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- Caballero, Daniel; Antequera, Teresa; Caro, Andres; Duran, Ma Luisa; Perez-Palacios, Trinidad
- Food and bioprocess technology 2016 v.9 no.4 pp. 699-708
- correlation; equations; ham; magnetic resonance imaging; prediction; sensory evaluation; sensory properties; texture
- ... In this study, data mining technique was applied on computational texture features obtained from the analysis of magnetic resonance imaging (MRI) of hams, with the main objective of determining sensory attributes of dry-cured ham non-destructively. For that, fresh and dry-cured hams were scanned and then the MRI images were analyzed by three methods of computational texture features. Data mining w ...
- Cheng, Hongyuan; Hansen, Jonas Høeg
- Food and bioprocess technology 2016 v.9 no.4 pp. 604-611
- bulk density; cooking; equations; extrusion; fish meal; ingredients; melting; mixing; models; prediction; rheological properties; soy protein; soybean meal; wheat
- ... A new extrudate bulk density model framework was developed, which is taking into account the melt rheological effects based on mixing principle and non-Newtonian power law theory for a twin-screw extrusion cooking process. The main ingredients in the extrusion process investigation were wheat, fish meal and soybean protein. The average absolute deviation (AAD) of the model prediction for extrudate ...