Agentes causadores de mastite e relações entre a CCS com a produção e com a composição do leite em vacas leiteiras

França, Marciel; Valle, Tiago A. Del; Campana, Mariana; Veronese, L.P.; Nascimento, George Vieira do; Morais, Jozivaldo Prudêncio Gomes de

doi:10.21071/az.v66i253.2124

Cited by 7 publications

(8 citation statements)

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“…The SCC coefficients confirmed the negative influence on SNF% and Lact% in line with the literature (França et al, 2017). Regarding milk fat concentration, the positive values of the PF3 and negative values of the PF1 imply that the supply of larger quantities of farm-made concentrate with the low supply of byproducts and corn silage and predominance of crossbred cows (Figure 1) are associated with a higher milk fat concentration.…”

Section: Discussionsupporting

confidence: 86%

“…The negative linear relation observed between PF2 and milk yield and SNF% and Lact% is explained by the use of high quantities of sugarcane in detriment of corn silage in the less intensified SDS (Figure 1, Table 4), decreasing nutrient supply and thus milk yield and SNF% (Oliveira et al, 2011). The lower nutrient supply and highest SCC lowered Lact% in the milk (França et al, 2017). In the present study, 38.7% of SDS provided corn silage and 48.3% sugarcane as a source of roughage, while 13% relied on pasture.…”

Section: Discussionmentioning

confidence: 51%

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Use of quali-quantitative feeding practices criteria in typology of smallholders’ dairy production systems

Dias¹,

Fischer²

2021

Revista Brasileira De Zootecnia

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Animal production systems and agribusinessFull-length research article Use of quali-quantitative feeding practices criteria in typology of smallholders' dairy production systems ABSTRACT -This study aimed to typify smallholders' dairy systems using qualiquantitative measures of feeding practices and detect the main discriminatory elements identifying the systems. We collected data from 30 farms distributed in 10 municipalities in the eastern region of Rio Grande do Sul, Brazil, using a survey with semi-structured questions, in addition to bimonthly observations of milking and feeding practices. Multivariate analysis based on principal factors and cluster analysis were performed. Multiple linear regressions were made between the principal factors scores and variables of milk production and composition. Three principal factors with eigenvalues ≥1.0 explained 58.9% of the total variance. The original variables with the highest factor loading values were production scale and feeding practices involving greater quantities of byproducts; use of corn silage and sugarcane; and commercial and farm-made concentrate for principal factor 1, principal factor 2, and principal factor 3, respectively. Milk yield and concentrations of lactose and solids non-fat increased linearly with principal factor 1 and principal factor 3 but decreased linearly with principal factor 2. Observations were grouped into three clusters. Farm area and quantity of corn silage and byproducts were the most important variables to set the clusters. The use of quali-quantitative feeding practices criteria to characterize dairy systems is effective to identify the opportunities for improving milk production and composition. Whereas high inclusion of sugarcane as roughage was detrimental for milk production, moderate supply of concentrate and byproducts enhanced milk yield without compromising milk composition.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 51%

Use of quali-quantitative feeding practices criteria in typology of smallholders’ dairy production systems

Dias¹,

Fischer²

2021

Revista Brasileira De Zootecnia

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“…With increasing milk yield, the amount of protein decreases, explaining the opposite signs of the path coefficients of milk yield and protein content in our model [46]. Regarding udder health, protein content reacted very sensitively, especially to somatic cell count alterations, while fat content was more stable [9]. In our SEM analogy, path coefficients were larger for protein than for fat content.…”

Section: Manifest Variables On Intramammary Infection and Productionmentioning

confidence: 59%

“…Intramammary infection impairs milk yield and milk composition. Additionally, in recursive biological systems, the level of milk yield and composition might influence the susceptibility of an udder infection [8,9]. In addition, from an "environmental" perspective, the age of the animal, the status of nutrition and many other factors such as climate play a role in determining an animal's susceptibility for an infection [2,3].…”

Section: Introductionmentioning

confidence: 99%

Inferring Causalities of Environmental and Genetic Factors for Differential Somatic Cell Count and Mastitis Pathogens in Dairy Cows Using Structural Equation Modelling

Wagner,

Brügemann,

Yin

et al. 2023

Genes

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The aim of this study was to establish and evaluate a structural equation model to infer causal relationships among environmental and genetic factors on udder health. For this purpose, 537 Holstein Friesian cows were genotyped, and milk samples were analyzed for novel traits including differential somatic cell counts and specific mastitis pathogens. In the structural model, four latent variables (intramammary infection (IMI), production, time and genetics) were defined, which were explained using manifest measurable variables. The measurable variables included udder pathogens and somatic differential cell counts, milk composition, as well as significant SNP markers from previous genome-wide associations for major and minor pathogens. The housing system effect (i.e., compost-bedded pack barns versus cubicle barns) indicated a small influence on IMI with a path coefficient of −0.05. However, housing system significantly affected production (0.37), with ongoing causal effects on IMI (0.17). Thus, indirect associations between housing and udder health could be inferred via structural equation modeling. Furthermore, genotype by environment interactions on IMI can be represented, i.e., the detection of specific latent variables such as significant SNP markers only for specific housing systems. For the latent variable genetics, especially one SNP is of primary interest. This SNP is located in the EVA1A gene, which plays a fundamental role in the MAPK1 signaling pathway. Other identified genes (e.g., CTNNA3 and CHL1) support results from previous studies, and this gene also contributes to mechanisms of the MAPK1 signaling pathway.

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“…However, dairy production has a major problem, mastitis, which consists of an infection of the mammary gland. It is responsible for major economic losses, for causing a reduction in the production and quality of milk in the affected mammary quarters, in addition to interfering in the industrial dairy process (França et al, 2017;Terra et al, 2020). The loss of production can be drastic, especially when a significant percentage of the herd is infected, which can reduce milk production by up to 50% in addition to decreasing the productive life of the cow (Mostert et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Diagnosis of clinical and subclinical mastitis in a rural property in Carambeí, State of Paraná

Clock

Gabardo

Luz³

et al. 2021

RSD

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The aim of the present study was to diagnose clinical and subclinical bovine mastitis in a property in the municipality of Carambeí-PR. 86 dairy cows were diagnosed in two evaluations carried out on July 23 and November 4, 2020. The detection of clinical mastitis was performed by testing the black-bottomed mug, whereas the detection of animals with sub-clinical mastitis by the California Mastitis Test (CMT) and laboratory analysis of bacteria and fungi present. In the first evaluation, 9.4% of the animals had mastitis, while in the second 5.16% of the herd. The milk of the animals that tested positive were submitted to laboratory analysis. In the first evaluation, they were diagnosed with an incidence of 15% Escherichia coli, 15% Prothoteca / yeast, 23% Staphlococcus aureus, 46% Streptococcus agalactiae. In the second evaluation, there was an incidence of 25% Enterococcus sp. and 25% S. agalactiae, the other animals showed 50% Staphlococcus non aureus. There was a higher occurrence of subclinical mastitis in the property, in both evaluations. There was a reduction from the first to the second evaluation in the incidence of cases of subclinical mastitis and the cases of clinical mastitis were resolved. Contributing to the lower disposal of milk caused by the high somatic cell count.

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Agentes causadores de mastite e relações entre a CCS com a produção e com a composição do leite em vacas leiteiras

Cited by 7 publications

References 0 publications

Use of quali-quantitative feeding practices criteria in typology of smallholders’ dairy production systems

Use of quali-quantitative feeding practices criteria in typology of smallholders’ dairy production systems

Inferring Causalities of Environmental and Genetic Factors for Differential Somatic Cell Count and Mastitis Pathogens in Dairy Cows Using Structural Equation Modelling

Diagnosis of clinical and subclinical mastitis in a rural property in Carambeí, State of Paraná

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