Effects of Early Lactation Milking Frequency in an Automated Milking System on Cow Performance

Automated milking systems (AMS) are increasingly adopted for dairy cow production, promoting individualized cow management dependent on factors like lactation stage, age, and productivity. The study objective was to investigate the effects of early lactation milking frequency on cows milked via AMS. Multiparous Holstein cows blocked by parity and due date were randomly assigned to treatments (n = 8 per treatment): three (3X) or six (6X) milkings per day (MPD). The experimental phase (EXP) was defined as 4 to 29 days in milk (DIM). The AMS settings were programed so 3X cows were limited to three MPD while 6X cows were allowed six MPD. Afterwards was the carry over phase (CO) ranging from 30 to 90 DIM; all cows were allowed up to six MPD. Measurements by the AMS included bodyweight, milk yield (MY), and pellet intake. Weekly composite milk samples were analyzed for macronutrient composition and fatty acid (FA) profile. Coccygeal blood was sampled at 3, 8 ± 1, and 13 ± 1 DIM; concentrations of blood plasma analytes were quantified. Greater MPD was achieved for 6X cows versus 3X cows during EXP, but similar during the CO. Daily MY was non-separable during the EXP while 6X cows in their third or greater lactation group (3 + LG) had greater MY than 3X cows of the same LG during the CO. Milk fat content and 4% fat-corrected MY were both greater for 6X, 3 + LG cows during the EXP compared to 3X, 3 + LG cows. Milk FA methyl esters (FAME) proportions were different between MPD groups, with 6X, 3 + LG cows having the lowest short, even-chain FA from de novo or post-absorptive origin. Differences in analytes indicated that 6X, 3 + LG cows experienced metabolic stress and incorporated greater FA from adipose tissue. Greater early lactation MPD in AMS may shift cow nutrient partitioning to support greater production in 3+ parity cows.

A time series analysis of milk productivity in US dairy states

As US dairy cow production evolves, it is important to characterize trends and seasonal patterns to project amounts and fluctuations in milk and milk components by states or regions. Hence, this study aimed to (1) quantify historical trends and seasonal patterns of milk and milk components production associated with calving date by parities and states; (2) classify parities and states with similar trends and seasonal patterns into clusters; and (3) summarize the general pattern for each cluster for further application in simulation models. Our data set contained 9.18 million lactation records from 5.61 million Holstein cows distributed in 17 states during the period January 2006 to December 2016. Each record included a cow's total milk, fat, and protein yield during a lactation. We used time series decomposition to obtain each state's annual trend and seasonal pattern in milk productivity for each parity. Then, we classified states and parities with agglomerative hierarchical clustering into groups according to 2 methods: (1) dynamic time warping on the original time series and (2) Euclidean distance on extracted features of trend and seasonality from the decomposition. Results showed distinguishable trends and seasonality for all states and lactation numbers for all response variables. The clusters and cluster centroid pattern showed a general upward trend for all yields [energy-corrected milk (ECM), milk, fat, and protein] and a steady trend for fat and protein percent for all states except Texas. We also found a larger seasonality amplitude for all yields (ECM, milk, fat, and protein) from higher lactation numbers and a similar amplitude for fat and protein percent across lactation numbers. The results could be used for advising management decisions according to farm productivity goals. Furthermore, the trend and seasonality patterns could be used to adjust the production level in a specific state, year, and season for farm simulations to accurately project milk and milk components production.

Reducing milking frequency from 3 to 2 times daily in early lactation: effects on milk production, health and body condition

The objective of this experiment was to investigate the effect of reducing early lactation milking frequency on milk yield and persistency through lactation and early lactation fat mobilization, measured by body condition score (BCS) and BHB in milk. We hypothesized that milking cows twice per day in early lactation before milking them 3 times per day for the remaining lactation would cause less fat mobilization in early lactation, a lower peak milk yield but improved persistency throughout lactation compared with milking cows 3 times per day for the entire lactation. The experiment took place on 2 commercial dairy farms in Denmark. All cows calving in a period of nine months (n = 239) in their current first and later parities were randomly allocated at dry-off to 1 of 3 treatments based on expected calving date. The treatments were (1) cows milked 2 times per day for 1 week after calving, (2) cows milked 2 times per day for 4 weeks after calving and (3) cows milked 2 times per day for 7 weeks after calving. All cows were then milked 3 times per day for the remaining lactation. Milk yield peaked 3.3 and 3.6 d later and milk yield persistency improved with 18 and 19 g per day when cows were milked 2 times per day for 4 and 7 weeks, respectively, compared with milking 2 times per day for 1 week after calving. We found a significant highest milk BHB in treatment 2, but the underlying effect of milking cows 2 times per day for 4 weeks compared with 1 or 7 weeks was unclear. In conclusion, we did not confirm our hypothesis that milking cows 2 times per day compared to 3 times in early lactation would reduce fat mobilization and reduce peak yield. We did, however, find an improved milk yield persistency, which partially offset a numerical reduction in peak yield, and hence there was no significant effect of reducing early lactation milking frequency on total lactation (305 DIM) milk yield.

Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence

New and emerging technologies, especially those based on non-invasive video and thermal infrared cameras, can be readily tested on robotic milking facilities. In this research, implemented non-invasive computer vision methods to estimate cow's heart rate, respiration rate, and abrupt movements captured using RGB cameras and machine learning modelling to predict eye temperature, milk production and quality are presented. RGB and infrared thermal videos (IRTV) were acquired from cows using a robotic milking facility. Results from 102 different cows with replicates (n = 150) showed that an artificial neural network (ANN) model using only inputs from RGB cameras presented high accuracy (R = 0.96) in predicting eye temperature (°C), using IRTV as ground truth, daily milk productivity (kg-milk-day^-1), cow milk productivity (kg-milk-cow^-1), milk fat (%) and milk protein (%) with no signs of overfitting. The ANN model developed was deployed using an independent 132 cow samples obtained on different days, which also rendered high accuracy and was similar to the model development (R = 0.93). This model can be easily applied using affordable RGB camera systems to obtain all the proposed targets, including eye temperature, which can also be used to model animal welfare and biotic/abiotic stress. Furthermore, these models can be readily deployed in conventional dairy farms.

The Effect of Compositional Changes Due to Seasonal Variation on Milk Density and the Determination of Season-Based Density Conversion Factors for Use in the Dairy Industry

The objective of this study was to determine the effect of seasonal variation on milk composition and establish an algorithm to predict density based on milk composition to enable the calculation of season-based density conversion calculations. A total of 1035 raw whole milk samples were collected from morning and evening milking of 60 spring-calving individual cows of different genetic groups, namely Jersey, Elite HF (Holstein–Friesian) and National Average HF, once every two weeks for a period of 9 months (March–November, 2018). The average mean and standard deviation for milk compositional traits were 4.72 ± 1.30% fat, 3.85 ± 0.61% protein and 4.69 ± 0.30% lactose and density was estimated at 1.0308 ± 0.002 g/cm³. The density of the milk samples was evaluated using three methods: a portable density meter, DMA 35; a standard desktop version, DMA 4500M; and an Association of Official Agricultural Chemists (AOAC) method using 100-mL glass pycnometers. Statistical analysis using a linear mixed model showed a significant difference in density of milk samples (p < 0.05) across seasonal and compositional variations adjusted for the effects of days in milk, parity, the feeding treatment, the genetic group and the measurement technique. The mean density values and standard error of mean estimated for milk samples in each season, i.e., spring, summer and autumn were 1.0304 ± 0.00008 g/cm³, 1.0314 ± 0.00005 g/cm³ and 1.0309 ± 0.00007 g/cm³, respectively.

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 acute phase protein orosomucoid 1 is upregulated in early lactation but does not trigger appetite-suppressing STAT3 signaling via the leptin receptor

Dairy cows consume inadequate amounts of feed in early lactation and during conditions and diseases such as excessive fatness, heat stress, and infectious diseases. Affected cows often experience increases in plasma concentrations of acute phase proteins consistent with the negative effect of inflammation on appetite. The acute phase protein orosomucoid 1 (ORM1), also known as alpha-1-acid glycoprotein, was recently reported to reduce appetite in the mouse through its ability to bind the full-length leptin receptor (Ob-Rb) and activate appetite-suppressing signal transducer and activator of transcription 3 (STAT3) signaling. These observations raise the possibility that ORM1 exerts appetite-suppressing effects in dairy cattle during periods of increased inflammatory tone. The applicability of this model was assessed in 2 ways. First, we asked whether ORM1 is regulated during periods of inadequate appetite such as the transition from late pregnancy to early lactation and periods of increased inflammatory tone. Plasma ORM1 was invariant in late pregnancy but increased 2.5-fold between parturition and d 7 of lactation. Gene expression studies showed that liver was the major source of this elevation with little contribution by adipose tissue or mammary gland. Additional studies showed that plasma ORM1 was not increased further by excessive fatness or by reproductive dysfunction in early lactation and was completely unresponsive to inflammatory stimuli such as heat stress or intravascular administration of the endotoxin lipopolysaccharide during established lactation. Second, we tested the ability of ORM1 to trigger STAT3 signaling through Ob-Rb using Chinese hamster ovary K1 (CHO-K1) cells transfected with a STAT3 expression plasmid. In this configuration, CHO-K1 cells did not express Ob-Rb and were incapable of leptin-induced STAT3 phosphorylation. Leptin responsiveness was conferred by co-transfecting with bovine Ob-Rb, with leptin causing increases of 5.7-fold in STAT3 phosphorylation and 2.1-fold in the expression of the STAT3-dependent gene, SOCS3. In contrast, neither bovine or human ORM1 triggered STAT3 phosphorylation irrespective of dose and period of incubation tested. In summary, bovine ORM1 is not increased during periods of increased inflammatory tone except in early lactation and is incapable of Ob-Rb-dependent STAT3 signaling. Overall, these data are inconsistent with ORM1 mediating the appetite-suppressing effects of inflammation in cattle through Ob-Rb.

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.

Effects of concentrate location on the behavior and production of dairy cows milked in a free-traffic automated milking system

The objective of this study was to determine whether the amount of concentrate allowance in an automated milking system (AMS) affects partial mixed ration (PMR) sorting behavior, milking activity, and production of lactating dairy cows fed isocaloric diets. Fifteen primiparous Holstein cows were used in a crossover design with 28-d periods, including 14 d of adaptation and 14 d of data collection. The cows were housed in a freestall pen with free-traffic access to the AMS. Treatments consisted of a higher-concentrate PMR (H-PMR) with a pelleted concentrate allowance of 3.0 kg/d on a dry matter (DM) basis in the AMS, or a lower-concentrate PMR (L-PMR) with a pelleted concentrate allowance of 6.0 kg/d in the AMS. As designed, cows on the L-PMR had greater AMS concentrate intake (6.3 vs. 3.1 kg/d of DM) compared with the H-PMR. The standard deviation for mean concentrate intake among days increased from 0.38 to 1.0 kg/d with greater targeted AMS concentrate intake. When fed the L-PMR diet, PMR intake was reduced compared with when cows were fed the H-PMR diet (17.1 vs. 19.1 kg/d of DM). The reduction in PMR intake was compensated for by greater AMS concentrate intake; thus, cows on the L-PMR had greater total dry matter intake (DMI; 23.6 vs. 22.3 kg/d). Cows sorted against long (>19 mm) and fine (<4 mm) PMR particle fractions, and in favor of medium (8 to 19 mm) and short (4 to 8 mm) PMR fractions when on the H-PMR treatment, but only sorted against the medium and in favor of the short PMR fractions on the L-PMR treatment. PMR eating rate and total time spent eating PMR did not differ significantly between the 2 treatments; however, meal size tended to be larger when cows were fed the H-PMR compared with the L-PMR (2.2 vs. 2.1 kg DM/meal). Cows tended to spend 30.8 min/d more time lying down when fed the L-PMR. On the L-PMR treatment, cows tended to have more voluntary AMS visits (5.9 vs. 4.6 visits/d), were fetched less (0.1 vs. 0.5 times daily), and had a greater milking frequency (3.5 vs. 3.0 milkings/d) compared with when they were on the H-PMR treatment. However, milk yield was not affected by treatment. These data suggest that allocating a greater proportion of total dietary concentrate to the AMS, in a free-traffic setup, may improve milking activity and decrease the need for fetching, as well as promoting greater amounts of and maintaining consistency in total dry matter consumption.

The effects of incomplete milking and increased milking frequency on milk production rate and milk composition1

Increased milking frequency and incomplete milking have differential effects on milk yield and mammary gland physiology that are important for optimization of milking practices in dairy herds. The objectives of this experiment were to determine the effects of increased milking frequency and incomplete milking on milk production rate (MPR) and milk composition and to determine if milking 3 times daily (3×) could rescue the negative production effects of incomplete milking. Twenty-two multiparous cows were enrolled onto this experiment beginning at 5 days in milk (DIM) and continuing through 47 DIM. A split-plot design was used to randomize the 2 treatments, which were milking frequency and incomplete milking. Eleven cows were randomly assigned to be milked 2 times (2×) daily and 11 cows were randomly assigned to be milked 3×. Within each cow, a contralateral half-udder was randomly assigned to be incompletely milked (30% milk remaining in the gland; IM), and the other half-udder was randomly assigned to be milked completely (CM). Quarter-level milk yields were recorded at each milking session. Milk samples from all quarters were collected twice weekly at the beginning of the morning milking for analysis. Cows milked 2× tended to have reduced MPR compared with 3× milked cows (1.81 ± 0.06 vs. 1.97 ± 0.06 kg milk/h; P = 0.06). Half-udders that were CM and IM produced 1.09 ± 0.03 and 0.80 ± 0.03 kg milk/h, respectively. There was an interaction between incomplete milking treatment and week of lactation (P = 0.04). No interaction was detected between milking frequency and incomplete milking for MPR or milk components. Cows milked 3× had increased milk fat percent (1.93 ± 0.09% vs. 1.65 ± 0.09%, P = 0.047), decreased milk lactose percent (4.80 ± 0.04% vs. 4.93 ± 0.04%, P = 0.04), and exhibited no differences in milk protein percent or milk somatic cell count (SCC) compared with cows milked 2×. Half-udders that were IM had increased milk fat percent (2.15 ± 0.07% vs. 1.43 ± 0.07%, P < 0.0001), decreased lactose percent (4.75 ± 0.03% vs. 4.99 ± 0.03%, P < 0.0001), increased milk log10SCC (4.22 ± 0.05 vs. 4.41 ± 0.05, P = 0.0004), and no differences in milk protein percent compared with CM half-udders. These results indicate that a 3× milking frequency in IM half-udders was not able to improve milk production compared with IM half-udders milked 2×. Our results indicate that 30% milk remaining in the gland had an irreversible impact on milk yield as increased milking frequency was not able to reverse the milk yield lost.

Metabolic Disorders in the Transition Period Indicate that the Dairy Cows' Ability to Adapt is Overstressed

Simple Summary

Metabolic disorders are a key problem in the transition period of dairy cows and often appear before the onset of further health problems. Problems derive from difficulties animals have to adapt to large variations and disturbances occurring both outside and inside the organism. A lack of success in solving these issues may be due to predominant approaches in farm management and agricultural science, dealing with such disorders as merely negative side effects. Instead, a successful adaptation of animals to their living conditions should be seen as an important end in itself. Both farm management and agricultural sciences should support animals in their ability to cope with nutritional and metabolic challenges by employing a functional and result-driven approach.

Abstract

Metabolic disorders are a key problem in the transition period of dairy cows and often appear before the onset of further health problems. They mainly derive from difficulties the animals have in adapting to changes and disturbances occurring both outside and inside the organisms and due to varying gaps between nutrient supply and demand. Adaptation is a functional and target-oriented process involving the whole organism and thus cannot be narrowed down to single factors. Most problems which challenge the organisms can be solved in a number of different ways. To understand the mechanisms of adaptation, the interconnectedness of variables and the nutrient flow within a metabolic network need to be considered. Metabolic disorders indicate an overstressed ability to balance input, partitioning and output variables. Dairy cows will more easily succeed in adapting and in avoiding dysfunctional processes in the transition period when the gap between nutrient and energy demands and their supply is restricted. Dairy farms vary widely in relation to the living conditions of the animals. The complexity of nutritional and metabolic processes and their large variations on various scales contradict any attempts to predict the outcome of animals’ adaptation in a farm specific situation. Any attempts to reduce the prevalence of metabolic disorders and associated production diseases should rely on continuous and comprehensive monitoring with appropriate indicators on the farm level. Furthermore, low levels of disorders and diseases should be seen as a further significant goal which carries weight in addition to productivity goals. In the long run, low disease levels can only be expected when farmers realize that they can gain a competitive advantage over competitors with higher levels of disease.

Accuracy of milk ketone bodies from flow-injection analysis for the diagnosis of hyperketonemia in dairy cows

The objectives of this study were (1) to determine the correlations between blood β-hydroxybutyrate (BHBA) and milk components [BHBA, acetone, fat, protein, and fat:protein (F:P) ratio], and (2) to establish optimal thresholds for milk components to predict hyperketonemia in dairy cows. Data on 163 cows from 37 herds were used in this cross-sectional study. Herds were visited once during the study period, and cows between 2 and 90 d in milk were blood sampled within 4h of milk sampling for the Dairy Herd Improvement test. Blood BHBA concentrations were measured using a cow-side electronic meter, Precision Xtra, which was considered the gold standard test in this study. Milk BHBA and acetone concentrations were measured in Dairy Herd Improvement milk samples by flow-injection analysis; whereas, milk fat and protein were tested using Fourier transform infrared spectroscopy. Hyperketonemia was defined by a blood BHBA concentration ≥ 1.4 mmol/L. The prevalence of hyperketonemia (based on blood BHBA values) in this study population was 21.0%. Pearson correlation coefficients between blood BHBA and milk BHBA, acetone, fat, protein, and F:P ratio were 0.89, 0.73, 0.21, 0.04, and 0.17, respectively. Receiver operating characteristic curves were generated and thresholds for each individual milk component were determined based on the maximal sum of sensitivity and specificity. Optimal threshold values for hyperketonemia were milk BHBA ≥ 0.20 mmol/L, acetone ≥ 0.08 mmol/L, fat ≥ 4.2%, and F:P ratio ≥ 1.3. Based on these thresholds, milk BHBA and acetone had greater sensitivity (84 and 87%, respectively) and greater specificity (96 and 95%, respectively) than the other milk components (fat, protein, and F:P). Series and parallel testing slightly improved the accuracy of milk BHBA and acetone values to predict hyperketonemia. A multivariable model that accounted for milk BHBA and milk acetone values simultaneously had the highest accuracy of all tested models for predicting hyperketonemia. These results support that milk BHBA and milk acetone values from flow-injection analysis are accurate diagnostic tools for hyperketonemia in dairy cows and could potentially be used for herd-level hyperketonemia surveillance programs.

Effects of increased milking frequency during early lactation on milk yield and udder health of primiparous Holstein heifers

In dairy cows, increased milking frequency (IMF) during early lactation stimulates an increase in milk yield that partially persists through the remainder of lactation. However, the effects of IMF on lactation performance and udder health of primiparous heifers have not been clearly established. The objective of this study was to determine the effects of IMF during early lactation on milk yield and composition, udder edema, and teat-end condition of primiparous Holstein heifers. Thirteen heifers were assigned at parturition to unilateral frequent milking (twice-daily milking of the left udder half (2X), and 4-times-daily milking of the right udder half (4X)) from d 1 to 21 of lactation. Heifers were milked twice daily at 0130 and 1330 h, with additional milking of the right udder half at 0430 and 1630 h. Half-udder milk yield and composition were recorded on d 1 and 4, weekly through 35 d in milk (DIM), monthly through 210 DIM, and on d 270±1 of lactation. Udder edema and teat-end scores were evaluated on d 1 and 4, weekly through d 35, and on d 60±1 of lactation. A 1-sided paired t test was used to compare milk yield of 4X- to 2X-udder halves. A 2-sided paired t test was used to test for differences in milk composition, udder edema, and teat-end scores. Overall, 4X stimulated an immediate increase in milk yield. Differential milk yield peaked on d 21 of lactation, with 4X udder halves producing 2.8 kg/d more milk than 2X udder halves (P<0.001). After cessation of 4X, the milk yield differential decreased, but 4X udder halves continued to produce 0.8 kg/d more milk than 2X udder halves through d 270 of lactation (P<0.05). Over the entire lactation, milk component yields and 3.5% fat-corrected milk or energy-corrected milk were greater (P<0.05), whereas somatic cell counts in milk were lower, in 4X udder halves (P<0.05). Udder edema and teat-end condition did not differ between 4X and 2X (P>0.19). In conclusion, IMF during early lactation stimulated a persistent increase in milk yield without negatively affecting several indicators of udder health of primiparous dairy heifers.

Triennial Lactation Symposium: A local affair: How the mammary gland adapts to changes in milking frequency

Regular removal of milk from the mammary gland is critical to maintaining milk secretion. Early studies in rodents demonstrated that changes in milking frequency influenced mammary blood flow, as well as mammary cell number and activity. Later studies in ruminants confirmed those observations and that the response was regulated locally within the mammary gland. In addition, it was discovered that increased milking frequency (IMF) during early lactation stimulated an increase in milk production that partially persisted through late lactation, indicating long-term effects on mammary function. The local mechanisms regulating the mammary response to IMF are poorly understood, although several have been proposed. To gain insight into the mechanisms underlying the mammary response to IMF, and to identify genes associated with the response, we used a functional genomics approach and conducted experiments on dairy cows exposed to unilateral frequent milking [UFM; twice daily milking (2X) of the left udder half and 4-times daily milking (4X) of the right udder half]. Across multiple experiments, we were unable to detect an effect of UFM on mammary cell proliferation or apoptosis. We have, however, identified distinct transcriptional signatures associated with the mammary response to milk removal and to UFM during early lactation. Sequential sampling of mammary tissue revealed that when UFM was imposed during early lactation, at least 2 sets of genes were coordinately regulated with changes in differential milk production of 4X vs. 2X udder halves. Moreover, some genes were persistently differentially expressed in 4X vs. 2X udder halves after UFM and were associated with the persistent increase in milk yield. We conclude that a coordinated transcriptional response is associated with the increase in milk yield elicited by IMF during early lactation and that the 2 sets of differentially expressed genes may be a marker for the autocrine up-regulation of milk production. Moreover, we propose that we have identified a novel form of imprinting associated with persistent alteration of mammary function, which we term "lactational imprinting."