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Browsing by Author "Clark, Daniel, committee member"

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    Association between beef ribeye area measurements and steak portion size
    (Colorado State University. Libraries, 2024) Schiefelbein, Abbey Faith, author; Nair, Mahesh N., advisor; Geornaras, Ifigenia, committee member; Clark, Daniel, committee member; Hess, Ann, committee member
    As cattle weights have increased over the past decades, hot carcass weight and ribeye area (REA) have also increased. The REA is an important determinant of carcass value as it impacts the thickness of steaks when portioned to a pre-determined weight. Additionally, previous research has indicated that steak thickness impacts consumers' eating experience potentially due to its impact on the degree of doneness. The objective of this study was to examine the relationship between carcass REA and steak portion size. Beef carcasses (n = 100) were selected from a commercial beef harvesting facility based on REA in 1 in2 (6.45 cm2) increments ranging from less than 11 in2 (70.97 cm2) to greater than 19 in2 (122.58 cm2) based on a United States Department of Agriculture-approved camera (E+V) with 10 total categories. Data (hot carcass weight, back fat thickness, and marbling) were collected from each selected carcass. The REA measurements were obtained using the grading camera, a manual grid, and pen tracing and measured using ImageJ software. Strip loins (IMPS#180) from selected carcasses were collected, and weight, length, and three width (anterior, middle, and posterior) measurements of the strip loins were measured manually. Each strip loin was then scanned through a Marel I-Cut 56 portion cutter to determine the thickness of 12 oz (340.19 g) and 16 oz (453.59 g) portions and to determine the weight of a 1-in (2.54 cm) thick portion. To quantify and describe the relationship between steak thickness (cut to 12 oz and 16 oz portions) and steak weight (cut at 1-in. thickness), linear regression models were developed using traced REA as the independent variable. Additionally, more exhaustive linear regression models were developed to predict steak thickness or weight based on the traced REA, hot carcass weight, fat thickness, strip loin weight, strip loin length, strip loin width, and average maximum height of the strip loin. Each model was evaluated separately for the main effects of each variable, with significance determined at ɑ=0.05. There was a significant (P < 0.001) correlation and linear relationship (P < 0.05) between traced REA measurement and 12 oz (R2 = 0.71), 16 oz (R2 = 0.71), and 1-in.-thick (R2 = 0.75) portions examined in this study. For 12 oz steaks, the steak thickness decreased by an estimated 0.055 in. (0.14 cm) for every 1-in. increase in REA. Similarly, for the 16 oz steaks, the steak thickness decreased by an estimated 0.074 in. (0.19 cm) for every square in. increase in REA. The 1-in. steak portions had a mean weight of 340 g, and the steak weight increased an estimated 18 g for each square in. increase in REA. In addition, using the strip loin measurements, linear regression models were able to predict steak thickness for 12 oz and 16 oz portions with an R2 of 0.95 each and predict the steak weight for the 1-in. portion with an R2 of 0.98. As expected, REA strongly correlated with the portion size of strip loin steaks cut to a specified weight or thickness. Additionally, our results indicated that the weight and length of the strip loin were good predictors of steak thickness (for 12 oz and 16 oz portions) or steak weight (for 1-in.-thick portions). Further research exploring consumer acceptance and degree of doneness for steaks with varying thicknesses would provide data to determine REA ranges and targets that would optimize steak portion sizes and consumer acceptability.