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High moisture food extrusion
Open accessAbstract
Extrusion at higher moisture contents (> 40%), also known as wet extrusion, is relatively less investigated compared to low and intermediate moisture extrusion. Literature on high moisture food extrusion has been reviewed. Wet extrusion applications utilise twin screw extruders due to their efficient conveying capabilities. Extruders can be used as bioreactors for starch hydrolysis using thermally stable enzymes. This process is usually followed by saccharification inside or outside an extruder to produce a high DE (dextrose equivalent) syrup. Starch-based high moisture extrusion research also reports a few modelling studies. The rheological properties, torque and energy requirements of high moisture extrusion systems are different from those of low and intermediate systems. Other research reviewed includes the extrusion of low-cost plant and animal proteins to manufacture nutritious food products that imitate the texture, flavour, and mouthfeel of meat.
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Cited by
Dalbhagat, C. G., Mahato, D. K., & Mishra, H. N. (2019) · Trends in Food Science & Technology · doi:10.1016/j.tifs.2019.01.001 · Cited by 283
Textured Vegetable Proteins (TVP): Future Foods Standing on Their Merits as Meat Alternatives
Baune, M.-C., Terjung, N., Tülbek, M. Ç., & Boukid, F. (2022) · Future Foods · doi:10.1016/j.fufo.2022.100181 · Cited by 124
Metadata
- Authors
- Akdogan, H.
- Venue
- International Journal of Food Science and Technology
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-06-01
- Volume
- 34
- Issue
- 3
- Pages
- 195-207
- ISSN
- 0950-5423 (ISSN-L)
- 1365-2621
- OpenAlex
- W1981242519
- Cited by
- 269
- References
- 0
- FWCI
- 0.87
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Akdogan, H. (1999). High moisture food extrusion. International Journal of Food Science and Technology. https://doi.org/10.1046/j.1365-2621.1999.00256.x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.