scholarly journals Effect of a metabolically created systemic acidosis on calcium homeostasis and the diurnal variation in urine pH in the non-lactating pregnant dairy cow

2006 ◽  
Vol 74 (1) ◽  
pp. 34-39 ◽  
Author(s):  
John R Roche ◽  
Dawn E Dalley ◽  
Frank P O'Mara
Keyword(s):  
Diurnal Variation ◽  
Effective Means ◽  
Basal Diet ◽  
Diurnal Pattern ◽  
Urine Ph ◽  
Urinary Hydroxyproline ◽  
Balance Study ◽  
Rumen Ph ◽  
Holstein Friesian ◽  
Friesian Cows

Reducing the dietary cation-anion difference (DCAD) has been shown to be an effective means of preventing parturient paresis in confinement systems where cows are offered a total mixed ration containing DCAD-reducing mineral compounds (anionic salts). Such a supplementation strategy is not possible in cows being group fed forages precalving, and little is known about the effect of supplementing these cows with large amounts of anionic salts twice daily.Eight non-lactating, pregnant Holstein-Friesian cows were allocated to two levels of DCAD (−20 and +18 meq/100 g DM) for 24 d, with an intensive Ca balance undertaken in metabolism stalls following a 2-week acclimatization to diet. The basal diet was 3 kg DM of crushed barley and 7 kg DM of pasture-hay. Urine and faeces were collected separately, weighed daily for 5 d and analysed for Ca content. Urinary Ca, creatinine and hydroxyproline concentration and plasma Ca concentration were determined during the period of the balance study. The diurnal pattern in urine and rumen pH was determined over 2 d. Decreasing DCAD reduced (P<0·001) the pH of urine, and increased (P<0·05) Ca absorption. Plasma Ca concentration was not affected by DCAD, and DCAD did not affect the output of urinary hydroxyproline, a marker of bone resorption. Twice-daily supplementation of anionic salts was sufficient to reduce the pH of blood and increase gastrointestinal Ca absorption. There was no diurnal variation in the pH of urine, suggesting that time of sampling to determine efficacy of DCAD in reducing systemic pH was not important.

scholarly journals Diurnal Concentration of Urinary Nitrogen and Rumen Ammonia Are Modified by Timing and Mass of Herbage Allocation

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 961
Author(s):  
Ignacio E. Beltran ◽  
Pablo Gregorini ◽  
José Daza ◽  
Oscar A. Balocchi ◽  
Alvaro Morales ◽  
...  
Keyword(s):  
Latin Square ◽  
Time Of Day ◽  
Diurnal Pattern ◽  
Grass Silage ◽  
Lactating Dairy Cows ◽  
N Concentration ◽  
Holstein Friesian ◽  
And Storage ◽  
Urinary Nitrogen ◽  
Friesian Cows

The objective of this work was to evaluate whether changes in time of herbage allocation and herbage mass (HM) (low (L) or medium (M)) modify the diurnal pattern of urinary nitrogen (N) concentration and ruminal ammonia (NH3) of lactating dairy cows. Four Holstein-Friesian cows fitted with rumen cannula were randomly allocated to one of four treatments: 1) low herbage mass in the morning (L-AM) (Access to new herbage allocation after morning milking with a herbage mass (HM) of 2000 kg DM/ha); 2) low herbage mass in the afternoon (L-PM) (Access to new herbage allocation after afternoon milking with a HM of 2000 kg DM/ha); 3) medium herbage mass in the morning (M-AM) (Access to new herbage allocation after morning milking with a HM of 3000 kg DM/ha); and 4) medium herbage mass in the afternoon (M-PM) (Access to new herbage allocation after afternoon milking with a HM of 3000 kg DM/ha). A four by four Latin Square design with four treatments, four cows, and four experimental periods was used to evaluate treatment effects. Rumen NH3 concentration was greater for L-AM compared to L-PM and M-PM at 13:00 and 16:00 h. Urine urea and N concentrations were lower for M-AM compared to L-AM. Urine N concentration was greater for L-AM than other treatments at 10:00 hours and greater for M-PM compared to M-AM at 16:00 hours. Results suggest that maintaining the cows in the holding pen at the milking parlor for two hours after morning grass silage supplementation for L-AM and for two hours after afternoon grass silage supplementation for M-PM, could allow collection of urine from cows at the holding pen and storage of urine in the slurry pit during the time of peak N concentration, returning cows to the pasture at a time of day when urinary N concentration is decreased.

Effects of divergent Holstein-Friesian strain and diet on diurnal patterns of plasma metabolites and hormones

2010 ◽  
Vol 77 (4) ◽  
pp. 432-437 ◽  
Author(s):  
Susanne Meier ◽  
Eric S Kolver ◽  
Gwyneth A Verkerk ◽  
John R Roche
Keyword(s):  
Diurnal Variation ◽  
Plasma Concentrations ◽  
Time Of Day ◽  
Plasma Metabolites ◽  
Lactating Cows ◽  
Diurnal Patterns ◽  
Holstein Friesian ◽  
Main Effects ◽  
Different Levels ◽  
Friesian Cows

Commonly measured metabolite and hormone concentrations used to describe the metabolic status of lactating cows undergo diurnal variation resulting in distinct patterns. Studies have shown that feeding events can modulate these diurnal patterns as cows respond to the nutrient intake. What is less clear is the extent to which cow genetics and diet interact to modify the diurnal patterns of specific nutritionally related metabolites and hormones. The objective of this study was to investigate diurnal patterns in circulating metabolite and hormone concentrations in divergent strains of Holstein-Friesian cows (North American, NA; and New Zealand, NZ) offered either fresh pasture (FP) or a total mixed ration (TMR). Plasma concentrations of growth hormone (GH), insulin-like growth factor-1 (IGF-1), glucose, insulin, β-hydroxybutyrate (BHBA), and non-esterified fatty acids (NEFA) were determined at 4-h intervals for a minimum of three consecutive days. All of the above metabolites and hormones exhibited within-day variability. Main effects of genetic strain and diet were observed for plasma IGF-1, and a strain by diet interaction was observed for GH. Time of day×diet interactions were observed for both glucose and insulin. Three-way interactions (time of day×diet×strain) were observed for BHBA and NEFA. These data indicate different levels of diurnal variation, with glucose, insulin, NEFA and BHBA having the largest daily variation. These diurnal patterns need to be considered in future investigations of these metabolites and hormones.

Rumen degradability characteristics of five starch-based concentrate supplements used on Australian dairy farms

2017 ◽  
Vol 57 (7) ◽  
pp. 1512 ◽  
Author(s):  
R. P. McDonnell ◽  
M. vH. Staines ◽  
M. L. Douglas ◽  
M. J. Auldist ◽  
J. L. Jacobs ◽  
...  
Keyword(s):  
Crude Protein ◽  
Degradation Kinetics ◽  
Basal Diet ◽  
Exponential Model ◽  
Holstein Friesian ◽  
Custom Made ◽  
Maize Grain ◽  
Ruminal Digestion ◽  
Friesian Cows ◽  
In Sacco

This experiment compared the rumen degradability characteristics of five starch-based concentrate supplements used by Western Australia (WA) dairy producers. Six rumen-fistulated, non-lactating, Holstein-Friesian cows were used to measure the in sacco rumen degradability of maize grain, oats, wheat, sodium hydroxide-treated wheat (NaOH wheat) and Maximize® (a commercial pellet commonly used by WA dairy producers). Cows were offered a basal diet of custom-made cubes (60 : 40 lucerne hay : wheat grain) at maintenance feeding level. Rumen disappearance of dry matter (DM), starch and crude protein was determined for each concentrate at 0, 1, 2, 4, 8, 16, 24, 36, 48 and 72 h, and fitted to an exponential model to estimate degradation kinetics. Effective degradability coefficients were then calculated at three rumen solid-outflow rates (0.02, 0.05 and 0.08/h). Degradability of DM at 0.08/h was lowest (P < 0.001) in maize grain (0.64) and oats (0.68) and greatest in wheat (0.83), with that in NaOH wheat (0.80) and Maximize (0.76) being intermediate. Starch degradability at 0.08/h was also lowest (P < 0.001) in maize grain (0.70), intermediate for NaOH wheat (0.83) and Maximize (0.87), and greatest for wheat (0.96) and oats (0.98). Degradability of crude protein was lowest (P = 0.001) in Maximize (0.66) and NaOH wheat (0.69), greatest in oats (0.85), with that in maize grain (0.72) and wheat (0.79) being intermediate. For producers where availability of maize grain for dairy cow rations is limited, such as in WA, these results indicated that NaOH wheat and Maximize may be considered as alternative starch sources to increase post-ruminal digestion of starch, although the magnitude of this increase will still not be as great as for maize grain.

Adding bentonite to sorghum grain-based supplements has no effect on cow milk production

1997 ◽  
Vol 37 (5) ◽  
pp. 505 ◽  
Author(s):  
W. K. Ehrlich ◽  
T. M. Davison
Keyword(s):  
Milk Production ◽  
Crude Protein ◽  
Lolium Multiflorum ◽  
Latin Square ◽  
Cow Milk ◽  
Meat And Bone Meal ◽  
Rumen Ph ◽  
Holstein Friesian ◽  
Sorghum Grain ◽  
Friesian Cows

Summary. Twenty-four Holstein–Friesian cows were used in an experiment comparing milk production from cows offered rolled sorghum grain either alone at 8 or 10 kg/head. day of air-dried grain or with 4% sodium bentonite. The design was a 4 × 4 latin square with a 1 week adjustment period and a 3 week treatment period. This design was used to highlight the effects of high levels of grain feeding and changing that level of grain or grain–bentonite every 4 weeks. Cows grazed either ryegrass (Lolium multiflorum cv. Tetila) or oats (Avena sativa cv. Cluan) during the day and a mixed ration based on maize silage, lucerne hay, and meat and bone meal at night. There was no significant effect of treatments on milk yield or composition. Cows fed bentonite had a higher (P<0.05) rumen pH, tended to eat less grain sorghum and have lower concentrations of rumen ammonia and faecal starch. Faecal crude protein tended to increase with the use of bentonite indicating cows may have substituted pasture or mixed ration for grain and maintained a more stable rumen fermentation.

Effects of concentrate acidogenicity on the performance of cows on maize silage-based diets

1999 ◽  
Vol 1999 ◽  
pp. 74-74
Author(s):  
D. Wadhwa ◽  
M.S. Dhanoa ◽  
W.J. Fisher ◽  
L.P. Borgida ◽  
R.J. Dewhurst
Keyword(s):  
Energy Requirements ◽  
Maize Silage ◽  
The Third ◽  
Rumen Ph ◽  
Holstein Friesian ◽  
Acid Load ◽  
Ad Libitum ◽  
Fermentable Carbohydrates ◽  
Friesian Cows

Feeding of highly fermentable carbohydrates is often necessary to meet the energy requirements of high producing cows. Unfortunately, these diets can lead to reduced rumen pH and impaired productivity. Earlier work showed that maize silage intake was greatly reduced when concentrates producing a high rumen acid load (Acidogenicity Value (AV); Wadhwa et al., 1998) were included at 0.5 of feed DM intake (Dewhurst et al., 1998). This further experiment sought to define the level of concentrate feeding at which AV becomes important.Sixteen Holstein-Friesian cows in the third month of lactation were used. After a covariance period, cows went onto a cyclical changeover design with four periods each lasting for 21 days. Maize silage was offered ad libitum, through Calan gates, along with a fixed allocation of one of 8 concentrates.

scholarly journals The influence of slowly and rapidly degradable concentrate protein on a number of rumen parameters in dairy cattle.

1986 ◽  
Vol 34 (2) ◽  
pp. 199-216
Author(s):  
W.A.G. Veen
Keyword(s):  
Volatile Fatty Acids ◽  
Rumen Fluid ◽  
Rumen Content ◽  
Ammonia Content ◽  
Rumen Ph ◽  
Holstein Friesian ◽  
Sampling Times ◽  
Degradable Protein ◽  
Friesian Cows ◽  
Protein Degradability

In 5 trials with Dutch Black Pied or Dutch Black Pied X Holstein-Friesian cows the effects of feeding concentrates with rapidly and slowly degradable protein on rumen values were investigated. Samples of rumen fluid were taken before and 45, 90, 135 and 180 min after the morning concentrate feed. Rumen pH was not affected by protein degradability. Rumen ammonia content was higher when easily degradable protein was given than when slowly degradable protein was given; peak concentration varied from 10 to 12.5 and from 4 to 8 mmol/litre, respectively. Maximum concentration of lactate was not influenced by protein degradability. Rumen content of volatile fatty acids increased more rapidly when the slowly degradable protein rather than when the rapidly degradable protein was given. At all sampling times the molar acetate:propionate ratio was higher after feeding on slowly degradable protein than after rapidly degradable protein. (Abstract retrieved from CAB Abstracts by CABI’s permission)

scholarly journals The Use of Artificial Neural Networks and a General Discriminant Analysis for Predicting Culling Reasons in Holstein-Friesian Cows Based on First-Lactation Performance Records

Animals ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 721
Author(s):  
Krzysztof Adamczyk ◽  
Wilhelm Grzesiak ◽  
Daniel Zaborski
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Discriminant Analysis ◽  
Multilayer Perceptrons ◽  
Correct Classification ◽  
Correct Classification Rate ◽  
Classification Rate ◽  
Holstein Friesian ◽  
Artificial Neural ◽  
Friesian Cows

The aim of the present study was to verify whether artificial neural networks (ANN) may be an effective tool for predicting the culling reasons in cows based on routinely collected first-lactation records. Data on Holstein-Friesian cows culled in Poland between 2017 and 2018 were used in the present study. A general discriminant analysis (GDA) was applied as a reference method for ANN. Considering all predictive performance measures, ANN were the most effective in predicting the culling of cows due to old age (99.76–99.88% of correctly classified cases). In addition, a very high correct classification rate (99.24–99.98%) was obtained for culling the animals due to reproductive problems. It is significant because infertility is one of the conditions that are the most difficult to eliminate in dairy herds. The correct classification rate for individual culling reasons obtained with GDA (0.00–97.63%) was, in general, lower than that for multilayer perceptrons (MLP). The obtained results indicated that, in order to effectively predict the previously mentioned culling reasons, the following first-lactation parameters should be used: calving age, calving difficulty, and the characteristics of the lactation curve based on Wood’s model parameters.

scholarly journals Determination of Body Parts in Holstein Friesian Cows Comparing Neural Networks and k Nearest Neighbour Classification

Animals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Jennifer Salau ◽  
Jan Henning Haas ◽  
Wolfgang Junge ◽  
Georg Thaller
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Body Parts ◽  
Nearest Neighbour ◽  
Data Set ◽  
3D Data ◽  
Holstein Friesian ◽  
Knn Classification ◽  
Friesian Cows

Machine learning methods have become increasingly important in animal science, and the success of an automated application using machine learning often depends on the right choice of method for the respective problem and data set. The recognition of objects in 3D data is still a widely studied topic and especially challenging when it comes to the partition of objects into predefined segments. In this study, two machine learning approaches were utilized for the recognition of body parts of dairy cows from 3D point clouds, i.e., sets of data points in space. The low cost off-the-shelf depth sensor Microsoft Kinect V1 has been used in various studies related to dairy cows. The 3D data were gathered from a multi-Kinect recording unit which was designed to record Holstein Friesian cows from both sides in free walking from three different camera positions. For the determination of the body parts head, rump, back, legs and udder, five properties of the pixels in the depth maps (row index, column index, depth value, variance, mean curvature) were used as features in the training data set. For each camera positions, a k nearest neighbour classifier and a neural network were trained and compared afterwards. Both methods showed small Hamming losses (between 0.007 and 0.027 for k nearest neighbour (kNN) classification and between 0.045 and 0.079 for neural networks) and could be considered successful regarding the classification of pixel to body parts. However, the kNN classifier was superior, reaching overall accuracies 0.888 to 0.976 varying with the camera position. Precision and recall values associated with individual body parts ranged from 0.84 to 1 and from 0.83 to 1, respectively. Once trained, kNN classification is at runtime prone to higher costs in terms of computational time and memory compared to the neural networks. The cost vs. accuracy ratio for each methodology needs to be taken into account in the decision of which method should be implemented in the application.

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