DocumentCode :
381798
Title :
Sensory and electronic nose analysis of porcine meat loaf in relation to ingredient quality
Author :
Hansen, Thomas ; Boholt, Karsten ; Gammelgaard, Eigil ; Byrne, Derek V.
Author_Institution :
Dept. of Dairy & Food Sci., R. Veterinary & Agric. Univ., Frederiksberg, Denmark
Volume :
1
fYear :
2002
fDate :
2002
Firstpage :
736
Abstract :
A sensory profile was carried out to evaluate the eating quality of a pork based, cooked, canned and formed meat product (meat loaf). A part of The Danish Odour Sensor System (DOSS) was used to measure headspace volatiles in the meat loaf and in all meat ingredients. A data analytical strategy involving analysis of variance-partial least squares regression (APLSR), to determine causal relationships between the samples and the sensory/electronic nose/GC-MS data, was utilized. The sensory profiling gave rise to two parameters that could be ascribed to, e.g. loss of meaty attributes, increasing levels of off-flavors and odors, and increasing texture related defects (first parameter), and color changes (second parameter). The metal oxide sensors (MOS) in the DOSS could not differentiate the meat loaf samples that were deemed unacceptable in sensory profiling from the other samples. However, when measuring the raw materials the MOS sensors correlated well to the sensory. The results indicate that measuring volatiles with the DOSS system on raw materials for processed meat products may be a feasible strategy in sensory related quality control and may even have potential in predicting the sensory quality of the final product.
Keywords :
electric sensing devices; food processing industry; gas sensors; least squares approximations; quality control; Danish Odour Sensor System; causal relationships; color changes; data analytical strategy; eating quality; electronic nose analysis; headspace volatiles; ingredient quality; metal oxide sensors; off-flavors; porcine meat loaf; processed meat products; quality control; raw materials; sensory profiling; texture related defects; variance-partial least squares regression; Analysis of variance; Control systems; Data analysis; Electronic noses; Least squares methods; Production; Raw materials; Sensor arrays; Sensor phenomena and characterization; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sensors, 2002. Proceedings of IEEE
Print_ISBN :
0-7803-7454-1
Type :
conf
DOI :
10.1109/ICSENS.2002.1037195
Filename :
1037195
Link To Document :
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