Quantification and mapping of tissue damage from freezing in cod by magnetic resonance imaging. (May 2021)
- Record Type:
- Journal Article
- Title:
- Quantification and mapping of tissue damage from freezing in cod by magnetic resonance imaging. (May 2021)
- Main Title:
- Quantification and mapping of tissue damage from freezing in cod by magnetic resonance imaging
- Authors:
- Anderssen, Kathryn E.
Syed, Shaheen
Stormo, Svein Kristian - Abstract:
- Abstract: Freezing of fish is an important processing method that can extend the shelf life of the product but can also lead to significant damage to the tissue if performed incorrectly. In order to thoroughly evaluate different freezing protocols, a method to characterize the extent and distribution of damage from freezing is needed. Magnetic resonance imaging (MRI) was tested as a technique to map and quantify tissue damage from freezing in fish. Groups of packaged cod ( Gadus morhua) loin were frozen to either −5, −20, or −40 °C, thawed and then imaged with a T2 -weighted MRI sequence. Areas of damage appear as bright clusters in the muscle tissue. To provide repeatable, objective classification, image analysis using a convolutional neural network was then performed on the MRI data to identify regions of damaged tissue. As expected, the colder the freezing procedure, the less damage the process generally produced. Results show non-uniform damage throughout the fillet, with tissue damage due to freezing concentrated in the center of the fillet. This suggests that surface limited methods, such as hyperspectral imaging, may not fully capture the extent of damage due to freezing and thawing. The percent of tissue classified as damaged by the neural network generally correlated well with liquid loss ( cor = 0.83). Highlights: T2 -Weighted MRI images allowed identification of tissue damage in cod. Image analysis allowed classification of tissue into damaged and non-damaged.Abstract: Freezing of fish is an important processing method that can extend the shelf life of the product but can also lead to significant damage to the tissue if performed incorrectly. In order to thoroughly evaluate different freezing protocols, a method to characterize the extent and distribution of damage from freezing is needed. Magnetic resonance imaging (MRI) was tested as a technique to map and quantify tissue damage from freezing in fish. Groups of packaged cod ( Gadus morhua) loin were frozen to either −5, −20, or −40 °C, thawed and then imaged with a T2 -weighted MRI sequence. Areas of damage appear as bright clusters in the muscle tissue. To provide repeatable, objective classification, image analysis using a convolutional neural network was then performed on the MRI data to identify regions of damaged tissue. As expected, the colder the freezing procedure, the less damage the process generally produced. Results show non-uniform damage throughout the fillet, with tissue damage due to freezing concentrated in the center of the fillet. This suggests that surface limited methods, such as hyperspectral imaging, may not fully capture the extent of damage due to freezing and thawing. The percent of tissue classified as damaged by the neural network generally correlated well with liquid loss ( cor = 0.83). Highlights: T2 -Weighted MRI images allowed identification of tissue damage in cod. Image analysis allowed classification of tissue into damaged and non-damaged. Fish frozen rapidly showed significantly less damage than those frozen slowly. Percentage of tissue classified as damaged showed cor = 0.83 with liquid loss. … (more)
- Is Part Of:
- Food control. Volume 123(2021)
- Journal:
- Food control
- Issue:
- Volume 123(2021)
- Issue Display:
- Volume 123, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 123
- Issue:
- 2021
- Issue Sort Value:
- 2021-0123-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-05
- Subjects:
- Magnetic resonance imaging -- Fish -- Cod -- Freezing -- Image analysis -- Deep learning
Food -- Quality -- Periodicals
Food -- Analysis -- Periodicals
Food handling -- Periodicals
Food industry and trade -- Quality control -- Periodicals
Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques
Aliments -- Qualité -- Périodiques
Aliments -- Analyse -- Périodiques
Hygiène alimentaire -- Périodiques
Food -- Analysis
Food handling
Food -- Quality
Periodicals
Electronic journals
664.07 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09567135 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.foodcont.2020.107734 ↗
- Languages:
- English
- ISSNs:
- 0956-7135
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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- British Library DSC - 3977.291500
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