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.

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.

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.

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.

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.

Effect of dietary energy source on energy balance, production, metabolic disorders and reproduction in lactating dairy cattle.

The pathway for oxidation of energy involves a balanced oxidation of C2 and C3 compounds. During early lactation in dairy cattle this C2/C3 ratio is out of balance, due to a high availability of lipogenic (C2) products and a low availability of glycogenic (C3) products relative of the C2 and C3 products required for milk production. This review compares studies which manipulated dietary energy source and shows that dietary energy source can affect the balance of the C2/C3 ratio, as indicated by plasma NEFA, beta-hydroxybutyrate (BHBA) and glucose levels. It is shown that glycogenic nutrients increase glucose and insulin concentrations and decrease NEFA and BHBA plasma levels. Extra lipogenic nutrients elevate NEFA and BHBA and decrease plasma glucose concentrations. Lipogenic nutrients generally increase milk fat percentage and decrease milk protein percentage, suggesting a surplus of C2 compounds. The inverse is the case for feeding extra glycogenic nutrients, implying reduced deamination and oxidation of glycogenic amino acids. Feeding extra glycogenic nutrients improved the energy balance (EB), in contrast to ambiguous results of lipogenic nutrients on EB. Moreover, glycogenic feed may reduce the severity of ketosis and fatty liver, but increased the incidence of (sub)clinical acidosis. Since studies are scarce, it seems difficult to draw conclusions on the effects of dietary energy source on reproduction. However, lipogenic nutrients decrease glucose and increase NEFA and BHBA plasma levels. High plasma NEFA and BHBA and low plasma glucose levels are associated with decreased reproductive performance, which might imply the C2/C3 compound balance to be important for reproductive function.