A three-year comparison of once-a-day and twice-a-day milking in seasonal-calving pasture-based systems

Globally, the majority of dairy cows are milked twice a day (TAD); however, in pasture-based production systems, such as in Ireland, the idea of milking once a day (OAD) is being considered for reasons such as improved work-life balance. The immediate effects within a lactation, as well as the multilactation consequences of OAD, compared with TAD milking, require understanding. The objective of this randomized experiment was to compare OAD and TAD milking, over a 3-yr period, by examining the differences in milk production and composition, body weight (BW), body condition score (BCS), dry matter intake (DMI), udder characteristics, locomotion score, and milking time. Over the 3-yr period, 83 cows were enrolled in the experiment; 32, 44, and 48 cows in yr 1, 2, and 3 of the experiment, respectively. Each year, 23% of the herds were primiparous animals, while the remainder were second lactation or greater in parity. All cows were milked in the morning at 0700 h; only cows milked TAD were milked a second time each day at 1600 h. Cows rotationally grazed pastures for the duration of the lactating period and were housed during the nonlactating period. Milking cows OAD reduced cumulative milk yield by 26%, and milk solids yield (kg of fat + kg of protein) by 21%, across the 3 yr of the experiment when compared with cows milked TAD which produced 4,126 and 365 kg/cow, respectively. A contributory factor to the reduced production was a shorter lactation length (9.7 d) of the cows milked OAD compared with TAD (294 d). Milk fat percent of cows milked TAD was similar for all 3 yr of the study (5.05%), whereas milk fat percent of the cows milked OAD increased year on year, with each year being greater than the previous year (5.02%, 5.32%, and 5.70% for yr 1, 2, and 3; respectively). Milk protein percent was greater (+0.19%) for cows milked OAD compared with TAD which was 3.78%. Compared with cows milked TAD, total DMI for cows milked OAD was 22% less at the start of lactation (<167 d), but as the lactation progressed (>167 d) we observed no difference in DMI between treatments. Similar to the literature, milking cows OAD significantly increased average somatic cell score, both during (+16%) and at the end of lactation (+19%), compared with milking cows TAD which were 4.69 and 4.79, respectively. We detected positive aspects associated with OAD milking such as greater BW, BCS, and fertility performance. Milking OAD reduced both milking time per cow per day (reductions ranged from 34% in the first 4 mo of lactation to 43% during mo 5-9 of lactation) and milking time per liter of milk (-3.5 s/L) throughout lactation, leading to less labor inputs on-farm which can have positive implications for farmer work-life balance. The significant time saving and potential savings in costs (e.g., electricity) need to be considered in conjunction with the milk production reduction when considering OAD milking for the entire lactation.

Temporal profiles describing markers of inflammation and metabolism during the transition period of pasture-based, seasonal-calving dairy cows

The physiology of the dairy cow while transitioning from pregnancy to lactation is complex, with multifactorial processes studied extensively for the role they play in manifestation of disease along with associated economic losses and compromised animal welfare. Manuscripts outlining associations among nutrition, production, physiology, and genetics variables and transition cow disorders are common in literature, with blood analytes that are central to energy metabolism (e.g., nonesterified fatty acids; NEFA, β-hydroxybutyrate; BHB) often reported. Immunity and inflammation have increasingly been explored in the pathogenesis and persistence of disorders, with cytokines and acute phase proteins well documented. However, most of these studies have involved cows fed total mixed rations, which may not always reflect profiles of blood analytes and other physiological indicators of transition cow health in grazing cows consuming fresh pasture. Considering the comparatively lesser characterization of these analytes and markers in pasture-based, seasonal-calving dairy cows, we compiled a database consisting of 2,610 cow lactations that span 20 yr of transition cow research in New Zealand. Using this database, analyte profiles from approximately 28 d precalving to 35 d postcalving were identified in dairy cows with a range of genetics, milk production potentials, and pasture-based farm management systems. These profiles characterize changes in energy reserves and metabolism (NEFA, BHB, glucose, insulin, growth hormone, insulin-like growth factor-1, leptin, body condition score, body weight), liver function (globulin, aspartate aminotransferase, glutamate dehydrogenase, gamma-glutamyl transpeptidase, bilirubin, cholesterol, liver triacylglycerides), protein metabolism (albumin, total protein, albumin:globulin ratio, creatinine, urea, creatine kinase), mineral balance (calcium, magnesium, phosphate, potassium, sodium, chloride, bicarbonate), inflammation (IL-1β, IL-6, haptoglobin, reactive oxygen species, total antioxidant capacity), and uterine health (polymorphonuclear cells, macrophage cells, vaginal discharge score). Temporal changes are generally consistent with previously characterized homeorhetic changes experienced by the dairy cow during the transition from pregnancy to lactation in both pastoral and housed systems. Some of the profiles had not previously been presented for pastoral systems, or in some cases, presented for either system. Our results indicate that moderate-yielding dairy cows undergo similar homeorhetic changes to high-yielding housed cows; however, differences in diet composition result in greater BHB concentrations than expected, based on their milk production and NEFA concentrations. In addition, most cows were able to transition to a state of higher energy requirement following calving, albeit with an increased metabolic challenge in the liver, and only a small percentage of cows were classified with severe hepatic lipidosis or severe hyperketonemia. Increases in metabolic function of the liver were accompanied by changes in indicators of the immune system and changes in mineral balance that, combined, probably reflect the innate response to the transition from gestation to lactation.

Physiologically based modelling of the pharmacokinetics of three beta-lactam antibiotics after intra-mammary administration in dairy cows

Understanding the pharmacokinetics of intra-mammary antibiotics is important for the prediction of drug residues in milk and for the design of optimal dosage regimens. Unfortunately, compartmental pharmacokinetic models are not valid for this unique system. A minimal physiologically based pharmacokinetic model is presented incorporating the physiology of milk secretion, drug administration at the quarter level, drug absorption and dispersion, drug retention during the inter-milking interval and episodic drug elimination at milking. The primary objective of the study was the development and exploration of a model for major factors controlling drug concentration in milk, rather than generation of rigorously predictive pharmaco-statistical models for any particular drug. This model was implemented in a two-stage approach, using published concentration data for penicillin, cefuroxime, cephapirin and desacetyl-cephapirin in milk of healthy cows. Model simulations evaluated sensitivity and developed predictions of drug residues. The model successfully predicted both drug concentrations and drug residues in milk. The postmilking residual milk volume did not adequately explain antibiotic pharmacokinetics, requiring additional considerations for drug retention. Local sensitivity analysis indicated that increasing the number of quarters treated, the dosage, or the duration of the inter-milking interval prolonged both the persistence of drug residues and the duration that antibiotic concentration exceeded typical minimum inhibitory concentrations. The model was flexible across different beta-lactam drugs as a general description of intra-mammary pharmacokinetics. This model is suitable for the design and analysis of dosage regimens, and could be applied for the prediction of withholding periods when these antibiotic preparations are used off-label. The final model indicates that explicit consideration of the milking regimen is fundamental to the design and interpretation of pharmacokinetic studies of antibiotics in bovine milk.

A decision-support tool for autumn management in a spring-calving pasture-based dairy system

Success in a pasture-based dairy system relies on matching feed supply and feed demand in a profitable manner. Autumn is an important period for decision making to maximise current-season profitability, while ensuring key targets such as cow body condition score and the level of average pasture cover are met for the upcoming season. There are many tactical management strategies for farmers to consider during autumn to ensure that profitability is maximised in the current and next season (e.g. feeding crops, purchasing or using available supplementary feeds, reducing milking frequency, grazing off young stock, culling, or drying off cows). The complexity of trade-offs among these factors from January to calving, and the need to assess the impact of each of these on seasonal profitability led to the development of the ‘DairyNZ Autumn Management Resource’. This resource is an energy-based model that calculates the profit from different management strategies in pasture-based spring-calving systems. Feed demand is initially set to ensure that target body condition is achieved for the next season, and can then be altered using variables such as milking frequency, number of cows in milk and stock grazing on-farm. The assumption is made that energy supply comes from grazed pasture and crop first, followed by conserved forages, with the opportunity to fill remaining gaps with purchased feed. The model is a decision-support resource for farmers during the autumn that compares the economics of different management strategies in the current season, while ensuring that the performance in the next season is not compromised.