Abstract

CONTEXTSheep production systems need to become more carbon efficient to meet growing public demands on climate change. Some of the ways postulated to achieve this is to implement new technologies and management strategies such as precision livestock farming (PLF), increased use of high genetic merit animals with estimated breeding values through artificial insemination (AI) where practical, and the use of prolific breeds. However, the carbon footprint impact of these strategies has not to-date been quantified. Additionally, international experience indicates that uptake of such strategies is low due, in part, to the perception of increased workload especially during busy periods of the sheep year. OBJECTIVESThis trans-European study investigates the impact of differing sheep management strategies on farm labour input, carbon footprint as well as the on-farm profitability, to address these concerns. METHODSFour management strategies were considered i) use of technology (PLF), ii) use of performance recording for higher genetic merit, iii) use of AI for higher genetic merit and iv) and use of prolific breeds, in 14 case study flocks located in areas typical of Northern European grassland sheep production systems across Scotland, France, Ireland and Norway. For each management strategy, paired case study flocks were identified. Labour was assessed at key handling events using video recording, farmers' diaries, and questionnaires, which were later quantified and classed into key tasks to create normalised labour profiles for each case study flock. The carbon footprint was quantified using a carbon calculator tool (www.agrecalc.com). Financial net margins were calculated. RESULTS AND CONCLUSIONSResults highlighted that introducing PLF technology on extensive farms reduced labour by 20% and increased economic margins by £9/ewe but with a concurrent increase in carbon emissions (kg CO2e/ kg of meat produced). Using performance recording on sheep farms for achieving higher genetic merit increased economic margins by £6/ewe, and reduced carbon emissions (kg CO2e) per kg of meat produced but resulted in 10% extra labour. AI on farms increased economic margins by £50/ewe, did not incur extra labour and increased carbon efficiency in terms of kg CO2e/kg meat produced. Finally, high prolific breeds did not significantly increase labour input at key handling events and resulted by higher economic margins (+£3/ewe), without a change in terms of kg CO2e/kg meat produced. SIGNIFICANCEThese novel case studies clearly illustrate it is possible to increase carbon and labour efficiency by adopting technology, changing breeding management or ewe breed on sheep farms.

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