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.

The objective of this paper was to estimate the effect of the costs of mastitis on the profitability of Irish dairy farms as indicated by various ranges of bulk milk somatic cell count (BMSCC). Data were collected from 4 sources and included milk production losses, cases treated, and on-farm practices around mastitis management. The Moorepark Dairy Systems Model, which simulates dairying systems inside the farm gate, was used to carry out the analysis. The cost components of mastitis that affect farm profitability and that were included in the model were milk losses, culling, diagnostic testing, treatment, veterinary attention, discarded milk, and penalties. Farms were grouped by 5 BMSCC thresholds of ≤ 100,000, 100,001-200,000, 200,001-300,000, 300,001-400,000, and > 400,000 cells/mL. The ≤ 100,000 cells/mL threshold was taken as the baseline and the other 4 thresholds were compared relative to this baseline. For a 40-ha farm, the analysis found that as BMSCC increased, milk receipts decreased from €148,843 at a BMSCC <100,000 cells/mL to €138,573 at a BMSCC > 400,000 cells/mL. In addition, as BMSCC increased, livestock receipts increased by 17%, from €43,304 at a BMSCC <100,000 cells/mL to €50,519 at a BMSCC > 400,000 cells/mL. This reflected the higher replacement rates as BMSCC increased and the associated cull cow value. Total farm receipts decreased from €192,147 at the baseline (< 100,000 cells/mL) to €189,091 at a BMSCC > 400,000 cells/mL. Total farm costs increased as BMSCC increased, reflecting treatment, veterinary, diagnostic testing, and replacement heifer costs. At the baseline, total farm costs were €161,085, increasing to €177,343 at a BMSCC > 400,000 cells/mL. Net farm profit decreased as BMSCC increased, from €31,252/yr at the baseline to €11,748/yr at a BMSCC > 400,000 cells/mL. This analysis highlights the impact that mastitis has on the profitability of Irish dairy farms. The analysis presented here can be used to develop a "cost of mastitis" tool for use on Irish dairy farms to motivate farmers to acknowledge the scale of the problem, realize the value of improving mastitis control, and implement effective mastitis control practices.

The objectives of this study were to estimate the levels of technical and scale efficiency for a sample of pasture based Irish dairy producers, to identify the factors that contributed to reaching the optimum scale and to examine the relationship between technical and scale efficiency with farm size, intensification and specialisation. Efficiency scores were calculated using Data Envelopment Analysis (DEA). Technical efficiency was on average 0.757 under constant returns to scale (CRS), 0.799 under variable returns to scale (VRS) and scale efficiency was estimated at 0.951. Twelve per cent of the sample was operating at optimum scale (CRS). Fifty six percent of the sample was operating below optimum scale and 32% of the sample was operating above optimum scale. Overall optimum scale was associated with production systems operating with larger land area, with reduced proportion of rented land, increased amounts of hired labour, a higher quantity of quota and achieving a longer grazing season. It was also shown that increased farm size, intensification and dairy specialisation were associated with increases in technical and scale efficiency at farm level.

A seasonal processing sector model was developed to simulate dairy product manufacture in Ireland. Outputs include the quantity of product manufactured, net returns and component values of milk (protein and fat) per month of year. Two milk supply profiles representative of mean calving dates of mid-February and mid-March were evaluated across three milk processing plants with differing capacities for cheese and casein. The analysis was carried out based on average Dutch National quotations over the period 2008-10

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