Economic assessment of Holstein-Friesian dairy cows of divergent Economic Breeding Index evaluated under seasonal calving pasture-based management

Investigating How Genetic Merit and Country of Origin Impact the Profitability of Grass-Based Sheep Production Systems

The objective of this study was to simulate and assess the profitability of sheep production systems that varied in maternal genetic merit (high or low) and country of origin (New Zealand (NZ) or Ireland), using the Teagasc Lamb Production Model (TLPM). A production system study performed at Teagasc Athenry, Co. Galway, Ireland, from 2016 to 2019, inclusive, provided key animal performance input parameters, which were compared across three scenarios: high maternal genetic merit NZ (NZ), high maternal genetic merit Irish (High Irish) and low maternal genetic merit Irish (Low Irish). Prior to the beginning of the study ewes and rams were imported from New Zealand to Ireland in order to compare animals within the same management system. Ewes were selected based on the respective national maternal genetic indexes; i.e., either the New Zealand Maternal Worth (NZ group) or the €uro-star Replacement index (Irish groups). The TLPM was designed to simulate the impact of changes in physical and technical outputs (such as number of lambs, drafting rates and replacement rates) on a range of economic parameters including variable costs, fixed costs, gross margin and net profit. Results showed that total farm costs (variable and fixed) were similar across the three scenarios, driven by the similar number of ewes in each scenario. The number of lambs produced and the cost of production per lamb was 14.05 lambs per hectare for the NZ scenario at a cost of EUR 82.35 per lamb, 11.40 lambs per hectare for the High Irish scenario at a cost of EUR 101.42 per lamb and 11.00 lambs per hectare for the Low Irish scenario at a cost of EUR 105.72 per lamb. The net profit of the three scenarios was EUR 514, EUR 299, and EUR 258 per hectare, for the NZ, High Irish and Low Irish scenarios, respectively. Overall, the NZ scenario had a lower cost of production in comparison to either Irish group, while the High Irish scenario had a 14% greater net profit than the Low Irish scenario, equating to an additional EUR 41 per hectare net profit. Output from this simulation model reiterates the importance, for overall farm profitability, of maximising the number of lambs weaned per hectare, particularly through maximising income and diluting the total farm costs. To conclude, the use of high-maternal-genetic-merit animals, regardless of their country of origin impacts farm profitability.

Assessment of feed and economic efficiency of dairy farms based on multivariate aggregation of partial indicators measured on field

Many of the metrics used to evaluate farm performance are only partial indicators of farm operations, which are assumed to be best predictors of the whole farm efficiency. The main objective of this work was to identify aggregated multiple indexes of profitability using common partial indicators that are routinely available from individual farms to better support the short-term decision-making processes of the cattle-feeding process. Data were collected from face-to-face interviews with farmers from 90 dairy farms in Italy and used to calculate 16 partial indicators that covered almost all indicators currently used to target feeding and economic efficiency in dairy farms. These partial indicators described feed efficiency, energy utilization, feed costs, milk-to-feed price ratio, income over feed costs, income equal feed cost, money-corrected milk, and bargaining power for feed costs. Calculations of feeding costs were based on lactating cows or the whole herd, and income from milk deliveries was determined with or without considering the milk quality payment. Multivariate factor analysis was then applied to the 16 partial indicators to determine simplified and latent structures. The results indicated that 5 factors explained 70% of the variability. Each of the original partial indicator was associated with all factors in different proportions, as indicated by loading scores from the multivariate factor analysis. Based on the loading scores, we labeled these 5 factors as "economic efficiency," "energy utilization," "break-even point," "milk-to-feed price," and "bargaining power of the farm," in decreasing order of explained communality. The first 3 factors shared 83% of the total communality. Feed efficiency was similarly associated with factor 1 (53% loading) and factor 2 (66% loading). Only factor 4 was significantly affected by farm location. Milk production and herd size had significant effects on factor 1 and factor 2. Our multivariate approach eliminated the problem of multicollinearity of partial indicators, providing simple and effective descriptions of farm feeding economics. The proposed method allowed the evaluation, benchmarking, and ranking of dairy herd performance at the level of single farms and at territorial level with high opportunity to be used or replicated in other areas.

Herd solutions from genetic evaluations can be used as a tool to rescale the expected expression of genetic potential in cattle

The objective of this study was to determine whether response to selection for carcass weight (CW), conformation (CC) and fat (CF), and the association between heterosis and carcass performance varied by herd environment in cattle. Following edits, carcass information was available for 4,616,761 cattle, of which the majority were some crossbred combination of the following breeds: Angus, Aubrac, Belgian Blue, Blonde d'Aquitaine, Charolais, Hereford, Holstein-Friesian, Jersey, Limousin, Saler, Shorthorn and Simmental. Herd environment was defined separately for each carcass trait using herd solutions outputted from carcass trait genetic evaluations. A total of 3,859 herds were stratified, for each trait, into one of five strata based on their corresponding percentile herd solution rank, with the response to selection and the effect of heterosis then estimated within each stratum. The response in CW and CC from selection on the respective estimated breeding values (EBV) increased between the lowest (0.71 kg and 0.89 CC score increase per unit increase in the respective EBV) and highest (0.99 kg and 1.25 CC score increase per unit increase in the respective EBV) corresponding herd stratum. The response in CF from selection on CF EBV, however, reduced between the lowest and highest CF herd stratum (respective increases of 0.93 and 0.83 CF scores per unit increase in CF EBV). In addition, the effect of a unit increase in heterosis coefficient on CW, CC and CF also varied by herd stratum. Furthermore, results (i.e. the area under relative operating characteristic curves) from the present study demonstrated that the response to selection and heterosis effects estimated for the different herd stratum can be used, along with EBVs and the herd solutions themselves, to improve the accuracy of phenotypic predictions. Results from the present study could help producers to make more informed breeding decisions that are bespoke to their herd.

Greenhouse gas emissions and nitrogen efficiency of dairy cows of divergent economic breeding index under seasonal pasture-based management

Greenhouse gas (GHG) emissions and nitrogen (N) efficiencies were modeled for 2 genetic groups (GG) of Holstein-Friesian cows across 3 contrasting feeding treatments (FT). The 2 GG were (1) high economic breeding index (EBI) animals representative of the top 5% of cows nationally (elite) and (2) EBI representative of the national average (NA). The FT represented (1) generous feeding of pasture, (2) a slight restriction in pasture allowance, and (3) a high-concentrate feeding system with adequate pasture allowance. Greenhouse gas and N balance models were parameterized using outputs generated from the Moorepark Dairy Systems model, a stochastic budgetary simulation model, having integrated biological data pertaining to the 6 scenarios (2 GG × 3 FT) obtained from a 4-yr experiment conducted between 2013 and 2016. On a per hectare basis, total system GHG emissions were similar for both elite and NA across the 3 FT. Per unit of product, however, the elite group had 10% and 11% lower GHG emissions per kilogram of fat- and protein-corrected milk and per kilogram of milk solids (MSO; fat + protein kg), respectively, compared with the NA across the 3 FT. The FT incorporating high concentrate supplementation had greater absolute GHG emissions per hectare as well as GHG per kilogram of fat- and protein-corrected milk and MSO. The elite group had a slightly superior N use efficiency (N output/N input) and lower N surplus (N input - N output) compared with the NA group. The high concentrate FT had an inferior N use efficiency and a higher N surplus. The results of the current study demonstrate that breeding for increased EBI will lead to a general improvement in GHG emissions per unit of product as well as improved N efficiency. The results also illustrate that reducing concentrate supplementation will reduce GHG emissions, GHG emissions intensity, while improving N efficiency in the context of pasture-based dairy production.

Mammary microbial dysbiosis leads to the zoonosis of bovine mastitis: a One-Health perspective

Bovine mastitis is a prototypic emerging and reemerging bacterial disease that results in cut-by-cut torture to animals, public health and the global economy. Pathogenic microbes causing mastitis have overcome a series of hierarchical barriers resulting in the zoonotic transmission from bovines to humans either by proximity or remotely through milk and meat. The disease control is challenging and has been attributed to faulty surveillance systems to monitor their emergence at the human-animal interface. The complex interaction between the pathogens, the hidden pathobionts and commensals of the bovine mammary gland that create a menace during mastitis remains unexplored. Here, we review the zoonotic potential of these pathogens with a primary focus on understanding the interplay between the host immunity, mammary ecology and the shift from symbiosis to dysbiosis. We also address the pros and cons of the current management strategies and the extent of the success in implementing the One-Health approach to keep these pathogens at bay.