1,721,163 research outputs found
Changes in milk lactose content as indicators for longevity and udder health in Holstein cows
Full text linkChanges in milk production traits over time might be informative of the health status of cows and may contain useful information for selective breeding purposes. In particular, early indicators are useful for traits such as longevity, which become available late in the cow's life. Lactose percentage (LP) tends to decrease in the presence of udder infection and with parity. Therefore, it can be hypothesized that cows exhibiting limited changes in LP across lactations have experienced fewer udder infections in their productive life and have a higher chance to stay longer in the herd than cows with more pronounced reduction of LP across lactations. In this study, 9 descriptors of change in LP during a cow's lifetime were defined and evaluated as potential indicators for selective breeding. For the purpose of this study, test-day records of the first 44 days in milk (DIM) of each lactation were discarded, and cows were required to have at least 5 test-days/cow per lactation (≥45 DIM) over the first 3 lactations. In this study, descriptors of LP were available for 69,586 Italian Holstein cows. Changes in LP in each lactation were quantified by regressing LP on DIM; thus, β1, β2, and β3 represented the changes in LP within lactations 1, 2, and 3, respectively. Changes in LP across multiple lactations were also quantified by regressing LP on DIM (with exclusion of the first 44 DIM of each lactation); briefly, β12 was the change of LP over lactation 1 and 2, β23 was the change of LP over lactation 2 and 3, and β123 was the change of LP over lactation 1, 2, and 3. Alternatively, changes in the LP lactation means (Δ) were quantified between lactations 1 and 2 (Δ12), 2 and 3 (Δ23), and 1 and 3 (Δ13). For comparison, β and Δ were also derived for milk yield (kg/d), somatic cell score, and log-transformed total somatic cells excreted daily in milk (units). Variance components and estimated breeding values (EBV) for all β's and Δ's were estimated. In addition, EBV for bulls with at least 25 daughters were used to assess Calo's genetic correlations between descriptors of change in LP with official published EBV for functional traits. Heritabilities for β and Δ of LP ranged from 0.06 (Δ23) to 0.20 (Δ13), and differed significantly from 0. Furthermore, LP EBV for β and Δ were correlated with official EBV for functional longevity index, udder health index, udder score (mammary gland morphology) index, and milk persistency; Calo's genetic correlations of LP β123 with functional longevity and udder health index were 0.52 and 0.33, respectively. Cows with a stronger reduction of LP across lactations (i.e., stronger and negative β, and greater and positive Δ) were characterized by lower milk persistency, impaired longevity, and worse udder health and morphology than cows with smaller reduction in LP across lactations. Results highlighted that changes in milk LP have the potential to be exploited as indicators for functional traits in Italian Holstein cattle. Further research on the biological relationship between changes in LP and mastitis is recommended
Genetic parameters of bovine milk fatty acid profile, yield, composition, total and differential somatic cell count
Full text linkThe growing interest of consumers for milk and dairy products of high nutritional value has pushed researchers to evaluate the feasibility of including fatty acids (FA) in selection programs to modify milk fat profile and improve its nutritional quality. Therefore, the aim of this study was to estimate genetic parameters of FA profile predicted by mid-infrared spectroscopy, milk yield, composition, and total and differential somatic cell count. Edited data included 35,331 test-day records of 25,407 Italian Holstein cows from 652 herds. Variance components and heritability were estimated using single-trait repeatability animal models, whereas bivariate repeatability animal models were used to estimate genetic and phenotypic correlations between traits, including the fixed effects of stage of lactation, parity, and herd-test-date, and the random effects of additive genetic animal, cow permanent environment and the residual. Heritabilities and genetic correlations obtained in the present study reflected both the origins of FA (extracted from the blood or synthesized de novo by the mammary gland) and their grouping according to saturation or chain length. In addition, correlations among FA groups were in line with correlation among individual FA. Moderate negative genetic correlations between FA and milk yield and moderate to strong positive correlations with fat, protein, and casein percentages suggest that actual selection programs are currently affecting all FA groups, not only the desired ones (e.g., polyunsaturated FA). The absence of association with differential somatic cell count and the weak association with somatic cell score indicate that selection on FA profile would not affect selection on resistance to mastitis and vice versa. In conclusion, our findings suggest that genetic selection on FA content is feasible, as FA are variable and moderately heritable. Nevertheless, in the light of correlations with other milk traits estimated in this study, a clear breeding goal should first be established
Short communication: Genetic aspects of milk differential somatic cell count in Holstein cows: A preliminary analysis
No full textThe aim of the present study was to assess genetic variation and heritability of a novel indicator of udder health, milk differential somatic cell count (DSCC), which represents the percentage of neutrophils plus lymphocytes in the total somatic cell count (SCC). Furthermore, we estimated genetic and phenotypic correlations of DSCC with other milk traits routinely measured in Italian Holstein cows. Besides DSCC, test-day data included milk yield, composition traits (i.e., fat, protein, casein, and lactose percentages), pH, milk urea nitrogen, and SCC. After editing, the final data set included 10,709 test-day records of 5,142 cows in 299 herds. Mean of DSCC was 62.07%, which means that macrophages were approximately 38% of total SCC. Comparing our results with the literature offered compelling evidence of the importance of acquiring information about the proportion of the different cell types in milk to better define the udder health status. In addition, our analysis revealed, for the first time, that DSCC is a heritable trait, and heritability (0.08 ± 0.02) was higher than that of traditional somatic cell score (0.04 ± 0.02). Nevertheless, heritability of DSCC is still low compared with milk yield and quality traits. Single-trait analysis within parity showed that DSCC was less heritable in primiparous than in multiparous cows, whereas bivariate analysis confirmed that DSCC and somatic cell score were 2 different traits, as their genetic and phenotypic correlations differed from unity. From a genetic point of view, the DSCC was positively weakly associated with milk yield, lactose percentage, and milk urea nitrogen, and negatively associated with pH. Our findings contributed to the understanding of the genetic background of DSCC and are a precursor to the potential use of DSCC in breeding programs to enhance cow resistance to mastitis. However, further research is needed to determine the weight this novel trait should receive in a selection program aimed to reduce udder health problems
Factors affecting differential somatic cell count, an additional parameter for mastitis screening in dairy cows
No full text
CO2 laser welding of aluminium matrix composites
No full textThe development of suitable welding techniques is a key-point for the use of Metal Matrix Composites in engineering applications. High energy welding techniques. such as laser beam, may have both positive and negative effects (high cooling rates, so minimum time is available for matrix-reinforcement reactions, but also high temperature, with strong beam-reinforcement interactions). This work is focussed on the set up of CO, laser welding processes for discontinuously reinforced Aluminium Matrix Composites. Both unalloyed Al and an At-Si casting alloy (A354) have been used as matrices, reinforced by particulate Silicon Carbide (5 and 15%vol). The composites have been submitted to penetration tests (traverse speed = 3.7 m/min, laser beam power = 4 kW). Two kinds of filler wires (ER4043 and ER4047) have been also employed. Microstructural characterisations have been carried out on the beads, leading, together with an analytical thermal model of the process, to the definition of guidelines for obtaining good welded joints on such composites
Alternative somatic cell count traits exploitable in genetic selection for mastitis resistance in Italian Holstein and Jersey cows
No full textBreeding for mastitis resistance represents an important strategy to decrease the incidence of the disease in the farm. However, as routine disease-recording systems are currently not widely implemented, genetic selection for mastitis resistance is mostly based on test-day (TD) or lactation-mean somatic cell count (SCC) (Martin et al., 2018). Nevertheless, alternative traits derived from SCC and genetically correlated with clinical mastitis have been suggested to better describe SCC variation throughout the lactation and the dynamic of infection (de Haas et al., 2008;
Urioste et al., 2010; Koeck et al., 2012). Therefore, the aim of this study was to characterize alternative SCC traits, derived from TD data from routine recording system, and to estimate phenotypic and genetic correlations with milk production traits in Italian Holstein Friesian (HF) and Jersey (JE) cows. Test-day records of 66,407 primiparous HF cows from 404 herds sampled between 1999 and 2014 and TD records of 12,754 primiparous JE cows from 428 herds sampled between 2004 and 2016 were extracted from the databases of the Italian Holstein Association (Cremona, Italy). Along with the traditional lactation-mean somatic cell score (SCS), analyzed traits included average SCS in early lactation (SCS_150), standard deviation of SCS of the whole lactation (SCS_SD), presence or absence of at least one TD SCC above 400,000 cells/mL (Infection) and the ratio of number of TD with SCC above 400,000 cells/mL to total number of TD (Severity). A subset of 22,695 HF and a subset of 8,133 JE cows were randomly extracted from the edited original databases and used for genetic analysis. Multivariate animal models were run to estimate heritability of and genetic correlations between alternative SCC traits, and genetic correlations between alternative SCC traits and milk production traits. Herd-year-season of calving and number of TD were included as fixed effects, and additive genetic animal (n = 62,146 for HF and n = 18,314 for JE cows) as random terms. Holsteins had lower SCS than JE cows, both when averaged over the entire lactation or over the first 150 days in milk: 2.86 vs 3.09 for SCS and 2.66 vs 3.01 for SCS_150, respectively. However, compared to JE, HF showed greater SCS_SD (1.29 vs 1.10), higher Infection (47.4% vs 42.9%) and greater Severity (14% vs 11%). Heritability of novel SCC traits was smaller in comparison to traditional lactation-mean SCS (0.13 for HF and 0.14 for JE), ranging from 0.04 (SCS_SD) to 0.11 (SCS_150) in both breeds. With the only exception of SCS_SD, genetic correlations between SCC traits were strong and comprised between 0.79 and 0.99. Regardless the breed, negative phenotypic correlations were estimated between milk yield and SCC traits, whereas positive genetic relationships were observed, especially with those traits related to variation of SCC (SCS_SD, Infection and Severity). Phenotypic and genetic correlations between SCC traits and milk composition (fat and protein percentage) were mostly close to zero. In conclusion, alternative SCC traits analyzed in the present study showed enough genetic variation to be exploited in breeding programs for mastitis resistance. Moreover, our findings confirmed that high milk SCC is associated with reduced milk production (negative phenotypic correlation) and support the hypothesis that high producing cows could be more susceptible to mastitis (positive genetic correlation). The unfavorable genetic correlation between SCC traits and production highlights the need of improving selection for mastitis resistance. A comparison of alternative SCC traits with clinical mastitis information would be required. de Haas, Y., W. Ouweltjes, J. ten Napel, J. J. Windig, and G. de Jong. 2008. Alternative somatic cell count traits as mastitis indicators for genetic selection. J. Dairy Sci. 91:2501–2511. Koeck, A., F. Miglior, D. F. Kelton, and F. S. Schenkel. 2012. Alternative somatic cell count traits to improve
mastitis resistance in Canadian Holsteins. J. Dairy Sci. 95:432–439. Martin, P., H. W. Barkema, L. F. Brito, S. G. Narayana, and F. Miglior. 2018. Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle. J. Dairy Sci. 101:2724-2736. Urioste, J. I., J. Franzén, and E. Strandberg. 2010. Phenotypic and genetic characterization of novel somatic cell count traits from weekly or monthly observations. J. Dairy Sci. 93:5930–5941
Comparison of machine learning methods to predict udder health status based on somatic cell counts in dairy cows
Full text linkBovine mastitis is one of the most important economic and health issues in dairy farms. Data collection during routine recording procedures and access to large datasets have shed the light on the possibility to use trained machine learning algorithms to predict the udder health status of cows. In this study, we compared eight different machine learning methods (Linear Discriminant Analysis, Generalized Linear Model with logit link function, Naïve Bayes, Classification and Regression Trees, k-Nearest Neighbors, Support Vector Machines, Random Forest and Neural Network) to predict udder health status of cows based on somatic cell counts. Prediction accuracies of all methods were above 75%. According to different metrics, Neural Network, Random Forest and linear methods had the best performance in predicting udder health classes at a given test-day (healthy or mastitic according to somatic cell count below or above a predefined threshold of 200,000 cells/mL) based on the cow’s milk traits recorded at previous test-day. Our findings suggest machine learning algorithms as a promising tool to improve decision making for farmers. Machine learning analysis would improve the surveillance methods and help farmers to identify in advance those cows that would possibly have high somatic cell count in the subsequent test-day
Genetic parameters for body condition score, locomotion, angularity, and production traits in Italian Holstein cattle
No full textThe objectives of this research were to estimate genetic parameters for body condition score (BCS) and locomotion (LOC), and to assess their relationships with angularity (ANG), milk yield, fat and protein content, and fat to protein content ratio (F:P) in the Italian Holstein Friesian breed. The Italian Holstein Friesian Cattle Breeders Association collects type trait data once on all registered first lactation cows. Body condition score and LOC were introduced in the conformation scoring system in 2007 and 2009, respectively. Variance (and covariance) components among traits were estimated with a Bayesian approach via a Gibbs sampling algorithm and an animal model. Heritability estimates were 0.114 and 0.049 for BCS and LOC, respectively. The genetic correlation between BCS and LOC was weak (-0.084) and not different from zero; therefore, the traits seem to be genetically independent, but further investigation on possible departures from linearity of this relationship is needed. Angularity was strongly negatively correlated with BCS (-0.612), and strongly positively correlated with LOC (0.650). The genetic relationship of milk yield with BCS was moderately negative (-0.386), and was moderately positive (0.238) with LOC. These results indicate that high-producing cows tend to be thinner and tend to have better locomotion than low-producing cows. The genetic correlation of BCS with fat content (0.094) and F:P (-0.014) was very weak and not different from zero, and with protein content (0.173) was weak but different from zero. Locomotion was weakly correlated with fat content (0.071), protein content (0.028), and F:P (0.074), and correlations were not different from zero. Phenotypic correlations were generally weaker than their genetic counterparts, ranging from -0.241 (BCS with ANG) to 0.245 (LOC with ANG). Before including BCS and LOC in the selection index of the Italian Holstein breed, the correlations with other traits currently used to improve type and functionality of animals need to be investigated
Heritability estimates of predicted blood β-hydroxybutyrate and nonesterified fatty acids and relationships with milk traits in early-lactation Holstein cows
Full text linkAt the beginning of lactation, high-producing cows commonly experience an unbalanced energy status that is often responsible for the onset of metabolic disorders and impaired health and performance. Blood β-hydroxybutyrate (BHB) and nonesterified fatty acids (NEFA) are indicators of excessive fat mobilization and circulating ketone bodies. Recently, prediction models based on mid-infrared (MIR) spectroscopy have been developed to assess blood BHB and NEFA from routinely collected individual milk samples. This study aimed to estimate genetic parameters of blood BHB and NEFA predicted from milk MIR spectra and to assess their phenotypic and genetic correlations with milk production and composition traits in early-lactation Holstein cows. The data set comprised the first test-day record within lactation and spectra of individual milk samples (n = 22,718) of 13,106 Holstein cows collected from 5 to 35 d in milk (DIM). Blood BHB and NEFA were predicted from milk MIR spectra using previously developed prediction models. Genetic parameters of blood metabolites and milk traits were estimated for the whole observational period (5–35 DIM) and within 6 classes of DIM. Blood BHB and NEFA showed similar genetic variation across DIM, with the highest heritability in the first 10 d after calving (0.31 ± 0.06 and 0.19 ± 0.05 for BHB and NEFA, respectively). The genetic correlation between BHB and NEFA was moderate (0.51 ± 0.05). Genetic correlations of BHB with milk yield, SCS, protein percentage, lactose percentage, and urea nitrogen content were similar to, or at least in the same direction as, the correlations of NEFA with the same traits, whereas opposite correlations were observed with fat percentage and fat-to-protein ratio. Results of the current study suggest that blood BHB and NEFA predicted from milk MIR spectra have genetic variation that is potentially exploitable for breeding purposes. Therefore, they could be used as indicator traits of hyperketonemia in a selection index aimed to reduce the susceptibility of dairy cows to metabolic disorders in early lactation
- …
