The objective of this study was to identify and understand grassland management practices employed on dairy farms in the Republic of Ireland, including grazing-season length, concentrate-feed input, uptake of new grassland-management technologies and frequency and methods of sward renewal. The sample population for the survey was chosen from a proportionate representation of all milk suppliers taken from three of the largest dairy processors in the Republic of Ireland. The sample was subsequently broken down into three stocking rate (SR) and three size categories of milk quota (Qcat) to investigate their effects on the survey variables. Both SR and Qcat had significant effects on the proportion of participants adopting grassbased technologies and on the amount of supplementary feed offered. Grazing-season length increased from 228 d in Qcat1 to 249 d in Qcat 3 but was unaffected by SR (241 d; s.d. 3AE05). The proportion of the grazing area reseeded annually was significantly affected by SR, increasing from 0AE044 to 0AE095 of the grassland area as SR increased from SR1 to SR3, with no effect of Qcat (0AE068). The results show that on-farm grass utilization is low, with significant potential for expansion and increased efficiency through increased SRs, greater adoption of grassland-management technologies and higher levels of sward renewal.

Precision technologies and data have had relatively modest impacts in grass-based livestock ruminant production systems compared with other agricultural sectors such as arable. Precision technologies promise increased efficiency, reduced environmental impact, improved animal health, welfare and product quality. The benefits of precision technologies have, however, been relatively slow to be realised on pasture based farms. Though there is significant overlap with indoor systems, implementing technology in grass-based dairying brings unique opportunities and challenges. The large areas animals roam and graze in pasture based systems and the associated connectivity challenges may, in part at least, explain the comparatively lower adoption of such technologies in pasture based systems. With the exception of sensor and Bluetooth-enabled plate metres, there are thus few technologies designed specifically to increase pasture utilisation. Terrestrial and satellite-based spectral analysis of pasture biomass and quality is still in the development phase. One of the key drivers of efficiency in pasture based systems has thus only been marginally impacted by precision technologies. In contrast, technological development in the area of fertility and heat detection has been significant and offers significant potential value to dairy farmers, including those in pasture based systems. A past review of sensors in health management for dairy farms concluded that although the collection of accurate data was generally achieved, the processing, integration and presentation of the resulting information and decision-support applications were inadequate. These technologies' value to farming systems is thus unclear. As a result, it is not certain that farm management is being sufficiently improved to justify widespread adoption of precision technologies currently. We argue for a user need-driven development of technologies and for a focus on how outputs arising from precision technologies and associated decision support applications are delivered to users to maximise their value. Further cost/benefit analysis is required to determine the efficacy of investing in specific precision technologies, potentially taking account of several yet to ascertained farm specific variables.

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