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type:Article, Antibacterial factors act as innate immune components, which respond as soon as bacteria enter a living organism. To prevent and treat mastitis in cattle, understanding the concentrations of these substances inside the udder is important; however, they remain to be studied. In this investigation, the concentration of lingual antimicrobial peptide (LAP), S100 protein (S100A7), lactoferrin (LF), and immunoglobulin antibody were measured in the different fractions of foremilk. Lactating Holstein cows were examined, and 10 foremilk fractions were obtained from sequential samples up to 150 ml. The LAP concentrations in milk samples increased until 25 ml. The LF concentrations increased up to the 10 ml fraction, then stabilized at low level after the 50 ml fraction. For S100A7, some fractions had significantly higher (p < .05) concentrations than the 5 or 10 ml fractions. The IgA antibody concentration increased up to the 5 ml fraction, then after 50 ml fraction showed relatively low concentrations. This investigation determined the concentration patterns of LAP, LF, S100A7, and IgA antibody secreted in milk inside the udders of healthy lactating cows as baseline data. These distinct concentration patterns might indicate various protective responses.

Mathematical models for predicting P excretions play a key role in evaluating P use efficiency and monitoring the environmental impact of dairy cows. However, the majority of extant models require feed intake as predictor variable, which is not routinely available at farm level. The objectives of the study were to (1) explore factors explaining heterogeneity in P output; (2) develop a set of empirical models for predicting P output in feces (Pf), manure (PMa), and milk (Pm, all in g/cow per day) with and without dry matter intake (DMI) using literature data; and (3) evaluate new and extant P models using an independent data set. Random effect meta-regression analyses were conducted using 190 Pf, 97 PMa, and 118 Pm or milk P concentration (PMilkC) treatment means from 38 studies. Dietary nutrient composition, milk yield and composition, and days in milk were used as potential covariates to the models with and without DMI. Dietary phosphorus intake (Pi) was the major determinant of Pf and PMa. Milk yield negatively affected Pi partitioning to Pf or PMa. In the absence of DMI, milk yield, body weight, and dietary P content became the major determinants of Pf and PMa. Milk P concentration (PMilkC) was heterogeneous across the treatment groups, with a mean of 0.92 g/kg of milk. Milk yield, days in milk, and dietary Ca-to-ash ratio were negatively correlated with PMilkC and explained 42% of the heterogeneity. The new models predicted Pf and PMa with root mean square prediction error as a percentage of observed mean (RMSPE%) of 18.3 and 19.2%, respectively, using DMI when evaluated with an independent data set. Some of the extant models also predicted Pf and PMa well (RMSPE%=19.3 to 20.0%) using DMI. The new models without DMI as a variable predicted Pf and PMa with RMSPE% of 22.3 and 19.6%, respectively, which can be used in monitoring P excretions at farm level. When evaluated with an independent data set, the new model and extant models based on milk protein content pre

Mathematical models for predicting P excretions play a key role in evaluating P use efficiency and monitoring the environmental impact of dairy cows. However, the majority of extant models require feed intake as predictor variable, which is not routinely available at farm level. The objectives of the study were to (1) explore factors explaining heterogeneity in P output; (2) develop a set of empirical models for predicting P output in feces (Pf), manure (PMa), and milk (Pm, all in g/cow per day) with and without dry matter intake (DMI) using literature data; and (3) evaluate new and extant P models using an independent data set. Random effect meta-regression analyses were conducted using 190 Pf, 97 PMa, and 118 Pm or milk P concentration (PMilkC) treatment means from 38 studies. Dietary nutrient composition, milk yield and composition, and days in milk were used as potential covariates to the models with and without DMI. Dietary phosphorus intake (Pi) was the major determinant of Pf and PMa. Milk yield negatively affected Pi partitioning to Pf or PMa. In the absence of DMI, milk yield, body weight, and dietary P content became the major determinants of Pf and PMa. Milk P concentration (PMilkC) was heterogeneous across the treatment groups, with a mean of 0.92 g/kg of milk. Milk yield, days in milk, and dietary Ca-to-ash ratio were negatively correlated with PMilkC and explained 42% of the heterogeneity. The new models predicted Pf and PMa with root mean square prediction error as a percentage of observed mean (RMSPE%) of 18.3 and 19.2%, respectively, using DMI when evaluated with an independent data set. Some of the extant models also predicted Pf and PMa well (RMSPE%=19.3 to 20.0%) using DMI. The new models without DMI as a variable predicted Pf and PMa with RMSPE% of 22.3 and 19.6%, respectively, which can be used in monitoring P excretions at farm level. When evaluated with an independent data set, the new model and extant models based on milk protein content pre

Objective. This study was conducted during winter season at rural livestock farm of district Sargodha, Pakistan, in order to define the macrominerals status in blood plasma of lactating and dry Desi breed cows. Material and methods. Twenty lactating and twenty dry cows were used and their blood plasma was analyzed for Ca, Mg, Zn, Cu and Fe using atomic absorption spectrophotometer. Results. In lactating cows, the plasma Ca concentration was lower than dry cows (6.8 vs. 7.6 mg/dl, p<0.001), while Mg concentration was similar between lactating and dry cows. Plasma Zn concentration in lactating cows was higher than dry cows (0.78 vs. 0.60mg/l, p<0.01) and it resulted lower than the normal range in both groups. Plasma Cu level in lactating cows was lower than dry cows (0.56 vs. 0.76 mg/L, p<0.001) and it was lower than the normal range only in lactating cows. Lactating cows resulted in higher plasma Fe concentration compared to dry cows (3.8 versus 2.6 mg/L; p<0.01). Conclusions. From our findings, it can be concluded that the observed minerals level meets the needs of ruminants and the plasma level of different minerals is affected by the physiological stages of cows., Objetivo. Este estudio se realizó durante la estación de invierno en la granja de ganado rural del distrito de Sargodha, Pakistán, con el fin de definir el estado de macrominerales en el plasma sanguíneo de vacas lactantes y secas de raza Desi. Materiales y métodos. Veinte vacas lactantes y veinte vacas secas fueron utilizadas y se analizó el plasma para el Ca, Mg, Zn, Cu y Fe utilizando un espectrofotómetro de absorción atómica. Resultados. En las vacas lactantes, la concentración de Ca en plasma fue menor que en las vacas secas (6.8 frente a 7.6 mg/dl, p<0.001), mientras que la concentración de Mg fue similar entre las lactantes y las vacas secas. La concentración plasmática de Zn en las vacas lactantes fue mayor que en las vacas secas (0.78 frente a 0.60 mg/L, p<0.01) y resultó inferior al rango normal en ambos grupos. Nivel de plasma de Cu en vacas lactantes fue inferior al de las vacas secas (0.56 vs a 0.76 mg/L, p<0.001) y fue inferior al rango normal sólo en las vacas lactantes. Las vacas lactantes resultaron en mayor concentración de Fe plasmático en comparación con las vacas secas (3.8 frente a 2.6 mg/l, p<0.01). Conclusiones. A partir de los resultados, se puede concluir que el nivel de minerales observados satisface las necesidades de los rumiantes y el nivel plasmático de diferentes minerales se ve afectado por las etapas fisiológicas de las vacas.

This study explored the ability of an existing lifetime nutrient partitioning model for simulating individual variability in genetic potentials of dairy cows. Generally, the model assumes a universal trajectory of dynamic partitioning of priority between life functions and genetic scaling parameters are then incorporated to simulate individual difference in performance. Data of 102 cows including 180 lactations of 3 breeds: Danish Red, Danish Holstein, and Jersey, which were completely independent from those used previously for model development, were used. Individual cow performance records through sequential lactations were used to derive genetic scaling parameters for each animal by calibrating the model to achieve best fit, cow by cow. The model was able to fit individual curves of body weight, and milk fat, milk protein, and milk lactose concentrations with a high degree of accuracy. Daily milk yield and dry matter intake were satisfactorily predicted in early and mid lactation, but underpredictions were found in late lactation. Breeds and parities did not significantly affect the prediction accuracy. The means of genetic scaling parameters between Danish Red and Danish Holstein were similar but significantly different from those of Jersey. The extent of correlations between the genetic scaling parameters was consistent with that reported in the literature. In conclusion, this model is of value as a tool to derive estimates of genetic potentials of milk yield, milk composition, body reserve usage, and growth for different genotypes of cow. Moreover, it can be used to separate genetic variability in performance between individual cows from environmental noise.

High-sugar grass varieties have received considerable attention for their potential ability to decrease N excretion in cattle. However, feeding high-sugar grasses alters the pattern of rumen fermentation, and no in vivo studies to date have examined this strategy with respect to another environmental pollutant: methane (CH4). Modeling allows us to examine potential outcomes of feeding strategies under controlled conditions, and can provide a useful framework for the development of future experiments. The purpose of the present study was to use a modeling approach to evaluate the effect of high-sugar grasses on simulated CH4 emissions in dairy cattle. An extant dynamic, mechanistic model of enteric fermentation and intestinal digestion was used for this evaluation. A simulation database was constructed and analysis of model behavior was undertaken to simulate the effect of (1) level of water-soluble carbohydrate (WSC) increase in dietary dry matter, (2) change in crude protein (CP) and neutral detergent fiber (NDF) content of the plant with an increased WSC content, (3) level of N fertilization, and (4) presence or absence of grain feeding. Simulated CH4 emissions tended to increase with increased WSC content when CH4 was expressed as megajoules per day or percent of gross energy intake, but when CH4 was expressed in terms of grams per kilogram of milk, results were much more variable due to the potential increase in milk yield. As a result, under certain conditions, CH4 (g/kg of milk) decreased. The largest increases in CH4 emissions (MJ/d or % gross energy intake) were generally seen when WSC increased at the expense of CP in the diet and this can largely be explained by the representation in the model of the type of volatile fatty acid produced. Effects were lower when WSC increased at the expense of NDF, and intermediary when WSC increased at the expense of a mixture of CP and NDF. When WSC increased at the expense of NDF, simulated milk yield increased and, ther

One primiparous and 3 multiparous lactating Holstein cows fitted with ruminal and duodenal cannulas were used in a 4 × 4 Latin square design to determine the efficacy of adding urea to a corn silage-based diet on ruminal fermentation and microbial protein synthesis. Dietary treatments were 0, 0.3, 0.6, and 0.9% urea in diet dry matter (DM); urea was manually top dressed and incorporated into the ration. The basal diet contained (DM basis) 52% forage (with 61% of forage provided as corn silage) and 48% concentrate ingredients. The basal diet was formulated to meet National Research Council (NRC, 2001) requirements for energy and all nutrients except rumen-degradable protein (RDP) and metabolizable protein. Experimental periods lasted 14 d with the first 9 d for adaptation. The basal diet, without urea addition, contained 9.2% RDP in DM and had a predicted RDP balance of −167 g/d (NRC, 2001). There were no effects of dietary treatment on ruminal true digestibility of organic matter or ruminal apparent digestibility of neutral detergent fiber and acid detergent fiber. Total ruminal volatile fatty acid concentrations increased linearly with increasing urea level. Feeding increasing amounts of urea quadratically increased rumen ammonia N concentrations (9.0, 11.9, 12.8, and 17.4 mg/dL at 0, 0.3, 0.6, and 0.9% urea supplementation, respectively), passage of microbial N, and microbial N in duodenal digesta as a percentage of nonammonia N. The results of this study indicate that there were some positive effects of adding urea to the described lactating dairy cow diet, and that microbial protein synthesis was maximized at an average ruminal ammonia N concentration of 12.8 mg/dL when urea was added at 0.6% in diet DM.

The objective of these studies was to determine the effects of forage fiber, social hierarchy, and stocking density on stress in lactating cows during relocation to new dairy facilities. In experiment one, 23 lactating cows were fed a basal ration, or the basal ration plus grass or alfalfa hay at 10% of DM offered from 3 wk pre-move to 9 wk post-move. In experiment two, 17 lactating cows were housed together before and after relocation and evaluated for dominance rank. In experiment three, 44 cows were housed together before relocation, then in pens of varying stocking density (0.67, 0.83, 1.0, or 1.17 cows per stall) post-move. In these studies, the effects of treatment on MY, lameness, behaviors, plasma cortisol, cow cleanliness, and DMI were monitored. In experiment one, cows fed grass or alfalfa hay diets had higher plasma cortisol concentrations on the day of relocation than cows fed TMR, but there were no differences in DMI or MY. Cows fed alfalfa hay or TMR had increased lameness scores following relocation; cows fed grass hay did not have increased lameness scores. In experiment two, there were no differences in plasma cortisol or lameness scores between dominant and subordinate cows. Subordinate cows had lower MY following relocation compared to dominant cows. In experiment three, cows housed at a stocking rate of 1.17 had higher plasma cortisol than cows housed at a stocking rate of 0.67. All cows had higher lameness scores following relocation, but cows housed at a stocking rate of 0.67 tended to have higher lameness scores than cows housed at stocking rates of 0.83, 1.0, and 1.17. In summary, some management practices may decrease the negative effects of stress on lactating cows during relocation.