Meat Standards Australia sought a consistent measure of the beef eating experience to the consumer. Rather than objective measurements or trained panel sensory assessment, it was decided to proceed with direct consumer assessment. Consumer-based assessment has much greater variation, but it has the decided advantage of validity. This paper summarises the path taken to obtain consistent consumer assessment. What meat samples to present to consumers? What responses to ask for? What to do with these responses when they were obtained? The answers to these questions have led to the MQ4 measure of consumer assessment of meat eating quality, which now forms the basis of the MSA predictive model.

In this paper, the statistical aspects of the methodology that led to the Meat Standards Australia (MSA) prediction model for beef palatability are explained and described. The model proposed here is descriptive: its intention is to describe the large amounts of data collected by MSA. The model is constrained to accord with accepted meat science principles. The combined dataset used in development of the prediction model reported is around 32 000 rows × 140 columns. Each row represents a sample tasted by 10 consumers; each column specifies a variable relating to the sample tested. The developed model represents the interface between experimental data, scientific evaluation and commercial application. The model is used commercially to predict consumer satisfaction, in the form of a score out of 100, which in turn determines a grade outcome. An important improvement of the MSA model relative to other beef grading systems is that it assigns an individual consumer-based grade result to specific muscle portions cooked by designated methods; it does not assign a single grade to a carcass.

A consumer study was conducted in Lubbock, Texas, to determine the effects of fat level of beef strip steaks on the palatability traits of tenderness, juiciness, flavor liking, and overall liking, while further investigating the window of acceptability for fat content of beef. Thirty beef strip loins were selected by trained personnel to equally represent USDA Prime, High Choice (upper 1/3 Choice), Low Choice (lower 1/3 Choice), Select, and Standard. Proximate analysis was conducted on all strip loins to determine percentage fat, moisture, protein, and collagen. Three strip loins from each quality grade were selected based on fat percentages from proximate analysis to best represent each USDA quality grade for use in the consumer evaluations. Strip loins were fabricated into 2.5-cm steaks, and further processed into 5 × 5 cm pieces. In addition to the US-sourced product, beef LM pieces from 6 Australian Wagyu steers (Wagyu) and 6 Australian grain finished steers (Australian) were used in the consumer evaluations. Consumers (n = 120) were served 7 samples: a warm-up sample, 1 sample from each USDA quality grade treatment, and either a Wagyu or Australian sample, in a balanced order in accordance with a 6 × 6 Latin square. Consumers rated each steak sample for tenderness, juiciness, flavor, and overall liking and rated each palatability trait as either acceptable or unacceptable. Moreover, consumers rated each sample as unsatisfactory, good everyday quality, better than everyday quality, or premium quality. Tenderness, juiciness, flavor liking, and overall liking increased with increasing fat content (P < 0.05). However, Wagyu and Australian samples did not follow this trend for flavor and overall liking. A decrease in consumer acceptability of each palatability trait was observed as fat level decreased (P < 0.05). Consumer overall liking was correlated (P < 0.05) with consumer tenderness (r = 0.76) and juiciness ratings (r = 0.73), but most highly correlated with flavor liking (r = 0.88). Results of this study indicated that increased fat level in beef strip steaks positively affected tenderness, juiciness, flavor liking, and overall liking of beef strip steaks. Moreover, flavor liking was the most highly correlated palatability trait with overall liking. In US-sourced samples, fat level had a large effect on the flavor liking of beef as determined by consumers. Copyright © 2012. American Society of Animal Science .

The Australian Beef Industry identified variable eating quality as a major contributor to declining beef consumption in the early 1990s and committed research funding to address the problem. The major issue was the ability to predict the eating quality of cooked beef before consumption. The Meat Standards Australia (MSA) program developed a consumer testing protocol, which led to MSA grading standards being defined by consumer score outcomes. Traditional carcass grading parameters proved to be of little value in predicting consumer outcomes. Instead a broader combination of factors forms the basis of an interactive prediction model that performs well. The grading model has evolved from a fixed parameter ‘Pathway’ approach, to a computer model that predicts consumer scores for 135 ‘cut by cooking method’ combinations for each graded carcass. The body of research work conducted in evaluating critical control points and in developing the model predictions and interactions has involved several Australian research groups with strong support and involvement from the industry.