Metabolic Status Of Dairy Cows Research Articles

Time profiles of energy balance in dairy cows in association with metabolic status, inflammatory status, and disease

The early lactation period in dairy cows is characterized by complex interactions among energy balance (EB), disease, and alterations in metabolic and inflammatory status. The objective of this study was to cluster cows based on EB time profiles in early lactation and investigate the association between EB clusters and inflammatory status, metabolic status, oxidative stress, and disease. Holstein-Friesian dairy cows (n = 153) were selected and monitored for disease treatments during wk 1 to 6 in lactation. Weekly EB was calculated based on energy intake and energy requirements for maintenance and milk yield in wk 1 to 6 in lactation. Weekly plasma samples were analyzed for metabolic variables in wk 1 to 6, and inflammatory and oxidative stress variables in wk 1, 2, and 4 in lactation. Liver activity index (LAI) was computed from plasma albumin, cholesterol, and retino-binding protein concentration. First, cows were clustered based on time profiles of EB, resulting in 4 clusters (SP: stable positive; MN: mild negative; IN: intermediate negative; SN: severe negative). Cows in the SN cluster had higher plasma nonesterified fatty acids and β-hydroxybutyrate concentrations, compared with cows in the SP cluster, with the MN and IN cluster being intermediate. Cows in the SN cluster had a higher milk yield, lower dry matter intake in wk 1, lower insulin concentration compared with cows in the SP cluster, and lower glucose and IGF-1 concentration compared with cows in the SP and MN clusters. Energy balance clusters were not related with plasma haptoglobin, cholesterol, albumin, paraoxonase, and liver activity index (LAI). Second, cows were grouped based on health status [IHP: cows with treatment for inflammatory health problem (endometritis, fever, clinical mastitis, vaginal discharge or retained placenta); OHP: cows with no IHP but treatment for other health problem (milk fever, cystic ovaries, claw, and leg problems, rumen and intestine problems or other diseases); NHP: cows with no treatments, in the first 6 weeks after calving]. Energy balance was not different among health status groups. The IHP cows had lower nonesterified fatty acids and greater insulin concentration in plasma compared with OHP. The IHP cows had lower plasma albumin concentration, lower LAI and higher haptoglobin concentration compared with OHP and NHP. Overall, EB time profiles were associated with the metabolic status of dairy cows in early lactation, but were only limitedly related with markers of inflammation and oxidative stress status. Inflammatory and metabolic status were related to disease events in early lactation and caused prolonged effects on liver metabolism.

In-Line Registered Milk Fat-to-Protein Ratio for the Assessment of Metabolic Status in Dairy Cows.

This study endeavors to ascertain alterations in the in-line registered milk fat-to-protein ratio as a potential indicator for evaluating the metabolic status of dairy cows. Over the study period, farm visits occurred biweekly on consistent days, during which milk composition (specifically fat and protein) was measured using a BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania). Clinical examinations were performed at the same time as the farm visits. Blood was drawn into anticoagulant-free evacuated tubes to measure the activities of GGT and AST and albumin concentrations. NEFA levels were assessed using a wet chemistry analyzer. Using the MediSense and FreeStyle Optium H systems, blood samples from the ear were used to measure the levels of BHBA and glucose in plasma. Daily blood samples were collected for BHBA concentration assessment. All samples were procured during the clinical evaluations. The cows were categorized into distinct groups: subclinical ketosis (SCK; n = 62), exhibiting elevated milk F/P ratios without concurrent clinical signs of other post-calving diseases; subclinical acidosis (SCA; n = 14), characterized by low F/P ratios (<1.2), severe diarrhea, and nondigestive food remnants in feces, while being free of other post-calving ailments; and a healthy group (H; n = 20), comprising cows with no clinical indications of illness and an average milk F/P ratio of 1.2. The milk fat-to-protein ratios were notably higher in SCK cows, averaging 1.66 (±0.29; p < 0.01), compared to SCA cows (0.93 ± 0.1; p < 0.01) and healthy cows (1.22). A 36% increase in milk fat-to-protein ratio was observed in SCK cows, while SCA cows displayed a 23.77% decrease. Significant differences emerged in AST activity, with SCA cows presenting a 26.66% elevation (p < 0.05) compared to healthy cows. Moreover, SCK cows exhibited a 40.38% higher NEFA concentration (p < 0.001). A positive correlation was identified between blood BHBA and NEFA levels (r = 0.321, p < 0.01), as well as a negative association between BHBA and glucose concentrations (r = -0.330, p < 0.01). Notably, AST displayed a robust positive correlation with GGT (r = 0.623, p < 0.01). In light of these findings, this study posits that milk fat-to-protein ratio comparisons could serve as a non-invasive indicator of metabolic health in cows. The connections between milk characteristics and blood biochemical markers of lipolysis and ketogenesis suggest that these markers can be used to check the metabolic status of dairy cows on a regular basis.

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.

Milk yield residuals and their link with the metabolic status of dairy cows in the transition period

The transition period is one of the most challenging periods in the lactation cycle of high-yielding dairy cows. It is commonly known to be associated with diminished animal welfare and economic performance of dairy farms. The development of data-driven health monitoring tools based on on-farm available milk yield development has shown potential in identifying health-perturbing events. As proof of principle, we explored the association of these milk yield residuals with the metabolic status of cows during the transition period. Over 2 yr, 117 transition periods from 99 multiparous Holstein-Friesian cows were monitored intensively. Pre- and postpartum dry matter intake was measured and blood samples were taken at regular intervals to determine β-hydroxybutyrate, nonesterified fatty acids (NEFA), insulin, glucose, fructosamine, and IGF1 concentrations. The expected milk yield in the current transition period was predicted with 2 previously developed models (nextMILK and SLMYP) using low-frequency test-day (TD) data and high-frequency milk meter (MM) data from the animal's previous lactation, respectively. The expected milk yield was subtracted from the actual production to calculate the milk yield residuals in the transition period (MRT) for both TD and MM data, yielding MRTTD and MRTMM. When the MRT is negative, the realized milk yield is lower than the predicted milk yield, in contrast, when positive, the realized milk yield exceeded the predicted milk yield. First, blood plasma analytes, dry matter intake, and MRT were compared between clinically diseased and nonclinically diseased transitions. MRTTD and MRTMM, postpartum dry matter intake and IGF1 were significantly lower for clinically diseased versus nonclinically diseased transitions, whereas β-hydroxybutyrate and NEFA concentrations were significantly higher. Next, linear models were used to link the MRTTD and MRTMM of the nonclinically diseased cows with the dry matter intake measurements and blood plasma analytes. After variable selection, a final model was constructed for MRTTD and MRTMM, resulting in an adjusted R2 of 0.47 and 0.73, respectively. While both final models were not identical the retained variables were similar and yielded comparable importance and direction. In summary, the most informative variables in these linear models were the dry matter intake postpartum and the lactation number. Moreover, in both models, lower and thus also more negative MRT were linked with lower dry matter intake and increasing lactation number. In the case of an increasing dry matter intake, MRTTD was positively associated with NEFA concentrations. Furthermore, IGF1, glucose, and insulin explained a significant part of the MRT. Results of the present study suggest that milk yield residuals at the start of a new lactation are indicative of the health and metabolic status of transitioning dairy cows in support of the development of a health monitoring tool. Future field studies including a higher number of cows from multiple herds are needed to validate these findings.

Prediction of metabolic status of dairy cows in early lactation using milk fatty acids and test-day variables

Early lactation metabolic imbalance is an important physiological change affecting the health, production, and reproduction of dairy cows. The aims of this study were (1) to evaluate the potential of test-day (TD) variables with or without milk fatty acids (FA) content to classify metabolically imbalanced cows and (2) to evaluate the robustness of the metabolic classification with external data. A data set was compiled from 3 experiments containing plasma β-hydroxybutyrate, nonesterified FA, glucose, insulin-like growth factor-I, FA proportions in milk fat, and TD variables collected from 244 lactations in wk 2 after calving. Based on the plasma metabolites, 3 metabolic clusters were identified using fuzzy c-means clustering and the probabilistic membership value of each cow to the 3 clusters was determined. Comparing the mean concentration of the plasma metabolites, the clusters were differentiated into metabolically imbalanced, moderately impacted, and balanced. Following this, the 2 metabolic status groups identified were imbalanced cows (n = 42), which were separated from what we refer to as "others" (n = 202) based on the membership value of each cow for the imbalanced cluster using a threshold of 0.5. The following 2 FA data sets were composed: (1) FA (groups) having high prediction accuracy by Fourier-transform infrared spectroscopy and, thus, have practical significance, and (2) FA (groups) formerly identified as associated with metabolic changes in early lactation. Metabolic status prediction models were built using FA alone or combined with TD variables as predictors of metabolic groups. Comparison was made among models and external evaluations were performed using an independent data set of 115 lactations. The area under the receiver operating characteristics curve of the models was between 75 and 91%, indicating their moderate to high accuracy as a diagnostic test for metabolic imbalance. The addition of FA groups to the TD models enhanced the accuracy of the models. Models with FA and TD variables showed high sensitivities (80-88%). Specificities of these models (73-79%) were also moderate and acceptable. The accuracy of the FA models on the external data set was high (area under the receiver operating characteristics curve between 76 and 84). The persistently good performance of models with Fourier-transform infrared spectroscopy-quantifiable FA on the external data set showed their robustness and potential for routine screening of metabolically imbalanced cows in early lactation.

Medium chain fatty acid supplementation improves animal metabolic and immune status during the transition period: A study on dairy cattle.

The transition period is the stage of the high incidence of metabolic and infectious diseases in dairy cows. Improving transition dairy cows' health is crucial for the industry. This study aimed to determine the effects of dietary supplementation medium-chain fatty acids (MCFAs) on immune function, metabolic status, performance of transition dairy cows. Twenty multiparous Holstein cows randomly assigned to two treatments at 35 d before calving. 1) CON (fed the basal 2) MCFA treatment (basal diet was supplemented at an additional 20 g MCFAs mixture every day) until 70 d after calving. The results showed that the serum amyloid A myeloperoxidase concentrations in the blood of cows in MCFA treatment significantly decreased during the early lactation (from 1 d to 28 d after calving) 0.03, 0.04, respectively) compared with the CON, while the tumor necrosis factor concentration was significantly decreased at 56 d after calving (P = 0.02). In addition, the concentration of insulin in the pre-calving (from 21 d before calving to calving) blood of cows in MCFA treatment was significantly decreased (P = 0.04), and concentration of triglyceride also showed a downward trend at 28 d after calving 0.07). Meanwhile, MCFAs supplementation significantly decreased the concentrations of lithocholic acid, hyodeoxycholic acid, and hyocholic acid in the blood at 1 d calving (P = 0.02, < 0.01, < 0.01, respectively), and the level of hyocholic acid taurocholic acid concentrations (P < 0.01, = 0.01, respectively) decreased dramatically at 14 d after calving. However, compared with the CON, the pre-calving dry matter intake and the early lactation milk yield in MCFA treatment were significantly decreased (P = 0.05, 0.02, respectively). In conclusion, MCFAs supplementation transition diet could improve the immune function and metabolic status of dairy cows, and the health of transition cows might be beneficial from the endocrine status.

Effects of dry period length on milk production and physiological responses of heat-stressed dairy cows during the transition period

The objective of this study was to investigate the effects of a traditional dry period (60 d) versus a no dry period (0 d) on the milk production, physiological response, and metabolic status of dairy cows exposed to heat stress during the transition period. Holstein dairy cows (n = 15) with similar expected calving dates were randomly assigned to two different dry period lengths: (1) no dry period (n = 7) and (2) a traditional dry period of 60 days (n = 8). All cows were studied from 8 weeks before expected calving to 10 weeks after calving and experienced heat stress during the transition period. The results showed that cows with no dry period decreased their milk yield in subsequent lactation, but compensated for the loss of milk yield accounted for by additional milk yield before calving. The energy balance at postpartum was improved in cows with no dry period compared to cows with a traditional dry period. There were no significant differences in the physiological response and blood metabolites at postpartum between the dry period lengths of dairy cows exposed to heat stress during the transition period. Taken together, our results showed that omitting the dry period improved the milk production and metabolic status of dairy cows exposed to heat stress during the transition period.

Cow metabolic status assessed from fat/protein ratio in milk affected ovarian response and number of transferable embryos after superovulation

This work aimed to evaluate the quantity and the quality of flushed embryos based on the metabolic status of dairy cows, lactation number, and size of the ovaries. Fifty-nine Holstein cows on 1&lt;sup&gt;st&lt;/sup&gt; to 5&lt;sup&gt;th&lt;/sup&gt; lactation were enrolled in the experiment. Monitoring took place during the period from October to November and from March to June. Cows with corpus luteum were included for the hormonal treatment – superovulation and timed insemination. The cow was inseminated, resp. re-inseminated, during the induced heat with insemination doses from one bull from the same batch. Embryo flushing was performed on the 7&lt;sup&gt;th&lt;/sup&gt; day after the first insemination. We isolated individual embryos after flushing, and morphologically evaluated them under a stereo microscope. The metabolic status of tested cows was determined based on the ratio between fat and protein in milk around the period of embryo flushing (&amp;lt; 1.1; 1.1–1.3; &amp;gt; 1.3). Data about fat and protein content were taken from milking parlour records. Data were evaluated in SAS v9.4 with GLM procedure. The results of our study showed that there is a significant relationship between the fat/protein ratio and the total number of flushed embryos, resp. the number of transferable embryos. The highest number of flushed and transferable embryos were collected from the group of cows with fat/protein ratio between 1.1–1.3. The fat/protein ratio within these values represents cows in an optimal metabolic state. We also observed a significant positive relationship between the size of the ovaries and the number of flushed and transferable embryos. Lactation number did not significantly affect monitored parameters. The assessment of the fat/protein ratio might become a useful tool for the evaluation of cows selected for embryo transfer. Our findings could be used to improve the efficacy of the superovulation system, with the aim to extract the maximum number of transferable embryos.

Dietary supplementation with rumen-protected capsicum during the transition period improves the metabolic status of dairy cows

In ruminants, it has been observed that capsicum oleoresin can alter insulin responses and that high-intensity artificial sweetener can increase glucose absorption from the small intestine. Because glucose metabolism and insulin responses are critical during early lactation, these supplements might have an effect on the metabolic status of dairy cows during the transition period. The objective of this experiment was to evaluate the effects of rumen-protected capsicum oleoresin fed alone or in combination with artificial sweetener during the transition period on lactational performance and susceptibility to subclinical ketosis in dairy cows. Fifteen primiparous and 30 multiparous Holstein cows (a total of 39 cows finished the study) were arranged in a randomized complete block design during d -21 to 60 relative to parturition. Cows within block were randomly assigned to one of the following treatments: no supplement (CON), supplementation with 100 mg of rumen-protected capsicum/cow per day (RPCap), or RPCap plus 2 g of high-intensity artificial sweetener/cow per day (RPCapS). For both the RPCap and RPCapS treatments, only rumen-protected capsicum was fed during the dry period. From d 8 to 11 of lactation, intake was limited to 70% of predicted dry matter intake to induce subclinical ketosis. Production variables were recorded daily, samples for milk composition were collected on wk 2, 4, 6, and 8, and blood samples were collected on wk -2, 1, 2, and 4 of the experiment for analysis of metabolic hormones and blood cell counts. Supplementation with rumen-protected capsicum increased serum insulin and decreased β-hydroxybutyrate concentrations precalving, indicating a decrease in lipolysis. During the lactation period, RPCap was associated with a trend for increased milk production and feed efficiency following the ketosis challenge. Supplementation with RPCapS appeared to negate the response to rumen-protected capsicum. All cows developed subclinical ketosis during the challenge, and this was not affected by treatment. We conclude that treatments did not decrease susceptibility to subclinical ketosis; however, dietary supplementation with rumen-protected capsicum was effective at improving energy status precalving and tended to increased milk production and feed efficiency. The mechanism underlying these responses is unclear.

Effects of postpartum acetylsalicylic acid on metabolic status, health, and production in lactating dairy cattle

The transition period is one of the most challenging times for dairy cattle. Previous research suggests that treatment of postpartum cows with anti-inflammatory drugs may decrease pain and inflammation, enhancing cow welfare and performance during this challenging period. However, these strategies involve numerous time-consuming interventions, which require extra labor and do not fit modern farm logistics. The objective of this experiment was to assess the effects of acetylsalicylic acid (ASA) every 24 h for 2 d after calving on (1) daily milk yield, daily milk conductivity, and daily rumination during the first 60 days in milk (DIM), and 305-d mature-equivalent milk, milk fat, and milk protein yields, (2) body condition score, β-hydroxybutyrate (BHB), and haptoglobin, and (3) incidence of clinical diseases during the first 60 DIM. Dairy cows (n = 246) from a dairy farm located in Pennsylvania were enrolled in this experiment. Cows were blocked by parity and assigned randomly to 1 of 2 treatments: (1) ASA (n = 121), in which cows received 2 treatments with ASA (200 mg/kg; 4 boluses), the first within 12 h after parturition and the second 24 h later; or (2) untreated (UNT; n = 125), in which cows remained untreated. Blood samples were collected at 30 ± 6 h, 7 ± 3 d, and 14 ± 3 d after calving to measure BHB and haptoglobin concentrations. Body condition score was assessed at enrollment, 7 ± 3 DIM, 14 ± 3 DIM, and 50 ± 10 DIM. Furthermore, incidences of diseases, daily rumination, daily milk yield, and daily milk conductivity during the first 60 DIM and 305-d mature-equivalent milk, milk fat, and milk protein yields were collected from on-farm computer records. The data were analyzed using mixed multiple linear and logistic regression models as a randomized complete block design. Multiparous cows treated with ASA produced 1.64 kg/d more milk compared with multiparous cows that remained untreated (ASA = 41.66 ± 0.88 kg/d; UNT = 40.02 ± 0.81 kg/d) during the first 60 DIM. There was no difference in daily milk conductivity and rumination between treatments. Cows treated with ASA had lower concentration of BHB (ASA = 1.16 ± 0.64 mmol/L; UNT = 1.23 ± 0.80 mmol/L) during the first 14 ± 3 DIM and had higher body condition score within the first 50 ± 10 DIM compared with cows that remained UNT. There were no differences in circulating concentrations of haptoglobin between treatments. These results support previous findings showing that the use of anti-inflammatory drugs after calving may increase milk production and affect the metabolic status of dairy cows.

Effects of stearic acid supplementation and starch concentration in close-up diets on performance and metabolic responses of transition dairy cows

This study evaluated the effects of feeding close-up diets differing in starch content with or without stearic acid supplementation (SA) on performance, and metabolic status of dairy cows during the transition period. Forty-six multiparous dry cows were used in a completely randomized design with a 2 × 2 factorial arrangement of starch content [(200 or 250 g/kg of dry matter (DM); L vs H)] and SA supplementation (0 or 20 g/kg of DM; NO vs SA) from 21 d before expecting calving to parturition date. After calving, all cows were fed the same postpartum diet containing 250 g/kg of DM starch and 11.9 g/kg of DM SA supplement. Results indicated that dietary starch concentration did not affect intakes during close-up period, while, stearic acid supplementation had more pronounced effect on increasing dry matter intake (DMI) in H diet than L diet (21.6% vs 5.71%, respectively; significant interaction). Also, SA feeding increased NEL intake compared to NO cows. There was an interaction between starch content and SA supplementation on body weight (BW) change, as cows fed SA diets had greater BW gain in H diets, but this response was not observed in L diets during close-up period. At the postpartum period, an interaction effect was observed between starch and SA for DMI, indicating SA increased postpartum DMI and DMI as a percentage of BW in L diet while cow received NO had more DMI in H diet. Animals fed L diets had less negative EB, and lower BW and BCS losses compared to those received H diets. Milk fat enhanced in cows fed L diets compared to those fed H diets. Interactions between starch and SA treatments were observed for insulin (HNO and LSA had highest concentrations), and aspartate aminotransferase (AST) activity (L group had highest activity) on −7 d to calving. Also, there were significant interactions among treatments for glucose, insulin, non-esterified fatty acids (NEFA) and AST activity over the postpartum period. Cows assigned to the HNO and LSA groups had higher serum glucose and insulin, lower NEFA concentration, while HSA treatment has lowest AST activity. The results from this study indicate that feeding 20 g/kg DM of fat supplement rich in stearic acid in a low starch close-up ration (200 g/kg DM), improved prepartum intake, and had positive carryover effects on postpartum performance and metabolic status compared to high starch diet (250 g/kg DM).

Milk fatty acid composition reflects metabolic adaptation of early lactation cows fed hay rich in water-soluble carbohydrates with or without concentrates

We hypothesized that alterations in metabolic status systematically affect the milk fatty acid (FA) composition and thus milk FA can reveal the metabolic status of dairy cows. We, therefore, investigated changes in the milk FA profile of 24 Simmental cows fed high-quality ryegrass hay (HQ hay) rich in water-soluble carbohydrates (WSC) in the diet, which was shown to affect energy partitioning towards either milk production or body reserve retention, and consequently the metabolic status depending on the dietary proportion of concentrates supplied. The test diets (per kg dry matter (DM)) were CON (600 g fiber-rich hay + 400 g concentrate), 60HQ (600 g HQ hay + 400 g concentrate), 75HQ (750 g HQ hay + 250 g concentrate), and 100HQ (100 g HQ hay). As opposed to the fiber-rich hay, the HQ hay was richer in crude protein (CP; 223 vs. 65 g/kg CP in DM), WSC (198 vs. 110 g/kg WSC in DM) and 18:3 n-3 (560 vs. 316 g/kg FA). The feeding trial was performed from 10 d before calving until 28 d thereafter and milk samples were collected on 7, 14, 21 and 28 d after calving for the FA analysis. Linear and non-linear regression analyses of milk FA and serum metabolites (NEFA and BHB) concentrations were performed. Energy secreted with the milk relative to the intake was highest in cows fed CON and 100HQ and lowest in the 75HQ cows. Both energy-deficient groups (CON and 100HQ) showed elevated levels of milk 18:1 n-9 at the expense of some mammary de novo FA compared to the other two groups (P < 0.05). Cows fed 60HQ secreted greater amounts (g/d) of the de novo FA compared to 75HQ and CON (P < 0.05). The HQ hay promoted the level of conjugated linoleic acids in milk regardless of the inclusion level, and, when used at 75 % or more in the diet, also promoted the level of 18:3 n-3 (P < 0.001) due to increased 18:3 n-3 intake with the hay. The modeled data using the ratios of 15:0 to 18:1 n-9, 14:0 to 18:1 n-9 and the sum of de novo FA to 18:1 n-9 were consistently associated with serum concentrations of NEFA and BHB with a ratio below 0.02, 0.2 and 0.4 indicating excessive mobilization and greater risk of metabolic disturbances. The relationships between the FA ratios and BHB were confirmed with a meta-analysis using means of published studies. In summary, milk FA reflect the metabolic status of early lactation dairy cows. Feeding HQ hay generally promotes health beneficial C18 FA in milk.

Milk metabolites as noninvasive indicators of nutritional status of mid-lactation Holstein and Montbéliarde cows

The objective was to investigate the effects of feed restriction on concentrations of selected milk metabolites in mid-lactation Holstein and Montbéliarde cows and to explore their correlations with energy balance and classic plasma and milk indicators of nutritional status. Eight Holstein and 10 Montbéliarde cows (165 ± 21 d in milk) underwent 6 d of feed restriction during which feed allowance was reduced to meet 50% of their net energy for lactation (NEL) requirements. The experiment was divided in 4 periods: control (CON; d -3 to -1), restriction (RES; d 1 to 6), wk 1 (W1; d 7 to 13), and wk 2 (W2; d 14 to 18) after refeeding at ad libitum intake. Intake, milk production, energy balance and plasma metabolites were used to validate the feed restriction model. Concentrations of 7 milk metabolites: β-hydroxybutyrate (BHB), glucose, glucose-6-phosphate, isocitrate, glutamate, uric acid, and free amino groups were measured in morning milk samples, and fatty acids were measured in pooled p.m. and a.m. samples. Feed restriction induced a negative energy balance (-42.5 ± 4.4 MJ/d), increased plasma nonesterified fatty acids and BHB, and decreased plasma glucose concentrations. Feed restriction increased milk glucose-6-phosphate and isocitrate (+38% and +39%, respectively) and decreased milk BHB, glucose, glutamate, uric acid and free amino group concentrations (-20%, -57%, -65%, -42%, and -14%, respectively), compared with pre- restriction. Milk concentrations of medium-chain fatty acids (e.g., sum of C10 to C15) decreased and those of long chain (e.g., 18:0, cis-9 18:1) increased during restriction. Breed differences were not detected for the majority of variables. All studied milk metabolites were significantly correlated with energy balance (Spearman correlation = 0.48, 0.63, -0.31, -0.45, and 0.61 for BHB, glucose, glucose-6-phosphate, isocitrate, and glutamate, respectively). Milk glucose and glutamate showed the strongest correlations with plasma metabolites and milk FA associated with lipomobilization. These results suggest that milk metabolites may be used as noninvasive indicators of negative energy balance and metabolic status of dairy cows.

PSXII-2 DI/LC-MS/MS-based plasma metabolomics reveals the effects of sequestering agents on the metabolic status of dairy cows challenged with dietary aflatoxin B1

Abstract The study applied a targeted quantitative metabolomics approach using a combination of direct injection and tandem mass spectrometry (DI-MS/MS) with a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based plasma metabolomics to evaluate the effects of supplementing clay and/or a Saccharomyces cerevisiae fermentation product (SCFP) on the metabolic status of dairy cows challenged with aflatoxin B1. Eight lactating cows were randomly assigned to 1 of 4 treatments in a balanced 4 × 4 Latin square design with 2 squares. Treatments were control, toxin (T; 1725 µg AFB1/head/day), T with clay (CL; 200 g/head/day), and CL with SCFP (CL+SCFP; 35 g of SCFP/head/day). Cows in T, CL, and CL+SCFP were dosed with aflatoxin B1 (AFB1) from d 26 to 30. The sequestering agents were top-dressed from d 1 to 33. On d 30 of each period, 15 mL of blood was taken from the coccygeal vessels and plasma samples were prepared by centrifugation. Plasma samples were analyzed using a kit that combines DI-MS/MS with LC-MS/MS. The data were analyzed using the GLIMMIX procedure of SAS. The model included the effects of treatment, period, and random effects of cow and square. Significance was declared at P ≤ 0.05. A total of 128 metabolites, including amino acids, biogenic amines, acylcarnitines, glycerophospholipids, and organic acids were quantified. Compared to the control, T decreased (P ≤ 0.05) plasma concentrations of 16 metabolites (6 amino acids, 6 acylcarnitines, and 4 glycerophospholipids). In contrast, T increased plasma concentrations of sarcosine, uric acid, and aspartic acid. Treatment with CL increased concentrations of arginine, lysine, and 5 organic acids. Treatment with CL+SCFP increased the concentrations of 7 amino acids and 4 acylcarnitines, but reduced the concentrations of sarcosine and 3 organic acids. Results of this study indicate that supplementing clay and/or SCFP altered plasma metabolomic profile in dairy cows challenged with AFB1.

DI/LC-MS/MS-Based Metabolome Analysis of Plasma Reveals the Effects of Sequestering Agents on the Metabolic Status of Dairy Cows Challenged with Aflatoxin B1.

The study applied a targeted metabolomics approach that uses a direct injection and tandem mass spectrometry (DI–MS/MS) coupled with a liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based metabolomics of plasma to evaluate the effects of supplementing clay with or without Saccharomyces cerevisiae fermentation product (SCFP) on the metabolic status of dairy cows challenged with aflatoxin B1. Eight healthy, lactating, multiparous Holstein cows in early lactation (64 ± 11 DIM) were randomly assigned to one of four treatments in a balanced 4 × 4 duplicated Latin square design with four 33 d periods. Treatments were control, toxin (T; 1725 µg aflatoxin B1 (AFB1)/head/day), T with clay (CL; 200 g/head/day), and CL with SCFP (YEA; 35 g of SCFP/head/day). Cows in T, CL, and YEA were dosed with aflatoxin B1 (AFB1) from days 26 to 30. The sequestering agents were top-dressed from day 1 to 33. On day 30 of each period, 15 mL of blood was taken from the coccygeal vessels and plasma samples were obtained from blood by centrifugation and analyzed for metabolites using a kit that combines DI–MS/MS with LC–MS/MS-based metabolomics. The data were analyzed using the GLIMMIX procedure of SAS. The model included the effects of treatment, period, and random effects of cow and square. Significance was declared at p ≤ 0.05. Biomarker profiles for aflatoxin ingestion in dairy cows fed no sequestering agents were determined using receiver–operator characteristic (ROC) curves, as calculated by the ROCCET web server. A total of 127 metabolites such as amino acids, biogenic amines, acylcarnitines, glycerophospholipids, and organic acids were quantified. Compared with the control, T decreased (p < 0.05) plasma concentrations of alanine, leucine, and arginine and tended to decrease that of citrulline. Treatment with CL had no effects on any of the metabolites relative to the control but increased (p ≤ 0.05) concentrations of alanine, leucine, arginine, and that of citrulline (p = 0.07) relative to T. Treatment with YEA resulted in greater (p ≤ 0.05) concentrations of aspartic acid and lysine relative to the control and the highest (p ≤ 0.05) plasma concentrations of alanine, valine, proline, threonine, leucine, isoleucine, glutamic acid, phenylalanine, and arginine compared with other treatments. The results of ROC analysis between C and T groups revealed that the combination of arginine, alanine, methylhistidine, and citrulline had sufficient specificity and sensitivity (area under the curve = 0.986) to be excellent potential biomarkers of aflatoxin ingestion in dairy cows fed no sequestering agents. This study confirmed the protective effects of sequestering agents in dairy cows challenged with aflatoxin B1.

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 β-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.

Days-in-Milk and Parity Affected Serum Biochemical Parameters and Hormone Profiles in Mid-Lactation Holstein Cows.

Simple SummarySerum biochemical parameters and hormones play a role in directly reflecting the physiological state and modulating the milk performance of dairy cows. However, the variability of the serum biochemical parameters and hormones in multiparous mid-lactation cows have not drawn much attention due to their supposedly stable states, especially for those cows under the same nutrition and management condition. The aim of this study was to evaluate the effects of days-in-milk (DIM, within the mid-lactation) and parity (ranging from 2–6) on serum biochemical parameters and hormone profiles based on a large cohort of dairy cows. The results showed that DIM and parity contribute to the variations in serum biochemical parameters and hormones related to protein status, energy supply, liver and kidney function, and oxidative stress of mid-lactation dairy cows, with the effect of DIM being dominant over parity. Our result suggested that the DIM periods and parity should be taken into consideration to optimize nutritional strategies in order to improve the milk performance traits more precisely.It is well known that serum biochemical parameters and hormones contribute greatly to the physiological and metabolic status of dairy cows. However, few studies have focused on the variation of these serum parameters in multiparous mid-lactation cows without the interference of diet and management. A total of 287 Holstein dairy cows fed the same diet and maintained under the same management regime were selected from a commercial dairy farm to evaluate the effects of days-in-milk (DIM) and parity on serum biochemical parameters and hormone profiles. Milk yield and milk protein content were affected by DIM and parity (p < 0.05). Milk protein yield showed a numerically decreasing trend with parity, and it was relatively constant in cows with parities between 2 and 4 but lower in cows with parity 6 (p = 0.020). Ten and five serum biochemical parameters related to protein status, energy metabolism, liver and kidney function, and oxidative stress were affected by DIM and parity, respectively (p < 0.05). Glucagon, insulin-like growth factor 1 concentration, and the revised quantitative insulin sensitivity check index were significantly different (p < 0.05) among cows with different DIM. Parity had no effect on hormone concentrations. An interaction between DIM and parity effect was only detected for glucagon concentration (p = 0.015), which showed a significantly increasing trend with DIM and overall decreasing trend with parity. In summary, DIM and parity played an important role in affecting the serum biochemical parameters and/or hormones of dairy cows, with serum parameters affected more by DIM than parity.

Metabolic status and ultrasound traits of reproductive tract of estrus dairy cows in early postpartum period

Metabolic status of dairy cows influences reproductive tract and fertility in postpartum period. A study with 89 estrus dairy cows was performed to study the relationships among the concentration of metabolic hormones and ultrasound traits of genital system in heat dairy cows. Cows in estrus were examined with transrectal ultrasonography and palpation, and their blood samples were collected nearly to the time of insemination. Ultrasonography images of the uterine horns, ovarian follicles, and corpus luteum were recorded and interpreted. The concentration of insulin-like growth factor-1 (IGF-1), non-esterified fatty acids (NEFA), and β-hydroxyl butyric acid (BHBA) was determined in the serum samples of estrus cows. This study indicated that the correlation between ultrasound traits of uterus and metabolite hormones was not significant at the clean test in estrus dairy cows. Moreover, there was no relationship between serum level of IGF-1, NEFA, and BHBA with either dominant follicle diameter or existence of corpus luteum (CL). Significant association between ultrasound properties of the uterus and ovaries and metabolic hormone (IGF-1, NEFA, and BHBA) concentrations did not reveal in estrus dairy cows at day 28 ± 3 postpartum.

479 Recovery of milk somatic cell count and performance after an intramammary LPS challenge is dependent on the metabolic status of dairy cows.

479 Recovery of milk somatic cell count and performance after an intramammary LPS challenge is dependent on the metabolic status of dairy cows.

Metabolic Status of Dairy Cows Grouped by Anabolic and Catabolic Indicators of Metabolic Stress in Early Lactation

Background: Early lactation is period followed by changed metabolism in organism of the cow. This is the consequence of negativ energy balance, metabolic stress and milk production. Early lactation is characterised by high lipide catabolism (high NEFA) and low anabolic capacity (low insulin and IGF-I concentration). The aim of this study is to examine differences in metabolic adaptation of cows in early lactation (eight weeks after calving) in accordance to anabolic (insulin, IGF-I) and catabolic (NEFA) indicators in first week after calving.Materials, Methods &amp; Results: The experiment included 50 Holstein-Friesian cows. Blood samples were collected in first, second, fourth and eight week after calving by venepunction of v.coccigea. Based on median value of indicator, cows were significantly (P &lt; 0.001) classified in two groups: cows under metabolic stress (indicators of anabolism below the median Me-: indicators of catabolism above the medianMe+) and cows in control group (indicators of anabolism above the median Me+: indicators of catabolism under median Me-). Following criteria for comparison were given: based on classification of cows according to one indicator of metabolic load (insulinMe-:insulinMe+; IGF-IMe-:IGF-IMe+ and NEFAMe-:NEFA Me+); based on classification of cows according to combination of two indicators (insulinMe-+NEFAMe+: insulinMe++NEFAMe- and IGF-IMe-+NEFAMe+:IGF-IMe++NEFAMe-). Cows loaded with metabolic stress showed significan difference in metabolic adaptation in relation to control group (P &lt; 0.05 or P &lt; 0.01): higher values of STH, BHB (criteria were insulin, IGF-I, NEFA, insulin+NEFA, IGF-I+NEFA), higher values of bilirubin, AST, ALT, GGT, AP (criteria NEFA and IGF-I+NEFA) and MDA (criteria NEFA) and lower levels of glucose, total proteins, albumin (criteria IGF-I, NEFA, IGF-I+NEFA and body condition (criteria insulin, IGF-I, NEFA, insulin+ NEFA, IGF-I+ NEFA) were noted. Differences were expressed the most in first two weeks after calving. Differences in the body condition were the most notable later in weeks. Usage of NEFA indicator in first week after calving allows the most quality recognition of cows with metabolic parameters in extreme quartiles (ROC AUC= 0.87, P &lt; 0.01) in first eight week of lactation.Discussion: Inverse relation betwen NEFA with insulin and IGF-I is consequence of next phisiological concept: plasma insulin and IGF-I decrease in same mannure after calvig and insulin aplication increase IGF-I; low insulin concentration leads cow to lipolysis and low IGF-I leads to STH resistance with increase concentration of STH and high lipolysis. Catabolism of adipose tissue and high NEFA concentration is most important for metabolic adaptation in periparturient period. Cows with insulin resistance, ketosis and fatty liver with many problems in metabolic adaptation showed high NEFA concentration. Atenuation of NEFA by niacin or anti-inflammatory drug decreases metabolic change due to high lipide mobilisation in early lactation. Low antepartal IGF-I showed significant effect on postpartum health, but our measuremens are in first week postpartum. In addition, increase catabolism of lipide viewed in NEFA value contributes to metabolic variation and adaptation in the first eight weeks of lactation much more than decrease of anabolic indicators such as insulin and IGF-I. The combination of the indicators does not lead to better recognition of cows with extreme metabolic change in relation to classification only to the value of NEFA.