Heating decoys to mimic thermal signatures of live animals for drones.

Thermal sensors mounted on drones (unoccupied aircraft systems) are popular and effective tools for monitoring cryptic animal species, although few studies have quantified sampling error of animal counts from thermal images. Using decoys is one effective strategy to quantify bias and count accuracy; however, plastic decoys do not mimic thermal signatures of representative species. Our objective was to produce heat signatures in animal decoys to realistically match thermal images of live animals obtained from a drone-based sensor. We tested commercially available methods to heat plastic decoys of three different size classes, including chemical foot warmers, manually heated water, electric socks, pad, or blanket, and mini and small electric space heaters. We used criteria in two categories, 1) external temperature differences from ambient temperatures (ambient difference) and 2) color bins from a palette in thermal images obtained from a drone near the ground and in the air, to determine if heated decoys adequately matched respective live animals in four body regions. Three methods achieved similar thermal signatures to live animals for three to four body regions in external temperatures and predominantly matched the corresponding yellow color bins in thermal drone images from the ground and in the air. Pigeon decoys were best and most consistently heated with three-foot warmers. Goose and deer decoys were best heated by mini and small space heaters, respectively, in their body cavities, with a heated sock in the head of the goose decoy. The materials and equipment for our best heating methods were relatively inexpensive, commercially available items that provide sustained heat and could be adapted to various shapes and sizes for a wide range of avian and mammalian species. Our heating methods could be used in future studies to quantify bias and validate methodologies for drone surveys of animals with thermal sensors.•We determined optimal heating methods for plastic animal decoys with inexpensive and commercially available equipment to mimic thermal signatures of live animals.•Methods could be used to quantify bias and improve thermal surveys of animals with drones in future studies.

The importance of including metmyoglobin levels in reflectance-based oxygen consumption measurements.

Reflectance-based oxygen consumption measurement utilizes changes in oxymyoglobin levels between bloomed and vacuum-packaged meat, assuming that oxymyoglobin is converted to deoxymyoglobin. However, the interconversion of oxymyoglobin to deoxymyoglobin depends on the age of the meat and the length of display; hence, oxygen consumption calculations might yield inaccurate interpretations if deoxymyoglobin is not the final form. The objective was to evaluate the effectiveness of determining metmyoglobin levels during oxygen consumption analysis and its relationship to beef color stability. Seven psoas major (color labile) and longissimus (color stable) were displayed in retail for 6 d and evaluated for oxygen consumption on the retail (oxygen exposed) and interior (non­oxygen exposed) surfaces. The retail surface had greater (P < 0.05) metmyoglobin formed during oxygen consumption than the interior surface on d 6 of the display. Furthermore, the psoas major muscle exhibited greater (P < 0.05) metmyoglobin content during oxygen consumption than the longissimus on the retail surface paralleling with the decline in color stability. Therefore, the study indicates that sampling location and including metmyoglobin content in oxygen consumption calculations, along with changes in oxymyoglobin, will better explain meat color stability.

National Beef Quality Audit-2022: in-plant assessments of quality and yield determining carcass characteristics of fed steers and heifers.

The National Beef Quality Audit - 2022 serves as a benchmark of the current fed steer and heifer population of the U.S. beef industry and allows comparison to previous audits as a method of monitoring industry progress. In-plant cooler assessments and collections of beef carcass data took place from July 2021 to November 2022. During in-plant evaluations, 10% of 1-d production was surveyed for quality and yield indicating characteristics of fed beef carcasses (n = 9,746 beef carcasses). Distributions of sex classes among sampled carcasses were steer (65.0%) and heifer (35.0%), whereas distributions of breed type were native (87.7%), dairy (11.3%), and Bos indicus (0.9%). Mean values were observed for USDA Yield Grades (YG; 3.3), USDA Quality Grade (QG; Choice16), marbling score (Small98), ribeye area (91.0 cm2), adjusted fat thickness (1.49 cm), hot carcass weight (401.9 kg), and KPH (2.5%). Mean overall maturity was A66, with a mean lean maturity of A56 and mean skeletal maturity of A72. There were 28.1% of carcasses identified for use in a USDA-certified beef G-Schedule Program. Defects, such as dark cutting and blood splash, were observed at 1.8% and 0.5%, respectively. Distributions of USDA YG were YG 1 (8.2%), YG 2 (30.7%), YG 3 (40.2%), YG 4 (16.6%), and YG 5 (4.3%). USDA QGs were observed at 7.5% Prime, 69.2% Choice, 16.4% Select, and 6.8% other. The results of this study provide an updated look at the current grading trends of beef carcasses in the United States to drive progress in the fed beef industry.

National Beef Quality Audit-2022 Phase 1: face-to-face and digital interviews.

The National Beef Quality Audit (NBQA) has been conducted regularly since 1991 to assess and benchmark quality in the U.S. beef industry, with the most recent iteration conducted in 2022. The goal of NBQA Phase I is to evaluate what needs to be managed to improve beef quality and demand. Interviews (n = 130) of industry personnel were conducted with the aid of routing software. In total, packers (n = 24), retailers (n = 20), further processors (n = 26), foodservice (n = 18), and allied government agencies and trade organizations (n = 42) were interviewed. Interviews were routed in software based on interviewee involvement in either the fed steer and heifer market cow and bull sectors, or both. Interviews were structured to elicit random responses in the order of determining "must-have" criteria (quality factors that are required to make a purchase), best/worst ranking (of quality factors based on importance), how interviewees defined quality terms, a strength, weakness, opportunities, threats (SWOT) analysis, general beef industry questions, and sustainability goals (the latter four being open-ended). Quality factors were 1) visual characteristics, 2) cattle genetics, 3) food safety, 4) eating satisfaction, 5) animal well-being, 6) weight and size, and 7) lean, fat, and bone. Best/worst analysis revealed that "food safety" was the most (P < 0.05) important factor in beef purchasing decisions for all market sectors and frequently was described as "everything" and "a way of business." Culture surrounding food safety changed compared to previous NBQAs with interviewees no longer considering food safety as a purchasing criterion, but rather as a market expectation. The SWOT analysis indicated that "eating quality of U.S. beef" was the greatest strength, and cited that educating both consumers and producers on beef production would benefit the industry. Irrespective of whether companies' products were fed or market cow/bull beef, respondents said that they believed "environmental concerns" were among the major threats to the industry. Perceived image of the beef industry in the market sectors has improved since NBQA-2016 for both fed cattle and market cow/bull beef.

National Beef Quality Audit-2022: Transportation, mobility, live cattle, and hide assessments to determine producer-related defects that affect animal welfare and the value of market cows and bulls at processing facilities.

The National Beef Quality Audit (NBQA)-2022 serves as a benchmark of the current market cow and bull sectors of the U.S. beef industry and allows comparison to previous audits as a method of monitoring industry progress. From September 2021 through May 2022, livestock trailers (n = 125), live animals (n = 5,430), and post-slaughter hide-on animals (n = 6,674) were surveyed at 20 commercial beef processing facilities across the U.S. Cattle were transported in a variety of trailer types for an average distance of 490.6 km and a mean transport time of 6.3 h. During transit, cattle averaged 2.3 m2 of trailer space per animal indicating sufficient space was provided according to industry guidelines. Of all trailers surveyed, 55.3% transported cattle from an auction barn to a processing facility. When surveyed, 63.6% of all truck drivers reported to be Beef Quality Assurance certified. The majority (77.0%) of cattle were sound when evaluated for mobility. Mean body condition scores (9-point scale) for beef cows and bulls were 3.8 and 4.4, respectively, whereas mean body condition scores (5-point scale) for dairy cows and bulls were 2.3 and 2.6, respectively. Of the cattle surveyed, 45.1% had no visible live animal defects, and 37.9% had only a single defect. Of defects present in cows, 64.6% were attributed to an udder problem. Full udders were observed in 47.5% of all cows. Nearly all cattle were free of visible abscesses and knots (97.9% and 98.2%, respectively). No horns were observed in 89.4% of all cattle surveyed. Beef cattle were predominantly black-hided (68.9% and 67.4% of cows and bulls, respectively). Holstein was the predominant dairy animal observed and accounted for 85.7% of the cows and 98.0% of the bulls. Only 3.1% of all animals had no form of identification. Findings from the NBQA-2022 show improvements within the industry and identify areas that require continued education and research to improve market cow and bull welfare and beef quality.

Comparing the effects of packaging normal-pH and atypical dark-cutting beef in modified atmosphere conditions on surface color.

Limited studies have determined the effects of modified atmospheric packaging (MAP) on atypical dark-cutting beef surface color. The objective was to compare the impacts of using vacuum packaging, carbon monoxide (CO-MAP), and HiOx-MAP (high­oxygen) on the retail color of normal-pH and atypical dark-cutting beef aged 14 d. Atypical dark-cutting beef (pH 5.63) had numerically greater (P > 0.05) pH than normal-pH beef (pH 5.56). Atypical dark-cutting steaks were darker in color (lower L* values; P < 0.05) than normal-pH steaks. Atypical dark-cutting steaks had greater (P < 0.05) oxygen consumption, lower (P < 0.05) relative oxygenation, and less inter-muscle bundle space (P < 0.05) than normal-pH steaks. There were no differences (P > 0.05) in redness between normal-pH and atypical dark-cutting steaks when packaged in HiOx-MAP. Although a minimal increase in pH was observed in atypical dark-cutting beef, steaks in CO-MAP had lower redness than normal-pH steaks.

Novel needle-probe single-fiber reflectance spectroscopy to quantify sub-surface myoglobin forms in beef psoas major steaks during retail display.

Meat discoloration starts at the interface between the bright red oxymyoglobin layer and the interior deoxymyoglobin layer. Currently, limited tools are available to characterize myoglobin forms formed within the sub-surface of meat. The objective was to demonstrate a needle-probe based single-fiber reflectance (SfR) spectroscopy approach for characterizing sub-surface myoglobin forms of beef psoas major muscles during retail storage. A 400-µm fiber was placed in a 17-gauge needle, and the assembly was inserted into the muscle at five depths of 1 mm increment and 1 cm lateral shift. Metmyoglobin content increased at all depths during display and content at 1 mm was greater compared to that of 2 to 5 mm depth. The a* values decreased (P < 0.05) during retail display aligning with the sub-surface formation of metmyoglobin. In summary, the results suggest that needle-probe SfR spectroscopy can determine interior myoglobin forms and characterize meat discoloration.

Fusion of visible and thermal images improves automated detection and classification of animals for drone surveys.

Visible and thermal images acquired from drones (unoccupied aircraft systems) have substantially improved animal monitoring. Combining complementary information from both image types provides a powerful approach for automating detection and classification of multiple animal species to augment drone surveys. We compared eight image fusion methods using thermal and visible drone images combined with two supervised deep learning models, to evaluate the detection and classification of white-tailed deer (Odocoileus virginianus), domestic cow (Bos taurus), and domestic horse (Equus caballus). We classified visible and thermal images separately and compared them with the results of image fusion. Fused images provided minimal improvement for cows and horses compared to visible images alone, likely because the size, shape, and color of these species made them conspicuous against the background. For white-tailed deer, which were typically cryptic against their backgrounds and often in shadows in visible images, the added information from thermal images improved detection and classification in fusion methods from 15 to 85%. Our results suggest that image fusion is ideal for surveying animals inconspicuous from their backgrounds, and our approach uses few image pairs to train compared to typical machine-learning methods. We discuss computational and field considerations to improve drone surveys using our fusion approach.

Metabolomics and bioinformatic analyses to determine the effects of oxygen exposure within longissimus lumborum steak on beef discoloration.

Meat discoloration starts from the interior and spreads to oxymyoglobin layer on the surface. The effects of oxygen exposure within a steak on the metabolome have not been evaluated. Therefore, the objective of this study was to evaluate the impact of oxygen exposure on the metabolome of the longissimus lumborum muscle. Six United States Department of Agriculture (USDA) Low Choice beef strip loins were sliced into steaks (1.91-cm) and packaged in polyvinyl chloride overwrap trays for 3 or 6 d of retail display. The oxygen exposed (OE) surface was the display surface during retail, and the non-oxygen exposed (NOE) surface was the intact interior muscle. The instrumental color was evaluated using a HunterLab MiniScan spectrophotometer. To analyze the NOE surface on days 3 and 6, steaks were sliced parallel to the OE surface to expose the NOE surface. Metmyoglobin reducing ability (MRA) was determined by nitrite-induced metmyoglobin reduction. A gas chromatography-mass spectrometry was used to identify metabolites. The a* values of steaks decreased (P < 0.05) with display time. MRA was greater (P < 0.05) in the NOE surface compared with the OE surface on days 3 and 6. The KEGG pathway analysis indicated the tricarboxylic acid (TCA) cycle, pentose and glucuronate interconversions, phenylalanine, tyrosine, and tryptophan metabolism were influenced by the oxygen exposure. The decrease in abundance of succinate from days 0 to 6 during retail display aligned with a decline in redness during display. Furthermore, citric acid and gluconic acid were indicated as important metabolites affected by oxygen exposure and retail display based on the variable importance in the projection in the PLS-DA plot. Citric acid was lower in the NOE surface than the OE surface on day 6 of retail display, which could relate to the formation of succinate for extended oxidative stability. Greater alpha-tocopherol (P < 0.05) in the NOE surface supported less oxidative changes compared to the OE surface during retail display. These results indicate the presence of oxygen can influence metabolite profile and promote migration of the metmyoglobin layer from interior to surface.

In a retail setting, aerobic packaging allows beef steaks to form a bright-cherry red appearance. However, prolonged oxygen exposure can also lead to surface discoloration, which is negatively perceived by consumers. Surface discoloration results in either discounts or products being discarded in the grocery store resulting in approximately $3.7 billion loss annually in the United States. Hence, understanding the process of oxygen exposed discoloration would help to limit the economic loss and meat waste. The current study evaluated the impact of oxygen exposure on metabolites, oxygen consumption, and metmyoglobin reducing activity of beef strip loin steaks. The results indicated that oxygen exposure decreased metmyoglobin reducing activity. Furthermore, metabolites that could limit surface discoloration showed lower abundance in oxygen-exposed surface during retail display. Oxygen negatively impacts the color of beef loin steaks and the stability of the color during retail. Expanding our knowledge of processes involved in metmyoglobin formation could help to develop strategies to help limit economic loss associated with surface discoloration.

Evidence on the efficacy of small unoccupied aircraft systems (UAS) as a survey tool for North American terrestrial, vertebrate animals: a systematic map.

BACKGROUND: Small unoccupied aircraft systems (UAS) are replacing or supplementing occupied aircraft and ground-based surveys in animal monitoring due to improved sensors, efficiency, costs, and logistical benefits. Numerous UAS and sensors are available and have been used in various methods. However, justification for selection or methods used are not typically offered in published literature. Furthermore, existing reviews do not adequately cover past and current UAS applications for animal monitoring, nor their associated UAS/sensor characteristics and environmental considerations. We present a systematic map that collects and consolidates evidence pertaining to UAS monitoring of animals. METHODS: We investigated the current state of knowledge on UAS applications in terrestrial animal monitoring by using an accurate, comprehensive, and repeatable systematic map approach. We searched relevant peer-reviewed and grey literature, as well as dissertations and theses, using online publication databases, Google Scholar, and by request through a professional network of collaborators and publicly available websites. We used a tiered approach to article exclusion with eligible studies being those that monitor (i.e., identify, count, estimate, etc.) terrestrial vertebrate animals. Extracted metadata concerning UAS, sensors, animals, methodology, and results were recorded in Microsoft Access. We queried and catalogued evidence in the final database to produce tables, figures, and geographic maps to accompany this full narrative review, answering our primary and secondary questions. REVIEW FINDINGS: We found 5539 articles from our literature searches of which 216 were included with extracted metadata categories in our database and narrative review. Studies exhibited exponential growth over time but have levelled off between 2019 and 2021 and were primarily conducted in North America, Australia, and Antarctica. Each metadata category had major clusters and gaps, which are described in the narrative review. CONCLUSIONS: Our systematic map provides a useful synthesis of current applications of UAS-animal related studies and identifies major knowledge clusters (well-represented subtopics that are amenable to full synthesis by a systematic review) and gaps (unreported or underrepresented topics that warrant additional primary research) that guide future research directions and UAS applications. The literature for the use of UAS to conduct animal surveys has expanded intensely since its inception in 2006 but is still in its infancy. Since 2015, technological improvements and subsequent cost reductions facilitated widespread research, often to validate UAS technology to survey single species with application of descriptive statistics over limited spatial and temporal scales. Studies since the 2015 expansion have still generally focused on large birds or mammals in open landscapes of 4 countries, but regulations, such as maximum altitude and line-of-sight limitations, remain barriers to improved animal surveys with UAS. Critical knowledge gaps include the lack of (1) best practices for using UAS to conduct standardized surveys in general, (2) best practices to survey whole wildlife communities in delineated areas, and (3) data on factors affecting bias in counting animals from UAS images. Promising advances include the use of thermal sensors in forested environments or nocturnal surveys and the development of automated or semi-automated machine-learning algorithms to accurately detect, identify, and count animals from UAS images.

Responses of turkey vultures to unmanned aircraft systems vary by platform.

A challenge that conservation practitioners face is manipulating behavior of nuisance species. The turkey vulture (Cathartes aura) can cause substantial damage to aircraft if struck. The goal of this study was to assess vulture responses to unmanned aircraft systems (UAS) for use as a possible dispersal tool. Our treatments included three platforms (fixed-wing, multirotor, and a predator-like ornithopter [powered by flapping flight]) and two approach types (30 m overhead or targeted towards a vulture) in an operational context. We evaluated perceived risk as probability of reaction, reaction time, flight-initiation distance (FID), vulture remaining index, and latency to return. Vultures escaped sooner in response to the fixed-wing; however, fewer remained after multirotor treatments. Targeted approaches were perceived as riskier than overhead. Vulture perceived risk was enhanced by flying the multirotor in a targeted approach. We found no effect of our treatments on FID or latency to return. Latency was negatively correlated with UAS speed, perhaps because slower UAS spent more time over the area. Greatest visual saliency followed as: ornithopter, fixed-wing, and multirotor. Despite its appearance, the ornithopter was not effective at dispersing vultures. Because effectiveness varied, multirotor/fixed-wing UAS use should be informed by management goals (immediate dispersal versus latency).

Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks.

In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Automatic identification and classification of animals through images acquired using a sUAS may solve critical problems such as monitoring large areas with high vehicle traffic for animals to prevent collisions, such as animal-aircraft collisions on airports. In this research we demonstrate automated identification of four animal species using deep learning animal classification models trained on sUAS collected images. We used a sUAS mounted with visible spectrum cameras to capture 1288 images of four different animal species: cattle (Bos taurus), horses (Equus caballus), Canada Geese (Branta canadensis), and white-tailed deer (Odocoileus virginianus). We chose these animals because they were readily accessible and white-tailed deer and Canada Geese are considered aviation hazards, as well as being easily identifiable within aerial imagery. A four-class classification problem involving these species was developed from the acquired data using deep learning neural networks. We studied the performance of two deep neural network models, convolutional neural networks (CNN) and deep residual networks (ResNet). Results indicate that the ResNet model with 18 layers, ResNet 18, may be an effective algorithm at classifying between animals while using a relatively small number of training samples. The best ResNet architecture produced a 99.18% overall accuracy (OA) in animal identification and a Kappa statistic of 0.98. The highest OA and Kappa produced by CNN were 84.55% and 0.79 respectively. These findings suggest that ResNet is effective at distinguishing among the four species tested and shows promise for classifying larger datasets of more diverse animals.

Social information affects Canada goose alert and escape responses to vehicle approach: implications for animal-vehicle collisions.

BACKGROUND: Animal-vehicle collisions represent substantial sources of mortality for a variety of taxa and can pose hazards to property and human health. But there is comparatively little information available on escape responses by free-ranging animals to vehicle approach versus predators/humans. METHODS: We examined responses (alert distance and flight-initiation distance) of focal Canada geese (Branta canadensis maxima) to vehicle approach (15.6 m·s-1) in a semi-natural setting and given full opportunity to escape. We manipulated the direction of the vehicle approach (direct versus tangential) and availability of social information about the vehicle approach (companion group visually exposed or not to the vehicle). RESULTS: We found that both categorical factors interacted to affect alert and escape behaviors. Focal geese used mostly personal information to become alert to the vehicle under high risk scenarios (direct approach), but they combined personal and social information to become alert in low risk scenarios (tangential approach). Additionally, when social information was not available from the companion group, focal birds escaped at greater distances under direct compared to tangential approaches. However, when the companion group could see the vehicle approaching, focal birds escaped at similar distances irrespective of vehicle direction. Finally, geese showed a greater tendency to take flight when the vehicle approached directly, as opposed to a side step or walking away from the vehicle. CONCLUSIONS: We suggest that the perception of risk to vehicle approach (likely versus unlikely collision) is weighted by the availability of social information in the group; a phenomenon not described before in the context of animal-vehicle interactions. Notably, when social information is available, the effects of heightened risk associated with a direct approach might be reduced, leading to the animal delaying the escape, which could ultimately increase the chances of a collision. Also, information on a priori escape distances required for surviving a vehicle approach (based on species behavior and vehicle approach speeds) can inform planning, such as location of designated cover or safe areas. Future studies should assess how information from vehicle approach flows within a flock, including aspects of vehicle speed and size, metrics that affect escape decision-making.

Frequencies and severity of injection-site lesions in muscles from rounds of cow carcasses.

The frequency and severity of injection-site lesions in the outside round muscles of both beef and dairy cattle were evaluated through a series of audits. Audits were conducted in 2017 on 1,300 rounds from dairy and beef cows from seven locations throughout the United States. Outside round muscles were butterfly cut into 1.25-cm slices and, if present, lesions were counted, measured, and categorized. Rounds from beef (7%) and dairy cattle (15%) had at least one injection-site lesion present. The most common location of injection-site lesions was quadrant 2 and 3, which contained both the biceps femoris and semitendinosus muscles. Injection-site lesions were more frequent (P < 0.05) in the biceps femoris for both beef and dairy rounds. Clear lesions accounted for 57% of injection-sites in both beef and dairy rounds, whereas metallic lesions made up 23% of the total in beef and 25% in dairy. Overall, there was a dramatic decline in the frequency (P < 0.05) of injection-site lesions since the 1998 (24 and 45 percentage units greater in beef and dairy rounds, respectively) and 2000 audits (13 and 20 percentage units greater in beef and dairy rounds, respectively). Educational programs, such as Beef Quality Assurance (BQA) and requirements for BQA training, have resulted in substantial improvements in beef management practices for both the beef and dairy industries.

Quantification of avian hazards to military aircraft and implications for wildlife management.

Collisions between birds and military aircraft are common and can have catastrophic effects. Knowledge of relative wildlife hazards to aircraft (the likelihood of aircraft damage when a species is struck) is needed before estimating wildlife strike risk (combined frequency and severity component) at military airfields. Despite annual reviews of wildlife strike trends with civil aviation since the 1990s, little is known about wildlife strike trends for military aircraft. We hypothesized that species relative hazard scores would correlate positively with aircraft type and avian body mass. Only strike records identified to species that occurred within the U.S. (n = 36,979) and involved United States Navy or United States Air Force aircraft were used to calculate relative hazard scores. The most hazardous species to military aircraft was the snow goose (Anser caerulescens), followed by the common loon (Gavia immer), and a tie between Canada goose (Branta canadensis) and black vulture (Coragyps atratus). We found an association between avian body mass and relative hazard score (r2 = 0.76) for all military airframes. In general, relative hazard scores per species were higher for military than civil airframes. An important consideration is that hazard scores can vary depending on aircraft type. We found that avian body mass affected the probability of damage differentially per airframe. In the development of an airfield wildlife management plan, and absent estimates of species strike risk, airport wildlife biologists should prioritize management of species with high relative hazard scores.

National Beef Quality Audit-2016: assessment of cattle hide characteristics, offal condemnations, and carcass traits to determine the quality status of the market cow and bull beef industry.

To continue the series that began in 1994, the National Beef Quality Audit (NBQA) - 2016 was conducted to quantify the quality status of the market cow and bull beef sector, as well as determine improvements made in the beef and dairy industry since 2007. The NBQA-2016 was conducted from March through December of 2016, and assessed hide-on carcasses (n = 5,278), chilled carcasses (n = 4,285), heads (n = 5,720), and offal items (n = 4,800) in 18 commercial processing facilities throughout the United States. Beef cattle were predominantly black-hided; 68.0% of beef cows and 67.2% of beef bulls possessed a black hide. Holstein was the predominant type of dairy animal observed. Just over half (56.0%) of the cattle surveyed had no mud contamination on the hide, and when mud was present, 34.1% of cattle only had small amounts. Harvest floor assessments found 44.6% of livers, 23.1% of lungs, 22.3% of hearts, 20.0% of viscera, 8.2% of heads, and 5.9% of tongues were condemned. Liver condemnations were most frequently due to abscess presence. In contrast, contamination was the primary reason for condemnation of all other offal items. Of the cow carcasses surveyed, 17.4% carried a fetus at the time of harvest. As expected, mean carcass weight and loin muscle area values observed for bulls were heavier and larger than cows. The marbling scores represented by cull animal carcasses were most frequently slight and traces amounts. Cow carcasses manifested a greater amount of marbling on average than bull carcasses. The predominant fat color score showed all carcasses surveyed had some level of yellow fat. Only 1.3% of carcasses exhibited signs of arthritic joints. Results of the NBQA-2016 indicate there are areas in which the beef and dairy industries have improved and areas that still need attention to prevent value loss in market cows and bulls.

Novel nitrite-embedded packaging improves surface redness of dark-cutting longissimus steaks.

The objective of this research was to determine the effects of nitrite-embedded/FreshCase packaging on lean color of dark-cutting beef. Eight dark-cutting (pH > 6.0) and eight USDA Low Choice (normal-pH; mean pH = 5.6) beef strip loins (longissimus lumborum) were selected 3 day after harvest. Each dark-cutting loin was sliced into five 2.5-cm thick steaks and randomly assigned to 1) dark-cutting steak packaged in polyvinyl chloride film (PVC) overwrap, 2) dark-cutting steak packaged in nitrite-embedded film, 3) dark-cutting steaks dipped in 0.2% rosemary solution and packaged in nitrite-embedded film, and 4) dark-cutting steak dipped in deionized water and packaged in nitrite-embedded film. The fifth dark-cutting steak was used to determine pH and proximate composition. Normal-pH choice loins were used as a control and each loin was randomly assigned to either PVC overwrap for retail display or to determine pH and proximate composition. Packages were placed in coffin-style retail display cases under continuous fluorescent lighting for 3 days. A HunterLab MiniScan XE Plus spectrophotometer was utilized to characterize steak color every 24 h. There was a significant treatment × storage time interaction (P < 0.05) for a* values and nitric oxide myoglobin formation. On days 1, 2, and 3 of the display, nitrite-embedded treatment improved (P < 0.05) redness compared to other dark-cutting steaks in PVC. A 45% increase in redness (P < 0.05) was observed for nitrite-embedded rosemary treatment over dark-cutting steak in PVC on day 3 of display. Nitric oxide myoglobin formation on day 0 was less for all dark-cutting steaks in nitrite-embedded packaging. Metmyoglobin content was greater (P < 0.05) on day 0 for dark-cutting steaks packaged in nitrite-embedded treatments than dark-cutting steaks in PVC. However, metmyoglobin level in dark-cutting steaks packaged in nitrite-embedded treatments decreased (P < 0.05) on day 1 compared with day 0. Dark-cutting steaks packaged in PVC had greater (P < 0.05) L* values on day 0 than other dark-cutting steaks in nitrite-embedded packaging. Conversely, on days 1, 2, and 3, there were no differences (P > 0.05) in L* values between dark-cutting treatments. Dark-cutting steaks in nitrite-embedded packaging had lower total plate count (P < 0.05) than dark-cutting steak packaged in PVC. The current research indicated that nitrite-embedded packaging has the potential to improve surface color of dark-cutting beef.