Estimation of genetic parameters for first-lactation test-day milk yield in Holstein Friesian cows fitting random regression models

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New Test Day Model for the Genetic Evaluation of mastitis in dairy cattle

In this study, genetic parameters of test-day (TD) somatic cell score (SCS) and lactation average (LA)clinical mastitis (CM) were estimated using a random regression model (RRM) that combine two differentdata models. A multitrait RRM (mt-RRM) was then developed for the genetic evaluation of mastitis.Estimates of breeding values (EBVs) from the mt-RRM were compared to corresponding multitrait LAmodel (biv-LAM) and univariate LA models (univ-LAM). A total of 147500 and about 5.6 million recordsfrom 27500 and 1.4 million Finnish Ayrshire cows were used for estimation of genetic parameters andprediction of breeding values, respectively. Heritabilities of CM1 and CM2 traits: (CM1, -7 to 30 andCM2, 31 to 300 DIM) were 0.026 and 0.016, respectively, while for TD SCS they ranged from 0.06 to0.11. During first lactation, the genetic correlations between TD SCS and CM1 and between TD SCS andCM2 varied from 0.40 to 0.77 and from 0.34 to 0.71, respectively. In genetic evaluation of mastitis, modelcomparisons have showed that mt-RRM has high model predictive ability and high standard deviation ofbreeding values. Moreover, it has added advantages of making efficient use of available TD SCSinformation and offers proofs for bulls and cows. Therefore, mt-RRM can be used as best practical modelin the future evaluation of animals for mastitis resistance

Estimation of body composition in tropical sheep raised under seasonal feed supply conditions: Prediction models

Prediction models were developed from isotope dilution space (D2O) and live animal measurements (heart girth, height at withers, body length and tail volume measurements) to estimate chemical body components of indigenous tropical fat-tailed sheep breeds in vivo. A STEPWISE multiple regression procedure of SAS was used to assess the predictive power of combinations of variables and models which minimise the predicted residual sum of squares. With regard to the accuracy and robustness of prediction, models containing body weight as the only predictor variable resulted in less accurate estimates of body components, especially that of body fat and energy contents. However, the use of isotope dilution space (as an index of Total Body Water) along with body weight measurements showed significant improvements in R² and accuracy of prediction equations. Testing the predictive ability of models containing live animal measures only, the result obtained showed that, despite a small reduction in accuracy, indices of live animal measures gave comparable estimation of body components with models containing isotope dilution space. Therefore, considering the cost of D2O and its applicability in the field, indications are that the use of models containing indices of live animal measurements only (in various combinations) is promising for field applications, to provide longitudinal measures of change in body composition of tropical fat-tailed sheep

Genetic analysis of milk yield in first-lactation Holstein-Friesian in Ethiopia: A lactation average vs random regression test-day model analysis

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Study on the epidemiology of foot and mouth disease in Ethiopia

Summary This study was designed to describe the status of foot and mouth disease (FMD) in Ethiopia, through analysis of FMD outbreak reports and the detection of antibodies, to address the possibility of establishing a disease-free zone. The serum samples were tested using the 3ABC enzyme-linked immunosorbent assay kit, to identify antibodies against FMD. From a total of 4,465 sera, 10.5% (n = 467) tested positive. The highest seroprevalence was detected in samples from the Eastern zone of Tigray with 41.5%; followed by the Guji zone of Oromia and Yeka district of the city of Addis Ababa, with 32.7% and 30%, respectively. Antibodies specific to FMD virus were not detected in Gambella or Benishangul. The effects of cattle, sheep and goat density, both separately and together, were analysed with a spatial regression model, but did not have a significant effect on seroprevalence. This indicates that other factors, such as farming systems and livestock movement, play a significant role in the occurrence of FMD. Based on these study findings, it might be appropriate to establish disease-free zones in Gambella and Benishangul

Animal board invited review: Genomic-based improvement of cattle in response to climate change

Climate change brings challenges to cattle production, such as the need to adapt to new climates and pressure to reduce greenhouse emissions (GHG). In general, the improvement of traits in current breeding goals is favourably correlated with the reduction of GHG. Current breeding goals and tools for increasing cattle production efficiency have reduced GHG. The same amount of production can be achieved by a much smaller number of animals. Genomic selection (GS) may offer a cost-effective way of using an efficient breeding approach, even in low- and middle-income countries. As climate change increases the intensity of heatwaves, adaptation to heat stress leads to lower efficiency of production and, thus, is unfavourable to the goal of reducing GHG. Furthermore, there is evidence that heat stress during cow pregnancy can have many generation-long lowering effects on milk production. Both adaptation and reduction of GHG are among the difficult-to-measure traits for which GS is more efficient and suitable than the traditional non-genomic breeding evaluation approach. Nevertheless, the commonly used within-breed selection may be insufficient to meet the new challenges; thus, cross-breeding based on selecting highly efficient and highly adaptive breeds may be needed. Genomic introgression offers an efficient approach for cross-breeding that is expected to provide high genetic progress with a low rate of inbreeding. However, well-adapted breeds may have a small number of animals, which is a source of concern from a genetic biodiversity point of view. Furthermore, low animal numbers also limit the efficiency of genomic introgression. Sustainable cattle production in countries that have already intensified production is likely to emphasise better health, reproduction, feed efficiency, heat stress and other adaptation traits instead of higher production. This may require the application of innovative technologies for phenotyping and further use of new big data techniques to extract information for breeding

Progress with genetic selection for low methane traits in dairy cows

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Perioperative provider safety in the pandemic : Development, implementation and evaluation of an adjunct COVID-19 Surgical Patient Checklist

We would like to acknowledge Eliana Lillevik, Luciano Barbosa, Daniela Farchi, Dr Laila Woc-Colburn, Dr Gustavo Moraes, Suko Dwi Nugroho, Nguyen Tri Dung, Dr Rong Hu, Priya Desai and Senait Bitew for their contributions to language translations, survey distribution and data collection. Funding The authors disclosed receipt of the following financial support for the research, authorship, and publication of this article: NS received salary support during the conduct of this study from NIH Fogarty International Center (Global Health Equity Scholars NIH FIC D43TW010540).Peer reviewedPublisher PD

Stochastic simulation of restoration outcomes for a dry afromontane forest landscape in northern Ethiopia.

Forest and Landscape Restoration (FLR) is carried out with the objective of regaining ecological functions and enhancing human well-being through intervention in degrading ecosystems. However, uncertainties and risks related to FLR make it difficult to predict long-term outcomes and inform investment plans. We applied a Stochastic Impact Evaluation framework (SIE) to simulate returns on investment in the case of FLR interventions in a degraded dry Afromontane forest while accounting for uncertainties. We ran 10,000 iterations of a Monte Carlo simulation that projected FLR outcomes over a period of 25 years. Our simulations show that investments in assisted natural regeneration, enrichment planting, exclosure establishment and soil-water conservation structures all have a greater than 77% chance of positive returns. Sensitivity analysis of these outcomes indicated that the greatest threat to positive cashflows is the time required to achieve the targeted ecological outcomes. Value of Information (VOI) analysis indicated that the biggest priority for further measurement in this case is the maturity age of exclosures at which maximum biomass accumulation is achieved. The SIE framework was effective in providing forecasts of the distribution of outcomes and highlighting critical uncertainties where further measurements can help support decision-making. This approach can be useful for informing the management and planning of similar FLR interventions