• Factors associated with profitability in pasture-based systems of milk production

      Hanrahan, Liam; McHugh, Noirin; Hennessy, Thia; Moran, Brian; Kearney, R.; Wallace, Michael; Shalloo, Laurence (Elsevier, 2018-03-07)
      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.
    • PastureBase Ireland: A grassland decision support system and national database

      Hanrahan, Liam; Geoghegan, Anne; O'Donovan, Michael; Griffith, Vincent; Ruelle, Elodie; Wallace, Michael; Shalloo, Laurence (Elsevier BV, 2017-04-15)
      PastureBase Ireland (PBI) is a web-based grassland management application incorporating a dual function of grassland decision support and a centralized national database to collate commercial farm grassland data. This database facilitates the collection and storage of vast quantities of grassland data from grassland farmers. The database spans across ruminant grassland enterprises – dairy, beef and sheep. To help farmers determine appropriate actions around grassland management, we have developed this data informed decision support tool to function at the paddock level. Individual farmers enter data through the completion of regular pasture cover estimations across the farm, allowing the performance of individual paddocks to be evaluated within and across years. To evaluate the PBI system, we compared actual pasture cut experimental data (Etesia cuts) to PBI calculated outputs. We examined three comparisons, comparing PBI outputs to actual pasture cut data, for individual DM yields at defoliation (Comparison 1), for cumulative annual DM yields including silage data (Comparison 2) and, for cumulative annual DM yields excluding silage data (Comparison 3). We found an acceptable accuracy between PBI outputs and pasture cut data when statistically analyzed using relative prediction error and concordance correlation coefficients for the measurement of total annual DM yield (Comparison 2), with a relative prediction error of 15.4% and a concordance correlation coefficient of 0.85. We demonstrated an application of the PBI system through analysis of commercial farm data across two years (2014–2015) for 75 commercial farms who actively use the system. The analysis showed there was a significant increase in DM yield from 2014 to 2015. The results indicated a greater variation in pasture growth across paddocks within farms than across farms.