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High pH thresholding of beef with VNIR hyperspectral imaging

Crichton, Stuart O.J.; Kirchner, Sascha M.; Porley, Victoria E.; Retz, Stefanie K.; von Gersdorff, Gardis J.E.; Hensel, Oliver and Sturm, Barbara (2017) High pH thresholding of beef with VNIR hyperspectral imaging. Meat Science, 134, pp. 14-17.

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Summary in the original language of the document

Initial quality grading of meat is generally carried out using invasive and occasionally destructive sampling for the purposes of pH testing. Precise pH and thresholds exist to allow the classification of different statuses of meat, e.g. for detection of dry, firm, and dark (DFD) (when dealing with cattle and sheep), or pale, soft exudative meat (when dealing with pork). This paper illustrates that threshold detection for pH level in beef with different freshness levels (fresh, fresh frozen-thawed, matured, and matured frozen-thawed). Use of support vector machine (SVM) analysis allowed for the classification of beef samples with a pH above 5.9, and below 5.6, with an accuracy of 91% and 99% respectively. Biochemical and physical conditions of the meat concerning the pH are discussed.


EPrint Type:Journal paper
Keywords:Beef, Classification, Hyperspectral imaging, Non-invasive measurement, pH, BÖLN, BOELN, BÖL, BOEL, FKZ 14OE006, Core Organic Plus, SusOrganic
Subjects: Food systems > Food security, food quality and human health
Food systems > Processing, packaging and transportation
Research affiliation: European Union > CORE Organic > CORE Organic Plus > SusOrganic
Germany > Federal Organic Farming Scheme - BOEL > Food > Processing
UK > Other organizations United Kingdom
UK > Univ. Newcastle
Germany > University of Kassel
Related Links:http://coreorganicplus.org/research-projects/susorganic/, http://www.bundesprogramm.de, http://orgprints.org/perl/search/advanced?addtitle%2Ftitle=&keywords=14OE006&%20projects=BOELN&_order=bypublication&_action_search=Suchen
Deposited By: von Gersdorff, Gardis J.E.
ID Code:31330
Deposited On:13 Dec 2017 10:44
Last Modified:13 Dec 2017 10:44
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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