Interbreed Matings in Dairy Cattle. II. Herd Health and Viability

The periparturient period, typically defined as the period immediately before and after calving, is a challenging time for dairy cattle that must cope with physiological, metabolic and endocrine changes, as well as a variety of environmental and management-related stressors. These challenges likely contribute to the high incidence of disease observed during the weeks following parturition. Changes in behaviour during the period around parturition can be used to identify animals that are ill or at risk of disease. The aim of this review is to summarise current knowledge on the behavioural changes of dairy cattle during the periparturient period and how these changes relate to illness. We provide an overview of the concept of sickness behaviour and describe the normal changes in feeding behaviour, social behaviour, and resting behaviour around parturition and how these behaviours differ between animals that become ill after parturition and those that remain healthy. We also review the literature on behavioural responses to common farm management practices around parturition drawing on examples related to early cow–calf separation, space restriction, social re-grouping, and housing conditions. This review focuses primarily on indoor group-housed dairy cattle as the majority of research has been focussed in this area; however, literature related to pasture-based dairy production, other farm animal species, and rodents is also discussed. Reduced feeding time and intake, increased standing time, restlessness, and a reluctance or inability to successfully compete for access to important resources are examples of the behavioural changes that have been associated with illness after calving. Using behaviour to identify sick cattle and those at increased risk of becoming ill will facilitate prompt treatment and provide opportunities to identify management changes that prevent disease, improving overall herd health and animal welfare.

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A large-scale study of indicators of sub-clinical mastitis in dairy cattle by attribute weighting analysis of milk composition features: highlighting the predictive power of lactose and electrical conductivity

Journal of Dairy Research ◽

10.1017/s0022029918000249 ◽

2018 ◽

Vol 85 (2) ◽

pp. 193-200 ◽

Cited By ~ 13

Author(s):

Esmaeil Ebrahimie ◽

Faezeh Ebrahimi ◽

Mansour Ebrahimi ◽

Sarah Tomlinson ◽

Kiro R Petrovski

Keyword(s):

Electrical Conductivity ◽

Dairy Cattle ◽

Large Scale ◽

Economic Loss ◽

Milk Composition ◽

Clinical Mastitis ◽

Important Variable ◽

Herd Health ◽

Attribute Weighting ◽

Lactose Concentration

Sub-clinical mastitis (SCM) affects milk composition. In this study, we hypothesise that large-scale mining of milk composition features by pattern recognition models can identify the best predictors of SCM within the milk composition features. To this end, using data mining algorithms, we conducted a large-scale and longitudinal study to evaluate the ability of various milk production parameters as indicators of SCM. SCM is the most prevalent disease of dairy cattle, causing substantial economic loss for the dairy industry. Developing new techniques to diagnose SCM in its early stages improves herd health and is of great importance. Test-day Somatic Cell Count (SCC) is the most common indicator of SCM and the primary mastitis surveillance approach worldwide. However, test-day SCC fluctuates widely between days, causing major concerns for its reliability. Consequently, there would be great benefit to identifying additional efficient indicators from large-scale and longitudinal studies. With this intent, data was collected at every milking (twice per day) for a period of 2 months from a single farm using in-line electronic equipment (346 248 records in total). The following data were analysed: milk volume, protein concentration, lactose concentration, electrical conductivity (EC), milking time and peak flow. Three SCC cut-offs were used to estimate the prevalence of SCM: Australian ≥ 250 000 cells/ml, European ≥200 000 cells/ml and New Zealand ≥ 150 000 cells/ml. At first, 10 different Attribute Weighting Algorithms (AWM) were applied to the data. In the absence of SCC, lactose concentration featured as the most important variable, followed by EC. For the first time, using attribute weighted modelling, we showed that the concentration of lactose in milk can be used as a strong indicator of SCM. The development of machine-learning expert systems using two or more milk variables (such as lactose concentration and EC) may produce a predictive pattern for early SCM detection.

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Haematological profile of crossbred dairy cattle to monitor herd health status at medium elevation in Central Himalayas

Research in Veterinary Science ◽

10.1053/rvsc.2000.0400 ◽

2000 ◽

Vol 69 (2) ◽

pp. 141-145 ◽

Cited By ~ 10

Author(s):

B KUMAR ◽

S.P PACHAURI

Keyword(s):

Health Status ◽

Dairy Cattle ◽

Herd Health ◽

Central Himalayas ◽

Haematological Profile ◽

Crossbred Dairy Cattle

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Efficacy of Homeopathic Herd Health Management in Antibiotic Resistant Dairy Cattle in Northern Spain

10.1055/s-0040-1702105 ◽

2020 ◽

Author(s):

María Fernandez Portales

Keyword(s):

Dairy Cattle ◽

Health Management ◽

Herd Health ◽

Northern Spain ◽

Antibiotic Resistant

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Prevalence of Methicillin Resistant Staphylococcus aureus (MRSA) in Cattle Milk from dairy Herds in Oyo State, Nigeria

Journal of Veterinary and Biomedical Sciences ◽

10.36108/jvbs/9102.20.0280 ◽

2020 ◽

Vol 2 (2) ◽

Author(s):

O. O Oludairo

Keyword(s):

Staphylococcus Aureus ◽

Dairy Cattle ◽

Methicillin Resistant Staphylococcus Aureus ◽

Dairy Herd ◽

Diffusion Method ◽

Herd Health ◽

Biochemical Tests ◽

Disk Diffusion Method ◽

Methicillin Resistant ◽

Milk Samples

Methicillin-resistant Staphylococcus aureus (MRSA) has received a lot of attention in recent years as a zoonotic organism of global concern. Contaminated milk, especially those from mastitic cows, serve as reservoirs for humans in the epidemiology of antibiotic resistant MRSA. This study was designed to determine the level of contamination of bulk fresh milk from dairy cattle herds with MRSA in Ibarapa, Oyo and Oke-Ogun areas of Oyo State and the antibiotic resistance profile of the isolates. One hundred and sixty-five (165) milk samples were obtained from the study areas and used for the study. Staphylococcus aureus was isolated from the samples using bacterial culture and biochemical tests. Methicillin-resistant Staphylococcus aureus was identified using cefoxitin disk diffusion method. All the S. aureus isolates were subjected to microbial susceptibility test. Ninety (54.5%) milk samples were positive for Staphylococcus spp. out of which 52 (31.5%) were Staphylococcus aureus and 13 (7.9%) yielded MRSA. Antibiogram of S. aureus indicated highest resistance to Cloxacillin (88.5%) followed by (Augmentin 67.3%) and Ceftrazidine (67.3%). Ten out of the 13 MRSA isolates were multidrug resistance while all the isolates were 100% susceptible to ofloxacin. The results of this study showed that milk produced from dairy cattle in Oyo State was contaminated with MRSA. This portends serious food safety and public health risk among the consumers of such milk especially in raw or improperly pasteurized form. Proper dairy herd health management and prudent use of antibiotics and hygienic milking procedures are hereby recommended to prevent contamination of milk and subsequent spread of the organism to humans.

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Antimicrobial Usage for the Management of Mastitis in the USA: Impacts on Antimicrobial Resistance and Potential Alternative Approaches

10.5772/intechopen.101533 ◽

2021 ◽

Author(s):

Benti D. Gelalcha ◽

Getahun E. Agga ◽

Oudessa Kerro Dego

Keyword(s):

Antimicrobial Resistance ◽

Dairy Cattle ◽

Health Management ◽

Dairy Farms ◽

Raw Milk ◽

Herd Health ◽

Antimicrobial Usage ◽

Dry Cow Therapy ◽

Run Off ◽

The Usa

Mastitis is the most frequently diagnosed disease of dairy cattle responsible for the reduction in milk quantity and quality and major economic losses. Dairy farmers use antibiotics for the prevention and treatment of mastitis. Frequent antimicrobial usage (AMU) undeniably increased antimicrobial resistance (AMR) in bacteria from dairy farms. Antimicrobial-resistant bacteria (ARB) from dairy farms can spread to humans directly through contact with carrier animals or indirectly through the consumption of raw milk or undercooked meat from culled dairy cows. Indirect spread from dairy farms to humans can also be through dairy manure fertilized vegetables or run-off waters from dairy farms to the environment. The most frequently used antibiotics in dairy farms are medically important and high-priority classes of antibiotics. As a result, dairy farms are considered one of the potential reservoirs of ARB and antimicrobial resistance genes (ARGs). To mitigate the rise of ARB in dairy farms, reducing AMU by adopting one or more of alternative disease control methods such as good herd health management, selective dry-cow therapy, probiotics, and others is critically important. This chapter is a concise review of the effects of antimicrobials usage to control mastitis in dairy cattle farms and its potential impact on human health.

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