Effects of calving interval of dairy cows on development, metabolism and milk performance of their offspring.

Extending the voluntary waiting period (VWP) for insemination in dairy cows is of interest to reduce the frequency of calving events and inseminate at a moment with fewer fertility problems. Little is known about the calves born from dams with a different VWP followed by a different calving interval (CInt). The objective of the current study was to identify the effect of dam's CInt on body condition, metabolic status, and milk production of their offspring from birth till 100 DIM of the offspring's first lactation. Holstein Friesian dairy cows (n = 154, 41 primiparous, 113 multiparous) were blocked according to parity, milk yield, and somatic cell count (SCC), and randomly assigned to a VWP of 50, 125, or 200 d. Female calves (n = 62) from cows with different CInt were monitored from birth until their first calving event as heifer. Certain dams were not successfully inseminated soon after the planned VWP, resulting in differences between the intended VWP and the actual CInt. Calves were regrouped according to their dam's actual CInt (CInt_1: 324 - 408 d; CInt_2: 409 - 468 d; CInt_3: 469 - 586 d). The dam's CInt did not affect calf birth weight. From birth to weaning, the calves born to dams in CInt_1 (0.34 mmol/L (confidence interval (CI): 0.30, 0.37) had a higher plasma nonesterified fatty acids (NEFA) concentration than CInt_2 (0.28 mmol/L (CI: 0.26, 0.31)) and CInt_3 (0.26 mmol/L (CI: 0.24, 0.29)) calves. Calves born to dams with a shorter CInt (CInt_1) had greater IgG and IgM against keyhole limpet hemocyanin (KLH) than CInt_3 (IgG: 6.05 ± 0.30 vs. 4.64 ± 0.30; IgM: 6.45 ± 0.17 vs. 5.89 ± 0.16, respectively) before weaning. After weaning till calving, CInt_1-calves tended to have greater plasma NEFA concentration than CInt_3-calves. During the first 100 d in milk, a longer CInt of the dams resulted in lower plasma IGF_1 (CInt_2), lower milk lactose (CInt_3) and fat and protein corrected milk (FPCM) (CInt_2) in offspring, compared with shorter CInt of the dams (CInt_1). Collectively, a longer CInt in dams did not affect birth weight of their calves or body weight during the weaning or rearing phase. From birth till weaning, a longer CInt in dams resulted in less IgG against KLH and lower plasma NEFA concentration in plasma of the calves. During the first lactation of their offspring, a longer CInt in dams can result in a lower plasma IGF_1 and FPCM during the first 100 DIM, although effects were not present in all CInt categories.

Effects of endogenous DHA milk and exogenous DHA milk on oxidative stress and cognition in SAMP8 mice.

In this study, Senescence Accelerated Mice (SAMP8) were supplemented with exogenous DHA milk, endogenous DHA milk, normal milk, or 0.9 % saline solution. Enzyme-linked immunosorbent assay (ELISA), gas chromatography (GC), ultra-performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI MS/MS), and Morris water maze were used to characterize the effects of diet on oxidative stress and cognition in SAMP8 mice. Supplementation endogenous DHA milk or exogenous DHA milk can enhance the antioxidant capacity of mice organs. Endogenous DHA milk increased the superoxide dismutase (SOD) activity of mice brain and serum than normal milk and 0.9 % saline solution (P ≤ 0.05), as well as increased SOD activity of mice liver and glutathione peroxidase (GSH-Px) activity of mice brain than normal milk (P ≤ 0.05). Exogenous DHA milk increased SOD activity of mice brain than normal milk and 0.9 % saline solution, as well as increased SOD activity of mice serum than 0.9 % saline solution (P ≤ 0.05). Several polar lipid relative content, such as 18:0/18:2 PS, 17:0 Ceramide, and 20:4 LPC in mice brain was affected by dietary supplementation with DHA-containing milk. Lipid oxidation metabolites in mice brain were not affected by DHA-containing milk. Endogenous DHA milk increased the number of platform location crossing times of mice in the Morris water maze test, compared with Exogenous DHA milk, normal milk, and 0.9 % saline solution (P ≤ 0.05).

Effect of voluntary waiting period on metabolism of dairy cows during different phases of the lactation.

An extended calving interval (CInt) by extending the voluntary waiting period (VWP) could be associated with altered metabolism in dairy cows. The aim of this study was first to evaluate the effects of VWP on metabolism and body condition during the first 305 d after the first calving in the experiment (calving 1), around the end of the VWP, and during pregnancy (280 d before calving 2). Second, the effects of the VWP on metabolism were determined from 2 wk before until 6 wk after calving 2. Third, individual cow characteristics were used to predict milk production and body condition of cows after different VWP. Holstein-Friesian cows (N = 154, 41 primiparous [PP], 113 multiparous [MP]) were blocked for parity, milk production, and lactation persistency, randomly assigned to a VWP of 50, 125, or 200 d (VWP50, VWP125, or VWP200) and followed from calving 1 until 6 wk after calving 2. In the first 6 wk after calving 1 and from 2 wk before until 6 wk after calving 2, weekly plasma samples were analyzed for nonesterified fatty acids (NEFA), ß-hydroxybutyrate, glucose, insulin, and insulin-like growth factor 1 (IGF-1). From wk 7 after calving 1 until 2 wk before calving 2, insulin and IGF-1 were analyzed every 2 wk. Fat- and protein-corrected milk (FPCM) and body weight (BW) gain were measured weekly. Cows were divided in two parity classes based on calving 1 (PP and MP) and remained in these classes after calving 2. During pregnancy, MP cows in VWP200 had greater plasma insulin and IGF-1 concentration and lower FPCM compared with MP cows in VWP125 (insulin: 18.5 vs. 13.9 µU/mL, CI 13.0-19.7, P < 0.01; IGF-1: 198.5 vs. 175.3 ng/mL ± 5.3, P = 0.04; FPCM: 22.6 vs. 30.0 kg/d ± 0.8, P < 0.01) or VWP50 (insulin: 15.8 µU/mL, P < 0.01; IGF-1: 178.2 ng/mL, P < 0.01; FPCM: 26.6 kg/d, P < 0.01) and had a greater daily BW gain compared with cows in VWP50 (3.6 vs. 2.5 kg/d ± 0.2; P < 0.01). After calving 2, MP cows in VWP200 had greater plasma NEFA concentration (0.41 mmol/liter) compared with MP cows in VWP125 (0.30 mmol/liter, P = 0.04) or VWP50 (0.26 mmol/liter, P < 0.01). For PP cows, the VWP did not affect FPCM or body condition during the first lactation in the experiment, or metabolism after calving 2. Independent of the VWP, higher milk production and lower body condition before insemination were associated with higher milk production and lower body condition at the end of the lactation. Variation in these characteristics among cows could call for an individual approach for an extended VWP.

Extending the voluntary waiting period (VWP) reduces the frequency of calvings. This may benefit cow health but includes the risk of fattening and low milk yield at the end of the lactation. The aim of this study was to evaluate the effects of the VWP on metabolism and body condition during different phases of the lactation and start of the next lactation. Moreover, individual cow characteristics in early lactation were used to predict milk production and body condition of cows after different VWP. An extended VWP did not affect milk production or metabolism of primiparous cows. Multiparous cows with an extended VWP had a greater plasma insulin concentration and a lower milk production around the end of the VWP and during pregnancy, and a greater body condition during pregnancy. A higher milk production and a lower body condition before successful insemination were associated with a higher milk production and a lower body condition at the end of the lactation. Therefore, selecting multiparous cows with a higher milk production and a lower body condition for an extended lactation may reduce the risk of fattening and low milk production at the end of the lactation, while still having the benefit of a reduced frequency of calvings.

Udder health of dairy cows with an extended voluntary waiting period from calving until the first insemination.

This study aimed to evaluate the effect of an extended voluntary waiting period (VWP) on SCC, SCC elevations and clinical mastitis incidence during the complete lactation and the first 6 weeks of the next lactation. Holstein-Friesian dairy cows (N = 154) were blocked for parity, expected milk yield, calving season and breeding value for persistency and were randomly distributed across 3 VWP (50, 125, or 200 d: VWP-50, VWP-125, VWP-200). Cows were monitored from calving until 6 weeks into the next lactation, or until culling. An elevation of SCC in milk was defined as SCC in milk ≥200 000 cells/ml after two previous weeks with SCC < 200 000 cells/ml. Over the complete lactation, extending the VWP did not affect SCC elevations and the occurrence of clinical mastitis per lactation or per cow per year. There was no clear effect of VWP length on SCC in the complete lactation, except that multiparous cows in VWP-125 had a higher SCC compared with multiparous cows in VWP-50. Dry-off antibiotic usage per cow per year was lower in VWP-200 compared with VWP-50 for multiparous cows. In the first 6 weeks of the next lactation, cows in VWP-200 had a higher SCC compared with cows in VWP-50, with no effect of VWP on the number of elevations of SCC or the occurrence of clinical mastitis. Extending the VWP may therefore be used to reduce the frequency of transition periods and the associated use of dry-cow antibiotics, with limited impact on udder health, and a similar occurrence of SCC elevations and clinical mastitis per year.

Consequences of extending the voluntary waiting period for insemination on reproductive performance in dairy cows.

The aim of the study was to evaluate the effect of extended voluntary waiting period (VWP) on ovarian cyclicity and reproductive performance of dairy cows. Holstein-Friesian dairy cows (N = 154) were blocked and randomly assigned to one of 3 groups with different VWP (50, 125 or 200 d: VWP-50, VWP-125 or VWP-200). Milk samples were collected 3 times a week and analysed for progesterone concentration. Ovarian cycles were classified as: normal (18-24 days), short (<18 days) or prolonged (>24 days). For cows that became pregnant within 100 days after VWP, a VWP-200 d was related with fewer days until pregnancy after end of the VWP (19.4 d) compared with VWP-50 or VWP-125 (35.5, 37.3 d respectively). During 100 days (-50 until 50 d) around the end of VWP, cows in VWP-200 had a greater percentage of normal cycles (91.9 vs 58.0 %, P < 0.01) and a lower percentage of prolonged cycles (6.0 vs 32.7 %, P = 0.01) compared with cows in VWP-50. In the 4 weeks around the end of the VWP, cows in VWP-125 and VWP-200 had a lower milk yield compared with cows in VWP-50 (32.0, 27.5 vs 37.4 kg/d, P < 0.01). Inseminations continued until 300 days in milk, resulting in fewer pregnant cows for longer VWPs. In conclusion, extending the VWP from 50 to 125 or 200 days resulted in a greater percentage of cows with normal ovarian cycles and a lower milk yield around the end of VWP. Moreover, VWP-200 reduced days open after the end of the VWP, compared with VWP-50.

Effect of Prepartum Dietary Energy Level on Production and Reproduction in Nili Ravi Buffaloes.

The objective of this study was to evaluate the effect of prepartum dietary energy level on postpartum production and reproduction in Nili Ravi buffaloes (n = 21). The buffaloes were offered low energy (LE: 1.31 Mcal/kg DM NEL (net energy for lactation)), medium energy (ME: 1.42 Mcal/kg DM NEL) or high energy (HE: 1.54 Mcal/kg DM NEL) diet for 63 days prepartum, and received the same lactation diet (LD: 1.22 Mcal/kg DM NEL) during 14 weeks postpartum. The effects of dietary energy level and week were analyzed with Proc GLIMMIX model. Dry matter intake (DMI) was lower in buffaloes fed the LE diet compared with buffaloes fed the ME or HE diet. Calf birth weight (CBW) was higher in buffaloes fed the HE diet compared with buffaloes fed the ME or LE diet. Milk production was similar in buffaloes fed the HE, ME or LE diet within 14 weeks postpartum and throughout the lactation. Milk fat was higher in buffaloes fed the LE diet compared with buffaloes fed the ME or HE diet. Milk protein and lactose yields was high in buffaloes fed the HE diet compared with buffaloes fed the ME or LE diet. Body condition score was high in HE and was affected by diet × week interactions during pre and postpartum period. The concentrations of ß-hydroxybutyrate (BHBA) and triglycerides in serum was lowest in buffaloes fed the HE diet compared with the buffaloes fed the ME or LE diet. The buffaloes fed the HE diet had early uterine involution (UI), first estrus, short dry days, and calving interval (CI) compared with buffaloes fed the ME or LE diet. None of buffaloes fed the LE diet exhibited estrus during the first 14 weeks postpartum compared with buffaloes fed the ME or HE diet. In conclusion, prepartum feeding of high energy diet can be helpful in improving the postpartum productive and reproductive performance in Nili Ravi buffaloes.

Extending lactation length: consequences for cow, calf, and farmer.

Traditionally, a 1-yr calving interval is advised to farmers from an economical point of view, to realize a yearly peak in milk yield. A 1-yr calving interval, however, implies a yearly event of drying-off, calving and start of lactation, which are all associated with an increased risk for diseases and disorders. Deliberately extending the lactation length by extending the voluntary waiting period (VWP) for first insemination reduces the frequency of these challenging events. This reduction in frequency of calvings can be beneficial for cow health and fertility, but also can be of interest to reduce the number of surplus calves and labor associated with drying off, calving, and disease treatments. Current concerns with respect to an extended lactation are that milk yield is too low in late lactation, which might be associated with an increased risk of fattening of cows in late lactation, and compromised economic returns at herd level. In addition, limited knowledge is available with respect to consequences for cow performance in the subsequent lactation and for calves born to cows with an extended lactation. Moreover, response of dairy cows to an extended VWP depends on individual cow characteristics like parity, milk yield level or body condition. A customized strategy based on individual cow characteristics can be a future approach to select high-producing cows with persistent lactation curves for an extended lactation to limit the risk for fattening and milk yield reduction at the end of the lactation while benefitting from a reduction in challenging events around calving.

Traditionally, a 1-yr calving interval is advised to dairy farmers to realize a yearly peak in milk yield. A 1-yr calving interval, however, implies a yearly event of drying-off, calving, and start of lactation, which are all associated with an increased risk for diseases and disorders. Deliberately extending the lactation length reduces the frequency of these challenging events both for individual cows and at herd level. This reduction in frequency of calvings can be beneficial for cow health and fertility, but also can be of interest to reduce the number of surplus calves and labor associated with drying off, calving, and disease treatments. Current concerns with respect to an extended lactation are that milk yield is too low and cows can get fat in late lactation. Moreover, limited knowledge is available with respect to consequences for cows in the subsequent lactation and for calves born to cows with an extended lactation. Moreover, response of dairy cows to an extended voluntary waiting period depended on individual cow characteristics such as parity, milk yield level, or body condition. A customized strategy based on individual cow characteristics can be a future approach to select suitable cows for an extended lactation.

Correlations of feed intake predicted with milk infrared spectra and breeding values in the Dutch Holstein population.

Feed is a major cost in dairy production, and substantial genetic variation in feed efficiency exists between cows. Therefore, breeders aim to improve feed efficiency of dairy cattle. However, phenotypic data on individual feed intake on commercial farms is scarce, and accurate measurements are very costly. Several studies have shown that information from Fourier-transformed infrared spectra of milk samples (milk infrared, milk IR) can be used to predict phenotypes such as energy balance and energy intake, but this is usually based on small data sets obtained under experimental circumstances. The added value of information from milk IR spectra for estimation of breeding values is unknown. The objectives of this study were (1) to develop prediction equations for dry matter intake (DMI) and residual DMI (rDMI) from milk IR spectra; (2) to apply these for a data set of milk IR spectra from commercial Dutch dairy farms; (3) to estimate genetic parameters for these traits; and (4) to estimate correlations between these predictions and other traits in the breeding goal. We used data from feeding trials where individual feed intake was recorded daily and for which milk IR spectra were determined weekly to develop prediction equations for DMI and rDMI with partial least squares regression. This data set contained over 7,600 weekly averaged DMI records linked with milk IR spectra from 271 cows. The equations were applied for a data set with test day information from 676 Dutch dairy herds with 621,567 records of 78,488 cows. Both milk IR-predicted DMI and rDMI were analyzed with an animal model to obtain genetic parameters and sire effect estimates that could be correlated with breeding values. A partial least squares regression model with 10 components from the milk IR spectra explained around 25% of DMI variation and less than 10% of rDMI variation in the validation set. Nearly all variation in the milk IR spectra was captured by 7 components; additional components contributed marginally to the spectral variation but decreased prediction errors for both traits. Accuracies of predictions of DMI and rDMI from milk IR spectra for a large feeding experiment were 0.47 and 0.26 on average, respectively, with small differences between ration treatments (ranging from 0.43 to 0.55 and from 0.21 to 0.34, respectively) and among lactation stages (ranging from 0.24 to 0.59 and from 0.13 to 0.36, respectively), with the highest prediction accuracies in early lactation. The estimated heritabilities for predicted DMI and rDMI were 0.3 and 0.4, respectively, which suggests genetic potential for both predicted traits. The correlations of sire estimates for milk IR-predicted DMI with official Dutch breeding values were strongest with milk production (0.33), longevity (0.26), and fertility (-0.27), indicating that cows that eat more produce more, live longer, and have poorer fertility. The correlations of sire estimates for predicted DMI and rDMI with the official breeding values for DMI were low (0.14 and 0.03, respectively). This implies that the added value of including milk IR-predicted DMI information in the estimation procedure of breeding values for DMI would be considered insufficient for practical application.

Consequences of Transition Treatments on Fertility and Associated Metabolic Status for Dairy Cows in Early Lactation.

This study aimed to (1) investigate effects of reducing postpartum dietary energy level for cows after a 0-d dry period (DP) on resumption of ovarian cyclicity and reproductive performance, (2) relate days open with other reproductive measures, and (3) relate onset of luteal activity (OLA) and days open with metabolic status in early lactation. Holstein-Friesian dairy cows were randomly assigned to 1 of 3 transition treatments: no DP and low postpartum dietary energy level from 22 days in milk( DIM )onwards (0-d DP (LOW)) (n = 42), no DP and standard postpartum dietary energy level (0-d DP (STD)) (n = 43), and a short DP and standard postpartum dietary energy level (30-d DP (STD)) (n = 43). Milk progesterone concentration was determined three times per week until 100 DIM. Plasma metabolite and hormone concentrations were measured weekly until week 7 postpartum. Reducing postpartum dietary energy level in older cows (parity ≥ 3) after no DP and 22 DIM did not affect milk production but prevented a positive energy balance and shortened the interval from calving to OLA. In addition, services per pregnancy and days open were reduced in cows of parity ≥ 3 on 0-d DP (LOW), compared with cows of parity ≥ 3 with 0-d DP (STD), but not in cows of parity 2.

Metabolomics of Milk Reflects a Negative Energy Balance in Cows.

Dairy cows can experience a negative energy balance (NEB) in early lactation when feed intake is too low to meet the energy requirements for body maintenance and milk production. Metabolic changes occur in mammary gland cells of animals experiencing a negative energy balance. We studied these metabolic changes in milk samples from dairy cows in relation to energy balance status using liquid chromatography-mass spectrometry (QQQ-LC-MS) and nuclear magnetic resonance (1H NMR). NMR and LC-MS techniques are complementary techniques that enabled a comprehensive overview of milk metabolites in our study. Energy balance and milk samples were obtained from 87 dairy cows. A total of 55 milk metabolites were reliably detected, of which 15 metabolites were positively correlated to energy balance and 20 were negatively correlated to energy balance. Cows in NEB produced more milk with increased milk fat yield and higher concentrations of citrate, cis-aconitate, creatinine, glycine, phosphocreatine, galactose-1-phosphate, glucose-1-phosphate, UDP-N-acetyl-galactosamine, UDP-N-acetyl-glucosamine, and phosphocholine but lower concentrations of choline, ethanolamine, fucose, N-acetyl-neuraminic acid, N-acetyl-glucosamine, and N-acetyl-galactosamine. During NEB, we observed an increased leakage of cellular content, increased synthesis of nucleic acids and cell membrane phospholipids, an increase in one-carbon metabolic processes, and an increase in lipid-triglyceride anabolism. Overall, both apoptosis combined with cellular renewal is paramount in the mammary gland in cows in NEB.

Short communication: Prediction of hyperketonemia in dairy cows in early lactation using on-farm cow data and net energy intake by partial least square discriminant analysis.

The objectives of this study were (1) to evaluate if hyperketonemia in dairy cows (defined as plasma ß-hydroxybutyrate ≥1.0 mmol/L) can be predicted using on-farm cow data either in current or previous lactation week, and (2) to study if adding individual net energy intake (NEI) can improve the predictive ability of the model. Plasma ß-hydroxybutyrate concentration, on-farm cow data (milk yield, percentage of fat, protein and lactose, fat- and protein-corrected milk yield, body weight, body weight change, dry period length, parity, and somatic cell count), and NEI of 424 individual cows were available weekly through lactation wk 1 to 5 postpartum. To predict hyperketonemia in dairy cows, models were first trained by partial least square discriminant analysis, using on-farm cow data in the same or previous lactation week. Second, NEI was included in models to evaluate the improvement of the predictability of the models. Through leave-one trial-out cross-validation, models were evaluated by accuracy (the ratio of the sum of true positive and true negative), sensitivity (68.2% to 84.9%), specificity (61.5% to 98.7%), positive predictive value (57.7% to 98.7%), and negative predictive value (66.2% to 86.1%) to predict hyperketonemia of dairy cows. Through lactation wk 1 to 5, the accuracy to predict hyperketonemia using data in the same week was 64.4% to 85.5% (on-farm cow data only), 66.1% to 87.0% (model including NEI), and using data in the previous week was 58.5% to 82.0% (on-farm cow data only), 59.7% to 85.1% (model including NEI). An improvement of the accuracy of the model due to including NEI ranged among lactation weeks from 1.0% to 4.4% when using data in the same lactation week and 0.2% to 6.6% when using data in the previous lactation week. In conclusion, trained models via partial least square discriminant analysis have potential to predict hyperketonemia in dairy cows not only using data in the current lactation week, but also using data in the previous lactation week. Net energy intake can improve the accuracy of the model, but only to a limited extent. Besides NEI, body weight, body weight change, milk fat, and protein content were important variables to predict hyperketonemia, but their rank of importance differed across lactation weeks.

Relationship between energy balance and metabolic profiles in plasma and milk of dairy cows in early lactation.

Negative energy balance in dairy cows in early lactation is related to alteration of metabolic status. However, the relationships among energy balance, metabolic profile in plasma, and metabolic profile in milk have not been reported. In this study our aims were: (1) to reveal the metabolic profiles of plasma and milk by integrating results from nuclear magnetic resonance (NMR) with data from liquid chromatography triple quadrupole mass spectrometry (LC-MS); and (2) to investigate the relationship between energy balance and the metabolic profiles of plasma and milk. For this study 24 individual dairy cows (parity 2.5 ± 0.5; mean ± standard deviation) were studied in lactation wk 2. Body weight (mean ± standard deviation; 627.4 ± 56.4 kg) and milk yield (28.1 ± 6.7 kg/d; mean ± standard deviation) were monitored daily. Milk composition (fat, protein, and lactose) and net energy balance were calculated. Plasma and milk samples were collected and analyzed using LC-MS and NMR. From all plasma metabolites measured, 27 were correlated with energy balance. These plasma metabolites were related to body reserve mobilization from body fat, muscle, and bone; increased blood flow; and gluconeogenesis. From all milk metabolites measured, 30 were correlated with energy balance. These milk metabolites were related to cell apoptosis and cell proliferation. Nine metabolites detected in both plasma and milk were correlated with each other and with energy balance. These metabolites were mainly related to hyperketonemia; ß-oxidation of fatty acids; and one-carbon metabolism. The metabolic profiles of plasma and milk provide an in-depth insight into the physiological pathways of dairy cows in negative energy balance in early lactation. In addition to the classical indicators for energy balance (e.g., ß-hydroxybutyrate, acetone, and glucose), the current study presents some new metabolites (e.g., glycine in plasma and milk; kynurenine, panthothenate, or arginine in plasma) in lactating dairy cows that are related to energy balance and may be of interest as new indicators for energy balance.

Prediction of metabolic status of dairy cows in early lactation with on-farm cow data and machine learning algorithms.

Metabolic status of dairy cows in early lactation can be evaluated using the concentrations of plasma ß-hydroxybutyrate (BHB), free fatty acids (FFA), glucose, insulin, and insulin-like growth factor 1 (IGF-1). These plasma metabolites and metabolic hormones, however, are difficult to measure on farm. Instead, easily obtained on-farm cow data, such as milk production traits, have the potential to predict metabolic status. Here we aimed (1) to investigate whether metabolic status of individual cows in early lactation could be clustered based on their plasma values and (2) to evaluate machine learning algorithms to predict metabolic status using on-farm cow data. Through lactation wk 1 to 7, plasma metabolites and metabolic hormones of 334 cows were measured weekly and used to cluster each cow into 1 of 3 clusters per week. The cluster with the greatest plasma BHB and FFA and the lowest plasma glucose, insulin, and IGF-1 was defined as poor metabolic status; the cluster with the lowest plasma BHB and FFA and the greatest plasma glucose, insulin, and IGF-1 was defined as good metabolic status; and the intermediate cluster was defined as average metabolic status. Most dairy cows were classified as having average or good metabolic status, and a limited number of cows had poor metabolic status (10-50 cows per lactation week). On-farm cow data, including dry period length, parity, milk production traits, and body weight, were used to predict good or average metabolic status with 8 machine learning algorithms. Random Forest (error rate ranging from 12.4 to 22.6%) and Support Vector Machine (SVM; error rate ranging from 12.4 to 20.9%) were the top 2 best-performing algorithms to predict metabolic status using on-farm cow data. Random Forest had a higher sensitivity (range: 67.8-82.9% during wk 1 to 7) and negative predictive value (range: 89.5-93.8%) but lower specificity (range: 76.7-88.5%) and positive predictive value (range: 58.1-78.4%) than SVM. In Random Forest, milk yield, fat yield, protein percentage, and lactose yield had important roles in prediction, but their rank of importance differed across lactation weeks. In conclusion, dairy cows could be clustered for metabolic status based on plasma metabolites and metabolic hormones. Moreover, on-farm cow data can predict cows in good or average metabolic status, with Random Forest and SVM performing best of all algorithms.

Relationship between inflammatory biomarkers and oxidative stress with uterine health in dairy cows with different dry period lengths.

Earlier studies indicated that the inflammatory status of dairy cows in early lactation could not be fully explained by the negative energy balance (NEB) at that moment. The objective of the present study was to determine relationships between inflammatory biomarkers and oxidative stress with uterine health in dairy cows after different dry period lengths. Holstein-Friesian dairy cows were assigned to one of three dry period lengths (0-, 30-, or 60-d) and one of two early lactation rations (glucogenic or lipogenic ration). Cows were fed either a glucogenic or lipogenic ration from 10-d before the expected calving date. Part of the cows which were planned for a 0-d dry period dried themselves off and were attributed to a new group (0 → 30-d dry period), which resulted in total in four dry period groups. Blood was collected (N = 110 cows) in weeks -3, -2, -1, 1, 2, and 4 relative to calving to determine biomarkers for inflammation, liver function, and oxidative stress. Uterine health status (UHS) was monitored by scoring vaginal discharge (VD) based on a 4-point scoring system (0, 1, 2, or 3) in weeks 2 and 3 after calving. Cows were classified as having a healthy uterine environment (HU, VD score = 0 or 1 in both weeks 2 and 3), nonrecovering uterine environment (NRU, VD score = 2 or 3 in week 3), or a recovering uterine environment (RU, VD score = 2 or 3 in week 2 and VD score= 0 or 1 in week 3). Independent of dry period length, cows with NRU had higher plasma haptoglobin (P = 0.05) and lower paraoxonase levels (P < 0.01) in the first 4 weeks after calving and lower liver functionality index (P < 0.01) compared with cows with HU. Cows with NRU had lower plasma albumin (P = 0.02) and creatinine (P = 0.02) compared with cows with a RU, but not compared with cows with HU. Independent of UHS, cows with a 0 → 30-d dry period had higher bilirubin levels compared with cows with 0-, 30-, or 60-d dry period (P < 0.01). Cows with RU and fed a lipogenic ration had higher levels of albumin in plasma compared with cows with NRU and fed a lipogenic ration (P < 0.01). In conclusion, uterine health was related to biomarkers for inflammation (haptoglobin and albumin) and paraoxonase in dairy cows in early lactation. Cows which were planned for a 0-d dry period, but dried themselves off (0 → 30-d dry period group) had higher bilirubin levels, which was possibly related to a more severe NEB in these cows. Inflammatory biomarkers in dairy cows in early lactation were related to uterine health in this period.

Milk Metabolomics Data Reveal the Energy Balance of Individual Dairy Cows in Early Lactation.

In early lactation, dairy cows typically have a negative energy balance which has been related to metabolic disorders, compromised health and fertility, and reduced productive lifespan. Assessment of the energy balance, however, is not easy on the farm. Our aims were to investigate the milk metabolic profiles of dairy cows in early lactation, and to obtain models to estimate energy balance from milk metabolomics data and milk production traits. Milk samples were collected in week 2 and 7 after calving from 31 dairy cows. For each cow, the energy balance was calculated from energy intake, milk production traits and body weight. A total of 52 milk metabolites were detected using LC-QQQ-MS. Data from different lactation weeks was analysed by partial least squares analysis, the top 15 most relevant variables from the metabolomics data related to energy balance were used to develop reduced linear models to estimate energy balance by forward selection regression. Milk fat yield, glycine, choline and carnitine were important variables to estimate energy balance (adjusted R2: 0.53 to 0.87, depending on the model). The relationship of these milk metabolites with energy balance is proposed to be related to their roles in cell renewal.

Effects of dry period length on production, cash flows and greenhouse gas emissions of the dairy herd: A dynamic stochastic simulation model.

Shortening or omitting the dry period of dairy cows improves metabolic health in early lactation and reduces management transitions for dairy cows. The success of implementation of these strategies depends on their impact on milk yield and farm profitability. Insight in these impacts is valuable for informed decision-making by farmers. The aim of this study was to investigate how shortening or omitting the dry period of dairy cows affects production and cash flows at the herd level, and greenhouse gas emissions per unit of milk, using a dynamic stochastic simulation model. The effects of dry period length on milk yield and calving interval assumed in this model were derived from actual performance of commercial dairy cows over multiple lactations. The model simulated lactations, and calving and culling events of individual cows for herds of 100 cows. Herds were simulated for 5 years with a dry period of 56 (conventional), 28 or 0 days (n = 50 herds each). Partial cash flows were computed from revenues from sold milk, calves, and culled cows, and costs from feed and rearing youngstock. Greenhouse gas emissions were computed using a life cycle approach. A dry period of 28 days reduced milk production of the herd by 3.0% in years 2 through 5, compared with a dry period of 56 days. A dry period of 0 days reduced milk production by 3.5% in years 3 through 5, after a dip in milk production of 6.9% in year 2. On average, dry periods of 28 and 0 days reduced partial cash flows by €1,249 and €1,632 per herd per year, and increased greenhouse gas emissions by 0.7% and 0.5%, respectively. Considering the potential for enhancing cow welfare, these negative impacts of shortening or omitting the dry period seem justifiable, and they might even be offset by improved health.

Effect of shortening or omitting the dry period of Holstein-Friesian cows on casein composition of milk.

The aim of this study was to evaluate the effect of shortening or omitting the dry period of dairy cows on milk casein composition. For this study, we analyzed milk samples of 90 cows with a dry period of 0, 30, or 60d and either a glucogenic or a lipogenic ration in early lactation. Milk was sampled at 6 and 2wk prepartum and at 2, 6, and 12wk postpartum. Milk was analyzed for casein (CN) composition by capillary zone electrophoresis, and isoforms of κ-CN were measured by reversed phase-HPLC. Shortening the dry period from 60 to 30d reduced the αS1-CN fraction by 3.8% and increased the αS2-CN fraction by 5.5%. In milk from cows with a 0-d dry period, the glycosylated κ-CN fraction in late lactation increased from 8 to 12% between 6 and 2wk prepartum. After calving, the glycosylated κ-CN fraction in milk was higher for cows with a 0-d dry period (6.7%) compared with cows with a 60-d dry period (5.2%). The glycosylated κ-CN fraction at 2wk postpartum was negatively correlated with milk yield, suggesting that glycosylation was related to reduced productivity of mammary epithelial cells. In early lactation, the ß-CN fraction was reduced in milk of cows with a 0-d dry period. A lowered ß-CN fraction was associated with high somatic cell count and greater parity, indicating that it was the result of proteolytic activity. In conclusion, casein composition changes that result from shortening the dry period from 60 to 30d are not expected to affect processing characteristics of milk. Applying a 0-d dry period may affect processability of milk because of a higher glycosylated κ-CN fraction, and possibly because of higher proteolytic activity compared with a 60-d dry period.

Continuous milking of dairy cows disrupts timing of peak IgG concentration appearance in mammary secretions.

The length of the dry period in commercial dairy production is under close scrutiny. While the main concern is the composition and volume of milk produced, the evaluation of colostrum quality under these new paradigms has suggested a decline in IgG concentrations, while some reports indicate no change. Colostrum quality has been defined as an adequate concentration (>50 mg/ml) of immunoglobulin in the secretions to provide the newborn with maximal disease resistance. We investigated the appearance of IgG in mammary pre- and post partum secretions in cows without a dry period (continuously milked, Dry0) and compared the secretions with cows that experienced a dry period of 60 d (Dry60). Blood was collected during the experimental period and plasma analysed for progesterone (P4) and prolactin (Prl). Approximately -6 d relative to parturition, the Dry0 animals exhibited increased concentration of IgG in their secretions to an average of ∼35 mg/ml that remained rather constant through subsequent pregnancy and following parturition. Dry0 cows were producing an average IgG concentration in parturition colostrum of 44·2±17·6 mg/ml that was not different than that of controls (66·86±16·8 mg/ml). However, Dry0 cows exhibited high variation, different peak times (day) of IgG concentration including times that occurred both pre and post parturition. IgG mass of the Dry0 cows remained rather constant pre- and post partum and did not show the same declining mass following parturition that was shown for the Dry60 cows. The change in plasma P4 and Prl were shown to have no timing effect on colostrum IgG concentration.

Effects of shortening the dry period of dairy cows on milk production, energy balance, health, and fertility: a systematic review.

A dry period of 6-8 weeks for dairy cows is generally thought to maximise milk production in the next lactation. However, the value of such a long dry period is increasingly questioned. In particular, shortening the dry period shifts milk production from the critical period after calving to the weeks before calving. This shift in milk production could improve the energy balance (EB), health and fertility of dairy cows. The objective of this study was to systematically review the current knowledge on dry period length in relation to milk production, EB, fertility, and health of cows and calves. A meta-analysis was performed for variables where at least five studies were available. Overall, both shortening and omitting the dry period reduces milk production, increases milk protein percentage and tends to reduce the risk of ketosis in the next lactation. Individual studies reported an improvement of EB after a short or no dry period, compared with a conventional dry period. Shortening or omitting the dry period did not affect milk fat percentage and shortening the dry period did not alter the odds ratio for mastitis, metritis, or fertility measures in the next lactation. So, current evidence for an improvement of health and fertility of dairy cows is marginal and may be partly explained by the limited number of studies which have evaluated health and fertility in relation to dry period length, the limited number of animals in those studies and the variable responses reported.

Changes in milk proteome and metabolome associated with dry period length, energy balance, and lactation stage in postparturient dairy cows.

The early lactation period of dairy cows, which produce high quantities of milk, is normally characterized by an insufficient energy intake to cover milk production and maintenance requirements. Mobilization of body reserves occurs to compensate this negative energy balance (NEB), and probably as a consequence there is a higher susceptibility to diseases and metabolic disorders. There are several diagnostic methods to detect NEB, usually involving ketosis related parameters. Due to the easy availability of milk this is a preferred matrix, but simple and robust predictors of NEB level are missing. To better understand the physiological mechanism of NEB, milk of cows subjected to different dry period lengths, in different energy balance status and lactation stage, were analyzed by untargeted metabolomics and proteomics techniques. Milk of cows in severe NEB showed higher concentrations of acute phase response proteins, unsaturated fatty acids, and galactose-1-phosphate. Improved energy balance (EB) resulted in higher concentration of cholesterol, cholesterol synthesis related proteins, and stomatin. The presence of stomatin and galactose-1-phosphate in milk was strongly dependent on the EB of the cows. These novel and interesting findings warrant more in-depth research to assess their applicability as robust indicators of NEB in milk and to clarify the role of stomatin and galactose-1-phophate in milk of dairy cows in NEB.