20 research outputs found
Comparison of Machine Learning Algorithms for Predictive Modeling of Beef Attributes Using Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data
Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrated applications in both human health and food science. Here, we present an evaluation of REIMS as a tool to generate molecular scale information as an objective measure for the assessment of beef quality attributes. Eight different machine learning algorithms were compared to generate predictive models using REIMS data to classify beef quality attributes based on the United States Department of Agriculture (USDA) quality grade, production background, breed type and muscle tenderness. The results revealed that the optimal machine learning algorithm, as assessed by predictive accuracy, was different depending on the classification problem, suggesting that a “one size fits all” approach to developing predictive models from REIMS data is not appropriate. The highest performing models for each classification achieved prediction accuracies between 81.5–99%, indicating the potential of the approach to complement current methods for classifying quality attributes in beef
Metaphylactic antimicrobial effects on occurrences of antimicrobial resistance in \u3ci\u3eSalmonella enterica, Escherichia coli\u3c/i\u3e and \u3ci\u3eEnterococcus\u3c/i\u3e spp. measured longitudinally from feedlot arrival to harvest in high-risk beef cattle
Aims: Our objective was to determine how injectable antimicrobials affected populations of Salmonella enterica, Escherichia coli and Enterococcus spp. in feedlot cattle.
Methods and Results: Two arrival date blocks of high-risk crossbred beef cattle (n = 249; mean BW = 244 kg) were randomly assigned one of four antimicrobial treatments administered on day 0: sterile saline control (CON), tulathromycin (TUL), ceftiofur (CEF) or florfenicol (FLR). Faecal samples were collected on days 0, 28, 56, 112, 182 and study end (day 252 for block 1 and day 242 for block 2). Hide swabs and subiliac lymph nodes were collected the day before and the day of harvest. Samples were cultured for antimicrobial-resistant Salmonella, Escherichia coli and Enterococcus spp. The effect of treatment varied by day across all targeted bacterial populations (p ≤ 0.01) except total E. coli. Total E. coli counts were greatest on days 112, 182 and study end (p ≤ 0.01). Tulathromycin resulted in greater counts and prevalence of Salmonella from faeces than CON at study end (p ≤ 0.01). Tulathromycin and CEF yielded greater Salmonella hide prevalence and greater counts of 128ERYR E. coli at study end than CON (p ≤ 0.01). No faecal Salmonella resistant to tetracyclines or third-generation cephalosporins were detected. Ceftiofur was associated with greater counts of 8ERYR Enterococcus spp. at study end (p ≤ 0.03). By the day before harvest, antimicrobial use did not increase prevalence or counts for all other bacterial populations compared with CON (p ≥ 0.13).
Conclusions: Antimicrobial resistance (AMR) in feedlot cattle is not caused solely by using a metaphylactic antimicrobial on arrival, but more likely a multitude of environmental and management factors
Broad and Inconsistent Muscle Food Classification Is Problematic for Dietary Guidance in the U.S.
Dietary recommendations regarding consumption of muscle foods, such as red meat, processed meat, poultry or fish, largely rely on current dietary intake assessment methods. This narrative review summarizes how U.S. intake values for various types of muscle foods are grouped and estimated via methods that include: (1) food frequency questionnaires; (2) food disappearance data from the U.S. Department of Agriculture Economic Research Service; and (3) dietary recall information from the National Health and Nutrition Examination Survey data. These reported methods inconsistently classify muscle foods into groups, such as those previously listed, which creates discrepancies in estimated intakes. Researchers who classify muscle foods into these groups do not consistently considered nutrient content, in turn leading to implications of scientific conclusions and dietary recommendations. Consequentially, these factors demonstrate a need for a more universal muscle food classification system. Further specification to this system would improve accuracy and precision in which researchers can classify muscle foods in nutrition research. Future multidisciplinary collaboration is needed to develop a new classification system via systematic review protocol of current literature
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Effects of the F94L myostatin gene mutation in beef Ă— dairy crossed cattle on strip loin steak dimensionality, shear force, and sensory attributes
Carcasses (n = 115) from steers resulting from the mating of four Limousin × Angus sires heterozygous for the F94L myostatin mutation to Jersey, Jersey × Holstein, and Holstein dams were utilized to evaluate the effects of one copy of the F94L allele on strip loin dimensionality, Warner–Bratzler shear force and slice shear force, and sensory panel ratings. In phase I of a two-phase study, 57 carcasses from two sires were utilized to obtain samples of longissimus dorsi (LD), psoas major (PM), gluteus medsius (GM), semitendinosus (ST), serratus ventralis, triceps brachii, and biceps femori muscles, which were vacuum packaged, aged until 10 d postmortem, and frozen. Frozen strip loins were cut into 14, 2.5-cm-thick steaks each, and individual strip loin steaks were imaged at a fixed height on a gridded background and processed through image analysis software. In phase II, to obtain a greater power of test for LD palatability attributes, 58 additional carcasses from three sires were utilized to obtain LD samples only for sensory panel and shear force analysis. Cooked steak sensory attributes evaluated by trained panelists were tenderness, juiciness, beef flavor, browned flavor, roasted flavor, umami flavor, metallic flavor, fat-like flavor, buttery flavor, sour flavor, oxidized flavor, and liver-like flavor. In strip loin steaks from carcasses with one F94L allele, LD muscle area was larger in steaks 4, 5, 7, 8, and 9, and steaks 1, 6, 7, and 9 were less angular than those from carcasses with no F94L allele (P 0.20). F94L genotype did not affect sensory panel ratings of LD and GM steaks (P > 0.07). Cooked ST steaks from carcasses with one F94L rated lower in fat-like flavor compared to those from carcasses with no F94L allele (P = 0.035). Cooked PM steaks from carcasses with one F94L allele rated lower in juiciness, fat-like flavor, buttery flavor, and umami flavor compared to those with no copies of the F94L (P < 0.04). In summary, one copy of the F94L allele utilized in beef × dairy cross steers improved strip loin steak dimensionality, did not affect cooked steak tenderness across seven muscles, and decreased fat-associated flavors in the PM and ST. The use of F94L homozygous terminal beef sires would be an easily implemented strategy for dairy producers to improve steak portion size and shape in carcasses from nonreplacement calves.12 month embargo; first published 26 September 2023This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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Effects of the F94L myostatin gene mutation in beef Ă— dairy crossed cattle on muscle fiber type, live performance, carcass characteristics, and boxed beef and retail cut yields
Producer live performance data and carcasses from steers (n = 116) resulting from the mating of four Limousin/Angus sires heterozygous for the F94L myostatin mutation to Jersey/Holstein dams were utilized to evaluate the effects of one copy of the F94L allele on live performance, carcass traits and USDA grades, and boxed beef and retail yields. Slaughter data were collected at time of harvest and carcass data were collected 48 hours postmortem. One side from each of the 58 carcasses was fabricated into boxed beef and retail cuts by experienced lab personnel 5–8 d postmortem. One copy of the F94L allele did not affect gestation length, birth weight, percentage of unassisted births, feedlot average daily gain, live weight at harvest, hot carcass weight, or dressing percentage (P > 0.05). Muscle fiber analysis indicated that the increase in muscularity by the F94L allele in the semitendinosus and longissimus was likely due to hyperplasia as there was a 19% increase in the quantity of myosin heavy chain type IIA and IIX fibers in the semitendinosus (P 0.05). Carcasses from steers with one F94L allele had larger ribeye areas (99.2 vs. 92.3 sq.cm.), greater ribeye width:length ratios (0.498 vs. 0.479), lower USDA yield grades (2.21 vs. 2.66), and lower marbling scores (438 vs. 480) (P < 0.05). Additionally, for boxed beef yields, one F94L allele, vs. zero F94L alleles, increased (P < 0.05) 85/15 trimmings (+0.59%), top round (+0.28%), strip loin (+0.12%), eye round (+0.11%), tenderloin (+0.07%), boneless foreshank (+0.07%), cap/wedge (+0.06%), and tri-tip (+0.04%). Overall, carcasses from steers with one F94L allele had a greater boxed beef yield (+1.06%), boxed beef plus 85/15 trimmings yield (+1.65%), and total retail cuts plus ground beef 85/15 yield (+1.78%) than carcasses from steers with zero F94L alleles (P < 0.05). One copy of the F94L allele utilized in beef-on-dairy breeding system had no significant impact on live performance traits but resulted in lower marbling scores and increased muscularity as evidenced through larger, more beef-shaped ribeyes, lower USDA yield grades, and greater carcass cutout yields (both boxed beef and retail yields).National Cattlemen’s Beef Association12 month embargo; first published 26 September 2023This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
A Research Communication Brief: Gluten Analysis in Beef Samples Collected Using a Rigorous, Nationally Representative Sampling Protocol Confirms That Grain-Finished Beef Is Naturally Gluten-Free
Knowing whether or not a food contains gluten is vital for the growing number of individuals with celiac disease and non-celiac gluten sensitivity. Questions have recently been raised about whether beef from conventionally-raised, grain-finished cattle may contain gluten. To date, basic principles of ruminant digestion have been cited in support of the prevailing expert opinion that beef is inherently gluten-free. For this study, gluten analysis was conducted in beef samples collected using a rigorous nationally representative sampling protocol to determine whether gluten was present. The findings of our research uphold the understanding of the principles of gluten digestion in beef cattle and corroborate recommendations that recognize beef as a naturally gluten-free food
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Effects of Ceftiofur and Chlortetracycline on the Resistomes of Feedlot Cattle.
Treatment of food-producing animals with antimicrobial drugs (AMD) is controversial because of concerns regarding promotion of antimicrobial resistance (AMR). To investigate this concern, resistance genes in metagenomic bovine fecal samples during a clinical trial were analyzed to assess the impacts of treatment on beef feedlot cattle resistomes. Four groups of cattle were exposed, using a 2-by-2 factorial design, to different regimens of antimicrobial treatment. Injections of ceftiofur crystalline-free acid (a third-generation cephalosporin) were used to treat all cattle in treatment pens or only a single animal, and either chlortetracycline was included in the feed of all cattle in a pen or the feed was untreated. On days 0 and 26, respectively, pre- and posttrial fecal samples were collected, and resistance genes were characterized using shotgun metagenomics. Treatment with ceftiofur was not associated with changes to β-lactam resistance genes. However, cattle fed chlortetracycline had a significant increase in relative abundance of tetracycline resistance genes. There was also an increase of an AMR class not administered during the study, which is a possible indicator of coselection of resistance genes. Samples analyzed in this study had previously been evaluated by culture characterization (Escherichia coli and Salmonella) and quantitative PCR (qPCR) of metagenomic fecal DNA, which allowed comparison of results with this study. In the majority of samples, genes that were selectively enriched through culture and qPCR were not identified through shotgun metagenomic sequencing in this study, suggesting that changes previously documented did not reflect changes affecting the majority of bacterial genetic elements found in the predominant fecal resistome.IMPORTANCE Despite significant concerns about public health implications of AMR in relation to use of AMD in food animals, there are many unknowns about the long- and short-term impact of common uses of AMD for treatment, control, and prevention of disease. Additionally, questions commonly arise regarding how to best measure and quantify AMR genes in relation to public health risks and how to determine which genes are most important. These data provide an introductory view of the utility of using shotgun metagenomic sequencing data as an outcome for clinical trials evaluating the impact of using AMD in food animals
Comparison of Machine Learning Algorithms for Predictive Modeling of Beef Attributes Using Rapid Evaporative Ionization Mass Spectrometry (REIMS) Data
Abstract Ambient mass spectrometry is an analytical approach that enables ionization of molecules under open-air conditions with no sample preparation and very fast sampling times. Rapid evaporative ionization mass spectrometry (REIMS) is a relatively new type of ambient mass spectrometry that has demonstrated applications in both human health and food science. Here, we present an evaluation of REIMS as a tool to generate molecular scale information as an objective measure for the assessment of beef quality attributes. Eight different machine learning algorithms were compared to generate predictive models using REIMS data to classify beef quality attributes based on the United States Department of Agriculture (USDA) quality grade, production background, breed type and muscle tenderness. The results revealed that the optimal machine learning algorithm, as assessed by predictive accuracy, was different depending on the classification problem, suggesting that a “one size fits all” approach to developing predictive models from REIMS data is not appropriate. The highest performing models for each classification achieved prediction accuracies between 81.5–99%, indicating the potential of the approach to complement current methods for classifying quality attributes in beef
Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain
Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica, Listeria monocytogenes, Escherichia coli, Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni, C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica, E. coli, and C. botulinum were greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes
Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain.
Foodborne illnesses associated with pathogenic bacteria are a global public health and economic challenge. The diversity of microorganisms (pathogenic and nonpathogenic) that exists within the food and meat industries complicates efforts to understand pathogen ecology. Further, little is known about the interaction of pathogens within the microbiome throughout the meat production chain. Here, a metagenomic approach and shotgun sequencing technology were used as tools to detect pathogenic bacteria in environmental samples collected from the same groups of cattle at different longitudinal processing steps of the beef production chain: cattle entry to feedlot, exit from feedlot, cattle transport trucks, abattoir holding pens, and the end of the fabrication system. The log read counts classified as pathogens per million reads for Salmonella enterica,Listeria monocytogenes,Escherichia coli,Staphylococcus aureus, Clostridium spp. (C. botulinum and C. perfringens), and Campylobacter spp. (C. jejuni,C. coli, and C. fetus) decreased over subsequential processing steps. Furthermore, the normalized read counts for S. enterica,E. coli, and C. botulinumwere greater in the final product than at the feedlots, indicating that the proportion of these bacteria increased (the effect on absolute numbers was unknown) within the remaining microbiome. From an ecological perspective, data indicated that shotgun metagenomics can be used to evaluate not only the microbiome but also shifts in pathogen populations during beef production. Nonetheless, there were several challenges in this analysis approach, one of the main ones being the identification of the specific pathogen from which the sequence reads originated, which makes this approach impractical for use in pathogen identification for regulatory and confirmation purposes