Progeny testing dairy bulls at different management levels

1960 ◽  
Vol 2 (2) ◽  
pp. 141-152 ◽  
Author(s):  
Alan Robertson ◽  
L. K. O'Connor ◽  
J. Edwards
Keyword(s):  
Milk Yield ◽  
Coefficient Of Variation ◽  
Progeny Testing ◽  
Gradual Change ◽  
Breeding Values ◽  
England And Wales ◽  
True Breeding ◽  
The Mean ◽  
Dairy Bulls ◽  
Different Levels

1. Records used to compile the Contemporary Comparisons of 57 Friesian, 8 English Ayrshire and 11 Scottish Ayrshire A.I. bulls, each with at least 100 ‘effective daughters’ were analysed.2. For each bull, the herd-years were divided into three equal groups on the basis of the average heifer yield of both daughters and contemporaries (high-, medium-, and low-producing herd-years) and three independent Contemporary Comparisons were calculated for each bull, one at each of the three yield levels.3. In the data from England and Wales, the mean Contemporary Comparison declined with increasing mean level of production. This decline was such as to imply that some 20% of the differences in production between herds were genetic in origin. A possible explanation lies in the gradual change from Dairy Shorthorn to Friesian and Ayrshire which has taken place in England and Wales, but not in Scotland, during the last 15 years.4. The variance within progeny groups within herd-years increased from the low level to the high but the coefficient of variation decreased slightly. The variance between sires also increased with the mean level of production but almost exactly in parallel with that within sires so that the heritability and consequently the accuracy of the progeny test for milk yield was effectively the same at all production levels.5. The correlation between the true breeding values of the bulls at the different levels was very close to one.6. From these results it is concluded that there is no need to provide special strains within breeds to suit particular management levels or to concentrate progeny testing in the higher-producing herds and that daughter records from all herds, irrespective of level of production, can be used with equal confidence.

The progeny testing of dairy bulls at different levels of production

1956 ◽  
Vol 47 (4) ◽  
pp. 367-375 ◽  
Author(s):  
I. L. Mason ◽  
Alan Robertson
Keyword(s):  
Artificial Insemination ◽  
Coefficient Of Variation ◽  
Genetic Variance ◽  
Comparison Method ◽  
Breeding Value ◽  
Progeny Testing ◽  
Average Yield ◽  
Average Production ◽  
Dairy Bulls ◽  
Different Levels

1. An analysis has been made of milk records from 13,000 cows bred by artificial insemination in Denmark.2. The herds were divided into three equal groups on the basis of their average production. The variance of yield within herds increased as the average yield increased, but the coefficient of variation declined slightly. The genetic variance was more than five times as large in the high-yielding herds than in the low, and correspondingly the heritabilities in low, medium and high herds were 0·05, 0·15 and 0·22 respectively. These were estimated from the variation observed between progeny groups of the same 152 bulls at each production level.3. No evidence was obtained of any sire-herd interaction for yield, either within or between management levels. The true ranking of bulls for breeding value was apparently the same at all levels.4. The heritability of fat content in the three groups was 0·27, 0·47 and 0·49 respectively, and no evidence of sire-herd interaction was found.5. The contemporary comparison method of assessing A.I. bulls for yield was found to have the accuracy expected in theory.6. These results are discussed in relation to those of other workers with which there are some discrepancies. On our results, a policy of choosing bulls on the basis of their daughters' performance in high-yielding herds should be the most satisfactory way of progeny-testing bulls used in artificial insemination.

Heritability of milk yield and composition at different levels and variability of production

1983 ◽  
Vol 36 (1) ◽  
pp. 59-68 ◽  
Author(s):  
W. G. Hill ◽  
M. R. Edwards ◽  
M.-K. A. Ahmed ◽  
R. Thompson
Keyword(s):  
Protein Content ◽  
Milk Yield ◽  
Coefficient Of Variation ◽  
Milk Fat ◽  
Protein Production ◽  
Genetic Correlations ◽  
Progeny Testing ◽  
Low Levels ◽  
High Level ◽  
Different Levels

ABSTRACTAnalyses of variance were conducted on first lactation milk, fat and protein production records in England and Wales of daughters of British Friesian sires. Herds were split on milk yield into high and low levels of mean production and, in subsequent analyses, into high and low levels of within herd variance and coefficient of variation using all first lactation records. Data were then extracted on daughters of 798 young sires undergoing progeny test and on 118 widely used proven sires to generate connections. Least squares analyses were conducted within levels and genetic correlations estimated from the covariance of sire effects. W ith data split on mean yield, the heritability of milk yield was 0·24 at the low level and 0·30 at the high level, that of log transformed yield being 0·25 and 0·35 respectively.With data split on variance the corresponding figures were 0·24, 0·30, 0·27 and 0·36 respectively, and when split on coefficient of variation, 0·22,0·26,0·26 and 0·32. There were similar increases for fat and protein yield, proportionately smaller increases for fat and protein content.Genetic correlations were close to 1·0 between high and low levels for all traits on all criteria of data splitting. As a consequence progeny testing of bulls is rather more accurate at high mean or variance of production levels and data can be combined optimally without scaling. Cows of the highest predicted value using an index will be found in high variance herds.

scholarly journals Test-day or 305-day milk yield for genetic evaluation of Gir cattle

2019 ◽  
Vol 54 ◽  
Author(s):  
Rodrigo Junqueira Pereira ◽  
Denise Rocha Ayres ◽  
Mário Luiz Santana Junior ◽  
Lenira El Faro ◽  
Aníbal Eugênio Vercesi Filho ◽  
...  
Keyword(s):  
Regression Model ◽  
Milk Yield ◽  
Genetic Evaluation ◽  
Random Regression ◽  
Breeding Values ◽  
Random Regression Model ◽  
The Mean ◽  
Yield Record ◽  
Genetic Evaluations ◽  
Dairy Breed

Abstract: The objective of this work was to compare genetic evaluations of milk yield in the Gir breed, in terms of breeding values and their accuracy, using a random regression model applied to test-day records or the traditional model (TM) applied to estimates of 305-day milk yield, as well as to predict genetic trends for parameters of interest. A total of 10,576 first lactations, corresponding to 81,135 test-day (TD) records, were used. Rank correlations between the breeding values (EBVs) predicted with the two models were 0.96. The percentage of animals selected in common was 67 or 82%, respectively, when 1 or 5% of bulls were chosen, according to EBVs from random regression model (RRM) or TM genetic evaluations. Average gains in accuracy of 2.7, 3.0, and 2.6% were observed for all animals, cows with yield record, and bulls (sires of cows with yield record), respectively, when the RRM was used. The mean annual genetic gain for 305-day milk yield was 56 kg after 1993. However, lower increases in the average EBVs were observed for the second regression coefficient, related to persistency. The RRM applied to TD records is efficient for the genetic evaluation of milk yield in the Gir dairy breed.

Progeny Testing of Dairy Bulls at Different Levels of Management

1954 ◽  
Vol 1954 ◽  
pp. 83-85 ◽  
Author(s):  
I. L. Mason
Keyword(s):  
Dairy Cattle ◽  
Experimental Evidence ◽  
Environmental Conditions ◽  
The Other ◽  
Progeny Testing ◽  
Laboratory Mice ◽  
Dairy Bulls ◽  
The Tropics ◽  
Different Levels ◽  
European Cattle

There are two schools of thought concerning the most appropriate environment in which to select breeding animals. One says ‘ Always select animals under environmental conditions similar to those where they are to be used ‘. The other says ‘ Select breeding animals in the optimum environment so that they have the best chance of revealing their genetic capabilities ‘. Experiments on growth of laboratory mice and experience with European cattle in the tropics have shown the advisability of the first course in these cases. In regard to hill sheep and dairy cattle in Britain, on the other hand, practice favours the second course, but there is little experimental evidence to support it.

scholarly journals The precision of temporal judgement: milliseconds, many minutes, and beyond

2009 ◽  
Vol 364 (1525) ◽  
pp. 1897-1905 ◽  
Author(s):  
P.A. Lewis ◽  
R.C. Miall
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Human Subjects ◽  
Short Interval ◽  
Time Measurement ◽  
Scalar Property ◽  
Timing Mechanisms ◽  
Timing Data ◽  
The Mean ◽  
Different Levels

The principle that the standard deviation of estimates scales with the mean estimate, commonly known as the scalar property, is one of the most broadly accepted fundamentals of interval timing. This property is measured using the coefficient of variation (CV) calculated as the ratio between the standard deviation and the mean. In 1997, John Gibbon suggested that different time measurement mechanisms may have different levels of absolute precision, and would therefore be associated with different CVs. Here, we test this proposal by examining the CVs produced by human subjects timing a broad range of intervals (68 ms to 16.7 min). Our data reveal no evidence for multiple mechanisms, but instead show a continuous logarithmic decrease in CV as timed intervals increase. This finding joins other recent reports in demonstrating a systematic violation of the scalar property in timing data. Interestingly, the estimated CV of circadian judgements fits onto the regression of decreasing CV, suggesting a link between short interval and circadian timing mechanisms.

The progeny testing of dairy bulls: a comparison of special station and field results

1956 ◽  
Vol 47 (4) ◽  
pp. 376-381 ◽  
Author(s):  
Alan Robertson ◽  
I. L. Mason
Keyword(s):  
Milk Yield ◽  
Field Test ◽  
Fat Content ◽  
Production Level ◽  
Progeny Testing ◽  
Fat Percentage ◽  
Progeny Tests ◽  
Dairy Bulls ◽  
Accuracy Of Prediction

1. A comparison has been made between progeny tests in special stations and those available from field records. The variation between sires in milk yield is much greater at the stations even when they are compared with herds at the same production level.2. In respect of yield the repeatability of station tests in the field is not good. The regression of field results on station test is only about 0·2 in herds at all production levels. For fat percentage, the regression is 0·5.3. The tests in special stations (averaging seventeen daughters per bull) were compared with those in high herds (average twenty-seven daughters) in their accuracy of prediction of the performance of bulls in the poorer herds. The field test was slightly (but not significantly) better for both milk yield and fat content.4. In milk yield, there is undoubtedly some extra variation between progeny groups at the stations which is not repeated in the field. Perhaps the tying of the heifers in distinct daughter groups in the byre may be a cause of this. However, even without this, it is doubted whether the test stations can give as much useful information on the numerical aspects of performance as the field records usually available. It is suggested that the splitting of daughter groups within the byre might increase the accuracy of the special station in the assessment of yield.

scholarly journals Single and multitrait estimates of breeding values for survival using sire and animal models

2002 ◽  
Vol 75 (1) ◽  
pp. 15-24 ◽  
Author(s):  
T. H. E. Meuwissen ◽  
R. F. Veerkamp ◽  
B. Engel ◽  
S. Brotherstone
Keyword(s):  
Linear Model ◽  
Milk Yield ◽  
Survival Data ◽  
Weibull Model ◽  
Breeding Value ◽  
Breeding Values ◽  
Time Period ◽  
True Breeding ◽  
Estimated Breeding Values ◽  
Genetic Regression

AbstractSurvival data were simulated under the Weibull model in a half-sib family design, and about 50% of the records were censored. The data were analysed using the proportional hazard model (PHM) and, after transformation to survival scores, using a linear and a binary (logit) model (LIN and BIN, respectively), where the survival scores are indicators of survival during time period t given survival up to period t – 1. Correlations between estimated and true breeding values of sires (accuracies of selection) were very similar for all three models (differences were smaller than 0·3%). Daughter effects were however less accurately predicted by the LIN model, i.e.taking proper account of the distribution of the survival data yields more accurate predictions of daughter effects. The estimated variance components and regressions of true on estimated breeding values were difficult to compare for the LIN models, because estimated breeding values were expressed as additive effects on survival scores while the simulated true breeding values were expressed on the underlying scale. Also the differences in accuracy of selection between sire and animal model breeding value estimates were small, probably due to the half-sib family design of the data. To estimate breeding values for functional survival, i.e. the component of survival that is genetically independent of production (here milk yield), two methods were compared: (i) breeding values were predicted by a single-trait linear model with a phenotypic regression on milk yield; and (ii) breeding values were predicted by a two-trait linear model for survival and milk yield, and breeding values for survival corrected for milk yield were obtained by a genetic regression on the milk yield breeding value estimates. Both methods yielded very similar accuracies of selection for functional survival, and are expected to be equivalent.

scholarly journals Dairy progeny testing in Finland

1973 ◽  
Vol 45 (5) ◽  
pp. 565-572
Author(s):  
Ulf Lindström ◽  
Kalle Maijala ◽  
Mikko Varo
Keyword(s):  
Milk Yield ◽  
Present Method ◽  
Progeny Testing ◽  
Correction Factors ◽  
Progeny Tests ◽  
Dairy Bulls ◽  
Ranking Order

An account is given of the present method of progeny testing of dairy bulls. Correction factors used are presented and an example of their application given. It is noted that progeny tests for milk yield based on less than 30 daughters have a low repeatability. There were no significant changes in the ranking order of AI bulls in different geographical areas. In the Ostrobothnia area, however, the progeny tests seemed to be slightly less accurate than in other regions.

OVARIAN ASCORBIC ACID DEPLETION TEST FOR LUTEINIZING HORMONE

1967 ◽  
Vol 56 (4) ◽  
pp. 619-625 ◽  
Author(s):  
Hans Jacob Koed ◽  
Christian Hamburger
Keyword(s):  
Ascorbic Acid ◽  
Luteinizing Hormone ◽  
Dose Response ◽  
Response Curve ◽  
Dose Response Curve ◽  
Human Origin ◽  
Response Curves ◽  
Significant Difference ◽  
The Mean ◽  
Different Levels

ABSTRACT Comparison of the dose-response curves for LH of ovine origin (NIH-LH-S8) and of human origin (IRP-HMG-2) using the OAAD test showed a small, though statistically significant difference, the dose-response curve for LH of human origin being a little flatter. Two standard curves for ovine LH obtained with 14 months' interval, were parallel but at different levels of ovarian ascorbic acid. When the mean ascorbic acid depletions were calculated as percentages of the control levels, the two curves for NIH-LH-S8 were identical. The use of standards of human origin in the OAAD test for LH activity of human preparations is recommended.

Design and development of manually operated gladiolus planter

2018 ◽  
Vol 5 (01) ◽  
Author(s):  
TAPAN K. KHURA ◽  
H. L. KUSHWAHA ◽  
SATISH D LANDE ◽  
PKSAHOO . ◽  
INDRA L . KUSHWAHA
Keyword(s):  
Coefficient Of Variation ◽  
Field Capacity ◽  
Power Source ◽  
Forward Speed ◽  
Cereal Crop ◽  
Maximum Coefficient ◽  
Coefficient Of Uniformity ◽  
The Mean ◽  
The Cost ◽  
Immense Potential

Floriculture is an age-old farming activity in India having immense potential for generating selfemployment and income to farmers. However, the cost of cultivation of flower is high as compared to cereal crop. Level of mechanization for different field operations is one but foremost reason for the higher cost of cultivation. As most of the Indian farmers are marginal and small, a need for manually operated gladiolus planter was felt. The geometric properties of gladiolus corm were determined for designing the seed metering system and seed hopper of the planter. The planter was evaluated in the field when pulled by two persons as a power source and guided by a person. The coefficient of variation and highest deviation from the mean spacing was observed as 12.93% and 2.65cm respectively. The maximum coefficient of uniformity of 90.59% was observed for a nominal corm spacing of 15cm at 0.56 kmh-1 forward speed. An average MISS percentage was observed as 2.65 and 2.25 for nominal corm spacing of 15 and 20 cm. The multiple index was zero for two levels corm spacing and forward speed of operation. The QFI was found in the range of 97.2 and 97.9 percent. The average field capacity of the planter was observed as 0.02 hah-1.The average draft requirement of the planter was found as 821 ± 50.3 N.

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