An experimental protocol to determine quality parameters of dry-cured loins using low-field Magnetic Resonance Imaging

被引：4

作者：

Caballero, Daniel ^{[1
,2
]}

Rodriguez, Pablo G. ^{[2
]}

Caro, Andres ^{[2
]}

del Mar Avila, Maria ^{[2
]}

Torres, Juan P. ^{[2
]}

Antequera, Teresa ^{[3
]}

Perez-Palacios, Trinidad ^{[3
]}

机构：

[1] Univ Copenhagen, Chemometr & Analyt Technol, Food Technol Dept, Fac Sci, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark

[2] Univ Extremadura, Res Inst Meat & Meat Prod, Media Engn Grp, Avda Ciencias S-N, ES-10003 Caceres, Spain

[3] Univ Extremadura, Res Inst Meat & Meat Prod, Food Technol Dept, Avda Ciencias S-N, ES-10003 Caceres, Spain

来源：

JOURNAL OF FOOD ENGINEERING | 2022年 / 313卷

关键词：

Experimental protocol; Magnetic resonance imaging; Optimum procedures; Dry-cured loins; Quality parameters; SENSORY ATTRIBUTES; TEXTURE ANALYSIS; MRI; PREDICT; TRAITS; ALGORITHMS; FRACTALS; MEAT;

D O I：

10.1016/j.jfoodeng.2021.110750

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

The objective of this study was to achieve an experimental protocol (EP) to determine quality characteristics of dry-cured loins non-destructively by using low-field (LF) Magnetic Resonance Imaging (MRI). The MRI procedure is composed of three main stages: MRI acquisition, MRI analysis (computer vision techniques) and data analysis (data mining methods). Two procedures have been implemented within a EP and validated with real samples from the meat industry (dry-cured loins, n = 100) by means of different quality measures. The validation results may indicate the use of both implemented procedures and the development of an EP to determine quality characteristics of loins by LF MRI-computer vision-data mining in a non-destructive way, with high accuracy and reducing the dispersion of the values. This brings the possibility of implementing this methodology in meat processing plants.

引用

页数：8