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      Predictores a nivel de vaca y de rodeo del estatus de salud mamaria en una muestra aleatoria de tambos de argentina Translated title: Cow and herd predictors of udder health status in a random sample of argentinian dairy herds

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          Abstract

          El objetivo del presente estudio fue evaluar la relación entre la salud mamaria, utilizando recuento celular somático de leche compuesta, y factores a nivel de vaca y rodeo en tambos de Córdoba, Argentina. La población de estudio fueron rodeos con 100 a 250 vacas en ordeñe. En 48 tambos seleccionados aleatoriamente y visitados durante el año 2007, se inspeccionó la rutina de ordeñe, se entrevistó al tambero y se colectaron en promedio 45 muestras compuestas de leche de vacas seleccionadas aleatoriamente, de estas se registró fecha y número de parto. El recuento celular somático fue determinado con equipo Somacount 300 y su valor transformado a logaritmo natural. Se ajustó un modelo de regresión lineal generalizado mixto con el rodeo como efecto aleatorio. La media de recuento celular somático en las 2.140 vacas seleccionadas fue 5,38 (Desvío estándar =1,56). Terapia al secado, despunte y edad del tambero, como factores de rodeo, días en lactancia y número de partos, como factores a nivel de vaca, fueron asociados al recuento celular somático. El efecto incremental para los factores a nivel de vaca fue mayor que para los factores de rodeo. La información provista podría contribuir a diseñar programas para mejorar la salud mamaria en Argentina.

          Translated abstract

          The objective of this observational study was to evaluate the relationship between cow- and herd-level factors and cow udder health status, measured by composite milk sample somatic cell count (CSCC) in dairy herds from Córdoba, Argentina. The study population was dairy farms of a size of 100 to 250 cows; 48 randomly selected dairy herds were visited during 2007. Each visit involved a milking routine inspection, an interview to the dairyman and the collection of 45 milk composite samples from cows selected by a random systematic procedure. Parity and days in milk were recorded for each cow sampled. The somatic cell count was determined with a Somacount 300, and then a natural logarithmic transformation of SCC values was used. A general linear mixed regression model looking at herd as a random effect was fitted. The mean of somatic cell count in 2,140 cows was 5.38 (SD=1.56). Dry cow therapy, milk strip and dairymen age as herd factors, lactation days and parity as cow factors, were associated with somatic cell count. The incremental effect on somatic cell count for cow attributes was greater than herd factors. This information will help to device herd programs to improve udder health in Argentina.

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          Explaining mastitis incidence in Dutch dairy farming: the influence of farmers' attitudes and behaviour.

          When mastitis incidence increases, either infection pressure has increased or cows' resistance has decreased. This usually indicates that farm management is not optimal. Numerous quantitative studies have demonstrated the effect of management practices on mastitis. In most of these studies, the identified risk factors could explain only part of the variance in mastitis incidence on farms. Several studies suggest that the unexplained variance is caused by farmers' attitudes towards different aspects of mastitis treatment and preventive behaviour. This study aims to determine, to quantify and to specify the extent to which farmers' attitudes, over and above farmers' behaviour, are factors that explain the variation in mastitis incidence, measured in terms of the quantifiable effect of management factors. An extensive survey on self-reported attitudes, behaviour and mastitis incidence was conducted on 336 Dutch dairy farms. Results of multiple linear regression analyses show that farmers' self-reported behaviour and attitudes together explain 48%, 31% and 23% of the variation within, respectively, the average farm bulk milk somatic cell count (BMSCC), the clinical mastitis incidence and the combined clinical and subclinical mastitis incidence. Both behaviour and attitudes explain part of the variance. However, most of the variance in all three dependant measures is explained solely by the attitude variables. The variation in BMSCC value is best explained by (1) farmers' normative frame of reference about mastitis, (2) farmers' perceptions about the control of mastitis and (3) the perceived effect of a BMSCC penalty level. The variation in clinical mastitis is best explained by farmers' perceptions about mastitis control. The variation in the combined clinical and subclinical mastitis incidence rate is best explained by the perceived effect of a BMSCC penalty level and the frequency of contact with others. The results of this study show that farmers' attitudes are a better measure than farmers' self-reported behaviour to explain and predict differences in mastitis incidence between farms. Consequently, future research and animal health promotion programs should take into account not only farmers' behaviour, but also farmers' attitudes. This study provides a first empirical investigation into the social processes applicable to mastitis incidence and is therefore considered a good starting point for future research to further investigate the causal effect of attitude change on farmers' behaviour and animal health.
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            Effective use of dairy herd improvement somatic cell counts in mastitis control.

            J P RENEAU (1986)
            The single most important factor affecting somatic cell count in milk is mammary gland infection status. In comparison, all other factors are minor. Consideration needs to be given to diurnal effects on Dairy Herd Improvement a.m.-p.m. sampling schemes. Somatic cell count linear score of 5 (283,000) appears to be a good choice of threshold for mastitis control applications. A greater understanding of the nonbacteriological factors affecting somatic cell count is needed so that relative thresholds could be used to improve the clarity of somatic cell count interpretation. Linear score loss estimates are effective educational tools providing motivation for mastitis control implementation. Infection status or milk loss estimates based on single somatic cell count tests on individual cows are weak. A lactational average linear score on individual cows or linear score compilations across a herd provide credible estimates. Treatment of subclinical mastitis based on somatic cell count levels is not economically beneficial and is not recommended. Usefulness of Dairy Herd Improvement somatic cell count data as a mastitis management tool requires measures of mastitis level, new infection rate, and mastitis pattern within the herd over time.
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              Management practices and heifer characteristics associated with early lactation somatic cell count of Belgian dairy heifers.

              Associations between somatic cell counts (SCC) from heifers between 5 and 14 d in milk (DIM) and both herd-management practices and heifer characteristics were studied for 1912 heifers in 159 dairy herds in Flanders (Belgium). In higher-producing herds and in herds with an average calving age of heifers > 27 mo, SCC of heifers was lower than in less-producing herds or in herds with an average calving age < or = 27 mo. Heifers raised in herds with a higher bulk-milk somatic cell count had higher SCC. In herds in which heifers calved on slatted floors, heifers had lower SCC compared with herds in which heifers calved on nonslatted floors. A significant difference in SCC was observed between provinces. At the heifer level, SCC decreased with increasing DIM. On average, heifers calving in April to June had higher SCC, compared with those calving in the other months of the year. In the multilevel regression models, nearly all the variations of SCC resided at the heifer level, indicating that preventive measures against udder health problems in freshening dairy heifers should, in the short term, focus more on factors that vary between heifers than on factors that vary between herds. However, for the long term, the need to identify new, and to implement known, herd-level strategies is important.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                invet
                InVet
                InVet
                Facultad de Ciencias Veterinarias, Universidad de Buenos Aires (Ciudad Autónoma de Buenos Aires, , Argentina )
                1668-3498
                2017
                : 19
                : 1
                : 07-14
                Affiliations
                [02] orgnameCONICET Argentina
                [01] Río Cuarto Córdoba orgnameUniversidad Nacional de Río Cuarto orgdiv1Facultad de Agronomía y Veterinaria orgdiv2Departamento de Patología Animal Argentina
                [03] orgnameUniversidad Nacional de Río Cuarto orgdiv1Facultad de Ciencias Exactas orgdiv2Departamento de Microbiología e Inmunología
                Article
                S1668-34982017000100002
                80e62f24-9c26-4f18-a9ba-871011c1d058

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 30 January 2017
                : 06 November 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 15, Pages: 8
                Product

                SciELO Argentina


                Factores de riesgo,Recuento celular somático,Mixed regression model,Risk factors,Composite somatic cell count,Modelo de regresión mixto

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