Biomedical subjects

I L Mao

Publications and source records attributed to I L Mao.

At least 19 recordsLinked to original sources

PubMed1995

Association of alleles for the class I bovine lymphocyte antigens with conformation, semen traits, and growth rate of young bulls.

The 279 Norwegian bulls that were performance tested during 1988 and 1989 were typed for bovine lymphocyte antigens of class I, and relationships with performance test results of these bulls were investigated. A single-trait animal model was used to estimate the gene substitution effects of bovine lymphocyte antigens on conformation as well as semen volume, density, and quality; a fixed linear model was also applied to the breeding values of growth rate. Allelic frequencies ranged from .2 to 28%; alleles w16 (28%), A2 (15%), A10(w50) (12%), and A8 (10%) were the most frequent. Allele A12(A30) was significantly associated with decreased semen density and decreased growth rate, and allele A10(w50) was significantly associated with increased growth rate. No antigen showed a significant association with conformation, semen density, or semen quality. Heterozygosity at the locus for bovine lymphocyte antigen of class I did not show significant advantage in any of the traits. The bovine lymphocyte antigens appeared to be potential markers for quantitative trait loci controlling semen density and growth rate; however, further research is necessary to confirm these findings.

Alleles↗

PubMed1995

Energy intake and gross efficiency comparisons from calorimetric and field data on the same lactating cows.

Field estimates on gross efficiency were obtained from intake and production data on 30 pluriparous Holsteins cows during wk 5, 7, 9, 11, 13, and 15 postpartum. Energy intake and efficiency from the energy chamber on the same cows were measured during wk 6, 10, and 14 postpartum. Measures of gross efficiency were expressed in terms of the utilization of metabolizable energy or net energy for lactation and maintenance. Within corresponding postpartum periods, chamber measures and field estimates were compared by canonical correlation analysis. All estimates from field data of energy and gross efficiencies closely approximated measures of the same traits from energy chamber data. Variation among cows in traits of energy partition and gross efficiency was similar for field estimates and energy chamber measures. Correlations were > .66 between field estimates and chamber measures on observations of maintenance energy and milk energy. Field estimates and chamber measurements of metabolizable energy and net energy had correlations of .76 and .70, respectively.

Animal Nutritional Physiological Phenomena↗

PubMed1994

Genetic correlations in the feed conversion complex of primiparous cows at a recommended and a reduced plane of nutrition.

An experiment at the Agricultural University of Norway provided data to estimate genetic parameters of roughage intake (RI), fat-corrected milk yield (FCM), smoothed BW (SW), weight change (WC), and energy balance (EB). Weekly measurements were averaged in four consecutive 6-wk periods after parturition for each of 331 primiparous Norwegian cows of 20 sires. Amount of concentrate fed was adjusted according to stage of lactation and cows were randomly assigned to a normal or a low level. Animals were given ad libitum access to grass silage. Multiple-trait animal models with all additive genetic relationships incorporated were applied to the subsets of all averages of one trait and all averages in one period. Each model contained for every trait 165 observations, 24 mo-year seasons of calving, and 313 additive genetic effects. (Co)variance components were estimated by an EM-REML algorithm. The heritability of RI increased with negative energy balance from .25 to .86, whereas the estimates were approximately .2 for FCM, .6 to .7 for SW, and .03 to .4 for WC and EB. The correlations between RI and FCM were .37 to .58 phenotypically and -.11 to .88 genetically; between RI and SW they were .57 to .73 phenotypically and .7 to 1 genetically; between FCM and SW they were -.06 to .35 phenotypically and -.33 to .70 genetically; and between WC and EB they were .52 to .92 phenotypically and -.09 to .88 genetically. Correlations between WC and EB and other traits were inconsistent over periods and had very high SE.

Animal Nutritional Physiological Phenomena↗

PubMed1993

Genetic parameters in the feed conversion complex of primiparous cows in the first two trimesters.

Feed conversion has been described as a "milk yield-tissue balance-appetite complex" in which energy inputs from feed intake and tissue balance impose a limit on milk yield. An experiment at the Agricultural University of Norway provided data to estimate genetic parameters of variables in this "complex." Fat-corrected milk yield, NE from roughage (NER) and BW were measured weekly on 353 first-lactation, dual-purpose Norwegian cows of 20 sires. Weekly weight change (WC) was computed from BW. Residual energy intake (RES) was calculated from energy balance (EB) corrected for WC. Amount of concentrate fed was adjusted according to stage of lactation and cows were randomly assigned to a normal or low level. Animals were given ad libitum access to grass silage. Data from the first and second trimesters of lactation were analyzed separately using an animal model containing fixed effects of 145 seasons in weeks, 24 subclasses of stages of lactation by levels of concentrate, and linear regression on age at calving and random effects of 512 animals and permanent environmental effects for the 353 animals with records. Cows fed at the low level of concentrate consumed more roughage and lost more weight but produced less milk. Catabolism of adipose tissue was poorly reflected by weight change. Heritability estimates for NER were .32 in the first trimester and .20 in the second; repeatability was .60. For EB, the respective estimates of heritability were .14 and .06, whereas repeatability was .55. No additive genetic variation was found for RES.

Adipose Tissue↗

PubMed1993

Sources of variation in partitioning of intake energy for lactating Holstein cows.

Variation in energy partitioning was quantified. Data were from 34 multiparous Holstein cows using indirect respiration calorimetry during the 6th, 10th, and 14th wk postpartum. For each period, cows were placed in digestion stalls for a 6-d excreta collection, followed by two consecutive 11-h determinations of methane and heat production. Sources of variation among cows were analyzed for gross energy consumed; for fecal, urinary, CH4, heat, milk, and maintenance energies; for tissue energy balance; and for tissue partitioning. Ratios of heat production, energy balance, milk energy, and maintenance energy to intake energy were also analyzed for sources of variation. A within-period model was used that contained fixed effects of treatment, parity, season, and covariates for metabolic BW and SCM. None of the diet or parity effects were a significant source of variation in any of the variables. Season effects were only significant for milk energy and water intake. As a covariate, SCM was highly significant for all variables except energy for heat production and energy for maintenance. However, metabolic BW as a covariate was a significant effect for heat production at wk 10 and 14 postpartum. The significance of metabolic BW differed between periods for most energy partition and efficiency measures. The most significant proportion of the variation in energy utilization was attributable to the energy in the milk.

Animals↗

PubMed1992

Phenotypic and genetic relationships between residual energy intake and growth, feed intake, and carcass traits of young bulls.

Residual energy intake, defined as actual minus predicted energy intake during a production period, was estimated for each of 650 bull calves of 31 Holstein Friesian or Brown Swiss sires. Residual energy intake, measured under ad libitum feeding, had heritabilities similar to those of growth rate and energy conversion ratio with an estimate of approximately .3. Residual energy intake was related to average daily energy intake both phenotypically and genetically such that selection for decreased residual energy intake would lead to a decrease in daily feed intake. Such selection would also tend to increase carcass fatness (i.e., genetically fat animals are the most efficient). Residual energy intake estimated with and without correction for carcass composition were closely correlated. Thus, residual energy intake may be estimated without the knowledge of carcass composition in growing bulls of dual-purpose breeds.

Adipose Tissue↗

PubMed1992

Estimation of residual energy intake for lactating cows using an animal model.

Residual energy intake is defined as the remaining energy from total net energy intake after accounting for all energy uses. Residual energy intake is proposed as a measure of feed efficiency because animal efficiency increases as the proportion of accountable energy intake increases or the residual energy intake decreases. Residual energy intake was estimated for each of 247 Holstein cows, daughters of 127 sires and 226 dams distributed in five herds across the US. Data consisted of daily milk production and net energy intake, biweekly measures of milk components, and BW measures taken at varied intervals throughout a lactation. Average daily net energy intake in a lactation was the dependent variable in a model that contained fixed effects of parity and herd-season subclass; covariates of lactation average daily SCM, metabolic BW, and weight change in a lactation; and random animal effect. From this model, residual energy intake was a sum of animal and residual effects. Partial energy requirements for SCM, maintenance, and weight change estimated for all cows were .54, .15, and 1.52 Mcal/kg, respectively. Heritability estimate for residual energy intake was .016; phenotypic standard deviation was 2.455. The proportion of the phenotypic standard deviation in net energy intake that was due to residual energy was 68%.

Animal Feed↗

PubMed1991

Genetic parameters of growth, feed intake, feed conversion and carcass composition of dual-purpose bulls in performance testing.

Genetic parameters for growth, total energy intake, feed conversion ratio, average daily energy intake and carcass composition were estimated in an experiment with 650 bull calves from 31 half-sib groups of Holstein Friesian or Brown Swiss sires. All traits analyzed had an amount of additive genetic variance that allows for considerable response to selection. No interaction between genotype (sire group) and proportion of roughage in the diet was found. Daily gain was strongly correlated negatively with feed conversion ratio but positively correlated with daily energy intake. Results indicate that genetic selection for either daily gain or average daily energy intake would decrease carcass fatness at a constant slaughter weight. However, the environmental correlation between daily energy intake and carcass fatness was positive.

Animals↗

PubMed1991

Selection of bulls for progeny testing using pedigree indices and characteristics of potential bull-dams' herds.

A total of 209 bulls selected from herds in the northeastern US by Eastern AI Coop., Inc. from 1978 to 1981 were identified. The DHI data were obtained for the 145 herds from which these bulls were sampled. Also acquired were evaluations from both Modified Contemporary Comparison and animal model on these bulls and their ancestors and on cows and their sires in the bull-dam herds. From evaluation by animal model, animals appeared to have contributed information to each other effectively through relationship matrix, and thus the accuracy of cow evaluation has been improved. Bulls selected from herds of high genetic level were genetically superior to those from herds of low genetic level. However, there was no evidence that bulls from low intraherd milk variation herds were superior to those from high variation herds in the northeastern population, as was the case in Michigan herds. Parent indices were greater than bull PTA in herds of lower genetic level but less than bull PTA in herds of higher genetic level. The correlation between herd yield average and herd genetic level and that between herd yield average and intraherd yield SD were moderate but significantly different from zero. Other correlations between phenotypic and genetic measures of bull-dam herds were negligible. None of the herd characteristics showed promise in characterizing herds that were more successful in having their sampled bulls returned by AI organization after progency test.

Animals↗

PubMed1991

Estimation of genetic parameters using sampled data from populations undergoing selection.

In populations undergoing selection, genetic (co)variances may be altered in amounts dependent on selection intensity among parents and the mating structure. In order to estimate the genetic parameters of the unselected population, all information that led to the current population must be included in the analysis. This is often not possible due to missing information or computer limitations, and, therefore, only samples of data and pedigree information of recent generations are included in analysis, and simplified operational models are used. Biases in genetic parameters, which were estimated by multitrait derivative-free REML method, were investigated in different strategies of sampling data and pedigree. In dual purpose cattle, in which young bulls are selected for growth before being progeny tested for milk yield, heritabilities and additive genetic correlations were all unbiased when all data and all relationships were used in an animal model. Using only recent data but all relationships in an animal model also gave unbiased estimates of heritabilities. Using an animal model for growth but a sire model for milk with all data gave an unbiased estimate of heritability for milk. When only recent data were used, the heritability estimate for milk was biased downward. In single purpose dairy populations, sire models gave biased estimates of genetic parameters even when all data were included in the analysis. Treating sire effects on second crop of daughters as fixed did not overcome selection bias.

Algorithms↗

PubMed1990

Prediction of total intake of dry matter and net energy in a lactation.

Daily records on DM intake, net energy intake, and milk yield from 191 Holstein cows in six herds were used to study the differences in accuracy and precision among different methods of estimating total DM intake during a lactation. In using cumulative measures of intake from partial lactations to predict total intake, accuracy reached 85% at 100 d postpartum. Measurements of intake taken around midlactation gave better predictions of total intake than those taken during other periods of lactation. Methods were evaluated for estimating total feed intake during a lactation based on data collected intermittently and separated by either equal or unequal intervals throughout the lactation. The average percentage of bias across all sampling schemes was 6% or less of actual intake. Six of the seven sampling schemes using only 10 d of intake information throughout the lactation had correlations with actual intake of .97 or higher. For equally spaced methods, both accuracy and precision of estimation increased with increased frequency of sampling. For unequally spaced methods, accuracy increased with sampling frequency after 150 d in milk. Total milk production was used to predict feed intake during a lactation. Milk yield alone accounted for 37 and 33% of the variation of total intake using actual and estimated yields, respectively.

Animals↗

PubMed1990

Relationship between dam's age at bull's birth and bull's genetic evaluation.

After accounting for year of birth of bulls, younger dams produced superior sons. Bulls' PD, parent average, and pedigree index milk decreased with increasing age of dams at bull's birth. This appears to be due to decrease in maternal grandsire's PD milk and dam's Cow Index milk with increase in age of dam. Younger dams have an advantage of potentially higher genetic merit due to genetic trend but have less information included in their evaluations. Bull's latest parent average and pedigree index overestimated latest PD milk. This overestimation was not different with age of dam at bull's birth, suggesting that the bias in predicting bulls' PD from eventual evaluations of dams chosen at a younger age is not different than for dams chosen at a later age. Data were for 2826 bulls sampled by four AI organizations and born between 1965 and 1981. The increase in PD milk of bulls was about 27 kg/yr, but the trend was larger (45 kg/yr) during the last 5 yr. Inclusion of dam's age did not improve prediction of bull's PD milk. Maternal grandsire's PD milk was the primary variable associated with dam's age that accounted for lower bull's PD milk, mainly because older dams tended to have sires of lower genetic merit.

Age Factors↗

PubMed1990

Stochastic modeling of multiple ovulation and embryo transfer breeding schemes in small closed dairy cattle populations.

Genetic changes and genetic drift in three small closed dairy cattle populations were examined with a stochastic simulation model. Multiple ovulation and embryo transfer and AI techniques were simulated in three populations, two with 88 breeding females each and one with 352 breeding females. The selection goal was to maximize genetic improvement in milk yield. The reduction in genetic variation due to inbreeding and linkage disequilibrium was accounted for in the simulation. Strict restriction against inbred mating slowed genetic progress significantly in the small population but would not be consequential in the larger population. However, allowing inbred mating in the smaller population caused a rapid accumulation of inbreeding. Linkage disequilibrium was as important as inbreeding in reducing genetic variation. Genetic drift variance was much smaller in the larger population.

Animals↗

PubMed1989

Genetic parameters of estimated net energy efficiencies for milk production, maintenance, and body weight change in dairy cows.

Net efficiencies of converting intake energy into energy for maintenance, milk production, and body weight change in a lactation were estimated for each of 79 Holstein cows by a two-stage multiple regression model. Cows were from 16 paternal half-sib families, which each had members in at least two of the six herds. Each cow was recorded for milk yield, net energy intake, and three efficiency traits. These were analyzed in a multitrait model containing the same 14 fixed subclasses of herd by season by parity and a random factor of sires for each of the five traits. Restricted maximum likelihood estimates of sire and residual (co)variance components were obtained by an expectation maximization algorithm with canonical transformations. Between milk yield and net energy intake, net energy efficiencies for milk yield, maintenance, and body weight change, the estimated phenotypic correlations were .36, -.02, .08, and -.06, while the genetic correlations were .92, .56, .02, and -.32, respectively. Both genetic and phenotypic correlations were zero between net energy efficiency of maintenance and that of milk yield and .17 between net energy efficiency of body weight change and that of milk yield. The estimated genetic correlation between net efficiency for lactation and milk yield is approximately 60% of that between gross efficiency and milk yield. With a heritability of .32 equivalent.49, net energy efficiency for milk yield may be worth consideration for genetic selection in certain dairy cattle populations.

Animals↗

PubMed1989

Modeling net energy efficiencies as quantitative characteristics in lactating cows.

To date, researchers have measured net efficiencies of energy conversion using data from animals in energy chambers. The expense of this approach prevents the establishment of a large data base for quantitative studies. Our purpose was to investigate models that would enable us to use data collectable in normal field conditions to compare dairy cattle for their net energetic efficiency. Data from 357 Holstein cows in seven herds and in various parities consisted of daily measures of DM intake, net energy intake, milk production, biweekly measures of milk components, and bimonthly BW. Eighteen alternative multiple regression models were fitted to each of the cows to estimate simultaneously net efficiency of energy conversion for maintenance, lactation, pregnancy, and BW change during positive energy balance period, negative energy balance period, and whole lactation. Results from several fitted models approximated closely literature results based on data from cows in energy chambers. These comparative results suggest that it is possible to estimate efficiency of energy conversion on individual cows using data obtained from normal animal management situations.

Algorithms↗

PubMed1989

Relationships between characteristics of herd of bull-dams and predicting transmitting ability of young bull.

Young bulls selected from Michigan herds for sampling by Select Sires Incorporated from 1975 to 1982 were identified. Data for herds from which young bulls were selected for year of young bull's birth were acquired from the Michigan DHIA. Herd average milk production, intraherd standard deviation for milk production, coefficient of variation for milk production, average sire transmitting ability of cows in the herd, and intraherd standard deviation of sire transmitting ability were computed for each herd. These herd characteristics were used in prediction of young bull transmitting ability. When considered along with a pedigree index predictor, intraherd standard deviation for milk production was significant in prediction of young bull transmitting ability, but other herd characteristics were not. Young bulls were grouped by the intraherd milk variance of the herd from which they were selected. Evaluations based on progeny tests showed young bulls selected from herds with low intraherd milk variance were genetically superior to those selected from herds with high intraherd milk variance. Predicted transmitting abilities for young bulls selected from low variance herds were less biased, but predicted transmitting abilities for those selected from high variance herds were inflated. However, the variance of biasedness was slightly lower in higher variance herds.

Animals↗

PubMed1987

Effects of parity, age, and stage of lactation at classification on linear type scores of Holstein cattle.

Linear type scores of 60,121 Michigan and Wisconsin cows classified from January through November 1983 were obtained from the Holstein-Friesian Association of America. Joint effects of parity, age, and stage of lactation at classification on linear scores of Holstein body conformation characteristics were examined. The mixed model used had a random factor of sire within herd and had fixed factors of herd and the three-way subclass of parity, age, and stage of lactation. Herd effect included differences due to herd environment, classifier, and season. Sires within herds and herds were absorbed while constructing equations for the three-way subclass factors. Parity, age, and stage of lactation affected linear type scores after adjustment for herd and sire differences. There was little evidence of a parity by stage interaction or a parity by age interaction. Adjustment factors for the three-way subclass effects were derived. When compared with adjustment factors derived in this study, current adjustment factors overadjust for age and parity effects and underadjust for stage of lactation effects.

Aging↗

PubMed1985

Selecting for lactation curve and milk yield in dairy cattle.

Knowledge of genetic relationships between characteristics of lactation curves and lactation yields is essential for joint selection for both. An equation, yt = atbexp(-ct), was chosen to depict individual lactation curves for 5,927 first lactations by Holsteins in 557 herds in Michigan Dairy Herd Improvement where yt is daily milk yield at day t in lactation, a is yield at time zero, b is ascent to peak, and c is decline after peak. Genetic correlations for 305-day milk yield with initial production (a), ascent to peak (b), descent after peak (c), and peak yield were -.37, .40, 0, and .91. From empirical results from applied selection indexes, selecting for both increase of ascent to peak and peak yield did not decrease 305-day milk substantially. Rankings of sires on these indexes were similar to their rankings on milk yield alone. Attempts to decrease peak yield and increase persistency decreased milk yield greatly.

Age Factors↗