, often exhibit variations in biology and pesticide resistance, complicating control efforts. Accurate pest species identification is essential for effective control, but workplace safety in the grain bin associated with grain deterioration, clumping, fumigator hazards, and air quality create challenges. Therefore, there is a pressing need for an online automated detection system. In this work, we enriched the stored-grain pest sibling image dataset, which includes 25,032 annotated Tribolium samples of two species and five geographical strains from real warehouse and another 1774 from the lab. As previously demonstrated on the Sitophilus family, Convolutional Neural Networks demonstrate distinct advantages over other model architectures in detecting Tribolium. Our CNN model, MCSNet+, integrates Soft-NMS for better recall in dense object detection, a Position-Sensitive Prediction Model to handle translation issues, and anchor parameter fine-tuning for improved matching and speed. This approach significantly enhances mean Average Precision (mAP) for Sitophilus and Tribolium, reaching a minimum of 92.67 ± 1.74% and 94.27 ± 1.02%, respectively. Moreover, MCSNet+ exhibits significant improvements in prediction speed, advancing from 0.055 s/img to 0.133 s/img, and elevates the recognition rates of moving insect sibling species in real wheat storage and visible light, rising from 2.32% to 2.53%. The detection performance of the model on laboratory-captured images surpasses that of real storage facilities, with better results for Tribolium compared to Sitophilus. Although inter-strain variances are less pronounced, the model achieves acceptable detection results across different Tribolium geographical strains, with a minimum recognition rate of 82.64 ± 1.27%. In real-time monitoring videos of grain storage facilities with wheat backgrounds, the enhanced deep learning model based on Convolutional Neural Networks successfully detects and identifies closely related stored-grain pest images. This achievement provides a viable solution for establishing an online pest management system in real storage facilities. © 2023 by the authors.
- Authors: Yang, Haiying , Li, Yanyu , Xin, Liyong , Teng, Shyh , Pang, Shaoning , Zhao, Huiyi , Cao, Yang , Zhou, Xiaoguang
- Date: 2023
- Type: Text , Journal article
- Relation: Foods Vol. 12, no. 19 (2023), p.
- Full Text:
- Reviewed:
- Description: Insect pests like Tribolium and Sitophilus siblings are major threats to grain storage and processing, causing quality and quantity losses that endanger food security. These closely related species, having very similar morphological and biological characteristics, often exhibit variations in biology and pesticide resistance, complicating control efforts. Accurate pest species identification is essential for effective control, but workplace safety in the grain bin associated with grain deterioration, clumping, fumigator hazards, and air quality create challenges. Therefore, there is a pressing need for an online automated detection system. In this work, we enriched the stored-grain pest sibling image dataset, which includes 25,032 annotated Tribolium samples of two species and five geographical strains from real warehouse and another 1774 from the lab. As previously demonstrated on the Sitophilus family, Convolutional Neural Networks demonstrate distinct advantages over other model architectures in detecting Tribolium. Our CNN model, MCSNet+, integrates Soft-NMS for better recall in dense object detection, a Position-Sensitive Prediction Model to handle translation issues, and anchor parameter fine-tuning for improved matching and speed. This approach significantly enhances mean Average Precision (mAP) for Sitophilus and Tribolium, reaching a minimum of 92.67 ± 1.74% and 94.27 ± 1.02%, respectively. Moreover, MCSNet+ exhibits significant improvements in prediction speed, advancing from 0.055 s/img to 0.133 s/img, and elevates the recognition rates of moving insect sibling species in real wheat storage and visible light, rising from 2.32% to 2.53%. The detection performance of the model on laboratory-captured images surpasses that of real storage facilities, with better results for Tribolium compared to Sitophilus. Although inter-strain variances are less pronounced, the model achieves acceptable detection results across different Tribolium geographical strains, with a minimum recognition rate of 82.64 ± 1.27%. In real-time monitoring videos of grain storage facilities with wheat backgrounds, the enhanced deep learning model based on Convolutional Neural Networks successfully detects and identifies closely related stored-grain pest images. This achievement provides a viable solution for establishing an online pest management system in real storage facilities. © 2023 by the authors.
Application of micro-and nano-bubbles as a tool to improve the rheological and microstructural properties of formulated greek-style yogurts
- Babu, Karthik, Liu, Dylan, Amamcharla, Jayendra
- Authors: Babu, Karthik , Liu, Dylan , Amamcharla, Jayendra
- Date: 2022
- Type: Text , Journal article
- Relation: Foods Vol. 11, no. 4 (2022), p.
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- Description: The objective of this study was to develop an alternative novel process technology for enhancing the rheological and functional properties of Greek-style yogurt (GSY). The GSY was formulated and prepared in the lab using micellar casein concentrate as a source of protein to achieve a protein content of 10% (w/w). The changes in physicochemical, microstructural, rheological, and functional properties of control (C-GSY) and micro-and nano-bubbles-treated GSY (MNB-GSY) were studied and compared before and after storage for 1, 2, 3, and 4 weeks. Before storage, the apparent viscosity at 100 s−1 (η100 ) was 1.09 Pa·s for C-GSY and 0.71 Pa·s for MNB-GSY. Incorporation of MNBs into GSY significantly (p < 0.05) decreased the η100 by 30% on 1 week of storage. Additionally, the η100 of MNB-GSY was lesser than C-GSY on week 2, 3, and 4 of storage. Notable microstructural changes and significant rheological differences were observed between the C-GSY and MNB-GSY samples. Differences were also noticed in syneresis, which was lower for the MNB-GSY compared with the control. Overall, the incorporation of MNBs into GSY showed considerable improvements in rheological and functional properties. Additionally, it’s a simple, cost-effective process to implement in existing GSY production plants. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Babu, Karthik , Liu, Dylan , Amamcharla, Jayendra
- Date: 2022
- Type: Text , Journal article
- Relation: Foods Vol. 11, no. 4 (2022), p.
- Full Text:
- Reviewed:
- Description: The objective of this study was to develop an alternative novel process technology for enhancing the rheological and functional properties of Greek-style yogurt (GSY). The GSY was formulated and prepared in the lab using micellar casein concentrate as a source of protein to achieve a protein content of 10% (w/w). The changes in physicochemical, microstructural, rheological, and functional properties of control (C-GSY) and micro-and nano-bubbles-treated GSY (MNB-GSY) were studied and compared before and after storage for 1, 2, 3, and 4 weeks. Before storage, the apparent viscosity at 100 s−1 (η100 ) was 1.09 Pa·s for C-GSY and 0.71 Pa·s for MNB-GSY. Incorporation of MNBs into GSY significantly (p < 0.05) decreased the η100 by 30% on 1 week of storage. Additionally, the η100 of MNB-GSY was lesser than C-GSY on week 2, 3, and 4 of storage. Notable microstructural changes and significant rheological differences were observed between the C-GSY and MNB-GSY samples. Differences were also noticed in syneresis, which was lower for the MNB-GSY compared with the control. Overall, the incorporation of MNBs into GSY showed considerable improvements in rheological and functional properties. Additionally, it’s a simple, cost-effective process to implement in existing GSY production plants. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
The iconisation of yeast spreads—love them or hate them
- Vriesekoop, Frank, Russell, Carolyn, Tziboula-Clarke, Athina, Jan, Celine, Bois, Marine, Farley, Stephanie, McNamara, Allison
- Authors: Vriesekoop, Frank , Russell, Carolyn , Tziboula-Clarke, Athina , Jan, Celine , Bois, Marine , Farley, Stephanie , McNamara, Allison
- Date: 2022
- Type: Text , Journal article
- Relation: Beverages Vol. 8, no. 1 (2022), p.
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- Description: The production of beer yields a number of by-product streams, with spent brewers’ yeast being the second most abundant in volume. The high nutritional value of spent yeast has seen a large proportion of spent brewers’ yeast being used for both food and feed purposes. One of the uses of spent brewers’ yeast for human consumption has been the production of yeast spreads, which came onto the market in the early 20th century, first in the United Kingdom and shortly thereafter in the commonwealth dominions, especially Australia and New Zealand. In this research we investigated the national status of yeast spreads in the UK, Australia and New Zealand. We show that a brewery by-product such as spent brewers’ yeast is more than a mere novel utilisation of a waste stream but have become inherently associated with national identities of these countries to such an extent that some brands have become iconicised. Furthermore, some yeast spread brands have become a symbol of (inter)national polarisation, purely based on its initial sensorial characterisation. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Vriesekoop, Frank , Russell, Carolyn , Tziboula-Clarke, Athina , Jan, Celine , Bois, Marine , Farley, Stephanie , McNamara, Allison
- Date: 2022
- Type: Text , Journal article
- Relation: Beverages Vol. 8, no. 1 (2022), p.
- Full Text:
- Reviewed:
- Description: The production of beer yields a number of by-product streams, with spent brewers’ yeast being the second most abundant in volume. The high nutritional value of spent yeast has seen a large proportion of spent brewers’ yeast being used for both food and feed purposes. One of the uses of spent brewers’ yeast for human consumption has been the production of yeast spreads, which came onto the market in the early 20th century, first in the United Kingdom and shortly thereafter in the commonwealth dominions, especially Australia and New Zealand. In this research we investigated the national status of yeast spreads in the UK, Australia and New Zealand. We show that a brewery by-product such as spent brewers’ yeast is more than a mere novel utilisation of a waste stream but have become inherently associated with national identities of these countries to such an extent that some brands have become iconicised. Furthermore, some yeast spread brands have become a symbol of (inter)national polarisation, purely based on its initial sensorial characterisation. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
- Lin, Hao, Jiang, Hao, Lin, Jinjin, Chen, Quansheng, Ali, Shujat, Teng, Shyh, Zuo, Min
- Authors: Lin, Hao , Jiang, Hao , Lin, Jinjin , Chen, Quansheng , Ali, Shujat , Teng, Shyh , Zuo, Min
- Date: 2021
- Type: Text , Journal article
- Relation: Food Analytical Methods Vol. 14, no. 7 (2021), p. 1305-1314
- Full Text: false
- Reviewed:
- Description: In this work, two methods, which were visible near-infrared spectroscopy (VNIRS) and visible near-infrared spectroscopy combined with colorimetric sensor array (VNIRS-CSA), were used to identify the volatile compound changes of rice samples stored for 0 to 6 months. Principal component analysis (PCA), interval partial least squares (iPLS), and synergy interval partial least squares (SiPLS) were used for qualitative classification. A prediction model was established by linear discriminant analysis (LDA), which was compared with the traditional VNIRS detection technology. The results revealed that the VNIRS-CSA got better performance than VNIRS and exhibited a good result based on iPLS/SiPLS-PCA/LDA models. Furthermore, spectral data from VNIRS-CSA were the best for LDA with a high prediction value of 0.925 after standard normal variate (SNV) processing and variable selection by SiPLS. The research demonstrated that VNIRS-CSA is a quick, accurate, and non-destructive method for monitoring the storage time of rice. The strategy also has the potential for volatile organic components analysis. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.
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