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Prediction of meat tenderness using high resolution imaging

Date

2010

Authors

Howard, Scott Thomas, author
Belk, Keith Evan, 1961-, advisor
Tatum, J. Daryl, committee member
Chapman, Phillip L., committee member

Journal Title

Journal ISSN

Volume Title

Abstract

Tenderness plays an important role in the sensory attributes of beef products. The objective of this study was to obtain the highest quality and resolution images of cross-sections of beef Longissimus dorsi surfaces that could likely be replicated in a commercial environment; and, to develop algorithms and regression equations that predict aged beef shear force. Fifty carcasses were identified at each of three commercial beef processing facilities in Colorado, Nebraska and Texas (total N = 150). A-maturity carcasses were selected to fill an equal distribution over the entire range of beef marbling scores; 1/3 of carcasses represented marbling scores from Practically Devoid 00 to Slight 40, 1/3 from Slight 50 to Small 90 and 1/3 from Modest 00 or higher. Carcasses derived from cattle supplemented with Zilpaterol hydrochloride (n = 25, based on harvest facility records) were identified as such. Samples were excised from the Longissimus muscle immediately posterior to the 12 th /13 th rib interface and imaged using the Tenera Technology High Resolution Imaging System; in addition, reflectance measurements (L*, a*, b*) were obtained. Samples were aged for either 7 or 14 days prior to freezing. Steaks were fabricated from frozen samples for Warner-Bratzler shear force (WBSF) determination. Images were analyzed using the custom developed Tenera Technology ZARMT software program, generating 10 output variables (diaSml, propSml, diaLrg, propLrg, ratDia, ratProp, medDia, medProp, diaNormMax and propNormMax) thought to represent ultra-structural characteristics of muscle such as fiber diameter, proportion of large versus small fibers and predominant size of muscle fiber within a given sample, which have previously been associated with beef tenderness (Hiner et al., 1953; Tuma et al., 1962; Herring et al., 1965; Cooper et al., 1968). In 14d aged steaks from harvest facility one, the use of high resolution variables explained an additional 11% of the variation in WBSF value over the use of marbling and color variables alone. Within harvest facility two and three, high resolution variables allowed for explanation of an additional 25% and 17% of the variation in 14d WBSF respectively. For samples aged 7d, high resolution variables allowed for explanation of an additional 8%, 14% and 34% of the variation in WBSF values of steaks from harvest facility one, two and three respectively. Fourteen days postmortem, inclusion of high resolution variables improved classification of "tender" steaks (WBSF less than or equal to 3.7, Platter et al., 2003a) 40%, -3% and 7% from harvest facility one, two and three respectively. Classification of "tough" steaks (WBSF greater than 3.7, Platter et al., 2003a) within steaks aged 14d was improved by -10%, 0% and 0% through use of high resolution variables. In classification of "tough" versus "tender" steaks 7d postmortem, equations containing high resolution variables correctly classified an additional 6%, 14.3% and 7.1% of "tender" steaks and 0%, -5.9% and 9.1% of "tough" steaks from harvest facility one, two and three respectively. Compared with the use of marbling and reflectance measurements alone, the use of high resolution variables improved the ability to explain WBSF at 7d and 14d, as well as in the designation of "tough" and "tender" steaks/carcasses, suggesting this technology, or one measuring similar traits could improve the assurance of tender beef products at the consumer level.

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Subject

Beef -- Quality -- Testing
High resolution imaging

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