A stochastic budgetary simulation model of a dairy farm was developed to allow investigation of the effects of varying biological, technical, and physical processes on farm profitability. The model integrates animal inventory and valuation, milk supply, feed requirement, land and labor utilization, and economic analysis. A key model output is the estimated distribution of farm profitability, which is a function of total receipts from milk, calves, and cull cows less all variable and fixed costs (including an imputed cost for labor). An application of the model was demonstrated by modeling 2 calving patterns: a mean calving date of February 24 (S1) and a mean calving date of January 27 (S2). Monte Carlo simulation was used to determine the influence of variation in milk price, concentrate cost, and silage quality on farm profitability under each scenario. Model validation was conducted by comparing the results from the model against data collected from 21 commercial dairy farms. The net farm profit with S1 was 53,547 euros, and that with S2 was 51,687 euros; the annual EU milk quota was 468,000 kg, and farm size was 40 ha. Monte Carlo simulation showed that the S1 scenario was stochastically dominant over the S2 scenario. Sensitivity analyses showed that farm profit was most sensitive to changes in milk price. The partial coefficients of determination were 99.2, 0.7, and 0.1% for milk price, concentrate cost, and silage quality, respectively, in S1; the corresponding values in S2 were 97.6, 2.3, and 0.1%. Validations of the model showed that it could be used with confidence to study systems of milk production under Irish conditions.

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The global dairy industry needs to reappraise the systems of milk production that are operated at farm level with specific focus on enhancing technical efficiency and competitiveness of the sector. The objective of this study was to quantify the factors associated with costs of production, profitability, and pasture use, and the effects of pasture use on financial performance of dairy farms using an internationally recognized representative database over an 8-yr period (2008 to 2015) on pasture-based systems. To examine the associated effects of several farm system and management variables on specific performance measures, a series of multiple regression models were developed. Factors evaluated included pasture use [kg of dry matter/ha and stocking rate (livestock units/ha)], grazing season length, breeding season length, milk recording, herd size, dairy farm size (ha), farmer age, discussion group membership, proportion of purchased feed, protein %, fat %, kg of milk fat and protein per cow, kg of milk fat and protein per hectare, and capital investment in machinery, livestock, and buildings. Multiple regression analysis demonstrated costs of production per hectare differed by year, geographical location, soil type, level of pasture use, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, breeding season length, and capital investment in machinery, livestock, and buildings per cow. The results of the analysis revealed that farm net profit per hectare was associated with pasture use per hectare, year, location, soil type, grazing season length, proportion of purchased feed, protein %, kg of fat and protein per cow, dairy farm size, and capital investment in machinery and buildings per cow. Pasture use per hectare was associated with year, location, soil type, stocking rate, dairy farm size, fat %, protein %, kg of fat and protein per cow, farmer age, capital investment in machinery and buildings per cow, breeding season length, and discussion group membership. On average, over the 8-yr period, each additional tonne of pasture dry matter used increased gross profit by €278 and net profit by €173 on dairy farms. Conversely, a 10% increase in the proportion of purchased feed in the diet resulted in a reduction in net profit per hectare by €97 and net profit by €207 per tonne of fat and protein. Results from this study, albeit in a quota limited environment, have demonstrated that the profitability of pasture-based dairy systems is significantly associated with the proportion of pasture used at the farm level, being cognizant of the levels of purchased feed.

Paratuberculosis (also called Johne's disease) is a chronic disease caused by Mycobacterium avium ssp. paratuberculosis (MAP) that affects ruminants and other animals. The epidemiology of paratuberculosis is complex and the clinical manifestations and economic impact of the disease in cattle can be variable depending on factors such as herd management, age, infection dose, and disease prevalence, among others. Additionally, considerable challenges are faced in the control of paratuberculosis in cattle, such as the lack of accurate and reliable diagnostic tests. Nevertheless, efforts are directed toward the control of this disease because it can cause substantial economic losses to the cattle industry mainly due to increased premature culling, replacement costs, decreased milk yield, reduced feed conversion efficiency, fertility problems, reduced slaughter values, and increased susceptibility to other diseases or conditions. The variability and uncertainty surrounding the estimations of paratuberculosis prevalence and impact influence the design, implementation, and efficiency of control programs in diverse areas of the world. This review covers important aspects of the economic impact and control of paratuberculosis, including challenges related to disease detection, estimations of the prevalence and economic effects of the disease, and the implementation of control programs. The control of paratuberculosis can improve animal health and welfare, increase productivity, reduce potential market problems, and increase overall business profitability. The benefits that can derive from the control of paratuberculosis need to be communicated to all industry stakeholders to promote the implementation of control programs. Moreover, if the suspected link between Johne's disease in ruminants and Crohn's disease in humans was established, significant economic losses could be expected, particularly for the dairy industry, making the control of this disease a priority across dairy industries internationally.

European Union (EU) trade liberalisation policies will continue to push EU milk price downwards and necessitate increased efficiency and scale at farm and processing level to maintain profitability. In Ireland pasture‐based dairying, based on the efficient conversion of grazed grass into milk can be competitive within the EU. Continued technical innovation increasing animal performance from grazed grass, increasing herd genetic potential and developing labour efficient lower fixed cost systems will be essential. At processing level, increased efficiency in commodity processing, higher margin product development and the evolution of milk payment systems to reflect the true product value of supplies received will be required.

A processing-sector model was developed that simulates (i) milk collection, (ii) standardization, and (iii) product manufacture. The model estimates the product yield, net milk value, and component values of milk based on milk quantity, composition, product portfolio, and product values. Product specifications of cheese, butter, skim and whole milk powders, liquid milk, and casein are met through milk separation followed by reconstitution in appropriate proportions. Excess cream or skim milk are used in other product manufacture. Volume-related costs, including milk collection, standardization, and processing costs, and product-related costs, including processing costs per tonne, packaging, storage, distribution, and marketing, are quantified. Operating costs, incurred irrespective of milk received and processing activities, are included in the model on a fixed-rate basis. The net milk value is estimated as sale value less total costs. The component values of fat and protein were estimated from net milk value using the marginal rate of technical substitution. Two product portfolio scenarios were examined: scenario 1 was representative of the Irish product mix in 2000, in which 27, 39, 13, and 21% of the milk pool was processed into cheese (€ 3,291.33/t), butter (€ 2,766.33/t), whole milk powder (€ 2,453.33/t), and skim milk powder (€ 2,017.00/t), respectively, and scenario 2 was representative of the 2008 product mix, in which 43, 30, 14, and 13% was processed into cheese, butter, whole milk powder, and skim milk powder, respectively, and sold at the same market prices. Within both scenarios 3 milk compositions were considered, which were representative of (i) typical Irish Holstein-Friesian, (ii) Jersey, and (iii) the New Zealand strain of Holstein-Friesian, each of which had differing milk constituents. The effect each milk composition had on product yield, processing costs, total revenue, component values of milk, and the net value of milk was examined. The value per liter of milk in scenario 1 was 24.8, 30.8, and 27.4 cents for Irish Holstein-Friesian, Jersey, and New Zealand strain of Holstein-Friesian milk, respectively. In scenario 2 the value per liter of milk was 26.1, 32.6, and 28.9 cents for Irish Holstein-Friesian, Jersey, and New Zealand strain of Holstein-Friesian milk, respectively.

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