A current review of U.S. beef flavor I: Measuring beef flavor.

Historically, consumer acceptance of beef was determined by tenderness. Developments in genetics and management over the last couple of decades have improved tenderness to the point that it is secondary to other factors in beef's taste. Flavor, however, is an extraordinarily complex taste attribute dependent on biological sensors in the mouth, sinus cavity, and jaws. The culinary industry has recently focused on innovative ways to give consumers new products satisfying their curiosity about different foods, especially proteins. Competition from plant-based, cell-based, and even other animal-based proteins provides diversity in consumers' ability to select a protein that satisfies their desire to include unique products in their diet. Consequently, the beef industry has focused on flavor for the last 10 to 15 years to determine whether it can provide the guardrails for beef consumption in the future. The U.S. beef industry formed a Flavor Working Group in 2012 composed of the authors listed here to investigate new and innovative ways to manage and measure beef flavor. The results of this working group have resulted in dozens of papers, presentations, abstracts, and symposia. The objective of this manuscript is to summarize the research developed by this working group and by others worldwide that have investigated methodologies that measure beef flavor. This paper will describe the strengths of the research in beef flavor measurement and point out future needs that might be identified as technology advances.

A current review of U.S. beef flavor II: Managing beef flavor.

Beef flavor continues to be one of the largest drivers of beef demand and a differentiation point of beef from other competing proteins. Tenderness has long been identified as the most important palatability trait for consumer satisfaction. However, as technological advancements and industry practices evolve and improve in response to tenderness management, flavor has emerged as a key driver of consumer satisfaction. In response, the beef industry has recently invested in research focused on beef flavor development, measurement, and management to better understand the factors impacting flavor and help beef maintain this advantage. The current review paper is the second of two such papers focused on summarizing the present knowledge and identifying knowledge gaps. While the other review focuses on current practices related to beef flavor measurement, this review will cover research findings related to beef flavor management. Numerous production and product management factors influence beef flavor. Pre-harvest factors including marbling level, animal genetics/cattle type, diet, and animal age, can influence beef flavor. Moreover, numerous post-harvest product management factors, including product type, aging length and conditions, cookery methods, product enhancement, muscle-specific factors, packaging, retail display factors, and antimicrobial interventions, have all been evaluated for their impact on beef flavor characteristics. Results from numerous studies evaluating many of these factors will be outlined within this review in order to present management and production chain factors that can influence beef flavor.

Evaluation of a novel computer vision-based livestock monitoring system to identify and track specific behaviors of individual nursery pigs within a group-housed environment.

Animal behavior is indicative of health status and changes in behavior can indicate health issues (i.e., illness, stress, or injury). Currently, human observation (HO) is the only method for detecting behavior changes that may indicate problems in group-housed pigs. While HO is effective, limitations exist. Limitations include HO being time consuming, HO obfuscates natural behaviors, and it is not possible to maintain continuous HO. To address these limitations, a computer vision platform (NUtrack) was developed to identify (ID) and continuously monitor specific behaviors of group-housed pigs on an individual basis. The objectives of this study were to evaluate the capabilities of the NUtrack system and evaluate changes in behavior patterns over time of group-housed nursery pigs. The NUtrack system was installed above four nursery pens to monitor the behavior of 28 newly weaned pigs during a 42-d nursery period. Pigs were stratified by sex, litter, and randomly assigned to one of two pens (14 pigs/pen) for the first 22 d. On day 23, pigs were split into four pens (7 pigs/pen). To evaluate the NUtrack system's capabilities, 800 video frames containing 11,200 individual observations were randomly selected across the nursery period. Each frame was visually evaluated to verify the NUtrack system's accuracy for ID and classification of behavior. The NUtrack system achieved an overall accuracy for ID of 95.6%. This accuracy for ID was 93.5% during the first 22 d and increased (P < 0.001) to 98.2% for the final 20 d. Of the ID errors, 72.2% were due to mislabeled ID and 27.8% were due to loss of ID. The NUtrack system classified lying, standing, walking, at the feeder (ATF), and at the waterer (ATW) behaviors accurately at a rate of 98.7%, 89.7%, 88.5%, 95.6%, and 79.9%, respectively. Behavior data indicated that the time budget for lying, standing, and walking in nursery pigs was 77.7% ± 1.6%, 8.5% ± 1.1%, and 2.9% ± 0.4%, respectively. In addition, behavior data indicated that nursery pigs spent 9.9% ± 1.7% and 1.0% ± 0.3% time ATF and ATW, respectively. Results suggest that the NUtrack system can detect, identify, maintain ID, and classify specific behavior of group-housed nursery pigs for the duration of the 42-d nursery period. Overall, results suggest that, with continued research, the NUtrack system may provide a viable real-time precision livestock tool with the ability to assist producers in monitoring behaviors and potential changes in the behavior of group-housed pigs.

Impact of beef carcass size on chilling rate, pH decline, display color, and tenderness of top round subprimals.

Beef carcass weights in the United States have continued to increase over the past 30 yr. As reported by the United States Department of Agriculture, grid-based carcass weight discounts begin when carcasses exceed 408 kg. Despite weight discounts, beef carcass weights continue to increase. At the same time, an increased prevalence of discoloration and color variability in top round subprimals has been observed throughout the industry which may be influenced by the increases in carcass weights. The objectives of this study were to assess the effects of beef carcass size and its relationship to chill time, color, pH, and tenderness of the beef top round. In the current study, eight industry average weight beef carcasses (AW, 341-397 kg) and eight oversized beef carcasses (OW, exceeding 432 kg) were evaluated. Temperatures and pH measurements were observed on both sides of all carcasses for the initial 48 h postharvest at a consistent superficial and deep anatomical location of the respective top rounds. Carcasses were fabricated into subprimals at 48 h and top rounds were aged at 2 °C for an additional 12 d. The superficial location of both AW and OW carcasses cooled at a faster rate (P < 0.01) than the deep locations. The deep location of OW carcasses had a lower pH and a more rapid (P < 0.01) initial pH decline. Quantitative color of steaks from OW carcasses had greater mean L* (lightness; P = 0.01) and initial b* (yellowness; P < 0.01) values. The delayed temperature decline and the accelerated pH decline of the deep location of the top round of OW carcasses occur at different rates than AW carcasses. Delayed rate of cooling leads to irreversible impacts on steak appearance of top round steaks fabricated from OW beef carcasses when compared with AW carcasses.

Assessing outcomes of genetic selection panels to predict marbling in crossbred beef cattle.

The objective of this study was to evaluate the effectiveness of genetic panel marbling indexes [Igenity (IT) and PredicGEN (PG)] to predict marbling and tenderness of crossbred cattle. Steers (n = 23) were harvested at the University of Idaho Meat Science Laboratory, and blood samples were submitted to Neogen and Zoetis for genetic panel analysis. Forty-eight hours postharvest, one boneless strip loin was collected from each carcass, and six 2.54-cm thick steaks were cut from each strip loin. Steaks were aged for 14 and 21 d and assigned to consumer sensory evaluation or Warner-Bratzler Shear Force (WBSF) analysis. Results were analyzed using the Mixed Model procedure of the Statistical Analysis System (SAS Institute, Inc., Cary, NC). Carcasses were grouped by marbling index score into Low IT (IT indexes 3-6; n = 16; marbling score (MS) = 410), High IT (IT indexes 7-10; n = 7; MS = 496), Low PG (PG index <50; n = 9; MS = 398), or High PG (PG index ≥50; n = 14; MS = 458). Mean MS was observed to be greater in High IT steaks than Low IT (P < 0.01) and greater in High PG steaks than Low PG (P = 0.01). There was a trend observed in WBSF between IT marbling groups (P = 0.06); however, no difference in WBSF was observed between PG marbling groups (P = 0.83). Consumers did not report differences between IT marbling groups in terms of acceptability (P = 0.99) or tenderness (P = 0.24). Additionally, consumers could not detect differences between PG marbling groups in terms of acceptability (P = 0.75) or tenderness (P = 0.40). Consumers consistently preferred Choice steaks over Select steaks in terms of acceptability (P = 0.02) and tenderness (P = 0.02). In conclusion, though consumers were not able to tell the difference between steaks from each of the genetic panels, using genetic panels to predict marbling, in conjunction with proper nutrition and handling practices, could be a beneficial tool to producers making decisions about retaining ownership at the feedlot.