CONTEXT

Sheep 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.

OBJECTIVES

This 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.

METHODS

Four 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 CONCLUSIONS

Results 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.

SIGNIFICANCE

These 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.

中文翻译：

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北欧草原绵羊系统中不同管理策略的农场劳动力，利润率和碳足迹的比较

语境

绵羊生产系统需要提高碳效率，以满足日益增长的公众对气候变化的需求。为实现这一目标而设想的一些方法是实施新技术和管理策略，例如精准畜牧业（PLF），在可行的情况下通过人工授精（AI）来增加对具有估计育种价值的高遗传优势动物的使用，以及多产的使用品种。但是，这些策略对碳足迹的影响迄今尚未量化。另外，国际经验表明，这种策略的采用率很低，部分原因是人们认为工作量增加，尤其是在羊年的繁忙时期。

目标

这项跨欧洲的研究调查了不同的绵羊管理策略对农场劳动力投入，碳足迹以及农场利润率的影响，以解决这些问题。

方法

在以下14个案例研究鸡群中，考虑了以下四种管理策略：i）使用技术（PLF），ii）使用性能记录获得更高的遗传价值，iii）使用AI获得更高的遗传价值和iv）和多产品种。北欧苏格兰苏格兰，法国，爱尔兰和挪威的草原羊生产系统的典型区域。对于每种管理策略，都确定了成对的案例研究群。使用录像，农民日记和调查表在关键处理事件上对劳动力进行了评估，随后对这些劳动力进行了量化并归类为关键任务，以针对每个案例研究羊群创建标准化的劳动力概况。使用碳计算器工具（www.agrecalc.com）量化了碳足迹。计算财务净利润率。

结果与结论

结果表明，在广泛的农场中采用PLF技术可减少20％的劳动力，并增加9英镑/母羊的经济利润，但同时会增加碳排放量（kg CO2e /公斤肉）。利用绵羊农场的绩效记录来获得更高的遗传价值，可以使每头母羊经济利润增加6英镑/母羊，并减少每生产一公斤肉产生的碳排放量（kg CO2e），但又增加了10％的人工。农场上的人工授精将经济利润提高了50英镑/母羊，没有产生额外的劳动力，并且就生产的千克二氧化碳当量/千克肉而言提高了碳效率。最后，高产品种没有在关键操作事件上显着增加劳动力投入，而是由于较高的经济利润率（+3英镑/母羊）而没有改变千克二氧化碳当量/千克肉的产量。

意义

这些新颖的案例研究清楚地表明，通过采用技术，改变育种管理或绵羊场的母羊繁殖，有可能提高碳排放和劳动效率。