Instrument evaluation of lamb carcass yield and quality characteristics

An instrument system capable of predicting lamb carcass yield and simultaneously segregating carcasses into meaningful quality classes with accuracy and precision would advance the assessment of true carcass value and enhance production of a consumer preferred product. The objectives of this research were to: (1) Assist in the development of official performance standards, using methodologies acceptable to the United States Department of Agriculture (USDA), Agricultural Marketing Service (AMS), Livestock and Seed (LS) Program, for approving instruments to assess commercial lamb carcasses; (2) Gain approval for at least two commercial lamb instrument carcass assessment systems; (3) Determine consumer sensory panel ratings of American lamb meat; (4) Establish baseline tenderness of American lamb meat; (5) Initiate efforts to determine whether or not instruments may be used to assess lamb carcass quality parameters.;The USDA-AMS-LS intends to accept ovine carcass cutability measurements made by approved instruments. The USDA-AMS-LS intends to approve instrument systems that meet specific performance requirements for accuracy, precision, and repeatability for the prediction of saleable meat yield of lamb carcasses. The USDA-AMS-LS provided USDA quality and yield carcass factors, OCC yield, hot carcass weight, chilled carcass weight, and subprimals and their components weights' to technology providers for the carcasses assigned to the calibration data set. Technology providers were allowed to use the calibration data set to develop or refine their OCC yield prediction equations. Technology providers submitted instrument predicted OCC yield values for the validation data set to USDA-AMS-LS. The USDA-AMS-LS computed the necessary statistics to determine if instrument systems met the requirements for approval.;Whole-number expert Yield Grade (expert YG) was used to investigate mean differences between OCC yield, and yield of subprimals and their components. The ability of Research Management System-Computer Vision System (RMS-CVS) , one of the Video Image Analysis (VIA) systems investigate in this study, was compared to expert YG to the nearest-tenth. Using VIA systems to make more accurate estimates of carcass composition creates potential to assist in the development of a value-based marketing system that will induce the production of leaner carcasses and ultimately a consumer-preferred product.;Consumer sensory panel evaluation and Warner-Bratzler shear force (WBSF) were used to characterize lamb tenderness, flavor, and overall acceptability, and to establish a baseline tenderness value for American lamb meat. Consumers used a 15-cm unmarked line scale to rate samples for "like" or "dislike" for the attributes of tenderness, flavor, and overall acceptability (left = dislike, right = like). There were no differences (P > 0.05) in consumer ratings for tenderness, flavor, and overall acceptability for samples from different USDA Quality Grade (QG) classes or from different seasonal periods. Probability for overall "liking" of samples by consumers was not affected by QG (P = 0.2741) nor season (P= 0.4395) with samples from QG Choice and Prime being rated in the "like" category at least 87% of the time and over 83% of the time for all seasons.;Warner-Bratzler shear force values did not differ (P = 0.3211) for samples derived from QG Choice and Prime carcasses. Based on this study, and using 4.4 Kg as the WBSF threshold value for defining "tender," American lamb meat can be considered "very tender" among consumers that at least periodically purchase lamb at retail. The American lamb industry can use these results in marketing campaigns to increase consumer interest in American lamb meat.;Finally, models for prediction of eating quality parameters of lamb meat were developed using RMS-CVS system output. Models for prediction of tenderness, flavor, and overall acceptance used consumer response, a subjective measurement which explains in part the low performance of those models. The prediction of characteristics such as flavor and overall acceptance was very difficult due to the inherited subjectivity of consumer preferences and idea of what represent a desirable product among different groups of consumers. (Abstract shortened by UMI.)...