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.

Effect of glycerol supplementation in early lactation on metabolic health, milking activity, and production of dairy cows in automated milking system herds

The objective of this study was to quantify the effects of supplementing early-lactation cows with a dry pure glycerol product, delivered through the automated milking system (AMS) concentrate, in the first 21 d in milk (DIM) on metabolic markers, milking behavior, and milk production. In 5 commercial AMS dairy herds, 389 dairy cows were randomly assigned, controlling for parity, 21 d before expected calving to 1 of 2 treatments, within farm: (1) control group (CON) receiving the standard AMS pellet (n = 213) from 1 to 150 DIM, or (2) glycerol group (GLY) receiving the treatment AMS pellet (n = 176) formulated to deliver 250 as fed g/d of glycerol product from 1 to 21 DIM (mean actual = 249 g/d dry matter [DM]), then they received the standard AMS pellet from 22 to 150 DIM. Across all farms, cows were fed partial mixed rations (PMR) that were similar in ingredient and nutrient composition. One prepartum blood sample and 5 postpartum blood samples were collected from each cow to determine serum nonesterified fatty acids (NEFA), blood β-hydroxy butyrate (BHB), and blood glucose concentrations. Cow body condition score (BCS) was recorded every 21 d from -21 to 63 DIM. Data were collected and analyzed for the treatment period (1 to 21 DIM) and a follow-up period (22 to 150 DIM). There was no detected treatment effect on serum NEFA concentrations in the first week of lactation. There was a treatment by time interaction for blood BHB and blood glucose, where GLY cows tended to have increased BHB concentrations at 5 DIM and had decreased glucose concentrations at 9 and 12 DIM. There was an interaction of BCS with treatment on the incidence of BHB ≥1.2 mmol/L, whereby over-conditioned CON cows (BCS ≥3.5) were 3.5x more likely to have a high BHB test than CON cows with normal prepartum BCS. During the treatment period GLY cows had 0.1 ± 0.05 more successful milkings/d, were delivered 0.27 ± 0.05 DM kg/d more AMS concentrate and tended to yield 0.8 ± 0.47 kg/d more milk. During the follow-up period GLY cows had 0.1 ± 0.04 more successful milkings/d, were delivered 0.18 ± 0.06 DM kg/d more AMS concentrate, and yielded 1.5 ± 0.53 kg/d more milk than CON cows. Glycerol supplementation allowed cows to maintain better BCS, as GLY cows lost less BCS from calving to 63 DIM than CON cows. Overall, the results of this study demonstrate that supplementing pure glycerol through the AMS concentrate for the first 21 DIM can reduce BCS loss in early lactation, improve milking behavior, and increase milk yield to mid lactation.

Potential relationships between apelin and metabolic-associated indices in transition dairy cows

Metabolic disorders pose significant challenges in transition dairy cows. Numerous parameters have been investigated in this context, and apelin has recently emerged as a potential metabolic indicator. Accordingly, this study aimed to assess the associations between this hormone and other metabolic parameters. Twenty-two adult Holstein-Friesian dairy cows, 21 days before their expected calving date, were selected for blood sampling and serum separation at four time points: 21 and 10 days before calving and 10 and 21 days after parturition. Serum concentrations of apelin, leptin, insulin, cortisol, T3, T4, non-esterified fatty acids, glucose, total protein, albumin, globulin, aspartate aminotransferase, alanine transaminase, triglycerides, cholesterol, high, low and very low-density lipoproteins, total, direct and indirect bilirubin were measured in these samples. Surrogate indices for insulin resistance, body condition score, and milk production were also evaluated. Throughout the transition period, a significant increase in apelin levels was observed. Various models were employed to identify associations between apelin and the studied metabolic parameters. Notably, significant correlations between apelin and Leptin, Insulin, Cortisol, T3, T4, NEFA, Cholesterol, LDL, VLDL, Total Protein, Albumin, Globulin, Total Bilirubin, Direct Bilirubin and Indirect Bilirubin were observed, with some being immediate while others developed over time. These findings indicate a mutual influence between apelin and specific metabolic indices. Changes in any component of the metabolic profile at one stage can lead to alterations in apelin levels in subsequent stages. The correlations uncovered between apelin and other components of the metabolic profile in transitioning dairy cows offer valuable insights, contributing to a better understanding of the potential effects of apelin on the studied indicators and vice versa.

Farm-level risk factors associated with increased milk β-hydroxybutyrate and hyperketolactia prevalence on farms with automated milking systems

The objectives of this study were to determine the farm-level hyperketolactia (HKL) prevalence, as diagnosed from milk β-hydroxybutyrate (BHB) concentration, on dairy farms milking with an automatic milking system (AMS) and to describe the farm-level housing, management, and nutritional risk factors associated with increased farm-average milk BHB and the within-herd HKL prevalence in the first 45 DIM. Canadian AMS farms (n = 162; eastern Canada n = 8, Quebec n = 23, Ontario n = 75, western Canada n = 55) were visited once between April to September 2019 to record housing and herd management practices. The first test milk data for each cow under 45 DIM were collected, along with the final test of the previous lactations for all multiparous cows, from April 1, 2019 to September 30, 2020. The first test milk BHB was then used to classify each individual cow as having HKL (milk BHB ≥ 0.15 mmol/L) at the time of testing. Milk fat and protein content, milk BHB, and HKL prevalence were summarized by farm and lactation group (all, primiparous, and multiparous). During this same time period, formulated diets for dry and lactating cows, including ingredients and nutrient composition, and AMS milking data were collected. Data from the AMS were used to determine milking behaviors and milk production of each herd during the first 45 DIM. Multivariable regression models were used to associate herd-level housing, feeding management practices, and formulated nutrient composition with first test milk BHB concentrations and within-herd HKL levels separately for primiparous and multiparous cows. The within-herd HKL prevalence for all cows was 21.8%, with primiparous cows having a lower mean prevalence (12.2 ± 9.2%) than multiparous cows (26.6 ± 11.3%). Milk BHB concentration (0.095 ± 0.018 mmol/L) and HKL prevalence for primiparous cows were positively associated with formulated prepartum DMI and forage content of the dry cow diet while being negatively associated with formulated postpartum DMI, the major ingredient in the concentrate supplemented through the AMS, and the PMR-to-AMS concentrate ratio. However, multiparous cows' milk BHB concentration (0.12 ± 0.023 mmol/L) and HKL prevalence were positively associated with the length of the previous lactation, milk BHB at dry off, prepartum diet nonfiber carbohydrate content, and the major forage fed on farm, while tending to be negatively associated with feed bunk space during lactation. This is the first study to determine the farm-level risk factors associated with herd-level prevalence of HKL in AMS dairy herds, thus helping optimize management and guide diet formulation to promote the reduction of HKL prevalence.

Combination of milk variables and on-farm data as an improved diagnostic tool for metabolic status evaluation in dairy cattle during the transition period

Milk composition, particularly milk fatty acids, has been extensively studied as an indicator of the metabolic status of dairy cows during early lactation. In addition to milk biomarkers, on-farm sensor data also hold potential in providing insights into the metabolic health status of cows. While numerous studies have explored the collection of a wide range of sensor data from cows, the combination of milk biomarkers and on-farm sensor data remains relatively underexplored. Therefore, this study aims to identify associations between metabolic blood variables, milk variables, and various on-farm sensor data. Second, it seeks to examine the supplementary or substitutive potential of these data sources. Therefore, data from 85 lactations on metabolic status and on-farm data were collected during 3 wk before calving up to 5 wk after calving. Blood samples were taken on d 3, 6, 9, and 21 after calving for determination of β-hydroxybutyrate (BHB), nonesterified fatty acids (NEFA), glucose, insulin-like growth factor-1 (IGF-1), insulin, and fructosamine. Milk samples were taken during the first 3 wk in lactation and analyzed by mid-infrared for fat, protein, lactose, urea, milk fatty acids, and BHB. Walking activity, feed intake, and body condition score (BCS) were monitored throughout the study. Linear mixed effect models were used to study the association between blood variables and (1) milk variables (i.e., milk models); (2) on-farm data (i.e., on-farm models) consisting of activity and dry matter intake analyzed during the dry period ([D]) and lactation ([L]) and BCS only analyzed during the dry period ([D]); and (3) the combination of both. In addition, to assess whether milk variables can clarify unexplained variation from the on-farm model and vice versa, Pearson marginal residuals from the milk and on-farm models were extracted and related to the on-farm and milk variables, respectively. The milk models had higher coefficient of determination (R2) than the on-farm models, except for IGF-1 and fructosamine. The highest marginal R2 values were found for BHB, glucose, and NEFA (0.508, 0.427, and 0.303 vs. 0.468, 0.358, and 0.225 for the milk models and on-farm models, respectively). Combining milk and on-farm data particularly increased R2 values of models assessing blood BHB, glucose, and NEFA concentrations with the fixed effects of the milk and on-farm variables mutually having marginal R2 values of 0.608, 0.566, and 0.327, respectively. Milk C18:1 was confirmed as an important milk variable in all models, but particularly for blood NEFA prediction. On-farm data were considerably more capable of describing the IGF-1 concentration than milk data (marginal R2 of 0.192 vs. 0.086), mainly due to dry matter intake before calving. The BCS [D] was the most important on-farm variable in relation to blood BHB and NEFA and could explain additional variation in blood BHB concentration compared with models solely based on milk variables. This study has shown that on-farm data combined with milk data can provide additional information concerning the metabolic health status of dairy cows. On-farm data are of interest to be further studied in predictive modeling, particularly because early warning predictions using milk data are highly challenging or even missing.

Association between hyperketolactia and production in early-lactating dairy cows

Study aims were to investigate associations of hyperketolactia (HYKL) status of Holstein dairy cows between 6 and 60 d in milk (DIM), defined by milk acetone (mACE) and β-hydroxybutyrate (mBHB) content, with daily milk yield and composition. Milk samples (∼5.0 million) were collected over a 5-yr period (2014-2019) within the milk recording system in Poland. Concentrations of mACE and mBHB determined by Fourier-transform infrared spectroscopy were used to categorize samples into 4 ketolactia groups. Based on threshold values of ≥0.15 mmol/L mACE and ≥0.10 mmol/L mBHB, ketolactia groups were normoketolactia (NKL; mACE <0.15 mmol/L and mBHB <0.10 mmol/L), BHB hyperketolactia (HYKLBHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), ACE hyperketolactia (HYKLACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L), and ACE and BHB hyperketolactia (HYKLACEBHB; mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L). To investigate ketolactia association with production outcomes, a linear model was developed, including ketolactia group, DIM, parity, their interactions, year-season as fixed effects, and random effects of herd and cow. Among all milk samples, 31.2% were classified as HYKL, and of these, 52.6%, 39.6%, and 7.8% were HYKLACEBHB, HYKLBHB, and HYKLACE, respectively. Ketolactia groups differed for all traits studied in all parities and DIM. Among HYKL groups, lowest milk yield was found in HYKLACEBHB cows, except for 6 to 30 DIM in first- and second-lactation cows. Milk yield of HYKLBHB cows was higher than that of NKL cows until 20 to 30 DIM, and then it was lower than NKL cows. Milk yield of HYKLACE cows was mostly lower than NKL cows. Energy-corrected milk (ECM) yield of HYKLACEBHB cows was higher than that of NKL cows until 30 to 35 DIM for second lactation and third lactation or greater, and in the whole study period for first lactation. The yield of ECM for HYKLBHB cows was mostly higher than that of NKL cows, whereas HYKLACE cows had higher ECM than NKL cows until 15 to 25 DIM and then was lower for the HYKLACE group. Milk composition differed among HYKL groups. Highest milk fat (MF) and lowest milk lactose (ML) contents were observed in HYKLACEBHB cows. Cows in HYKLACEBHB and HYKLBHB groups had higher MF and lower milk protein (MP; except in 6-8 DIM in first lactation) and ML content than NKL cows. Milk fat content was higher in HYKLACE than NKL cows in first lactation and during the first 30 to 40 DIM in older cows. Lactose content was lower in HYKLACE than in NKL cows within 30 to 40 DIM; afterward it was higher in NKL cows. Lower MP content was found in HYKLACE than in NKL cows, except during 6 to 9 DIM for cows in first lactation and third lactation or greater. In conclusion, HYKL is associated with altered milk production in all parities, but a range of these negative relations depends on ketone status addressing both ACE and BHB contents. Further research is needed to ascertain underpinning biochemical defects of HYKL from elevated ACE, alone or in combination with BHB, during early lactation.

Patterns of Fourier-transform infrared estimated milk constituents in early lactation Holstein cows on a single New York State dairy

Cows undergo immense physiological stress to produce milk during early lactation. Monitoring early lactation milk through Fourier-transform infrared (FTIR) spectroscopy might offer an understanding of which cows transition successfully. Daily patterns of milk constituents in early lactation have yet to be reported continuously, and the study objective was to initially describe these patterns for cows of varying parity groups from 3 through 10 d postpartum, piloted on a single dairy. We enrolled 1,024 Holstein cows from a commercial dairy farm in Cayuga County, New York, in an observational study, with a total of 306 parity 1 cows, 274 parity 2 cows, and 444 parity ≥3 cows. Cows were sampled once daily, Monday through Friday, via proportional milk samplers, and milk was stored at 4°C until analysis using FTIR. Estimated constituents included anhydrous lactose, true protein, and fat (g/100 g of milk); relative % (rel%) of total fatty acids (FA) and concentration (g/100 g of milk) of de novo, mixed, and preformed FA; individual fatty acids C16:0, C18:0, and C18:1 cis-9 (g/100 g of milk); milk urea nitrogen (MUN; mg/100 g of milk); and milk acetone (mACE), milk β-hydroxybutyrate (mBHB), and milk-predicted blood nonesterified fatty acids (mpbNEFA) (all expressed in mmol/L). Differences between parity groups were assessed using repeated-measures ANOVA. Milk yield per milking differed over time between 3 and 10 DIM and averaged 8.7, 13.3, and 13.3 kg for parity 1, 2, and ≥3 cows, respectively. Parity differences were found for % anhydrous lactose, % fat, and preformed FA (g/100 g of milk). Parity differed across DIM for % true protein, de novo FA (rel% and g/100 g of milk), mixed FA (rel% and g/100 g of milk), preformed FA rel%, C16:0, C18:0, C18:1 cis-9, MUN, mACE, mBHB, and mpbNEFA. Parity 1 cows had less true protein and greater fat percentages than parity 2 and ≥3 cows (% true protein: 3.52, 3.76, 3.81; % fat: 5.55, 4.69, 4.95, for parity 1, 2, ≥3, respectively). De novo and mixed FA rel% were reduced and preformed FA rel% were increased in primiparous compared with parity 2 and ≥3 cows. The increase in preformed FA rel% in primiparous cows agreed with milk markers of energy deficit, such that mpbNEFA, mBHB, and mACE were greatest in parity 1 cows followed by parity ≥3 cows, with parity 2 cows having the lowest concentrations. When measuring milk constituents with FTIR, these results suggest it is critical to account for parity for the majority of estimated milk constituents. We acknowledge the limitation that this study was conducted on a single farm; however, if FTIR technology is to be used as a method of identifying cows maladapted to lactation, understanding variations in early lactation milk constituents is a crucial first step in the practical adoption of this technology.

Estimates of dairy herd health indicators of mastitis, ketosis, inter-calving interval, and fresh cow replacement in the Piedmont region, Italy

Test-day milk analysis has largely been used to study health and performance parameters in dairy cows. In this study, we estimated four health indicators of dairy cows using test-day data. Our purpose was to estimate (1) mastitis incidence rate, prevalence, and the probability of recovery; (2) the incidence proportion of ketosis; (3) the duration of inter-calving interval; and (4) the risk of a fresh cow being replaced, in a large cohort of dairy herds in the Piedmont region (Italy). We retrospectively analysed test day records of 261,121 lactating cows and 1315 herds during five years (2015-2020). Mastitis was defined by somatic cell count and ketosis by fat-to-protein ratio. Calving dates were used to calculate ICI and to estimate the removal of a fresh cow from the herd. Mixed-effect generalized linear models were used to adjust for unmeasured herd-level risk factors. The risk of mastitis increased by 120% with parity (Odds ratio [OR] = 2.20, confidence interval [CI]: 2.17 - 2.23), by 7% by months in milking (OR = 1.07, CI: 1.07 - 1.07), and even more if the cow was already affected during the same lactation (OR = 8.74, CI: 8.67 - 8.82). Lactose concentration on the previous test day was the best positive prognostic factor for mastitis recovery (OR = 1.12, CI: 1.08 - 1.17). Ketosis risk was the highest between 3rd and 4th lactations and itself increased the risk of having ICI longer than 440 days (OR = 1.12, CI: 1.02 - 1.22), and fresh-cow removal (OR = 1.75, CI: 1.58 - 1.93). Also, the removal of fresh cows was more likely when mastitis (OR = 1.31, CI: 1.19 - 1.45) or long ICI (OR = 1.34, CI: 1.22 - 1.48) occurred. For each health indicator, herd-level risk factors had an important role (18-56% of within-herd covariance). Our results indicate that milk analysis could be also useful for predicting mastitis, its cure rate, and ketosis. Cow-level risk factors are not enough to explain the risk of these issues. By studying a large population over a long period, this study provides an updated estimate of dairy cow health indicators in Piedmont (north-western Italy), useful for benchmarking dairy herds.

Association of herd hyperketolactia prevalence with transition management practices and herd productivity on Canadian dairy farms-A retrospective cross-sectional study

The objective of this observational study was to assess the relationship between herd-level prevalence of hyperketolactia (HPH) with management practices of the transition period and herd milk production. Dairy herds (n = 71) were selected based on their inclusion in a herd management risk assessment study (August 2014-March 2018) using a Vital 90 (Elanco) Risk Assessment tool (one assessment per farm). Data from multiple milk recording test-days (Dairy Herd Improvement, DHI; Lactanet) were included in the analysis. Tests performed within ±6 mo relative to each farm's risk assessment date were included (10 ± 2 SD tests per farm). The majority of the farms were located in Ontario (83%). For each farm DHI test, the data set included herd average milk yield (kg/cow per day), average milk fat and protein (%), average somatic cell count (cells/mL), average days in milk (DIM), number of cows tested for ketosis, number of ketosis-positive tests (milk β-hydroxybutyrate ≥0.15 mmol/L), and proportion of cows by parity groups. Overall HPH (5-21 DIM) was calculated based on data available per farm (sum of all positive tests within 5-21 DIM/sum of all cows tested within 5-21 DIM). Each farm average was obtained by considering all test-days. A logit-transformation was applied to hyperketolactia prevalence. Linear regression models (PROC GLM and MIXED of SAS, Version 9.4) were used to predict herd HPH (milk β-hydroxybutyrate ≥0.15 mmol/L within 5 to 21 DIM; the outcome of interest). Four initial models (far-off, close-up, and fresh periods, and DHI) were separately built to assess associations between their variables and HPH; a final model considered variables selected in the initial models. Univariable (liberal P < 0.25) followed by multivariable models were used to build specific models for each period of the risk assessment. Herd prevalence of hyperketolactia was 27 ± 14%, with an average herd size of 141 ± 110 cows. The final HPH model (R² = 24.8%) included weighted milk yield, the proportion of primiparous cows, water access in the close-up period, and access to rest areas or stall access in the fresh period. Herd prevalence of hyperketolactia was negatively associated with milk yield [odds ratio, OR = 0.96 (95% confidence interval 0.92-0.99)] and proportion of primiparous cows [OR = 0.98 (0.96-0.99)]. The odds of hyperketolactia were greater with poor water access and quality (<5 cm of linear access per cow; dirty water; only 1 water location in pen) than with ≥10.2 cm of linear access per cow; clean water; >2 water locations in pen [1.23 (1.11-2.39)] in the close-up period. The odds of hyperketolactia were greater in farms providing limited access to rest areas in the fresh period than in farms providing constant access to rest areas, without dead-ends [1.64 (1.03-2.80)]. In Canadian dairy herds, HPH in early lactation was associated with certain transition-period management practices and was negatively associated with herd productivity.

Characteristics of Holstein cows predisposed to ketosis during the post-partum transition period

BACKGROUND

Ketosis is a common metabolic disorder during the post-partum transition period of dairy cattle. How the method of reproduction, parturition time, and calf birth weight affect the occurrence of ketosis on dairy herds remains elusive.

OBJECTIVES

This study investigated factors associated with the severity of ketosis.

METHODS

We divided 186 Holstein cows into three classifications based on the highest β-hydroxybutyrate (BHBA) concentration during the post-partum transition period, namely non-ketosis (<1.2 mmol/L, n = 94), subclinical ketosis (1.2-2.9 mmol/L, n = 58), and clinical ketosis (≥3.0 mmol/L, n = 34). We evaluated characteristics of cows associated with the severity of ketosis.

RESULTS

Ketosis was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. Cows calving in spring and especially summer were at higher risk of severe ketosis (p < 0.01). Cows with increased body condition score (BCS) at parturition, age, lactation number, and calving interval were more likely to develop severe ketosis (p < 0.05). Cows with clinical ketosis produced most milk (29.9 ± 1.0 kg) from days four to six, whereas cows without ketosis produced the least (21.3 ± 0.8 kg) (p < 0.001). Heavier calf birth weight resulted in high risk of severe ketosis (p < 0.01), due to increased milk yield during the early lactation.

CONCLUSIONS

The severity of ketosis is associated with the calving season, BCS at parturition, age, lactation number, calving interval, milk yield in the early lactation period, and calf birth weight. Nonetheless, it was not associated with the method of reproduction, parturition time, pregnancy wastage, premature delivery, retained placenta, and type of calf. This study is the first to investigate the associations between ketosis and calf birth weight. Our findings could help predict cows at risk of ketosis and take precautions.

Predicting ketosis during the transition period in Holstein Friesian cows using hematological and serum biochemical parameters on the calving date

Ketosis often occurs during the postpartum transition period in dairy cows, leading to economic and welfare problems. Previously, ketosis was reported to be associated with hematological and serum biochemical parameters. However, the association between the parameters on the calving date and ketosis during the postpartum transition period remains unclear. This study aimed to investigate this association. Blood samples were collected from the jugular vein of Holstein cows on the calving date and β-hydroxybutyrate was tested once every 3 days (8 times in 21 days). The cows were divided into three groups: non-ketosis, subclinical ketosis, and clinical ketosis. The clinical ketosis group significantly had the highest values of mean corpuscular volume, mean corpuscular hemoglobin, β-hydroxybutyrate, non-esterified fatty acids, and total bilirubin, but the lowest values of red cell distribution width, the counts of white blood cell, monocyte, and eosinophil, albumin, alanine transaminase, lactate dehydrogenase, and amylase. In contrast, the non-ketosis group showed the opposite results (p < 0.05). In conclusion, these parameters are associated with the development and severity of ketosis. Our findings suggest that these parameters on the calving date may be useful indicators to identify dairy Holstein cow susceptible to ketosis during the transition period.

Characterization of ketolactia in dairy cows during early lactation

Fourier transform infrared spectroscopy (FTIR) allows for the determination of milk acetone (mACE) and β-hydroxybutyrate (mBHB) concentrations, providing a potential herd monitoring tool for hyperketolactia, defined as elevated milk ketone bodies. The study aim was to characterize mACE and mBHB concentration dynamics during early lactation in Polish Holstein-Friesian cows. Milk samples (n = 3,867,390) were collected within 6 to 60 days in milk (DIM) over a 4-yr period (April 1, 2013 to March 31, 2017) from approximately 21,300 dairy herds (average 38.7 cows/herd). Fixed effects of parity, DIM, and their interaction on mACE and mBHB concentrations were determined using a mixed model with a herd-year-season fixed effect and random cow effect. Published hyperketolactic mACE (≥0.15 mmol/L) and mBHB (≥0.10 mmol/L) threshold concentrations were used to classify study milk samples into ketolactia groups of normal (mACE <0.15 mmol/L and mBHB <0.10 mmol/L) and hyperketolactic (HYKL; either mACE ≥0.15 mmol/L or mBHB ≥0.10 mmol/L). Additionally, HYKL samples were categorized into subpopulations as having elevated mBHB and mACE (HYKL_ACEBHB, mACE ≥0.15 mmol/L and mBHB ≥0.10 mmol/L), only elevated mBHB (HYKL_BHB; mACE <0.15 mmol/L and mBHB ≥0.10 mmol/L), or only elevated mACE (HYKL_ACE; mACE ≥0.15 mmol/L and mBHB <0.10 mmol/L). Effects of parity, DIM, ketolactia group or subpopulation, and their interactions on mACE and mBHB concentrations were also determined using the mixed model that included ketolactia group or subpopulation as an independent variable. Across all data, mACE and mBHB concentrations were influenced by effects of parity, DIM, and their interaction as well as parity, DIM, ketolactia group or subpopulation, and their interactions. For all samples, mACE and mBHB concentrations decreased with increasing DIM, with mACE concentration declining more rapidly compared with mBHB. In the data set, 68% and 32% of all samples were defined as normal or HYKL, respectively. Among HYKL samples, mACE was elevated soon after calving and declined over time. In contrast, mBHB started lower after calving and increased reaching peak concentrations around 30 DIM, and then decreased. Within HYKL samples, 50.8, 41.3, and 7.9% were categorized as HYKL_ACEBHB, HYKL_BHB, and HYKL_ACE respectively. Between 6 and 21 DIM, 11.3% of HYKL were classified as HYKL_ACE. Primiparous cows had greater (14.8%) HYKL_ACE samples in this time period. In conclusion, this study has characterized mACE and mBHB concentrations during early lactation and determined effects of parity, DIM, and their interaction. Using published criteria interpreting mACE and mBHB concentrations, it was intriguing to identify a unique population of samples having elevated mACE without mBHB in early lactation, especially in primiparous cows. Further research is needed to determine if this sample population represents an unhealthy metabolic status that adversely affects cow health and performance.

Associations between the metabolic status of the cow and colostrum quality as determined by Brix refractometry

Supplying newborn calves with immunoglobins is critical for their health and a daily challenge in the dairy industry. Among various factors determining colostrum quality, the prepartum metabolic status of the cow might be of particular importance. The objective of this observational cross-sectional study was to evaluate relationships between cow-level variables and the colostrum quality as determined by Brix refractometry. A total of 873 cows of varying breed and parity from 124 German dairy herds were included in the study, and blood and urine samples were taken 3 to 1 wk before the expected calving date. Effectively, samples were collected on average 8.2 d (geometric mean) before calving, ranging from 2 to 45 d. The final variable set included body condition score, lameness score, breed, parity, vaccination of the cow, the activity of glutamate dehydrogenase and aspartate aminotransferase, the urine concentration of creatinine, net acid-base excretion, the serum concentration of cholesterol and calcium, and the difference in albumin and total protein concentration. Generalized linear mixed effects regression models with hierarchically structured random effects (cow within herd) using the maximum likelihood method were fitted to the data to identify associations between the Brix value as an outcome and cow-level variables as predictors. Cows entering second parity had lower Brix values compared with cows entering third or greater parity, and prepartum vaccination of cows led to higher Brix values compared with nonvaccinated cows. Cows with a moderate to high lameness score had lower Brix values than cows with low-grade lameness. An increase of glutamate dehydrogenase serum activity and serum calcium concentration were associated with lower Brix values, whereas an increase in the difference of total protein and albumin serum concentration led to higher Brix values. In conclusion, the metabolic health of the cow affects colostrum quality and may cause failure of passive immunoglobulin transfer as well as impaired calf health.

Milk fatty acids as indicators of negative energy balance of dairy cows in early lactation

Most dairy cows experience negative energy balance (NEB) in early lactation because energy demand for milk synthesis is not met by energy intake. Excessive NEB may lead to metabolic disorders and impaired fertility. To optimize herd management, it is useful to detect cows in NEB in early lactation, but direct calculation of NEB is not feasible in commercial herds. Alternative methods rely on fat-to-protein ratio in milk or on concentrations of non-esterified fatty acids (NEFA) and β-hydroxybutyrate (BHB) in blood. Here, we considered methods to assess energy balance (EB) of dairy cows based on the fatty acid (FA) composition in milk. Short- and medium-chain FAs (primarily, C14:0) are typically synthesized de novo in the mammary gland and their proportions in milk fat decrease during NEB. Long-chain FAs C18:0 and C18:1 cis-9 are typically released from body fat depots during NEB, and their proportions increase. In this study, these FAs were routinely determined by Fourier-transform infrared spectroscopy (FTIR) of individual milk samples. We performed an experiment on 85 dairy cows in early lactation, fed the same concentrate ration of up to 5 kg per day and forage ad libitum. Daily milk yield and feed intake were automatically recorded. During lactation weeks 2, 4, and 6 after calving, two milk samples were collected for FTIR spectroscopy, Tuesday evening and Wednesday morning, blood plasma samples were collected Thursday morning. Net energy content in feed and net energy required for maintenance and lactation were estimated to derive EB, which was used to compare alternative indicators of severe NEB. Linear univariate models for EB based on NEFA concentration (deviance explained = 0.13) and other metabolites in blood plasma were outperformed by models based on concentrations of metabolites in milk: fat (0.27), fat-to-protein ratio (0.18), BHB (0.20), and especially C18:0 (0.28) and C18:1 cis-9 (0.39). Analysis of generalized additive models (GAM) revealed that models based on milk variables performed better than those based on blood plasma (deviance explained 0.46 vs. 0.21). C18:0 and C18:1 cis-9 also performed better in severe NEB prediction for EB cut-off values ranging from -50 to 0 MJ NEL/d. Overall, concentrations of C18:0 and C18:1 cis-9 in milk, milk fat, and milk BHB were the best variables for early detection of cows in severe NEB. Thus, milk FA concentrations in whole milk can be useful to identify NEB in early-lactation cows.

Patterns of blood biochemical parameters of peripartum dairy cows raised in either smallholder or semi-commercial dairy farms in Thailand

Background and Aim:

Data about dynamics of serum biochemical parameters and negative energy balance (NEB) related conditions differ among geographical areas or farm types. It should be cautious about applying those data to justify control and prevention strategies of NEB problems. Therefore, dynamics of blood biochemical parameters related to NEB condition of peripartum dairy cows raised in either smallholder (SH) or semi-commercial (SC) farms were studied.

Materials and Methods:

Thirty-two healthy pregnant dry cows were selected from five dairy farms in Western part of Thailand, including 15 and 17 cows from three SH and two SC farms, respectively. Blood samples were collected at 2 weeks before the expected calving date, and 1, 2, 4, and 8 weeks postpartum to determine concentrations of glucose, non-esterified fatty acid (NEFA), and b-hydroxybutyrate (BHBA). Body condition scores (BCSs) and milk yields were also recorded.

Results:

Dairy cows in both farm types suffered from NEB by elevation of serum NEFA and BHBA, and loss of BCS postpartum. Degrees of elevation in serum NEFA and BHBA were different between farm types. The SC cows showed more BCS loss postpartum, but lower serum NEFA. In the SH cows, even with less BCS loss, the cows showed high serum NEFA concentrations.

Conclusion:

Dairy cows in our study entered NEB condition even with low milk yields. Moreover, elevation of serum NEFA and BHBA postpartum was higher in our studied cows as compared with other studies in high producing cows of commercial dairy farms in temperate areas.

Effects of a Multicomponent Herbal Extract on the Course of Subclinical Ketosis in Dairy Cows - a Blinded Placebo-controlled Field-study

A blinded placebo-controlled multi-center on-farm trial was conducted in dairy cows with subclinical ketosis to investigate effects of a multicomponent herbal extract. Blood ketone levels were measured weekly in early lactating cows from 16 Swiss herds. Cows were subclassified based on their initial blood-β-hydroxybutyrate levels (≥ 1.0 [KET-low, 84 cows] and > 1.2 mmol/L [KET-high, 39 cows]) and randomly distributed to 3 groups treated orally with herbal extract containing Camellia sinensis, Cichcorium intybus, Gentiana lutea, Glycyrrhiza glabra, Taraxacum officinale, Trigonella foenum-graecum, and Zingiber officinale, sodium propionate, or placebo twice a day for 5 days. Milk yield, milk acetone, blood-β-hydroxybutyrate, glucose, nonesterified fatty acids, gamma-glutamyl transferase, and glutamate dehydrogenase were analyzed over 2 wk. Linear mixed effect models were used for data analysis. No effects were found for nonesterifed fatty acids, gamma-glutamyl transferase, and glucose. Significantly higher glutamate dehydrogenase (29.71 U/L) values were found in herbal extract-treated animals compared to sodium propionate on day 7 (22.33 U/L). By trend, higher blood-β-hydroxybutyrate levels (1.36 mmol/L) were found in the placebo group of KET-high-cows on day 14 compared to the sodium propionate group (0.91 mmol/L). Milk yields of all treatment groups increased. Milking time and treatment showed a significant interaction for milk acetone: sodium propionate led to an immediate decrease, whereas herbal extracts resulted in a milk acetone decrease from day 7 on, reaching significantly lower milk acetone on day 14 (3.17 mg/L) when compared to placebo (4.89 mg/L). In conclusion, herbal extracts and sodium propionate are both likely to improve subclinical ketosis in dairy cows, however, by different modes of action.

Effect of hyperketonemia on the diurnal patterns of energy-related blood metabolites in early-lactation dairy cows

Most dairy cows experience a period of energy deficit in early lactation, resulting in increased plasma concentrations of nonesterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). Our objectives were to determine (1) the diurnal variation in plasma BHB and NEFA, (2) the correlation between plasma NEFA and BHB when accounting for diurnal changes, and (3) the effect of hyperketonemia (HYK) on the diurnal pattern of blood metabolites. Jugular catheters were placed in 28 multiparous Holstein cows between 3 and 9 days in milk, and blood samples were collected every 2 h for 96 h. Cows were retrospectively classified as HYK positive (HYK; n = 13) if they had plasma BHB concentrations ≥1.2 mmol/L for ≥3 study days, or HYK negative (non-HYK; n = 15) if they had plasma BHB concentrations ≥1.2 mmol/L for ≤2 study days. Generalized linear mixed models were used to analyze concentrations of analytes over time and differences in metabolites between HYK groups. The correlation between total plasma NEFA and BHB was analyzed by calculating the area under the curve for plasma NEFA and BHB for all cows. Plasma NEFA reached a peak approximately 2 h before morning feed delivery, falling to a nadir in the late evening. Plasma BHB was at a nadir at the time of morning feed delivery, peaking 4 h later. We observed a strong positive correlation between daily plasma NEFA and BHB. Additionally, HYK cows had greater concentrations of plasma NEFA and BHB than non-HYK cows. The HYK cows also experienced a greater magnitude of change in BHB throughout the day than the non-HYK cows. Our results suggest that the time relative to feeding should be considered when analyzing plasma metabolites, as classification of energy status may change throughout a day.

Fatty Acid Profiles from Routine Milk Recording as a Decision Tool for Body Weight Change of Dairy Cows after Calving

Cows mobilize body reserves during early lactation, which is reflected in the milk fatty acid (FA) profile. Milk FA can be routinely predicted by Fourier-transform infrared (FTIR) spectroscopy, and be, thus, used to develop an early indicator for bodyweight change (BWC) in early lactating cows in commercial dairy farms. Cow records from 165 herds in Denmark between 2015 and 2017 were used with bodyweight (BW) records at each milking from floor scales in automatic milking systems. Milk FA in monthly test-day samples was predicted by FTIR. Predictions of BWC were based on a random forest model and included parity, stage of lactation, and test day milk production and components (fat, protein, and FA). Bodyweight loss was mainly explained by decreased short-chain FA (C4:0-C10:0) and increased C18:0 FA. The root mean square error (RMSE) of prediction after cross-validation was 1.79 g/kg of BW (R2 of 0.94). Model evaluation with previously unseen BWC records resulted in reduced prediction performance (RMSE of 2.33 g/kg of BW; R2 of 0.31). An early warning system may be implemented for cows with a large BW loss during early lactation based on milk FA profiles, but model performance should be improved, ideally by using the full FTIR milk spectra.

Behavior, health, and productivity of early-lactation dairy cows supplemented with molasses in automated milking systems

The objective of this study was to determine the effect of molasses-based liquid feed (LF) supplementation within automated milking systems (AMS) on the behavior, health, and production of early-lactation dairy cows. In 6 commercial AMS dairy herds, 390 dairy cows were randomly assigned before calving to 1 of 2 treatments, within farm, balanced by parity: (1) control group (CON) receiving a standard AMS pellet [mean = 3.9 kg/d on a dry matter (DM) basis, n = 188], or (2) same amount of standard AMS pellet (mean = 3.6 kg/d on a DM basis, n = 202) plus 1 kg/d DM of LF for multiparous cows (1.6 kg/d as fed) and 0.88 kg/d DM for primiparous cows (1.4 kg/d as fed). Across farms, cows were fed partial mixed rations similar in ingredient and nutrient composition. Cows on the LF treatment received supplementation for the first 60 d in milk (DIM). Blood samples were taken 2 times/wk for the first 3 wk postcalving to assess β-hydroxybutyrate (BHB). Samples with BHB ≥1.2 mmol/L were classified as a positive case of subclinical ketosis (SCK). Cow body condition and lameness were scored every 10 d postcalving until 60 DIM. No differences were detected between treatments for milk yield (average milk yield = 37.4 ± 1.98 kg/d) and milking frequency (average milking frequency = 3.2 ± 0.01 times/d). Similarly, no difference between treatments in daily AMS visits was detected (average AMS visits = 5.3 ± 0.3 times/d). However, CON cows experienced more AMS refusals/d than LF cows (LF = 1.6 refusals/d, CON = 2.1 refusals/d). No difference between treatments in daily rumination time was detected (average rumination time = 476 ± 10.8 min/d). Treatment was associated with the number of times cows tested positive for SCK; cows on LF had fewer repeated diagnoses of SCK, such that 15% of cows on LF had ≥3 diagnoses of SCK out of 5 tests, compared with 27% of CON cows. Cows receiving molasses tended to have lower blood BHB values at ∼15 DIM. Molasses supplementation also allowed cows to maintain a more stable body condition score, as LF cows tended to lose less body condition over the first 60 DIM compared with CON cows. Overall, the results of this study demonstrate that supplementing a molasses-based LF to AMS cows may help support the energy demands of milk production in early lactation and, thus, reduce the incidence of repeat positive SCK tests during that time period.

Fasciola hepatica seroprevalence in Northern German dairy herds and associations with milk production parameters and milk ketone bodies

Infections with the liver fluke Fasciola hepatica remain a serious problem in dairy herds causing significant production losses. In sheep, a strong relationship between F. hepatica infections and an increase in serum ketone bodies due to reduced feed intake and liver damage was demonstrated. We hypothesized that F. hepatica infections might contribute to an increase in milk ketone bodies in dairy herds. Thus, the objective of the study was to estimate the association between F. hepatica bulk tank milk (BTM) antibodies and milk production parameters (milk yield, milk protein, fat yield), somatic cell count (SCC) and the milk ketone bodies ß-hydroxybutyrate (BHB) and acetone, inferred from Fourier transform infrared (FTIR) spectrometry, via linear mixed model analysis. A further aim was to follow up the F. hepatica seroprevalence in dairy herds in the northern German region East Frisia. We collected BTM samples between October and December from 1022 herds in 2017 and 1318 herds in 2018. Overall, 33.1 % of the herds tested positive in 2017 and 37.0 % in 2018, showing decreased F. hepatica seroprevalences compared to prior seroprevalence studies in the same region in 2010, 2008 and 2006 (> 45 % positive herds). We estimated a significant negative association (P < 0.001) between herd F. hepatica infection category and average milk yield with a loss of -1.62 kg per cow per day in strongly infected herds compared to BTM ELISA negative herds. Moreover, F. hepatica infection category had a significant effect on herd average milk protein and fat yield (P < 0.001), showing a decrease of 0.06 kg for both parameters from BTM ELISA negative herds to strongly infected herds. No significant association with milk SCC was found (P = 0.664). Regarding ketone bodies, we estimated significant higher average BHB values in strongly infected herds compared to the other three infection categories in the model analysis (P = 0.002). The association between F. hepatica infection category and acetone values was not significant (P = 0.079). Besides primary ketosis, fasciolosis should be considered as differential diagnosis in dairy herds with increased BHB values.

Serum adipokines play different roles in type I and II ketosis

Objective

This study was conducted to investigate the differences in several serum adipokines in perinatal dairy cows with type I and II ketosis, and the correlations between these adipokines and the two types of ketosis.

Methods

Serum adiponectin (ADP), leptin (LEP), resistin, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) levels, and energy balance indicators related to ketosis were measured. Type I and II ketosis were distinguished by serum glucose (Glu) and Y values and the correlations between adipokines in the two types of ketosis were analyzed.

Results

β-Hydroxybutyric acid of type I ketosis cows was significantly negatively correlated with insulin (INS) and LEP and had a significant positive correlation with serum ADP. In type II ketosis cows, ADP and LEP were significantly negatively correlated, and INS and resistin were significantly positively correlated. Revised quantitative INS sensitivity check index (RQUICKI) values had a significantly positive correlation with ADP and had a very significant and significant negative correlation with resistin, TNF-α, and IL-6. ADP was significantly negatively correlated with resistin and TNF-α, LEP had a significantly positive correlation with TNF-α, and a significantly positive correlation was shown among resistin, IL-6, and TNF-α. There was also a significant positive correlation between IL-6 and TNF-α.

Conclusion

INS, ADP, and LEP might exert biological influences to help the body recover from negative energy balance, whereas resistin, TNF-α, and IL-6 in type II ketosis cows exacerbated INS resistance and inhibited the production and secretion of ADP, weakened INS sensitivity, and liver protection function, and aggravated ketosis.

Prediction of blood metabolites from milk mid-infrared spectra in early-lactation cows

Dairy cows commonly experience an unbalanced energy status in early lactation, and this condition can lead to the onset of several metabolic disorders. Blood metabolic profile testing is a valid tool to monitor and detect the most common early lactation disorders, but blood sampling and analysis are time-consuming and expensive, and the procedure is invasive and stressful for the cows. Mid-infrared (MIR) spectroscopy is routinely used to analyze milk composition, being a cost-effective and nondestructive method. The present study aimed to assess the feasibility of using routine milk MIR spectra for the prediction of main blood metabolites in dairy cows, and to investigate associations between measured blood metabolites and milk traits. Twenty herds of Holstein Friesian, Brown Swiss, or Simmental cows located in Northeast Italy were visited 1 to 4 times between December 2017 and June 2018, and blood and milk samples were collected from all lactating cows within 35 d in milk. Concentrations of main blood metabolites and milk MIR spectra were recorded from 295 blood and milk samples and used to develop prediction models for blood metabolic traits through backward interval partial least squares analysis. Blood β-hydroxybutyrate (BHB), urea, and nonesterified fatty acids were the most predictable traits, with coefficients of determination of 0.63, 0.58, and 0.52, respectively. On the contrary, predictive performance for blood glucose, triglycerides, cholesterol, glutamic oxaloacetic transaminase, and glutamic pyruvic transaminase were not accurate. Associations of blood BHB and urea with their respective contents in milk were moderate to strong, whereas all other correlations were weak. Predicted blood BHB showed an improved performance in detecting cows with hyperketonemia (blood BHB ≥ 1.2 mmol/L), compared with commercial calibration equation for milk BHB. Results highlighted the opportunity of using milk MIR spectra to predict blood metabolites and thus to collect routine information on the metabolic status of early-lactation cows at a population level.

Association of mid-infrared-predicted milk and blood constituents with early-lactation disease, removal, and production outcomes in Holstein cows

Partial least squares regression estimates of milk and blood constituents using Fourier-transform mid-infrared (FTIR) analysis have shown promise as a tool for monitoring early-lactation excessive energy deficit in dairy herds. Our objective was to analyze milk via FTIR to determine the association of early-lactation predicted milk β-hydroxybutyrate (BHB) concentrations, predicted blood nonesterified fatty acid (NEFA) concentrations, and predicted milk de novo fatty acid (FA) percentages relative to total FA concentrations, with the risk of disease or removal in early lactation (hyperketonemia, displaced abomasum, metritis, culling, or death) and average daily milk yield during the first 15 wk of lactation. We enrolled 517 multiparous Holstein cows from 2 dairy farms in New York. Composite milk samples were collected twice weekly from 3 to 18 DIM for a total of 4 timepoints (T1, T2, T3, T4) and analyzed using FTIR spectrometry for milk BHB and FA composition and predicted blood NEFA. Blood samples were collected for hyperketonemia determination (BHB ≥ 1.2 mmol/L) using a handheld meter, and farm-diagnosed occurrence of disease or removal during the first 30 DIM and average daily milk yield during the first 15 wk of lactation were collected from herd management software. The incidence of disease or removal between 3 and 18 DIM was 20.2%. Explanatory models for disease or removal were developed for each predicted constituent of interest at each timepoint using fixed-effect multivariable Poisson regression. Repeated measures ANOVA models were developed for each predicted constituent to assess differences in average daily milk yield. For all timepoints, increased risk of disease or removal was associated with higher predicted milk BHB [relative risk (RR)_T1 = 2.0; RR_T2 = 3.4; RR_T3 = 5.2; RR_T4 = 9.1], higher predicted blood NEFA (RR_T1 = 2.7; RR_T2 = 2.5; RR_T3 = 3.8; RR_T4 = 10.0), and lower predicted milk de novo FA relative percentages (RR_T1 = 2.9; RR_T2 = 3.3; RR_T3 = 5.8; RR_T4 = 7.2). Average daily milk yield was increased for cows above the cut point for predicted milk BHB (2.1 kg/d) and predicted blood NEFA (3.5 kg/d) and below the cut point for de novo FA relative percentages (2.3 kg/d). Our results suggest that FTIR-predicted milk BHB, blood NEFA, and milk de novo FA relative percentages are promising indicators of subsequent disease or removal in early lactation; their positive relationship with milk yield warrants further exploration.

Hyperketolactia occurrence before or after artificial insemination is associated with a decreased pregnancy per artificial insemination in dairy cows

The reproductive parameters of dairy cattle have continuously declined worldwide over the last 50 years. Nutritional imbalances are identified as risk factors for this decrease of reproductive performance. The present paper aims to quantify the decrease in the pregnancy per artificial insemination (P/AI) in the case of high milk ketones before and after AI. A total of 388,731 test-day from the Brittany Milk Recording Program in France from 226,429 cow-lactations were provided for this trial. For each test-day, information about lactation characteristics, date of AI, date of the following calving, and acetone and β-hydroxybutyrate (BHB) values were included. Ketones were predicted by Fourier transform mid-infrared spectroscopy using MilkoScan Foss analyzers (Foss, Hillerød, Denmark). Many thresholds were evaluated to define cows with hyperketolactia. Hyperketolactia statuses were then categorized into 1 of 4 possible classes according to the milk ketone dynamics for each AI and each threshold of acetone or BHB values (low-low, high-low, low-high, and high-high) within 20 d before and after AI. Similarly, the dynamics of udder health were characterized by changes in somatic cell counts measured at the same test day as ketone bodies. A logistic regression with a Poisson correction was performed to explain the relationship of P/AI with milk ketones and somatic cell count dynamics. Predicted acetone and BHB ranged from -0.51 to 4.92 mM (mean = 0.08 mM, SD = 0.10 mM) and -0.62 to 5.85 mM (mean = 0.07 mM, SD = 0.1 mM), respectively. Hyperketolactia defined by high acetone levels before AI was not associated with decreased P/AI, but high acetone levels after AI were associated with a >10% reduction in P/AI for all thresholds >0.10 mM. Hyperketolactia, defined by high BHB values before, after, or before and after AI, was associated with a 6 to 14% reduction in P/AI compared with cows with low BHB values. These associations are lower than those reported in previous trials in which blood ketones were used. High ketones in advanced lactation are likely to be the result of various primary disorders (secondary ketosis). Because the present work demonstrated that this situation is considered a risk factor for deteriorated reproductive performance, we suggest that high ketones in early and advanced lactation should be of interest to farm advisors.

Short communication: Assessing the accuracy of inline milk fat-to-protein ratio data as an indicator of hyperketonemia in dairy cows in herds with automated milking systems

The objective of this study was to evaluate the accuracy of inline milk fat-to-protein (F:P) data to detect hyperketonemia (HYK) in herds with automated milking systems (AMS). The F:P ratio has been investigated as a tool for detecting HYK with moderate accuracy in past studies, but inline F:P data in AMS may also be useful for HYK screening. To assess the accuracy of these data in commercial settings, we monitored 484 cows from 9 AMS herds for their first 3 wk of lactation, taking blood samples once per week (n = 1,427). Positive cases of HYK were defined by whole-blood β-hydroxybutyrate (BHB) concentrations ≥1.2 or ≥1.4 mmol/L. Milk data were collected from the AMS software on each farm for each cow and converted into 4 different F:P values: (1) value from the same day as the BHB test; (2) 5-d centered-moving average (CMA); (3) 5-d backward-moving average (BMA); (4) 5-d forward-moving average (FMA). In linear regression models, all 4 values were associated with BHB, but slope estimates varied and R² were low: same day (slope = 0.95, R² = 0.07), CMA (slope = 1.05, R² = 0.07), BMA (slope = 0.65, R² = 0.04), and FMA (slope = 1.23, R² = 0.09). In logistic regression models, the odds of having HYK (BHB ≥1.2 mmol/L) increased with every 0.1-unit increase from the mean F:P ratio (1.16) using same-day values (odds ratio = 1.35, 95% confidence interval = 1.25-1.47) and CMA (odds ratio = 1.39, 95% confidence interval = 1.27-1.51). The same increase in F:P from mean BMA (1.14) and FMA (1.17) was associated with 1.22 and 1.49 times the odds of HYK, respectively. For all 4 F:P variations, we evaluated the sensitivity, specificity, positive predictive value, and negative predictive value of different F:P thresholds with HYK status. As the F:P threshold increased from 1.17 to 1.50, sensitivity decreased (range: 77 to 9%) but specificity increased (range: 58 to 96%). Same-day and CMA F:P cutoffs at which a balance was reached between sensitivity and specificity ranged from 1.18 to 1.22; however, even at these values we found high rates of false positives and negatives (range: 31-39%). These results suggest that inline milk F:P data from inconsistently calibrated sensors should not be used alone to detect HYK in AMS herds.

Prevalence of excessive negative energy balance in commercial United Kingdom dairy herds

The objectives of this study were to determine the individual animal and herd level prevalence of excessive negative energy balance (eNEB) in commercial UK dairy herds. Between April 2006 and March 2015, blood samples from 84,369 individual cows from 1748 different UK farms were received by a commercial laboratory service specializing in dairy cow nutritional monitoring. Following removal of all potential duplicate cows, the final dataset comprised 69,161 unique individual cows. The prevalence of eNEB was determined using plasma thresholds of β-hydroxybutyrate (BHB), non-esterified fatty acids (NEFA) and glucose. Overall prevalence of subclinical ketosis (SCK) in the first 20 days of lactation was 28.5%, 17.3% and 11.7% using BHB thresholds of 1.0, 1.2 and 1.4 mmol/L respectively. Prevalence of NEFA values ≥0.5 mmol/L in the last 10 days prior to calving was 26.0%, and 40.3% of cows had NEFA values ≥0.7 mmol/L in the first 20 days in milk (DIM). Combining BHB, NEFA and glucose showed that 52.0% of cows had one or more of the three biochemical measures of energy balance outside the respective threshold value in the last 10 days pre-calving, and 75.2% of cows showed a similar biochemical pattern in the first 20 DIM. The median herd prevalence of elevated BHB and/or NEFA was 37.5% in late pregnancy and 59.8% in the first 20 DIM, with substantial herd variation. Using multiple measures for the assessment of energy balance, this study has shown that eNEB affects substantial numbers of UK dairy cows.

Short communication: Validation of a test-day milk test for β-hydroxybutyrate for identifying cows with hyperketonemia

Subclinical ketosis is a common metabolic disorder affecting dairy cattle that results in a greater risk for the development of subsequent metabolic and infectious disease. Canwest Dairy Herd Improvement (DHI; Guelph, ON, Canada) has begun to use an infrared test (MilkoScan FT600, Foss Analytical A/S, Hillerød, Denmark) applied to metered composite milk samples to detect β-hydroxybutyrate (BHB) levels as a herd surveillance test for hyperketonemia. However, the test has not been compared with the gold standard, serum BHB as determined in a reference diagnostic laboratory. The objective of this cross-sectional diagnostic accuracy study was to validate the DHI milk BHB test to identify cows with hyperketonemia as determined by quantification of BHB in serum. A total of 316 cows from 17 dairy herds in southwestern Ontario had a milk and blood sample taken. Milk was collected at a routine DHI test, and blood from the same cow was sampled within 24 h of the milk test. The BHB concentration in milk was determined using the DHI milk BHB test, and serum was sent to the Animal Health Laboratory at the University of Guelph (Guelph, ON, Canada). A nonparametric receiver operating characteristic curve was generated to compare DHI milk BHB concentrations with serum BHB concentrations. Overall, a total of 34 cows (11%) had a level of serum BHB ≥1.2 mmol/L. The concentration of DHI milk BHB was moderately correlated with the concentration of serum BHB, yielding a coefficient of determination value of 0.61. The optimal cut point for determining hyperketonemia (≥1.2 mmol/L) on the DHI milk BHB test was ≥0.14 mmol/L, yielding a sensitivity of 81% and specificity of 92%. The performance of the DHI milk BHB test varied depending on the days in milk (DIM) of the cows tested, with a higher specificity being found in cows that were ≤25 DIM compared with cows tested >25 DIM. If the herd-level prevalence of hyperketonemia was ≥14%, the DHI milk BHB test had an improved sensitivity when compared with a herd-level prevalence of <14%. This study demonstrates that the DHI milk BHB test is a reliable measure for evaluating hyperketonemia using routine DHI milk samples and could be used as a herd-level monitoring tool for ketosis when evaluating nutritional management or preventative medicine strategies.

A 100-Year Review: Metabolic modifiers in dairy cattle nutrition

The first issue of the Journal of Dairy Science in 1917 opened with the text of the speech by Raymond A. Pearson, president of the Iowa State College of Agriculture, at the dedication of the new dairy building at the University of Nebraska (J. Dairy Sci. 1:4-18, 1917). Fittingly, this was the birth of a new research facility and more importantly, the beginning of a new journal devoted to the sciences of milk production and manufacture of products from milk. Metabolic modifiers of dairy cow metabolism enhance, change, or interfere with normal metabolic processes in the ruminant digestive tract or alter postabsorption partitioning of nutrients among body tissues. Papers on metabolic modifiers became more frequent in the journal around 1950. Dairy farming changed radically between 1955 and 1965. Changes in housing and feeding moved more cows outside, and cows and heifers in all stages of lactation, including the dry period, were fed as a single group. Rations became wetter with the shift to corn silage as the major forage in many rations. Liberal grain feeding met the requirements of high-producing cows and increased production per cow but introduced new challenges; for example, managing and feeding cows as a group. These changes led to the introduction of new strategies that identified and expanded the use of metabolic modifiers. Research was directed at characterizing the new problems for the dairy cow created by group feeding. Metabolic modifiers went beyond feeding the cow and included environmental and housing factors and additives to reduce the incidence and severity of many new conditions and pathologies. New collaborations began among dairy cattle specialties that broadened our understanding of the workings of the cow. The Journal of Dairy Science then and now plays an enormously important role in dissemination of the findings of dairy scientists worldwide that address existing and new technologies.

Descriptive study for culling and mortality in five high-producing Spanish dairy cattle farms (2006-2016)

Background

High turnover rate in dairy farms due to culling and mortality is associated with poor animal welfare, an increase in production costs and lower economic benefits for the dairy farm. Understanding cow elimination better would help to formulate specific prevention measures and improve the efficiency of milk production in dairy farms. Culling and mortality data from five standard high-producing dairy farms in Spain were analysed over a period of 11 years (2006–2016). Data were collected by the same veterinary team and using the same software system.

Results

Significant between-herd differences in eliminated cows were observed for type of elimination (slaughter or death on the farm), age at elimination, cause of elimination, number of lactations and production parameters, such as total days in milk, life milk yield, litres per day of productive life and litres per day of life. Culling and mortality were higher during the hot season and for cows of second and third parities. Between-herd differences were observed. Reproductive disorders (30.2%) were the most frequent reason for elimination, with low production (23.4%) being the second most frequent reason. Accidents on the farm (7.7%) were a more frequent cause of elimination than metabolic diseases (7.2%), locomotor disorders (2.4%) and obstetrics (2.4%).

Conclusions

Veterinary teams or farmers’ associations can use culling and mortality information for benchmarking cow farms if data collection and analysis is standardised for comparability. The analysis of culling and mortality information should help farmers to improve efficiency.

Electronic supplementary material

The online version of this article (10.1186/s13028-018-0399-z) contains supplementary material, which is available to authorized users.

Risk factors for clinical ketosis and association with milk production and reproduction variables in dairy cows in a hot environment

The aims of the present study were to investigate (1) the risk factors that influence the occurrence of clinical ketosis (CK; blood β-hydroxybutyrate > 3.0 mmol/L) and (2) to determine the influence of subclinical ketosis (SCK; 1.2 ≤ β-hydroxybutyrate ≤ 2.9 mmol/L) and CK on reproductive performance and milk yield in high-yielding Holstein cows in a hot environment. Cows (n = 345) were blood sampled from 6 to 15 days postpartum for β-hydroxybutyrate (BHB) determination with a hand-held meter. Cows calving in spring had 3.7 increased odds of having CK (20.7% incidence) than cows calving in summer (3.9% incidence) and autumn (9.4% incidence). Temperature-humidity index < 83 was associated with 1.6 times higher risk for CK compared with cows calving in warmer days. First-service conception rate was 12 and 16 percentage point higher (P < 0.05) in nonketotic cows compared with cows with SCK and CK, respectively. Actual 305-day milk yields for healthy, SCK, and CK cows were 9991 ± 1411, 10,123 ± 1442, and 10,386 ± 1435 kg (mean ± SD), respectively, with no difference (P > 0.05) between groups. In conclusion, this study documented that ketosis was seasonal with lower incidence of this metabolic disease during hot seasons and with increased ambient temperature at calving. Also, 305-day milk yield of Holstein cows was not related to blood BHB content early in lactation in this hot environment. However, elevated circulating BHB was negatively associated with conception rate at first service and fetal losses.

A randomized controlled trial on the effect of incomplete milking during early lactation on ketonemia and body condition loss in Holstein dairy cows

Limiting milk production for a short period of time in early lactation could be a relevant strategy to prevent hyperketonemia (HYK). From December 2013 to March 2015, 838 multiparous Holstein cows from 13 herds were enrolled in a randomized controlled trial evaluating the effect of incomplete milking in early lactation on ketonemia and its effect on body condition score (BCS) loss. Cows were randomly assigned 4 wk before expected calving date to 1 of 2 treatment groups, (1) a conventional milking protocol (CON) for which cows were completely milked or (2) an incomplete milking protocol (INC) for which a maximum of 10 to 14 kg of milk/d were withdrawn during the first 5 d in milk (DIM). β-Hydroxybutyrate (BHB) concentrations were measured from blood samples collected on each cow 3 times at weekly intervals. Hyperketonemia was defined as BHB ≥1.4 mmol/L. Body condition score variation in the postcalving period was calculated by subtracting BCS assessed at wk 7 from BCS assessed at first week after calving. Effect of treatment on ketonemia and prevalence of HYK were evaluated for 4 specific time periods: 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM. Effect of treatment on ketonemia was investigated using linear mixed models with natural logarithm of BHB measurements as outcome and treatment groups as fixed effect. Generalized linear mixed models with HYK as outcome, using logit link, and treatment groups as fixed effect were used to investigate effect of treatment on odds of HYK. A logistic regression model with BCS loss (<0.75 or ≥0.75) as outcome and treatment groups and herd as fixed effects was used to study effect of INC on odds of having BCS loss ≥0.75. A total of 813 lactations had complete data and were used for statistical analysis of ketonemia and HYK. A total of 709 lactations had complete data and were used for analysis of BCS loss. Geometric means of blood BHB concentrations during the 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM periods were, respectively, 0.72 (95% confidence interval = 0.66, 0.80), 0.66 (0.60, 0.73), 0.90 (0.80, 1.01), and 0.93 (0.83, 1.05) mmol/L for INC, and 0.65 (0.59, 0.72), 0.79 (0.72, 0.87), 0.94 (0.84, 1.06), and 0.92 (0.82, 1.04) mmol/L for CON. Cows in INC group had lower ketonemia during the 4 to 7 DIM period. Predicted prevalence of HYK during the 1 to 3, 4 to 7, 8 to 17, and 18 to 26 DIM periods were, respectively, 2.8 (3.2, 15.1), 4.6 (2.0, 10.0), 13.4 (8.4, 20.0), and 23.0% (17.4, 29.7) for INC and 2.6 (2.5, 13.8), 10.7 (5.6, 19.3), 19.4 (13.0, 27.9), and 21.3% (16.0, 27.8) for CON. The INC treatment reduced the prevalence of HYK during the 4 to 7 and 8 to 17 DIM periods. No association was observed between INC and BCS loss in the postcalving period. Overall, the incomplete milking protocol was effective for reducing ketonemia and prevalence of HYK during the early postpartum period.

Predicting hyperketonemia by logistic and linear regression using test-day milk and performance variables in early-lactation Holstein and Jersey cows

Although cowside testing strategies for diagnosing hyperketonemia (HYK) are available, many are labor intensive and costly, and some lack sufficient accuracy. Predicting milk ketone bodies by Fourier transform infrared spectrometry during routine milk sampling may offer a more practical monitoring strategy. The objectives of this study were to (1) develop linear and logistic regression models using all available test-day milk and performance variables for predicting HYK and (2) compare prediction methods (Fourier transform infrared milk ketone bodies, linear regression models, and logistic regression models) to determine which is the most predictive of HYK. Given the data available, a secondary objective was to evaluate differences in test-day milk and performance variables (continuous measurements) between Holsteins and Jerseys and between cows with or without HYK within breed. Blood samples were collected on the same day as milk sampling from 658 Holstein and 468 Jersey cows between 5 and 20 d in milk (DIM). Diagnosis of HYK was at a serum β-hydroxybutyrate (BHB) concentration ≥1.2 mmol/L. Concentrations of milk BHB and acetone were predicted by Fourier transform infrared spectrometry (Foss Analytical, Hillerød, Denmark). Thresholds of milk BHB and acetone were tested for diagnostic accuracy, and logistic models were built from continuous variables to predict HYK in primiparous and multiparous cows within breed. Linear models were constructed from continuous variables for primiparous and multiparous cows within breed that were 5 to 11 DIM or 12 to 20 DIM. Milk ketone body thresholds diagnosed HYK with 64.0 to 92.9% accuracy in Holsteins and 59.1 to 86.6% accuracy in Jerseys. Logistic models predicted HYK with 82.6 to 97.3% accuracy. Internally cross-validated multiple linear regression models diagnosed HYK of Holstein cows with 97.8% accuracy for primiparous and 83.3% accuracy for multiparous cows. Accuracy of Jersey models was 81.3% in primiparous and 83.4% in multiparous cows. These results suggest that predicting serum BHB from continuous test-day milk and performance variables could serve as a valuable diagnostic tool for monitoring HYK in Holstein and Jersey herds.