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N Gengler

Publications and source records attributed to N Gengler.

At least 19 recordsLinked to original sources
PubMed2026

Assessing the genetic potential of a milk mid-infrared prediction of heat stress response in dairy cows using a temperature-humidity index-independent approach.

Selection for heat tolerance remains challenging due to the difficulty of accessing reliable phenotypes at large scale. An alternative could be established using mid-infrared spectra, which are collected routinely through milk recording, and have already shown their value as proxies for a variety of phenotypes that are costly or difficult to measure. Recently, a first prediction of heat stress response in dairy cows based solely on milk mid-infrared spectra was developed. This prediction was obtained using models calibrated on surface body temperature and milk composition variations. Its potential as a detection tool was explored, but no genetic analyses has been performed. On this basis, the objectives of this study were to estimate the heritability of the predicted heat stress response, assess its genetic correlations with traits from the Walloon official genetic evaluation, and identify genomic regions associated with heat tolerance through a GWAS, all without using temperature-humidity index (THI) information. The estimated heritability (0.10) was low but sufficient to enable genetic selection and consistent with expectations for a heat stress-related trait. Also as expected, an antagonistic relationship between heat tolerance and milk production was observed, but its extent was notably reduced compared with traditional approaches. In addition, genetic correlations with other traits were neutral (fat yield) or favorable (protein yield, SCS, fertility, longevity). Concerning the GWAS, genomic regions and candidate genes previously associated with the response to heat stress were highlighted, as well as others related to energy balance maintenance. Overall, these results support the relevance of the prediction for the heat stress response as a new phenotype for heat tolerance selection that does not require any THI information. They also reinforce the importance of energy balance for dairy cows to cope with heat stress.

Journal Article↗
PubMed2007

Linear and curvilinear effects of inbreeding on production traits for walloon Holstein cows.

The nonlinear effects of inbreeding were studied by comparing linear and curvilinear regression models of phenotypic performances on inbreeding coefficients for production traits (milk, fat, and protein yields) of Holstein cows in their first lactation. Three different regression models (linear, quadratic, and cubic) were introduced separately into a single-trait, single-lactation, random regression test-day model. The significance of the different regression coefficients was studied based on a t-test after estimation of error variances and covariances associated with the different regression coefficients. All of the tested regression coefficients were significantly different from 0. The traditional regression coefficients of milk, fat, and protein yields on inbreeding were, respectively, -22.10, -1.10, and -0.72 kg for Holstein cows in their first lactation. However, the estimates of 305-d production losses for various classes of animals based on inbreeding coefficients showed that the effect of inbreeding was not a linear function of the percentage of inbreeding. The 305-d milk yield loss profiles attributable to inbreeding, obtained by the various regression models, were different. However, for inbreeding coefficients between 0 and 10%, these differences were small.

Animals↗
PubMed2006

Inbreeding depression for global and partial economic indexes, production, type, and functional traits.

The objective of this research was to examine the effects of inbreeding in the population of Holstein cattle in the Walloon region of Belgium. The effects of inbreeding on the global economic index and its components were studied by using data from the genetic evaluations of February 2004 for production, somatic cell score (SCS), computed from somatic cell counts and type. Inbreeding coefficients for 956,516 animals were computed using a method that allows assigning an inbreeding coefficient to individuals without known parents. These coefficients were equal to the mean inbreeding coefficient of contemporary individuals with known parents. The significance of inbreeding effects on the different evaluated traits and on the different indexes were tested using a t-test comparing estimated standard errors and effects. The inbreeding effect was significantly different from zero for the vast majority of evaluated traits and for all of the indexes. Inbreeding had the greatest deleterious effects on production traits. Inbreeding decreased yield of milk, fat, and protein during a lactation by 19.68, 0.96, and 0.69 kg, respectively, per each 1% increase in inbreeding. The regression coefficient of SCS per 1% increase in inbreeding was +0.005 SCS units. The inbreeding depression was thus relatively low for SCS, but inbred animals had higher SCS than non-inbred animals, indicating that inbred animals would be slightly more sensitive to mastitis than non-inbred animals. Estimates of inbreeding effects on evaluated type traits per 1% increase were small. The most strongly affected type traits were chest width, rear leg, and overall development on a standardized scale. For several type traits, particularly traits linked to the udder, the estimates suggested a favorable effect of inbreeding. The global economic index was depressed by around 6.13 euro of lifetime profit per 1% increase in inbreeding for the Holstein animals in the Walloon region of Belgium.

Animals↗
PubMed2006

Estimating fatty acid content in cow milk using mid-infrared spectrometry.

Interest in the fatty acid composition of dairy products is increasing; however, the measurement of fatty acids requires using gas-liquid chromatography. Although this method is suitable, it involves a time-consuming procedure, expensive reagents, and qualified staff. By comparison, the mid-infrared (MIR) spectrometry method could be a good alternative for assessing the fatty acid profile of dairy products. The objective of this study was to explore the calibration of MIR spectrometry for estimating fatty acid concentrations in milk and milk fat. Estimated concentrations in milk fat were less reliable than those for the same fatty acids in milk. Results also showed that when the fatty acid concentrations in milk increased, the efficiency of the infrared analysis method in predicting these values simultaneously increased. Selected prediction equations must have a high cross-validation coefficient of determination, a high ratio of standard error of cross-validation to standard deviation, and good repeatability of chromatographic data. Results from this study showed that the calibration equations predicting 12:0, 14:0, 16:0, 16:1cis-9, 18:1, and saturated and monounsaturated fatty acids in milk could be used. Thus, with its potential for use in regular milk recording, this infrared analysis method offers the possibility of assessing and improving the quality of milk produced. Indeed, it enables the fatty acid composition in milk to be estimated for each cow and the estimates to be used as indicator traits to determine the genetic values of underlying fatty acid concentrations. The knowledge of these genetic values would open up opportunities for animal selection aimed at improving the nutritional quality of cow milk.

Animals↗
PubMed2006

Variation in fatty acid contents of milk and milk fat within and across breeds.

The aim of this research was to study the potential for selection of cows with a higher nutritional quality of milk fat by studying the differences in fatty acid profiles within and across the following breeds: Dual Purpose Belgian Blue, Holstein-Friesian, Jersey, Montbeliarde, and non-Holstein Meuse-Rhine-Yssel type Red and White. Six hundred milk samples from 275 animals were taken from 7 herds. Several types of fatty acids in milk and milk fat were quantified using mid-infrared spectrometry and previously obtained calibration equations. Statistical analyses were made using a mixed linear model with a random animal effect. The variance components were estimated by using REML. Results showed breed differences for the fatty acid profile. The repeatability estimate obtained in the present study may suggest the existence of moderate additive genetic variance for the fatty acid profile within each breed. Results also indicated variation for each analyzed milk component in the whole cow population studied. Genetic improvement of the nutritional quality of milk fat based on fatty acid profiles might be possible, and further research and development are warranted.

Animals↗
PubMed2006

Genetic parameters and evaluation of rear legs (rear view) for Brown Swiss and Guernseys.

Genetic parameters were estimated for rear legs (rear view; RLRV) and 15 current linear type traits of Brown Swiss and Guernsey dairy cattle. The Brown Swiss Cattle Breeders' Association of the USA and the American Guernsey Association began scoring RLRV in 2004. For Brown Swiss, 8,502 records were available for 7,676 cows in 417 herds; Guernsey data included 5,437 records for 4,749 cows in 229 herds. Nine unknown-parent groups were defined for each breed, each with 2 birth years. The model included fixed effects for the interaction of herd, appraisal date, and parity; appraisal age within parity; and lactation stage within parity and random effects for animal, permanent environment, and residual error. The multitrait analysis for RLRV and the 15 linear type traits used canonical transformation, multiple diagonalization, and a decelerated expectation-maximization REML algorithm. For Brown Swiss, heritability was 0.102 for RLRV and ranged from 0.099 for rear legs (side view) to 0.453 for stature. For Guernseys, heritability ranged from 0.078 for RLRV to 0.428 for stature. For Brown Swiss, the highest genetic correlation with RLRV was 0.71 for rear udder width; the most negative correlation was -0.19 with rump angle. For Guernseys, the highest genetic correlations with RLRV were 0.43 for rear udder width and 0.42 for body depth; the most negative correlation was -0.46 with rear legs (side view). With heritability near 0.10, RLRV should be useful in selection for improved locomotion. Release of genetic evaluations for RLRV began in May 2006 for Brown Swiss and Guernseys.

Animals↗
PubMed2006

Accounting for heterogeneous variances in multitrait evaluation of Jersey type traits.

The multitrait genetic evaluation system for type traits was modified to estimate adjustments for heterogeneous variance (HV) simultaneously with estimated breeding values (EBV) for final score and 14 linear traits. Each variance within herd, year, and parity was regressed toward a predicted variance, which was determined by fitting a model with fixed effects of the mean final score for herd, size of the contemporary group, appraisal month, and year-season and a random effect for herd-appraisal date. Herd-appraisal date was included as a random effect to regress the observed heterogeneity for a given herd-appraisal date toward the fixed effects. Method R was used to estimate variances for the heterogeneity model in each EBV iteration. To evaluate the effect of the adjustment, parent averages were calculated from evaluations with recent appraisals removed. The adjustment slightly improved correlations within birth year between those parent averages and EBV from current data on bulls for most traits, but did not improve correlations for final score, strength, dairy form, teat length, or foot angle. Annual trends for EBV were lower with HV adjustment than for unadjusted EBV for all traits except final score and rump angle for cows and rump width for bulls, which were essentially unchanged. Standard deviations of Mendelian sampling (evaluation minus mean of parent evaluations) declined less over time for HV-adjusted than for unadjusted evaluations. The slope at year 2000 of Mendelian-sampling standard deviations from HV-adjusted evaluations ranged from 10.0% for udder depth to 42.7% for teat length compared with the slope for unadjusted evaluations. This HV adjustment, which was implemented for USDA evaluations in May 2001 for Jerseys and in 2002 for other breeds, improves the accuracy of evaluations, particularly comparisons over time, by accounting for the change in variation.

Animals↗
PubMed2005

Adjustment for heterogeneous covariance due to herd milk yield by transformation of test-day random regressions.

A method of accounting for differences in covariance components of test-day milk records was developed based on transformation of regressions for random effects. Preliminary analysis indicated that genetic and nongenetic covariance structures differed by herd milk yield. Differences were found for phenotypic covariances and also for genetic, permanent environmental, and herd-time covariances. Heritabilities for test-day milk yield tended to be lower at the end and especially at the start of lactation; they also were higher (maximum of approximately 25%) for high-yield herds and lower (maximum of 15%) for low-yield herds. Permanent environmental variances were on average 10% lower in high-yield herds. Relative herd-time variances were approximately 10% at start of lactation and then began to decrease regardless of herd yield; high-yield herds increased in midlactation followed by another decrease, and medium-yield herds increased at the end of lactation. Regressors for random regression effects were transformed to adjust for heterogeneity of test-day yield covariances. Some animal reranking occurred because of this transformation of genetic and permanent environmental effects. When genetic correlations between environments were allowed to differ from 1, some additional animal re-ranking occurred. Correlations of variances of genetic and permanent-environmental regression solutions within herd, test-day, and milking frequency class with class mean milk yields were reduced with adjustment for heterogeneous covariance. The method suggests a number of innovative solutions to issues related to heterogeneous covariance structures, such as adjusted estimates in multibreed evaluation.

Aging↗
PubMed2004

Type trait (co)variance components for five dairy breeds.

(Co)variance components were estimated for final score and 14 or 15 linear type traits for the Ayrshire, Brown Swiss, Guernsey, Jersey, and Milking Shorthorn breeds. Appraisals from 1995 or later were used. New estimates were calculated to accommodate changes in scoring of traits and because of a change from multiplicative to additive adjustment for age and lactation stage. The adjustment method was changed for better support of the adjustment for heterogeneous variance within iteration, which was implemented in 2002. The largest changes in heritability were an increase of 0.10 for rump angle for Milking Shorthorns and a decrease of 0.11 for udder depth for Jerseys. The new estimates of (co)variance components should provide improved accuracy of type evaluations, particularly for traits that have had variance changes over time.

Aging↗
PubMed2004

Estimated heterogeneity of phenotypic variance of test-day yield with a structural variance model.

First-lactation test-day milk, fat, and protein yields from New York, Wisconsin, and California herds from 1990 through 2000 were adjusted additively for age and lactation stage. A random regression model with third-order Legendre polynomials for permanent environmental and genetic effects was used. The model included a random effect with the same polynomial regressions for 2 yr of calvings within herd (herd-time effect) to provide herd-specific lactation curves that can change every 2 yr. (Co)variance components were estimated using expectation-maximization REML simultaneously with phenotypic variances that were modeled using a structural variance model. Maximum heritability for test-day milk yield was estimated to be approximately 20% around 200 to 250 d in milk; heritabilities were slightly lower for test-day fat and protein yields. Herd-time effects explained 12 to 20% of phenotypic variance and had the greatest impact at start of lactation. Variances of test-day yields increased with time, subclass size, and milking frequency. Test month had limited influence on variance. Variance increased for cows in herds with low and high milk yields and for early and late lactation stages. Repeatabilities of variances observed for a given class of herd, test-day, and milking frequency were 14 to 17% across nested variance subclasses based on lactation stage.

Age Factors↗
PubMed2004

Prediction of daily milk, fat, and protein production by a random regression test-day model.

Test-day genetic evaluation models have many advantages compared with those based on 305-d lactations; however, the possible use of test-day model (TDM) results for herd management purposes has not been emphasized. The aim of this paper was to study the ability of a TDM to predict production for the next test day and for the entire lactation. Predictions of future production and detection of outliers are important factors for herd management (e.g., detection of health and management problems and compliance with quota). Because it is not possible to predict the herd-test-day (HTD) effect per se, the fixed HTD effect was split into 3 new effects: a fixed herd-test month-period effect, a fixed herd-year effect, and a random HTD effect. These new effects allow the prediction of future production for improvement of herd management. Predicted test-day yields were compared with observed yields, and the mean prediction error computed across herds was found to be close to zero. Predictions of performance records at the herd level were even more precise. Discarding herds enrolled in milk recording for <1 yr and animals with very few tests in the evaluation file improved correlations between predicted and observed yields at the next test day (correlation of 0.864 for milk in first-lactation cows as compared with a correlation of 0.821 with no records eliminated). Correlations with the observed 305-d production ranged from 0.575 to 1 for predictions based on 0 to 10 test-day records, respectively. Similar results were found for second and third lactation records for milk and milk components. These findings demonstrate the predictive ability of a TDM.

Animals↗
PubMed2003

Within-herd effects of age at test day and lactation stage on test-day yields.

Variance ratios were estimated for random within-herd effects of age at test day and lactation stage, on test-day yield and somatic cell score to determine whether including these effects would improve the accuracy of estimation. Test-day data starting with 1990 calvings for the entire US Jersey population and Holsteins from California, Pennsylvania, Wisconsin, and Texas were analyzed. Test-day yields were adjusted for across-herd effects using solutions from a regional analysis. Estimates of the relative variance (fraction of total variance) due to within-herd age effects were small, indicating that regional adjustments for age were adequate. The relative variances for within-herd lactation stage were large enough to indicate that accuracy of genetic evaluations could be improved by including herd stage effects in the model for milk, fat, and protein, but not for somatic cell score. Because the within-herd lactation stage effect is assumed to be random, the effect is regressed toward the regional effects for small herds, but in large herds, lactation curves become herd specific. Model comparisons demonstrated the greater explanatory power of the model with a within-herd-stage effect as prediction error standard deviations were greater for the model without this effect. The benefit of the within-herd-stage effects was confirmed in a random regression model by comparing variance components from models with and without random within-herd regressions and through log-likelihood ratio tests.

Age Factors↗
PubMed2001

Estimation of genetic covariances with method R.

Method R is a simple and computationally inexpensive method for estimating (co)variances. The objective of the study was to investigate properties of Method R for estimation of (co)variance components with emphasis on covariance estimation. Theoretical Method R formulas were developed for simplified single-variate and bivariate models. In single-trait models, the curve of the regression of Method R was continuous and monotonic and its slope depended on the amount of information on each animal and on the variance ratio. The curve became steeper as the number of records per animal decreased. For covariance, the curve of the regression was monotonic but not continuous. However, a regression coefficient of 1 still corresponded to the correct covariance. Similar curves were observed in analyses of simulated data sets. Because of the observed discontinuity, algorithms implementing Method R that require a continuous regression curve would not work in models with covariances. An alternative algorithm was based on a transformation matrix obtained by multiplying a matrix of numerators with the inverse of a matrix of denominators of the regression factors. Such an algorithm converged reliably for all models tested. Method R can be modified to estimate covariances in models too large for other methods.

Algorithms↗
PubMed2000

Feed restriction in young bulls alters the onset of puberty in relationship with plasma insulin-like growth factor-I (IGF-I) and IGF-binding proteins.

The objectives of this study were to evaluate the effect of feed restriction and re-alimentation on the onset of puberty and IGF status in peripubertal male calves and to compare the radioimmunoassay (RIA) and western ligand blotting (WLB) methods for bovine IGFBP-2. Twelve prepubertal 290 d-old Belgian Blue bulls (mean weight: +/- 290 kg) were randomly assigned in three groups: a control group (NG; n = 4) receiving a classic fattening diet to induce "normal" growth (1.48 kg/d), a feed restricted group (RG; n = 4) to obtain reduced growth (0.50 kg/d) and, a severely restricted group (SG; n = 4) to nearly stop growth (0.08 kg/d). The feed restriction period was maintained over a period of 114 d. After the period of differential feeding, all animals received the control feed regime over a period of 100 d. Blood samples were collected at fortnightly intervals. Circulating IGF-I was measured by RIA whereas plasma IGFBPs was evaluated by WLB; IGFBP-2 was additionally quantified by RIA procedure. At the beginning of the trial, IGF-I levels were low (<100 ng/ml) and similar in the three groups in accordance with prepubertal status. In the NG group, a progressive rise in IGF-I was observed from Day 42 to Day 142 whereas in the RG and SG groups, IGF-I levels did not change until the experimental restriction period ended. The delay of the rise in plasma IGF-I was longer for the SG group, IGF-I remained low until 2 wk after the end of the period of restricted feeding. Surprisingly, although differences were detected for IGF-I levels between the three groups, the IGFBP-2 and -3 data, evaluated by WLB could only discriminate between NG and SG group and not between NG and RG. However, by using a RIA method, an IGFBP-2 decrease was observed in the NG group coincident with increasing IGF-I levels. For both RG and SG groups, IGFBP-2 levels remained high throughout the feed restriction period whereas plasma IGFBP-2 levels declined upon feeding in both groups. During this feed restriction period, IGFBP-2 was significantly lower in NG than in RG or SG groups. Moreover, SG group animals had higher levels in plasma IGFBP-2 than RG animals. In conclusion, puberty is characterized by developmental changes in plasma IGF-I and IGFBPs that were altered by feed restriction. Moreover, RIA evaluation of plasma IGFBP-2 is able to better reflect group differences than WLB.

Animals↗
PubMed1999

Candidate gene markers associated with somatotropic axis and milk selection.

One of the obstacles to progress in dairy cattle selection is that milk production traits are only expressed after the first calving. However, the use of the quantitative trait loci (QTL) technology will improve the efficiency of dairy industry with a positive image for the consumers. QTL are part of the genome showing a preponderant action and explaining the major part of variation of the trait production. At the present time, the two major strategies developed to detect such QTL are the candidate gene approach and the positional genetics approach. The somatotropic axis contains the most promising candidates in this respect, as it strongly regulates milk production. Then, the identification of favorable QTL associated with the somatotropic axis that are significantly correlated with genetic merits for milk production could lead to more effective selection programs.

Animals↗
PubMed1998

Estimation of the dominance variance for postweaning gain in the U.S. Limousin population.

The objective of this study was to estimate the dominance variance for postweaning gain in Limousin cattle. Data included 215,326 records of postweaning gain from 205 to 365 d, provided by the North American Limousin Foundation. Parental dominance subclasses were formed and related using the method of Hoeschele and VanRaden. Variance components were estimated using Method R based on six samples of 50%. Fixed effects in the model included contemporary group and covariates for inbreeding and breed composition (percentage Limousin). Heterozygosity was negatively correlated with breed composition (< -.99) and was therefore not included in the model. Two types of contemporary groups used as original groups from the National Cattle Evaluation were partially based on breed composition. Original contemporary groups that were too homogeneous for breed composition were replaced by herd-year-sex classes. Two models were used with the two data sets. Model 1 contained the fixed effects described above and an additive genetic effect. Model 2 included a dominance effect in addition to the effects contained in Model 1. In total, four combinations of contemporary group x model were used. Dominance variance was computed as being four times the estimated parental subclass variance. Estimates for inbreeding depression and breed composition (percentage Limousin) were all small and not greatly affected by inclusion of dominance effects or changes in contemporary groups. Estimates of the additive variance (expressed as percentage of the phenotypic variance) were only slightly affected, with values between 20 and 21%. Dominance estimates were highly affected when passing from original (10%) and to alternative contemporary groups (18%). Such large values may indicate that dominance is important for postweaning gain. Results showed the advantage of an individual dominance approach based on sire-dam combinations; therefore, expected gains through the use of specific combination ability as a part of the mating selection criteria for growth might be high.

Animals↗
PubMed1998

Estimation of dominance variance in purebred Yorkshire swine.

We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11.

Adipose Tissue↗