Fat-protein Ratio Research Articles

Alterations in Rumination, Eating, Drinking and Locomotion Behavior in Dairy Cows Affected by Subclinical Ketosis and Subclinical Acidosis

This study delves into the effects of subclinical ketosis (SCK) and subclinical acidosis (SCA) on various parameters related to dairy cow rumination, eating, drinking and locomotion behavior. The research hypothesized that these subclinical metabolic disorders could affect behaviors such as rumination, feeding, and locomotion. A total of 320 dairy cows, with a focus on those in their second or subsequent lactation, producing an average of 12,000 kg/year milk in their previous lactation, were examined. These cows were classified into three groups: those with SCK, those with SCA, and healthy cows. The health status of the cows was determined based on the milk fat–protein ratio, blood beta-hydroxybutyrate, and the results of clinical examinations performed by a veterinarian. The data collected during the study included parameters from the RumiWatch sensors. The results revealed significant differences between the cows affected by SCK and the healthy cows, with reductions observed in the rumination time (17.47%) and various eating and chewing behaviors. These changes indicated that SCK had a substantial impact on the cows’ behavior. In the context of SCA, the study found significant reductions in Eating Time 2 (ET2) of 36.84% when compared to the healthy cows. Additionally, Eating Chews 2 (EC2) exhibited a significant reduction in the SCA group, with an average of 312.06 units (±17.93), compared to the healthy group’s average of 504.20 units (±18.87). These findings emphasize that SCA influences feeding behaviors and chewing activity, which can have implications for nutrient intake and overall cow health. The study also highlights the considerable impact of SCK on locomotion parameters, as the cows with SCK exhibited a 27.36% reduction in the walking time levels. These cows also displayed reductions in the Walking Time (WT), Other Activity Time (OAT), and Activity Change (AC). In conclusion, this research underscores the critical need for advanced strategies to prevent and manage subclinical metabolic disorders within the dairy farming industry. The study findings have far-reaching implications for enhancing the well-being and performance of dairy cattle. Effective management practices and detection methods are essential to mitigate the impact of SCK and SCA on dairy cow health and productivity, ultimately benefiting the dairy farming sector.

Biochemical Indicators of Energy Balance in Blood and Other Secretions of Dairy Cattle: A Review

Negative energy balance condition during transition period is a gateway for production and infectious diseases during periparturient period. Energy balance is calculated directly through difference in energy input and energy output or indirect methods like estimation of energy metabolites (NEFA, BHBA and glucose level), Body condition scoring (BCS), back fat thickness, body weight and milk components (e.g., fat protein ratio), etc., at herd level. All the indirect energy balance indicators were studied in relation to postpartum health and performances in dairy animals. Blood biochemical parameters are routinely used for evaluation of general health status of animals. But, their relationship with energy balance in early lactating cows is not clear. In this review, effects of energy balance, critical period to assess the energy balance, and blood biochemical parameters in relation to energy balance, milk yield and health status of dairy animals are discussed. We also discussed energy balance indicators in other biological fluids in dairy cattle.

A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (-0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes.

Implications of negative energy balance in lactating Barki and Rahmani ewes

Context During lactation, ewes usually undergo a state of negative energy balance since the energy required for milk production and maintenance of body tissue functions exceeds energy ingested. Aims This study was performed to explore the impact of negative energy balance associated with lactation on milk yield and composition, metabolic profile and some reproductive traits in two different breeds of sheep. Methods In total, one hundred lactating Barki and Rahmani ewes (50 ewes per breed) were used for six consecutive parities to investigate the effects of breed, parity, week of lactation, and their interactions on milk yield and composition, including percentages of milk fat and milk protein, fat–protein ratio, energy-corrected milk, milk energy value, energy balance, some serum metabolites and reproductive traits. Milk and blood samples were collected weekly throughout the study. Key results Rahmani ewes had higher milk fat %, fat yield, protein %, protein yield and milk energy value, but lower fat–protein ratio than did Barki ewes. The greater value of energy balance and accumulated negative energy balance from parturition to energy balance equilibrium and fewer days from lambing to energy balance equilibrium were observed in Rahmani than in Barki ewes. Greater values of serum concentrations of total protein, albumin, cholesterol and lower values of aspartate aminotransferase and alanine aminotransferase were recorded in Rahmani than in Barki ewes. Reproductive traits, including days to the first oestrus and days to conception, recorded greater values in Barki than in Rahmani ewes. Conclusion Rahmani ewes possessed adaptive characteristics to the challenge of lactation, expressed as a lower value of fat–protein ratio, which indicated a tendency of energy balance stabilisation, than did Barki ewes. This tendency was reflected in improved reproductive traits by reducing days to first oestrus and days to conception in Rahmani compared with Barki ewes. Implications Lactation presents a critical stressful period in the dam productive life because of the high nutritional and other managerial requirements necessary for milk production. This study was conducted to assess and compare the sustainability of the two sheep breeds to the production expenditure during lactation.

Survival analysis of dairy cows in the Netherlands under altering agricultural policy

Culling of underperforming dairy cows by replacement heifers is a fundamental part of Dutch dairy farm management. Changes in national agricultural policies can influence farmers’ culling decisions. The objective of this study was to analyse the relevancy of cow-level risk factors for survival of Dutch dairy cows under perturbations due to national policy changes related to the -milk quota abolishment of 2015 and the phosphate regulations since 2017. For this purpose, an accelerated failure time model was fitted on-longitudinal dairy cows’ data at national level covering the period 2009−2019. The associated cow-level risk factors for culling such as lactation value (relative production level), parity number, rolling average of inseminations over all parities, very high fat-protein ratio (highFPR) and very low fat-protein ratio (lowFPR) in early lactation, test-day somatic cell count, were fitted in the model. Along with these, a factor representing three target policy periods, namely Milk Quota period (MQ), Post-Milk Quota period (PMQ) and Phosphate regulation period (PH) were fitted. The mean survival age for all producing cows was 441 weeks overall. The predicted median survival time for the policy periods MQ, PMQ and PH were 273 weeks, 271 weeks and 256 weeks, respectively. Risk factors such as lactation value, parity and highFPR, rolling average of inseminations over all parities were positively associated with survival time in all three policy periods. Risk factors such as test-day somatic cell count and lowFPR were negatively associated with survival time in all three policy periods. In conclusion, this study demonstrated the differences in survival of Dutch dairy cows in response to changing agricultural policy. The association of cow-level risk factors for culling was consistent across the three evaluated policy periods.

Ketone bodies - causes and effects of their increased presence in cows' body fluids: A review.

Ketosis is the most common metabolic disease in high-performance dairy cows during the first 6-8 weeks of lactation. Its main symptoms include an excessive amount of so-called ketone bodies in a cow’s body fluids. Ketone bodies consist of β-hydroxybutyric acid (βHBA), acetoacetic acid, and acetone. βHBA is the main component with its share of the total volume of ketone bodies in the blood of about 70%. Clinical symptoms of ketosis in cows include loss of appetite, preference for forage to concentrated feed, and acetone odor in their mouth and urine. Those symptoms are accompanied by a production drop, an increase of concurrent illness (mastitis, metritis, and displaced abomasum), and poor reproductive performance. One of the ketosis characteristic effects is an increase in the level of fat in milk (>5%), while protein levels decrease (<2.9%). In the case of subclinical ketosis (SCK), the fat–protein ratio in milk is increased to above 1.4:1. The current consensus for SCK is to consider a cutoff point of βHBA to be at least 1.2 mmol/L in blood plasma. Ketosis prevention is based on keeping perinatal cows in good condition, that is, with around 3.5 points in the five-point body condition scoring, carefully balancing food doses during the first 2 months of lactation with the correct energy–protein ratio. Glucose precursor products should be administered orally, in particular to at-risk herds. Ketosis occurs in 7-14% on average of the total number of cows in a herd. In general, data on the prevalence of SCK vary considerably, depending on their source. Moreover, the problem is mostly observed in poorly-fed animals with high milk production potential. The objectives of this review are to reveal the current situation of ketosis prevalence, the possibility of diagnosis, consequences in dairy cows and to provide some recommendations for ketosis treatment and prevention.

Relationship between milk constituents from milk testing and health, feeding, and metabolic data of dairy cows

A new evaluation scheme to assess the nutritional status of dairy cows on the basis of milk constituents was derived from 7.37 million German records of milk testing. The aim of this work was to validate this new scheme. Two data sets with fertility and health information (data set A) and with measured energy and nutrient intake and metabolic characteristics (data set B) were analyzed. Data set A included 32 commercial dairy farms in northeast Germany, with 72,982 records of 43,863 German Holstein cows; data set B included 12 German experimental farms, with 49,275 records of 1,650 German Holstein, Simmental, and Brown Swiss cows. Milk traits were linked to health disorders and metabolic and feeding characteristics. Frequently used limits of milk constituents were compared with ranges of the new "Dummerstorf feeding evaluation." To distinguish an optimal from a deficient energy supply, a milk protein content ≥3.20% (previously used) and a milk fat:protein ratio (FPR) ≤1.4 (new scheme) were chosen and compared with feed energy intake in relation to demand. Energy status was more often correctly assigned by FPR than by milk protein content (80.7 and 68.7%, respectively). Over all data, the new optimum range of milk urea between 150 and 250 mg/L was better suited to dietary crude protein intake in relation to demand than the previously used range of 150 to 300 mg/L (42.4 and 38.0%, respectively). Ketosis or blood values associated with ketosis such as β-hydroxybutyrate >1.2 mmol/L or nonesterified fatty acids >1,000 µmol/L, as well as strong mobilization of body weight ≥1.5 kg/d, loss of back fat thickness ≥10 mm, and loss of body condition score ≥1 unit in first 60 days in milk were compared with different milk trait thresholds. For the updated scheme FPR >1.4 was used in combination with either milk protein content below the individual statistical lower limit of milk protein content, or milk fat content greater than the individual statistical upper limit of milk fat content; FPR >1.5 was taken as a frequently used threshold. For these ketosis indicators, the new scheme had higher sensitivities. Energy oversupply or the risk of overconditioning could not be identified by milk constituents alone. Urinary acid-base content was not related to milk content. Similarly, milk testing data did not allow a clear distinction to be made between the diagnoses of acidosis and, for example, ketosis. Essential requirements for good herd management are the continuous observation of milk testing data in combination with other established instruments of feeding and animal monitoring.

The effect of physiological state, milk production traits and environmental conditions on milk fat globule size in cow's milk.

This research was carried out to quantify the effects of a range of variables on milk fat globule (MFG) size for a herd of Holstein-Friesian cows managed through an automatic milking system with year-round calving. We hypothesised that the overall variation in average MFG size observed between individual animals of the same herd cannot sufficiently be explained by the magnitude of the effects of variables that could be manipulated on-farm. Hence, we aimed to conduct an extensive analysis of possible determinants of MFG size, including physiological characteristics (parity, days in milk, days pregnant, weight, age, rumination minutes, somatic cell count) and milk production traits (number of milkings, milk yield, fat yield, protein and fat content, fat-protein ratio) on the individual animal level; and environmental conditions (diet, weather, season) for the whole herd. Our results show that when analysed in isolation, many of the studied variables have a detectable effect on MFG size. However, analysis of their additive effects identified days in milk, parity and milk yield as the most important variables. In accordance with our hypothesis, the estimated effects of these variables, calculated using a multiple variable linear mixed model, do not sufficiently explain the overall variation between cows, ranging from 2.70 to 5.69 µm in average MFG size. We further show that environmental variables, such as sampling day (across seasons) or the proportion of pasture and silage in the diet, have limited effects on MFG size and that physiological differences outweigh the effects of milk production traits and environmental conditions. This presents further evidence that the selection of individual animals is more important than the adjustment of on-farm variables to control MFG size.

Body and milk traits as indicators of dairy cow energy status in early lactation

The inclusion of feed intake and efficiency traits in dairy cow breeding goals can lead to increased risk of metabolic stress. An easy and inexpensive way to monitor postpartum energy status (ES) of cows is therefore needed. Cows' ES can be estimated by calculating the energy balance from energy intake and output and predicted by indicator traits such as change in body weight (ΔBW), change in body condition score (ΔBCS), milk fat:protein ratio (FPR), or milk fatty acid (FA) composition. In this study, we used blood plasma nonesterified fatty acids (NEFA) concentration as a biomarker for ES. We determined associations between NEFA concentration and ES indicators and evaluated the usefulness of body and milk traits alone, or together, in predicting ES of the cow. Data were collected from 2 research herds during 2013 to 2016 and included 137 Nordic Red dairy cows, all of which had a first lactation and 59 of which also had a second lactation. The data included daily body weight, milk yield, and feed intake and monthly BCS. Plasma samples for NEFA were collected twice in lactation wk 2 and 3 and once in wk 20. Milk samples for analysis of fat, protein, lactose, and FA concentrations were taken on the blood sampling days. Plasma NEFA concentration was higher in lactation wk 2 and 3 than in wk 20 (0.56 ± 0.30, 0.43 ± 0.22, and 0.13 ± 0.06 mmol/L, respectively; all means ± standard deviation). Among individual indicators, C18:1 cis-9 and the sum of C18:1 in milk had the highest correlations (r = 0.73) with NEFA. Seven multiple linear regression models for NEFA prediction were developed using stepwise selection. Of the models that included milk traits (other than milk FA) as well as body traits, the best fit was achieved by a model with milk yield, FPR, ΔBW, ΔBCS, FPR × ΔBW, and days in milk. The model resulted in a cross-validation coefficient of determination (R2cv) of 0.51 and a root mean squared error (RMSE) of 0.196 mmol/L. When only milk FA concentrations were considered in the model, NEFA prediction was more accurate using measurements from evening milk than from morning milk (R2cv = 0.61 vs. 0.53). The best model with milk traits contained FPR, C10:0, C14:0, C18:1 cis-9, C18:1 cis-9 × C14:0, and days in milk (R2cv = 0.62; RMSE = 0.177 mmol/L). The most advanced model using both milk and body traits gave a slightly better fit than the model with only milk traits (R2cv = 0.63; RMSE = 0.176 mmol/L). Our findings indicate that ES of cows in early lactation can be monitored with moderately high accuracy by routine milk measurements.

Evaluation of rumination time, subsequent yield, and milk trait changes dependent on the period of lactation and reproductive status of dairy cows.

The aim of this research was to determine rumination time (RT) and the subsequent milk yield, along with trait changes during lactation dependent on the reproductive status of dairy cows. 728 cows were selected for evaluation in regards to 1-150 days of milk production (DIM). According to their period of lactation and reproductive status, the cows were selected for the following groups: Inseminated (1-35 days after insemination, n=182), Open (45-90 days after calving, n=126), Fresh (1-44 days after calving, n=45); Not-pregnant (>35-60 days after inse- mination and not-pregnant, n=55); Pregnant (35-60 days after insemination and pregnant (n=320). The animals were milked with Lely Astronaut® A3 milking robots. The daily milk yield, rumination time, bodyweight, milk composition (fat, protein, lactose, somatic cell count and gynecological status date) were collected from the Lely T4C management program for analysis. We estimated the lowest productivity in the pregnant cows, where the average milk yield was 28.72 kg and the highest productivity in the fresh cow (p⟨0.001)(Table 1). The longest rumina- tion time was determined for the inseminated cows, statistically significantly higher at 9.92% (p⟨0.001) than in the non-pregnant cows, whose rumination time was the shortest. The statisti- cally reliably RT positively correlated with productivity (r=0.384, p⟨0.001) of the cows (from r=0.302 in the second lactation and r=0.471 in the first lactation to r=0.561 in multiparous cows; p0.001). Rumination time, according to groups of cows by milk yield, had a tendency to increase (2.14 times) from 202.0± 87.38 (in cows with a productivity of less than 10 kg milk) to 431.6±33.91 (in cows with a milk yield higher than 50 kg) by the linear regression equation: y = 38.02x + 232, R² = 0.721 (p⟨0.001). The relation between the gynecological status and milk fat-protein ratio of the cows was statistically significant (χ2=2.974, df= 8, p ⟨0.0001). The longest rumination time was determined for the inseminated cows (1 - 35 days after insemination), and the shortest for the not-pregnant cows (>35 - 60 days after insemination and not-pregnant). We can conclude that rumination time, subsequent yield, and milk trait change depends on the period of lactation and reproductive status of a dairy cow.

Genetic parameter estimation for milk β-hydroxybutyrate and acetone in early lactation and its association with fat to protein ratio and energy balance in Korean Holstein cattle.

ObjectiveThe objective of this study was to estimate the genetic parameters for milk β-hydroxybutyrate (BHBA), acetone (Ac), fat protein ratio (FPR), and energy balance (EB) using milk test day records and investigate the effect of early lactation FPR and EB on milk ketone body concentrations.MethodsTotal 262,940 test-day records collected from Korea Animal Improvement Association during the period of 2012 to 2016 were used in this study. BHBA and Ac concentrations in milk were measured by Fourier transform infrared spectroscopy (FTIR). FPR values were obtained using test day records of fat and protein percentage. EB was calculated using previously developed equation based on parity, lactation week, and milk composition data. Genetic parameters were estimated by restricted maximum likelihood procedure based on repeatability model using Wombat program.ResultsElevated milk BHBA and Ac concentrations were observed during the early lactation under the negative energy balance. Milk FPR tends to decrease with the decreasing ketone body concentrations. Heritability estimates for milk BHBA, Ac, EB, and FPR ranged from 0.09 to 0.14, 0.23 to 0.31, 0.19 to 0.52, and 0.16 to 0.42 respectively at parity 1, 2, 3, and 4. The overall heritability for BHBA, Ac, EB and FPR were 0.29, 0.32, 0.58, and 0.38 respectively. A common pattern was observed in heritability of EB and FPR along with parities.ConclusionFPR and EB can be suggested as potential predictors for risk of hyperketonemia. The heritability estimates of milk BHBA, Ac, EB, and FPR indicate that the selective breeding may contribute to maintaining the milk ketone bodies at optimum level during early lactation.

Long-term effect of minor genetic changes of milk components on somatic cell count

Selection pressure on protein content (PC), and thus milk composition changes have manifested as an increasingly narrow fat - protein ratio (FPR). In addition, higher somatic cell count (SCC) in milk has been observed in recent years, and that is why it is hypothesized that milk composition changes affect cow’s immune response resulting in higher SCC. 2,459,250 test day (TD) records of 127,499 Slovenian Simmental (SIM) cows from years 2004 to 2017 were used for this study. For the estimation of (co)variance components two multiple trait animal TD models were used (M1, M2). M1 included SCC and FPR while M2 included SCC, fat content (FC) and PC. For comparisson of results parameters from the routine single-trait national genetic evaluation were used. Heritability estimates (h²) for SCC, FC and PC from M2 (0.34, 0.29 and 0.38, respectively) were very similar to those form national evaluation; h² for FPR was lower than for the other traits (0.22). Both, estimated genetic correlation ("r" _"g" = 0.1) and estimated phenotypic correlation ("r" _"p" = 0.007) among SCC and FPR in M1 were negative and low. "r" _"p" in M2 were positive, but low for all three trait pairs (0.062 0.076) and "r" _"g" for SCC PC was similar (0.069). Conversely, FC PC "r" _"g" (0.502) was positive and moderate whereas SCC FC "r" _"g" ( 0.046) was negative and low. Results confirm the hypothesis by suggesting the possibillity of unpredicted and unwanted long term cumulative effect of seemingly irrelevantly small genetic changes of individual trait.

Implications of feed concentrate reduction in organic grassland-based dairy systems: a long-term on-farm study

In response to increasing efforts for reducing concentrate inputs to organic dairy production in grassland-rich areas of Europe, a long-term study was conducted, which assessed the impacts of concentrate reductions on cows’ performance, health, fertility and average herd age. In total, 42 Swiss commercial organic dairy cattle farms were monitored over 6 years (‘Y0’, 2008/09 until ‘Y5’, 2013/14). In comparison with overall data of Swiss herdbooks (including conventional and organic farms), the herds involved in the project had lower milk yields, similar milk solids, shorter calving intervals and higher average lactation numbers. During the first 3 project years farmers reduced the concentrate proportion (i.e. cereals, oilseeds and grain legumes) in the dairy cows’ diets to varying degrees. In Y0, farms fed between 0% and 6% (dietary dry matter proportion per year) of concentrates. During the course of the study they changed the quantity of concentrates to voluntarily chosen degrees. Retrospectively, farms were clustered into five farm groups: Group ‘0-conc’ (n=6 farms) already fed zero concentrates in Y0 and stayed at this level. Group ‘Dec-to0’ (n=11) reduced concentrates to 0 during the project period. Groups ‘Dec-strong’ (n=8) and ‘Dec-slight’ (n=12) decreased concentrate amounts by >50% and <50%, respectively. Group ‘Const-conc’ (n=5 farms) remained at the initial level of concentrates during the project. Milk recording data were summarised and analysed per farm and project year. Lactation number and calving intervals were obtained from the databases of the Swiss breeders’ associations. Dietary concentrate amounts and records of veterinary treatments were obtained from the obligatory farm documentations. Data were analysed with GLMs. Daily milk yields differed significantly between farm groups already in Y0, being lowest in groups 0-conc (16.0 kg) and Dec-to0 (16.7 kg), and highest in groups Dec-slight (19.6 kg) and Const-conc (19.2 kg). Milk yield decreases across the years within groups were not significant, but urea contents in milk decreased significantly during the course of the project. Milk protein, somatic cell score, fat–protein ratio, average lactation number, calving interval and frequency of veterinary treatments did not differ by group and year. In conclusion, 5 years of concentrate reduction in low-input Swiss organic dairy farms, affected neither milk composition, nor fertility and veterinary treatments. Milk yields tended to decline, but at a low rate per saved kilogram of concentrate.

Investigation of the association between the test day milk fat–protein ratio and clinical mastitis using a Poisson regression approach for analysis of time-to-event data

The objective of the present study was to investigate the association between the milk fat–protein ratio and the incidence rate of clinical mastitis including repeated cases of clinical mastitis to determine the usefulness of this association to monitor metabolic disorders as risk factors for udder health. Herd records from 10 dairy herds of Holstein cows in Saxony, Germany, from September 2005–2011 (36,827 lactations of 17,657 cows) were used for statistical analysis. A mixed Poisson regression model with the weekly incidence rate of clinical mastitis as outcome variable was fitted. The model included repeated events of the outcome, time-varying covariates and multilevel clustering. Because the recording of clinical mastitis might have been imperfect, a probabilistic bias analysis was conducted to assess the impact of the misclassification of clinical mastitis on the conventional results.The lactational incidence of clinical mastitis was 38.2%. In 36.2% and 34.9% of the lactations, there was at least one dairy herd test day with a fat–protein ratio of <1.0 or >1.5, respectively. Misclassification of clinical mastitis was assumed to have resulted in bias towards the null. A clinical mastitis case increased the incidence rate of following cases of the same cow. Fat–protein ratios of <1.0 and >1.5 were associated with higher incidence rates of clinical mastitis depending on week in milk. The effect of a fat–protein ratio >1.5 on the incidence rate of clinical mastitis increased considerably over the course of lactation, whereas the effect of a fat–protein ratio <1.0 decreased. Fat–protein ratios <1.0 or >1.5 on the precedent test days of all cows irrespective of their time in milk seemed to be better predictors for clinical mastitis than the first test day results per lactation.

Changes in milk oxidative stress biomarkers in lactating dairy cows with ovulatory and an-ovulatory oestrous cycles

This study was conducted to evaluate changes in milk profiles of oxidative stress (OS) biomarkers in dairy cows with ovulatory and an-ovulatory oestrous cycles. Thirty healthy, cycling Holstein cows averaging 60±17 days in milk, and producing 33±6kg of milk per day (the week before commencing the study) were enrolled in this study. Composite milk samples were collected thrice weekly and assayed for the following OS biomarkers: lipoperoxides (LPO), biological advanced potential, superoxide dismutase (SOD), advanced oxidation protein products (AOPP), ceruloplasmin, glutathione (GSH), β-carotene and glutathione peroxidase (GSH-Px). Milk samples were also tested for fat and protein composition and the fat:protein ratio (FPR) was categorized as low (≤1.31), medium (1.32–1.56) and high (>1.57) to evaluate their main effect and the interaction effect of FPR and the week of study on OS using linear mixed models with cow identification being a random factor. Cows with ovulatory oestrous cycles (n=20) presented significantly greater SOD levels than cows that did not ovulate ((n=10; P<0.05). On the other hand, LPO, GSH-Px and GSH concentrations were lower in ovulated cows compared to the an-ovulated cows (P<0.05). The highest level of LPO and AOPP were noted at prooestrus phase while β-carotene presented the lowest value at that phase of oestrous cycle. It could be postulated that the elevated level of milk SOD and the observed lower level of LPO, GSH-Px and GSH in ovulating cows may be an essential event preceding the ovulatory response.

Milk Composition Measures as Indicators of Energy Balance in Crossbred Dairy Cows

This study had the objective of evaluating the potentials of using milk composition measures as indicator of energy balance (EB) in dairy cows. Milk composition traits (milk protein, fat and lactose percentage) from thirteen (13) primaparous and 47 multiparous (F1) Friesian x Bunaji cows were used for this study. The milk composition was analyzed weekly from 4 to 300days postpartum. The analyzed percentage milk fat, protein and lactose were used to calculate the milk composition measures. The average estimates of EB based on milk measures for all the 3 stages of lactation were positive, however, the magnitude of the average estimates of the EB increased with stages of lactation; the average estimates of EB were 21.99, 46.514 and 59.097MJ/d, respectively, for stages 1, 2 and 3 of lactation. The EB appeared to be less repeatable even within stages of lactation; 0.23, 0.26, 0.31 respectively for stages 1, 2, and 3. The magnitude and direction of the correlations between EB and milk composition traits varied across stages of lactation; the correlation coefficient was relatively stronger in the 3 rd stage than the 1 st and 2 nd stages of lactation. The potential indicators of EB are the protein contained variables, such as milk protein percentage (MPC), fat-protein ratio (FPR), change in milk protein yield (dmPy) and change in fat-protein ratio (dFPR). These variables had strong relationship with EB both within and across lactation stages. However, the correlation between EB and change in milk protein yield (dmPy) was consistently strong both within and across lactation stages. Base on the foregoing, it can be deduced that the most reliable indicator of energy balance in the medium yield Friesian x Bunaji dairy cows is the change in milk protein yield (dmPy), although other variables such as milk protein content (MPC), fatprotein ration (FPR) and change in fat to protein ratio (dFPR) could also be used as indicators of energy balance. However, dmPy seems to be the component common to all of these potential milk production variables.

ASSESSMENT OF PERSISTENCE COMPONENTS OF MILK FROM SIMMENTAL COWS-HEIFERS OF DIFFERENT ORIGIN

It was found that the persistence of milk components positively correlated with the dynamics of daily milk yield per lactation. Mass fraction of fat and protein in milk reached lows in mid-lactation, while the time of launch in protein content were observed maximum values. A similar pattern was noted for the mass fraction of the dry matter, but on the percentage of lactose opposite trend: early and late lactation milk sugar content was less than the decrease peak periods and maximum daily milk yield. By reducing the ratio of fat-protein from calving to the end of lactation was observed simultaneous increase in the number of somatic cells in the milk of cows, heifers. The best estimate of the persistence of daily monitoring of indicators of milk components had a mass fraction of lactose and protein, and fat-protein ratio.

Evaluation of Nutritional status of Friesian x Bunaji dairy herd based on milk composition Analysis

The research was conducted on the dairy herd of National Animal Production Research Institute (NAPRI), Shika-Nigeria, to evaluation the nutritional status of Friesian x Bunaji dairy herd based on milk composition analysis. Milk samples were analysed weekly for percentage milk fat, protein and lactose for 120 days. These milk composition variables were used to calculate the fat-protein ratio (FPR) as well as the energy corrected milk (ECM). The result revealed that the mean fat, protein, and lactose content were 4.49%, 4.32%, and 4.43%, respectively, while the mean FPR and ECM was 1.05 and 8.05kg , respectively. Analysis of the average values of the milk components indicates that considerable number of cows (70%) had fibre deficient and energy surplus ration and only 26% of the animals had ration balanced in fibre and energy, while 4% had ration deficient in energy and fiber surplus. The FPR changes within the 120 day lactation revealed higher values of 1.19 at the beginning of lactation and decreased as the lactation progresses to as low as 0.82 by the 120th day of lactation. The percentage milk fat, lactose and FPR had significant inverse relationship with milk yield, milk protein percentage and ECM. An increasing trend in daily milk yield was observed as the parity of the cows advanced from the first to the third parity and then decreases thereafter. Using milk analysis results it is possible to estimate major problems in dairy cow nutrition, predict and prevent possible nutritional and metabolic disorder.

Genetic associations of test-day fat:protein ratio with milk yield, fertility, and udder health traits in Nordic Red cattle

Interest is growing in finding indicator traits for the evaluation of nutritional or tissue energy status of animals directly at the individual animal level. The development and subsequent use of such traits in practice demands a clear understanding of the genetic and phenotypic associations with the various production and functional traits. In this study, the relationships during lactation between milk fat:protein ratio (FPR) and production and functional traits were estimated for Nordic Red cattle, in which published information is scarce. The objectives of this study were to estimate genetic associations of FPR with milk yield (MY), fertility, and udder health traits during different stages of lactation. Traits included in the analyses were MY, 4 fertility traits—days from calving to insemination (DFI), days open (DO), number of inseminations (NI), and nonreturn rate to 56d (NRR)—and 2 udder health traits—test-day somatic cell score (SCS) and clinical mastitis (CM). Data were from a total of 22,422 first-lactation cows. Random regression models were used to estimate genetic parameters and associations between traits. The mean FPR in first-lactation cows was 1.28 and ranged from 1.25 to 1.45. During first lactation, the heritability of FPR ranged from 0.14 to 0.25. Genetic correlations between FPR and MY in early lactation (until 50d in milk) were positive and ranged from 0.05 to 0.22; later in lactation, they were close to zero or negative, indicating that cows may have come out of the negative state of energy balance. The strength of genetic associations between FPR and fertility traits varied during lactation. In early lactation, correlations between FPR and the interval fertility traits DFI and DO were positive and ranged from 0.14 to 0.28. Genetic correlations between FPR and the udder health traits SCS and CM in early lactation ranged from 0.09 to 0.20. Milk fat:protein ratio is a heritable trait and easily available from routine milk-recording schemes. It can be used as a low-cost monitoring tool of poor health and fertility in the most critical phases of lactation and as an important indicator trait to improve robustness in dairy cows through selection.

Association between blood β-hydroxybutyric acid in postparturient dairy cows and the incidence of clinical diseases, milk yield, milk components, reproduction, and culling during early lactation

The objectives of this study was to a) evaluate the association between subclinical ketosis (SCK) and the subsequent incidence of various clinical diseases; b) evaluate the association between various clinical diseases and the subsequent incidence of SCK; and c) evaluate the association between SCK and milk yield (MILK), fat content (FAT), protein content (PROT), fat:protein ratio (FPR), linear somatic cell count (LSCC) at first test, conception at first breeding (CFB), and culling before 60 DIM (CULL60).