Oral hydration therapy with water and bovine respiratory disease incidence affects rumination behavior, rumen pH, and rumen temperature in high-risk, newly received beef calves

The welfare of ill and injured feedlot cattle: a review of the literature and implications for managing feedlot hospital and chronic pens

By definition, ill and injured animals are on the negative valence of animal welfare. For beef cattle kept in feedlot settings, advances in cattle health management have resulted in a greater understanding and prevention of illness and injury. However, the management of cattle once they become ill and injured is an understudied area, and there are gaps in knowledge that could inform evidence-based decision-making and strengthen welfare for this population. The aim of this review is to provide a comprehensive overview of the acquired knowledge regarding ill and injured feedlot cattle welfare, focusing on existing knowledge gaps and implications for hospital and chronic pen management and welfare assurance. Ill and injured feedlot cattle consist of acutely impaired animals with short-term health conditions that resolve with treatment and chronically impaired animals with long-term health conditions that may be difficult to treat. A literature search identified 110 articles that mentioned welfare and ill and injured feedlot cattle, but the population of interest in most of these articles was healthy cattle, not ill and injured cattle. Articles about managing ill and injured cattle in specialized hospital (n = 12) or chronic (n = 2) pens were even more sparse. Results from this literature search will be used to outline the understanding of acutely and chronically ill and injured feedlot cattle, including common dispositions and welfare considerations, behavior during convalescence, and strategies for identifying and managing ill and injured cattle. Finally, by working through specific ailments common in commercial feedlot environments, we illustrate how the Five Domains Model can be used to explore feelings and experiences and subsequent welfare state of individual ill or injured feedlot cattle. Using this approach and our knowledge of current industry practices, we identify relevant animal-based outcomes and critical research questions to strengthen knowledge in this area. A better understanding of this overlooked topic will inform future research and the development of evidence-based guidelines to help producers care for this vulnerable population.

Intensive feeding alters the rumen microbiota and its fermentation parameters in natural grazing yaks

Introduction

Amidst the challenging environmental conditions characterized by low oxygen levels and cold temperatures on the plateau, alterations in nutrient supply emerge as pivotal factors influencing the survival and reproduction of yaks. Intensive feeding stands out as a substantial mechanism for nutrient provision, initiating discernible changes in the host's rumen flora. Within the extreme natural conditions prevailing in the plateau area of northwest Yunnan, China, there exists a con-strained comprehension of the variations in rumen microflora, fermentation parameters, and growth responses exhibited by yaks subjected to intensive feeding.

Methods

This study employs 16S rRNA and ITS sequencing methods to scrutinize the rumen flora of yaks engaged in both natural grazing (G) and intensive feeding (F) on the plateau.

Results

The outcomes unveil that, during the severe winter season, yaks adeptly modulate the abundance and diversity of rumen flora in response to dietary modifications under intensive feeding, aiming to optimize the efficient utilization of dietary fiber and energy. Principal Coordinate Analysis (PCoA) illustrates a substantial alteration in the rumen microbial community of naturally grazing yaks when exposed to intensive feeding. The natural grazing group manifests a higher prevalence of Firmicutes and Bacteroidetes, while the intensive feeding group exhibits heightened levels of Prevotella in the rumen. The Rikenellaceae _ RC9 _ gut_ group, associated with mycobacteria, prevails more abundantly in the natural grazing setting. PICRUSt2 analysis indicates that intensive feeding induces bacterial gene overexpression linked to protein metabolism. Rumen fungi showcase heightened diversity under intensification. Intensive feeding results in an augmented abundance of non-fiber-degrading bacteria and semi-fiber-degrading bacteria, accompanied by elevated concentrations of Volatile Fatty Acids (VFA).

Discussion

These findings yield novel insights into the shifts in the rumen microflora of yaks acclimated to intensive feeding in high-altitude environments, provide an important reference for the nutritional regulation of supplemental feeding of natural grazing yaks in the cold season, ultimately contributing to their enhanced growth.

Literature Review on Technological Applications to Monitor and Evaluate Calves' Health and Welfare

Precision livestock farming (PLF) research is rapidly increasing and has improved farmers' quality of life, animal welfare, and production efficiency. PLF research in dairy calves is still relatively recent but has grown in the last few years. Automatic milk feeding systems (AMFS) and 3D accelerometers have been the most extensively used technologies in dairy calves. However, other technologies have been emerging in dairy calves' research, such as infrared thermography (IRT), 3D cameras, ruminal bolus, and sound analysis systems, which have not been properly validated and reviewed in the scientific literature. Thus, with this review, we aimed to analyse the state-of-the-art of technological applications in calves, focusing on dairy calves. Most of the research is focused on technology to detect and predict calves' health problems and monitor pain indicators. Feeding and lying behaviours have sometimes been associated with health and welfare levels. However, a consensus opinion is still unclear since other factors, such as milk allowance, can affect these behaviours differently. Research that employed a multi-technology approach showed better results than research focusing on only a single technique. Integrating and automating different technologies with machine learning algorithms can offer more scientific knowledge and potentially help the farmers improve calves' health, performance, and welfare, if commercial applications are available, which, from the authors' knowledge, are not at the moment.

Technological Tools for the Early Detection of Bovine Respiratory Disease in Farms

Simple Summary

The inclusion of remote automatic systems that use continuous learning technology are of great interest in precision livestock cattle farming, since the average size of farms is increasing while time for individual observation is decreasing. Bovine respiratory disease is a main concern in both fattening and heifer rearing farms due to its impact on antibiotic use, loss of performance, mortality, and animal welfare. Much scientific literature has been published regarding technologies for continuous learning and monitoring of cattle’s behavior and accurate correlation with health status, including early detection of bovine respiratory disease. This review summarizes the up-to-date technologies for early diagnosis of bovine respiratory disease and discusses their advantages and disadvantages under practical conditions.

Abstract

Classically, the diagnosis of respiratory disease in cattle has been based on observation of clinical signs and the behavior of the animals, but this technique can be subjective, time-consuming and labor intensive. It also requires proper training of staff and lacks sensitivity (Se) and specificity (Sp). Furthermore, respiratory disease is diagnosed too late, when the animal already has severe lesions. A total of 104 papers were included in this review. The use of new advanced technologies that allow early diagnosis of diseases using real-time data analysis may be the future of cattle farms. These technologies allow continuous, remote, and objective assessment of animal behavior and diagnosis of bovine respiratory disease with improved Se and Sp. The most commonly used behavioral variables are eating behavior and physical activity. Diagnosis of bovine respiratory disease may experience a significant change with the help of big data combined with machine learning, and may even integrate metabolomics as disease markers. Advanced technologies should not be a substitute for practitioners, farmers or technicians, but could help achieve a much more accurate and earlier diagnosis of respiratory disease and, therefore, reduce the use of antibiotics, increase animal welfare and sustainability of livestock farms. This review aims to familiarize practitioners and farmers with the advantages and disadvantages of the advanced technological diagnostic tools for bovine respiratory disease and introduce recent clinical applications.

Effects of high concentrate rations on ruminal fermentation and microbiota of yaks

Ruminal microflora is closely correlated with the ruminant’s diet. However, information regarding the effect of high concentrate diets on rumen microflora in yaks is lacking. In the current study, 24 healthy male yaks were randomly assigned to two groups, each fed with different diets: less concentrate (LC; concentrate: coarse = 40: 60) and high concentrate (HC; concentrate: coarse = 80: 20) diets. Subsequently, a 21-day feeding trial was performed with the yaks, and rumen fluid samples were collected and compared using 16 s rRNA sequencing. The results showed that NH3-N, total VFA, acetate, butyrate, isobutyrate, and isovalerate were significantly higher in the HC group than that in the LC group (p < 0.05), while microbial diversity and richness were significantly lower in the HC group (p < 0.05). Principal coordinate analysis indicated that rumen microflora was significantly different in LC and HC groups (p < 0.05). In the rumen, phyla Firmicutes and Bacteroidota were the most abundant bacteria, with Firmicutes being more abundant, and Bacteroidota being less abundant in the HC group than those found in the LC group. Christensenellaceae_R-7_group and Prevotella are the highest abundant ones at the genus level. The relative abundance of Acetitomaculum, Ruminococcus, and Candidatus_Saccharimonas were significantly higher in the HC group than that in the LC group (p < 0.05), while the relative abundance of Olsenella was significantly lower in the HC group than in the LC group (p < 0.05). Compared to the LC group, the relative abundance of Prevotella, Ruminococcus, and Candidatus_Saccharimonas was significantly higher in the HC group. The relative abundances of Prevotella, Prevotellaceae_UCG-003, Olsenella, Ruminococcus, Acetitomaculum, Candidatus_Saccharimonas, and NK4A214_group were correlated with ruminal fermentation parameters (p < 0.05). Furthermore, PICRUSt 2 estimation indicated that microbial genes associated with valine, leucine, and isoleucine biosynthesis were overexpressed in the rumen microflora of yaks in the HC group (p < 0.05). Conclusively, our results suggest that high concentrate diets affect the microflora composition and fermentation function in yak rumen. The present findings would provide new insights into the health of yaks under high concentrate feeding conditions and serve as a potent reference for the short-term fattening processes of yaks.

Dietary forage to concentrate ratios impact on yak ruminal microbiota and metabolites

To improve the rumen fermentation function and growth performance of yaks (Bos grunniens), better understanding of the effect of different dietary forage to concentrate ratios on rumen microbiota and metabolites is needed. In the present study, three diets with different dietary forage to concentrate ratios (50:50, 65:35, and 80:20) were fed to 36 housed male yaks. The changes in the distribution of rumen microorganisms and metabolites and the interactions between them were studied by 16S rRNA gene sequencing and liquid chromatography-mass spectrometry (LC–MS). The diversity and richness of microorganisms in the rumen varied according to diet. The most abundant phyla were Firmicutes and Bacteroidetes. Firmicutes was the most abundant in the C50 group, and the relative abundance of Bacteroidetes was significantly lower in the C65 group than in the C80 group (p < 0.05). The Christensenellaceae_R-7_group, Rikenellaceae_RC9_gut_group, and Methanobrevibacter had the highest relative abundances at the genus level. Among them, Christensenellace_R-7_group had the highest relative abundance in the C50 group. The Rikenellaceae_RC9_gut_group was significantly abundant in the C80 group compared with the C50 group. The Methanobrevibacter content was higher in the C65 group than in the other two groups. Both the concentration and metabolic pathways of rumen metabolites were influenced by the dietary concentrate ratio; lipids, lipid-like molecules, organic acid metabolites, and organic oxide-related metabolites differed between the groups. Significant changes were found for six metabolic pathways, including arginine and proline metabolism; glycine, serine, and threonine metabolism; glyoxylate and dicarboxylate metabolism; arginine biosynthesis; glycerophospholipid metabolism; glycerolipid metabolism; and nitrogen metabolism.

Early Detection of Respiratory Diseases in Calves by Use of an Ear-Attached Accelerometer

Simple Summary

Bovine respiratory disease is one of the most important diseases in group-housed calves worldwide, with impacts on calf welfare and farm economics. Early detection of the disease is important for the well-being of the animals and a targeted treatment. Therefore, tools for an automated monitoring of individual calves would be a breakthrough in health management. In this study, we used an ear-attached accelerometer to evaluate its potential for the early detection of behavioral changes related to respiratory disease in calves. Our result showed that accelerometers are able to detect changes in activity and lying times that can be used to predict respiratory disease before clinical diagnosis.

Abstract

Accelerometers (ACL) can identify behavioral and activity changes in calves. In the present study, we examined the association between bovine respiratory disease (BRD) and behavioral changes detected by an ear-tag based ACL system in weaned dairy calves. Accelerometer data were analyzed from 7 d before to 1 d after clinical diagnosis of BRD. All calves in the study (n = 508) were checked daily by an adapted University of Wisconsin Calf Scoring System. Calves with a score ≥ 4 and fever for at least two consecutive days were categorized as diseased (DIS). The day of clinical diagnosis of BRD was defined as d 0. The data analysis showed a significant difference in high active times between DIS and healthy control calves (CON), with CON showing more high active times on every day, except d −3. Diseased calves showed significantly more inactive times on d −4, −2, and 0, as well as longer lying times on d −5, −2, and +1. These results indicate the potential of the ACL to detect BRD prior to a clinical diagnosis in group-housed calves. Furthermore, in this study, we described the ‘normal’ behavior in 428 clinically healthy weaned dairy calves obtained by the ACL system.

Assessment of diagnostic accuracy of biomarkers to assess lung consolidation in calves with induced bacterial pneumonia using receiver operating characteristic (ROC) curves

Bovine respiratory disease (BRD) is the most economically significant disease for cattle producers in the U.S. Cattle with advanced lung lesions at harvest have reduced average daily gain, yield grades and carcass quality outcomes. The identification of biomarkers and clinical signs that accurately predict lung lesions could benefit livestock producers in determining a BRD prognosis. Receiver operating characteristic (ROC) curves are graphical plots that illustrate the diagnostic ability of a biomarker or clinical sign. Previously we used the area under the ROC curve (AUC) to identify cortisol, hair cortisol and infrared thermography imaging as having acceptable (AUC > 0.7) diagnostic accuracy for detecting pain in cattle. Herein, we used ROC curves to assess the sensitivity and specificity of biomarkers and clinical signs associated with lung lesions after experimentally induced bovine respiratory disease (BRD). We hypothesized pain biomarkers and clinical signs assessed at specific timepoints after induction of BRD could be used to predict lung consolidation at necropsy. Lung consolidation of >10% was retrospectively assigned at necropsy as a true positive indicator of BRD. Calves with a score of <10% were considered negative for BRD. The biomarkers and clinical signs analyzed were serum cortisol; infrared thermography (IRT); mechanical nociceptive threshold (MNT); substance P; kinematic gait analysis; a visual analog scale (VAS); clinical illness score (CIS); computerized lung score (CLS); average activity levels; prostaglandin E2 metabolite (PGEM); serum amyloid A and rectal temperature. A total of 5,122 biomarkers and clinical signs were collected from 26 calves, eighteen of which were inoculated with M. haemolytica. All statistics were performed using JMP Pro 14.0. Results comparing calves with significant lung lesions to those without yielded the best diagnostic accuracy (AUC > 0.75) for right front stride length at 0 h; gait velocity at 32 h; VAS, CIS, average activity and rumination levels, step count and rectal temperature, all at 48 h; PGEM at 72 h; gait distance at 120 h; cortisol at 168 h; and IRT, right front force and serum amyloid A, all at 192 h. These results show ROC analysis can be a useful indicator of the predictive value of pain biomarkers and clinical signs in cattle with induced bacterial pneumonia. AUC values for VAS score, average activity levels, step count, and rectal temperature seemed to yield good diagnostic accuracy (AUC > 0.75) at multiple timepoints while MNT values, substance P concentrations, and CLS did not (all AUC values < 0.75).

Behavior assessment and applications for BRD diagnosis: beef

Assessment of behavior is a longstanding strategy to assist the diagnosis of clinical bovine respiratory disease (BRD) in beef cattle. Cattle with systemic inflammation caused by infectious pathogen(s) display predictable behavioral adaptations compared to healthy cohorts. Behavioral alterations in BRD-affected cattle include lethargy, social isolation, and anorexia. However, behavior assessment to support BRD case definition in the production setting is challenging because: (1) other bovine diseases cause behavior alterations similar to BRD; (2) cattle have inherent prey instinct to disguise sickness behavior during human evaluation; (3) labor constraints dictate very brief observation of animal behavior; and (4) traditional behavior assessment is subjective and agreement is often poor. Some of these challenges may be overcome with the use of advanced technologies that allow continuous, remote, and objective behavior assessment of individual cattle. Automated methodologies for behavior assessment include three-axis accelerometers that quantify physical behaviors, systems that document feeding/watering behavior, and triangulation systems that document spatial behavior. Each of these behavior-monitoring approaches generates unique information and may facilitate early detection of BRD compared to traditional methods. Nevertheless, adoption of behavior assessment technologies for BRD diagnosis in beef operations hinges upon improved detection, positive return on investment, and successful integration within existing BRD management practices.

Details to Attend to When Managing High-Risk Cattle

This article provides insights into the management of bovine respiratory disease in high-risk cattle populations. Biocontainment strategies, records, procurement, transport, arrival/receiving management, vaccination, and treatment protocols are discussed from practical and systems-thinking perspectives regarding their impact on health in high-risk cattle. Arrival management considerations, such as facilities, nutritional management, metaphylaxis, bovine viral diarrhea virus persistent infection testing, parasite control, and castration, are also addressed. Caretaker morale and job satisfaction are suggested as important factors to consider when managing high-risk cattle. The inter-relationships of variables within the system are explored as contributing causative factors to bovine respiratory disease in high-risk cattle.