Updating test-day milk yield factors for use in genetic evaluations and dairy production systems: a comprehensive review

Various methods have been proposed to estimate daily yield from partial yields, primarily to deal with unequal milking intervals. This paper offers an exhaustive review of daily milk yields, the foundation of lactation records. Seminal advancements in the late 20th century concentrated on two main adjustment metrics: additive additive correction factors (ACF) and multiplicative correction factors (MCF). An ACF model provides additive adjustments to two times AM or PM milk yield, which then becomes the estimated daily yields, whereas an MCF is a ratio of daily yield to the yield from a single milking. Recent studies highlight the potential of alternative approaches, such as exponential regression and other nonlinear models. Biologically, milk secretion rates are not linear throughout the entire milking interval, influenced by the internal mammary gland pressure. Consequently, nonlinear models are appealing for estimating daily milk yields as well. MCFs and ACFs are typically determined for discrete milking interval classes. Nonetheless, large discrete intervals can introduce systematic biases. A universal solution for deriving continuous correction factors has been proposed, ensuring reduced bias and enhanced daily milk yield estimation accuracy. When leveraging test-day milk yields for genetic evaluations in dairy cattle, two predominant statistical models are employed: lactation and test-day yield models. A lactation model capitalizes on the high heritability of total lactation yields, aligning closely with dairy producers' needs because the total amount of milk production in a lactation directly determines farm revenue. However, a lactation yield model without harnessing all test-day records may ignore vital data about the shapes of lactation curves needed for informed breeding decisions. In contrast, a test-day model emphasizes individual test-day data, accommodating various intervals and recording plans and allowing the estimation of environmental effects on specific test days. In the United States, the patenting of test-day models in 1993 used to restrict the use of test-day models to regional and unofficial evaluations by the patent holders. Estimated test-day milk yields have been used as if they were accurate depictions of actual milk yields, neglecting possible estimation errors. Its potential consequences on subsequent genetic evaluations have not been sufficiently addressed. Moving forward, there are still numerous questions and challenges in this domain.

Behavior of Cows in the Lying Area When the Exit Gates in the Pens Are Opened: How Many Cows Are Forced to Get Up to Go to the Milking Parlor?

Equipping a farm with a milking parlor requires moving groups of cows from their pens to the part of the barn where milking takes place. The task of moving cows, carried out two or three times each day, shows links to the lying area of the barn. When the cows are taken from the pen to the milking parlor, some of them may be lying down, and this lying down must be interrupted. The forced standing up of cows can be considered in terms of their welfare. The aim of the study was to examine the number of cows lying in the stalls at the time of opening the exit gates in the pens in order to take the cows to the milking parlor. The study covered four pens, each with 12 cows. The behavior of the cows in the pens before morning and afternoon milking was recorded over 26 days. In the analysis, the dependent variable was the number of lying cows, and the independent variables were the time of milking and the level of sand in the lying stalls. The results of the study showed the significance of differences in the number of lying cows for stalls with a low and high level of sand, both in the case of morning and afternoon milking. Differences in the number of lying cows were also found when comparing the time before morning and afternoon milking. To compare the tendency of individual cows to lie down before going to milking, an index of forced standing up was proposed. The research conducted showed differences in the behavior of cows before leaving the pen to the milking parlor. The stage to reduce the forced standing up of cows is to equip the farm with an automatic milking system (AMS) instead of using a milking parlor. In barns with AMS, cows have full freedom to get up and approach the milking stall. The results of the observations are thus an additional argument confirming the benefits of using an automatic milking system, considered in terms of the welfare of dairy cows, regarding their lying down and getting up.

Investigating the effect of temporal, geographic, and management factors on US Holstein lactation curve parameters

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.

Impact of a Dietary Citrus Extract on the Behavior and Production of Lactating Dairy Cows Following Regrouping: A Preliminary Study

Exposure of lab animals, humans, and pigs to olfactory sensory feed additives may reduce response to stress and anxiety. The objective of this preliminary study was to determine if feeding a citrus-based olfactory sensory functional feed extract (derived from Citrus sinensis) reduces the negative impact of regrouping of lactating dairy cows. Thirty-two (parity = 2.0 ± 1.2; mean ± SD), mid-lactation Holstein dairy cows (169.8 ± 16.8 DIM) were enrolled as focal cows in this study and housed individually in a tie-stall facility where they were randomly assigned to 1 of 2 treatment diets: (1) control total mixed ration (TMR) (control; n = 16; primiparous = 7; multiparous = 9), or (2) control TMR with 4 g/d of citrus extract (CE) (Phodé, Terssac, France) (CE; n = 16; primiparous = 7; multiparous = 9). Cows were fed their experimental diets for 7 d in the tie-stall facility (baseline), then moved to 1 of 2 experimental free-stall pens (containing 29 other cows) for a period of 7 d, where they remained on the same treatment diet as before. Compared with their baseline, primiparous control cows had decreased rumination time on d 1 and 2, had decreased lying time on d 1, and tended to have decreased lying time on d 2 and 3 following regrouping. In contrast, primiparous cows fed the CE diet did not experience a change in rumination and lying time. Primiparous CE cows had greater feeding time on d 1 and tended to have greater feeding time on d 2 after regrouping compared to primiparous control cows. Primiparous control cows had greater idle standing time, as compared to the CE cows, across the 7 d after regrouping. Primiparous CE cows initiated less total competitive behavior after regrouping, but were also displaced more frequently from the feed bunk and from the free stalls on d 1 after regrouping, as compared to the primiparous control cows. For multiparous cows, CE supplementation was not consistently associated with any benefits to behavior or production after regrouping, possibly because these cows were more experienced with social stressors. Results indicate that feeding CE to mid-lactation naïve primiparous dairy cows may reduce the initiation of competitive interactions and lessen the reduction in rumination and lying time after regrouping. These results need to be verified in further studies where potential confounding effects (e.g., pen social dynamics, pen location) are minimized.

Invited review: Lying time and the welfare of dairy cows

Adequate time lying down is often considered an important aspect of dairy cow welfare. We examine what is known about cows' motivation to lie down and the consequences for health and other indicators of biological function when this behavior is thwarted. We review the environmental and animal-based factors that affect lying time in the context of animal welfare. Our objective is to review the research into the time that dairy cows spend lying down and to critically examine the evidence for the link with animal welfare. Cows can be highly motivated to lie down. They show rebound lying behavior after periods of forced standing and will sacrifice other activities, such as feeding, to lie down for an adequate amount of time. They will work, by pushing levers or weighted gates, to lie down and show possible indicators of frustration when lying behavior is thwarted. Some evidence suggests that risk of lameness is increased in environments that provide unfavorable conditions for cows to lie down and where cows are forced to stand. Lameness itself can result in longer lying times, whereas mastitis reduces it. Cow-based factors such as reproductive status, age, and milk production influence lying time, but the welfare implications of these differences are unknown. Lower lying times are reported in pasture-based systems, dry lots, and bedded packs (9 h/d) compared with tiestalls and freestalls (10 to 12 h/d) in cross-farm research. Unfavorable conditions, including too few lying stalls for the number of cows, hard or wet lying surfaces, inadequate bedding, stalls that are too small or poorly designed, heat, and rain all reduce lying time. Time constraints, such as feeding or milking, can influence lying time. However, more information is needed about the implications of mediating factors such as the effect of the standing surface (concrete, pasture, or other surfaces) and cow behavior while standing (e.g., being restrained, walking, grazing) to understand the effect of low lying times on animal welfare. Many factors contribute to the difficulty of finding a valid threshold for daily lying time to use in the assessment of animal welfare. Although higher lying times often correspond with cow comfort, and lower lying times are seen in unfavorable conditions, exceptions occur, namely when cows lie down for longer because of disease or when they spend more time standing because of estrus or parturition, or to engage in other behaviors. In conclusion, lying behavior is important to dairy cattle, but caution and a full understanding of the context and the character of the animals in question is needed before drawing firm conclusions about animal welfare from measures of lying time.

Forecasting the milk yield of cows on farms equipped with automatic milking system with the use of decision trees

The purpose of this paper was to utilize the decision trees technique to determine the factors responsible for high monthly milk yield in Polish Holstein-Friesian cows from 27 herds equipped with milking robots. The applied statistical method-the decision tree technique-showed that the most important factors responsible for monthly milk yield of dairy cows using robots were, in descending order of importance: milking frequency, lactation number, month of milking, and type of lying stall. At the same time, it has been ascertained that the highest monthly milk yield (47.24 kg) can be expected from multiparous cows kept in barns with a deep bedding that were milked more frequently than three times per day. On the other hand, the lowest milk production (13.56 kg) was observed among dairy cows milked less frequently than two times a day, with an average number of milked quarters lower than 3.97. The application of the decision trees technique allows a breeder to select appropriate levels of environmental factors and parameters that will help to ensure maximized milk production.

The milking frequency of primiparous cows in their early stage of lactation and its impact on milking performance

An automatic milking system allows cows to present their full production capability by not limiting them to a specific time when the milking occurs or a fix number of milkings per day. The beginning of the first lactation is a key point in terms of subsequent milk production. The aim of the present study was to indicate the relationship between the milking frequency of primiparous cows during the first month of lactation and their subsequent milk performance. Material of the study consisted of 25 Polish herds of Holstein–Friesian dairy cattle. All cows were milked with the use of an automatic milking system. Animals were divided into five groups, depending on the milking frequency in the first month after calving (MFF). The collected data were statistically processed using the multifactorial ANOVA. The best milk and milking parameters characterised primiparous cows, for which the average number of milkings per day was at the level of 3–3.5 or above, this group did not have a preferred time for their milking. This group of cows milked more frequently during the first month of lactation (MFF5) and had the highest milk yield (MY) and milking duration. The highest culling percentage (57.77%) was noted within the group of primiparous cows with the lowest milking frequency during the first month of lactation (MFF1). MFF5 animals maintained better milk and milking parameters in all months of lactation than did those in the other groups. Older animals, that calved after the 28th month of life, and those that calved during warmer seasons, showed the tendency to have a lower milking frequency and poorer milk and milking parameters. The findings obtained in the present study are interesting in terms of their potential use, because they show that frequent milking during the first month after calving corresponds to a better overall MY during that lactation. Hopefully, by promoting frequent milkings at the beginning of lactation, farmer may increase the overall lactation MY.

Synchronization of Dairy Cows Does Not Limit the Behavioral Response to Treatment in Mixed Treatment Experimental Designs

In many research studies, animals assigned to different treatments are housed adjacently or together in a group. One critique of these designs has been the potential role of behavioral facilitation and synchronization between animals on different treatments in mixed treatment groups (heterogeneous groups). To evaluate this, we compared the synchrony of feeding behavior between dairy cows housed in heterogeneous groups to cows exposed to the same treatment simultaneously (homogenous groups). Twenty-four cows were exposed to each of the two treatments over 21 days in a replicated cross-over design. Treatments were two different schedules of timing of feed delivery: (A) feeding at milking time and (B) feeding halfway between milking times. For the last 7 days of each treatment period, feeding behavior was recorded electronically. Kappa coefficients were calculated for each animal within each group, as an estimate of agreement that any two cows within a group (i.e., each individual and each other cow in her group) would both be engaged in feeding activity for any hour of the day. The level of synchrony was similar for cows within homogenous groups (kappa = 0.31 ± 0.030) compared with cows on the same treatment within heterogeneous groups (kappa = 0.32 ± 0.037). Within heterogeneous groups, cows on the same treatment were nearly 50% more synchronized with each other than with those on the other treatment (kappa = 0.22 ± 0.029). These results suggest that synchronization of feeding behavior does not restrict our ability to impose different treatments on individual cows within a group.

Anaerobic digestion and milking frequency as mitigation strategies of the environmental burden in the milk production system

The aim of the study was to assess, through a cradle to farm gate Life Cycle Assessment, different mitigation strategies of the potential environmental impacts of milk production at farm level. The environmental performances of a conventional intensive dairy farm in Northern Italy (baseline scenario) were compared with the results obtained: from the introduction of the third daily milking and from the adoption of anaerobic digestion (AD) of animal slurry in a consortium AD plant. The AD plant, fed only with animal slurries coming also from nearby farms. Key parameters concerning on-farm activities (forage production, energy consumptions, agricultural machines maintenance, manure and livestock management), off-farm activities (production of fertilizers, pesticides, bedding materials, purchased forages, purchased concentrate feed, replacement animals, agricultural machines manufacturing, electricity, fuel) and transportation were considered. The functional unit was 1kg fat and protein corrected milk (FPCM) leaving the farm gate. The selected environmental impact categories were: global warming potential, acidification, eutrophication, photochemical oxidation and non-renewable energy use. The production of 1kg of FPCM caused, in the baseline scenario, the following environmental impact potentials: global warming potential 1.12kg CO2 eq; acidification 15.5g SO2 eq; eutrophication 5.62g PO4(3-) eq; photochemical oxidation 0.87g C2H4 eq/kg FPCM; energy use 4.66MJeq. The increase of milking frequency improved environmental performances for all impact categories in comparison with the baseline scenario; in particular acidification and eutrophication potentials showed the largest reductions (-11 and -12%, respectively). In anaerobic digestion scenario, compared to the baseline one, most of the impact potentials were strongly reduced. In particular the most important advantages were in terms of acidification (-29%), global warming (-22%) and eutrophication potential (-18%). The AD of cow slurry is confirmed as an effective strategy to mitigate the environmental impact of milk production at farm level.

Cluster analysis of Dairy Herd Improvement data to discover trends in performance characteristics in large Upper Midwest dairy herds

Principal component analysis (PCA) is a variable reduction method used on over-parameterized data sets with a vast number of variables and a limited number of observations, such as Dairy Herd Improvement (DHI) data, to select subsets of variables that describe the largest amount of variance. Cluster analysis (CA) segregates objects, in this case dairy herds, into groups based upon similarity in multiple characteristics simultaneously. This project aimed to apply PCA to discover the subset of most meaningful DHI variables and to discover groupings of dairy herds with similar performance characteristics. Year 2011 DHI data was obtained for 557 Upper Midwest herds with test-day mean ≥200 cows (assumed mostly freestall housed), that remained on test for the entire year. The PCA reduced an initial list of 22 variables to 16. The average distance method of CA grouped farms based on best goodness of fit determined by the minimum cophenetic distance. Six groupings provided the optimal fitting number of clusters. Descriptive statistics for the 16 variables were computed per group. On observations of means, groups 1, 2, and 6 demonstrated the best performances in most variables, including energy-corrected milk, linear somatic cell score (log of somatic cell count), dry period intramammary infection cure rate, new intramammary infection risk, risk of subclinical intramammary infection at first test, age at first calving, days in milk, and Transition Cow Index. Groups 3, 4, and 5 demonstrated the worst mean performances in most the PCA-selected variables, including DIM, age at first calving, risk of subclinical intramammary infection at first test, and dry period intramammary infection cure rate. Groups 4 and 5 also had the worst mean herd performances in energy-corrected milk, Transition Cow Index, linear somatic cell score, and new intramammary infection risk. Further investigation will be conducted to reveal patterns of management associated with herd categorization. The PCA and CA should be used when describing the multivariate performance of dairy herds and whenever working with over-parameterized data sets, such as DHI databases.