scholarly journals Conception Rates of Holstein-Friesian Cows Inseminated Artificially with Reducing Frozen Semen Doses

2016 ◽  
Vol 39 (2) ◽  
pp. 75-81
Author(s):  
A. Anggraeni ◽  
T. Herawati ◽  
L. Praharani ◽  
D. Utami ◽  
A. Argis
Keyword(s):  
Holstein Friesian ◽  
Frozen Semen ◽  
Conception Rates ◽  
Friesian Cows

Effect of abnormal vaginal discharge at oestrus on conception rate after artificial insemination in cows

2001 ◽  
Vol 72 (3) ◽  
pp. 535-538 ◽  
Author(s):  
A. R. Mahmoudzadeh ◽  
M. Tarahomi ◽  
H. Fotoohi
Keyword(s):  
Artificial Insemination ◽  
Dairy Herd ◽  
Normal Group ◽  
Cervical Mucus ◽  
Conception Rate ◽  
Holstein Friesian ◽  
Conception Rates ◽  
Mucous Discharge ◽  
Abnormal Group ◽  
Friesian Cows

AbstractDuring a 2-year study from January 1997 to December 1999, the visual characteristics of the cervical mucous discharge of cows and heifers in oestrus and their relations to conception rate were studied in a large dairy herd of Holstein-Friesian cows. Cows were divided into two groups based on mucous discharge being of normal or abnormal appearance and the group with abnormal discharge was further divided into the following classes: cervical mucus with urine (CMU), cervical mucus with microbes (CMM), cervical mucus with blood (CMB) and a group with no cervical mucus (NCM). From 6169 cases of cows in oestrus, 82·2% had normal discharge, and the remaining 17·8% had abnormal discharge classifications (6·1% CMU, 5·1% CMM, 0·5% CMB and 6·1% NCM). Conception rate after artificial insemination (AI) in the normal group (38·3%) was significantly higher than that of the abnormal group (27·9%), (P < 0·05). When the conception rate of the normal group was compared with each one of the abnormal classifications, it was significantly different from that of CMU (26·5%), CMM (22·6%) and CMB (21·8%), (P < 0·05), but not from that of NCM (34·4%), (P > 0·05). From 1734 cases of heifers in oestrus, only 6% had abnormal discharges, and the conception rates of the normal and abnormal groups were not significantly different (P > 0·05).We conclude that AI of cows in oestrus discharging cervical mucus that is contaminated with urine, microbes or blood produces conception rates significantly lower than those of cows discharging a normal and clear mucus. Absence of a cervical mucous discharge at the time of AI of cows does not imply a low conception rate. In the case of heifers, appearance of cervical mucus had no effect on the conception rate after AI.

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.

Evaluation of intrauterine insemination of sheep with frozen semen: effects of time of insemination and semen dose on conception rates

1991 ◽  
Vol 53 (1) ◽  
pp. 89-96 ◽  
Author(s):  
R. C. F. Findlater ◽  
W. Haresign ◽  
R. M. Curnock ◽  
N. F. G. Beck
Keyword(s):  
Intrauterine Insemination ◽  
Field Application ◽  
Conception Rate ◽  
Laparoscopic Technique ◽  
Motile Sperm ◽  
Treatment Groups ◽  
Frozen Semen ◽  
Significant Difference ◽  
Conception Rates ◽  
Serum Gonadotropin

ABSTRACTThe field application of a laparoscopic technique to permit intra-uterine insemination of ewes with frozen-thawed semen was examined in two trials, conducted over successive years, to (i) determine the optimum time of insemination relative to sponge removal/pregnant mares's serum gonadotropin (PMSG) injection and (ii) establish the relationship between semen dose and conception rate. Pooled semen was used in both trials, and each involved > 900 ewes in a number of commercial flocks.Maximum conception rates were achieved when insemination was conducted between 54 h and 60 h after sponge removal/ PMSG injection. However, there was no significant difference in conception rate when motile sperm numbers were reduced from 52·2 × 106to 13·0 × 106 motile sperm per uterine horn.The overall conception rates (pooled over flocks and treatment groups) were 56% and 58% for the two trials, with a wide degree of variation between flocks in both cases (45% to 79% for trial 1 and 45% to 69% for trial 2). However, there was evidence for consistent differences in conception rates between the six flocks involved in both years of the trials.

scholarly journals Flow Cytometric Assessment of the Viability and Functionality of Uterine Polymorphonuclear Leukocytes in Postpartum Dairy Cows

Animals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 1081
Author(s):  
Leen Lietaer ◽  
Kristel Demeyere ◽  
Stijn Heirbaut ◽  
Evelyne Meyer ◽  
Geert Opsomer ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Polymorphonuclear Leukocytes ◽  
Reproductive Tract ◽  
Inflammatory Diseases ◽  
Flow Cytometric ◽  
Holstein Friesian ◽  
Uterine Health ◽  
Intracellular Proteolysis ◽  
Friesian Cows

Postpartum dairy cows experience impaired peripheral polymorphonuclear leukocyte (PMN) functionality, which has been associated with reproductive tract inflammatory diseases. However, it has not been elucidated yet whether endometrial PMN functionality is (equally) impaired. We developed a method for endometrial PMN isolation and flow cytometric assessment of their viability and functionality. We also evaluated PMN immunolabeling, using a specific bovine granulocyte marker, CH138A. Blood and endometrial cytobrush samples were collected in duplicate from seventeen clinically healthy Holstein-Friesian cows between 9 and 37 days in milk. The proportion of viable, apoptotic, and necrotic PMN in endometrial samples roughly ranged from 10 to 80%, indicating highly dynamic endometrial PMN populations in the postpartum uteri. Endometrial PMN functionality testing revealed that PMN immunolabeling increased the accuracy, although this protocol might influence the median fluorescence intensity of the sample. Phagocytosis seemed the most stable and reliable endometrial PMN function and could be assessed satisfactorily without prior CH138A immunolabeling. However, the interpretation of oxidative burst and intracellular proteolysis tests remains challenging. The correlation between peripheral and endometrial PMN functionality was poor. Further research is warranted to unravel the role of uterine PMN viability and functionality in bovine uterine health.

The effect of space allowance and milk yield level on the performance and behaviour of dairy cattle housed in straw yards

1998 ◽  
Vol 1998 ◽  
pp. 108-108
Author(s):  
J. A. Fregonesi ◽  
J.D. Leaver
Keyword(s):  
Dairy Cattle ◽  
Milk Yield ◽  
Stocking Density ◽  
Important Variable ◽  
Early Lactation ◽  
Ways Of Coping ◽  
Yield Level ◽  
Face Width ◽  
Holstein Friesian ◽  
Friesian Cows

Space allowance could be an important variable affecting production, health, reproductive performance and behaviour of dairy cattle. Also, high and low yielding cows may have different ways of coping with insufficient space allowance. The aim of this experiment was to study the influence of space allowance and milk yield level on the performance and behaviour of strawyard housed dairy cows.The experiment was carried out using 24 Holstein Friesian cows with two groups in early lactation of high (over 30 kg/day milk yield) and two groups in late lactation of low yield (under 25 kg/day milk yield). The groups were allocated to strawyard systems with low stocking density (bed area/cow = 9 m2; pen area/cow = 13.5 m2; feed face width/cow = 1.5 m) or high stocking density (bed area/cow = 4.5 m2; pen area/cow = 6.75 m2; feed face width/cow = 0.75m) conforming to a changeover design with two periods, each of four weeks. The cows were fed a total mixed ration ad libitum and 2kg/cow/day of concentrate in the milking parlour. All animals were milked twice daily.

Acidogenicity of feeds for dairy cows. 2. Production responses

1998 ◽  
Vol 1998 ◽  
pp. 206-206
Author(s):  
R.J. Dewhurst ◽  
D. Wadhwa ◽  
L.P. Borgida ◽  
D.W.R. Davies ◽  
W.J. Fisher
Keyword(s):  
Dairy Cows ◽  
Milk Protein ◽  
Latin Squares ◽  
Standard Diet ◽  
Lactation Performance ◽  
Maize Silage ◽  
Beneficial Effects ◽  
Grass Silage ◽  
Holstein Friesian ◽  
Friesian Cows

Falling prices for cereals and beneficial effects on milk protein concentrations may promote greater inclusions of rapidly fermented ingredients in dairy rations. There is, however, a limit to the inclusion of these feeds into dairy rations beyond which performance declines due to sub-acidosis and related disorders. The feed compounder will need to be able to set limits on levels of feeding concentrates according to these risks. The objective of this experiment was to evaluate the effect of feeds of different acidogenicity (Wadhwa et al., 1998) on lactation performance of dairy cows offered diets based on grass- or maize-silage.Twelve multiparous Holstein-Friesian cows in the third month of lactation were used for this experiment. The experimental design involved adaptation and covariance recording on a standard diet (grass silage and 10 kg concentrates per day), followed by three 21-day experimental periods arranged as four 3x3 Latin Squares. The Latin Squares were constrained to a single forage to avoid difficulties in changeovers between grass silage and maize silage.

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