1AbacusBio Limited,PO Box 5585,Dunedin,New Zealand.
2Irish Cattle Breeding Federation,Highfield House,Shinagh,Bandon,County Cork,Ireland.
Animal. 2018 Jan;12(1):5-11. doi: 10.1017/S1751731117001549. Epub 2017 Jul 11.
A methodological framework was presented for deriving weightings to be applied in selection indexes to account for the impact genetic change in traits will have on greenhouse gas emissions intensities (EIs). Although the emission component of the breeding goal was defined as the ratio of total emissions relative to a weighted combination of farm outputs, the resulting trait-weighting factors can be applied as linear weightings in a way that augments any existing breeding objective before consideration of EI. Calculus was used to define the parameters and assumptions required to link each trait change to the expected changes in EI for an animal production system. Four key components were identified. The potential impact of the trait on relative numbers of emitting animals per breeding female first has a direct effect on emission output but, second, also has a dilution effect from the extra output associated with the extra animals. Third, each genetic trait can potentially change the amount of emissions generated per animal and, finally, the potential impact of the trait on product output is accounted for. Emission intensity weightings derived from this equation require further modifications to integrate them into an existing breeding objective. These include accounting for different timing and frequency of trait expressions as well as a weighting factor to determine the degree of selection emphasis that is diverted away from improving farm profitability in order to achieve gains in EI. The methodology was demonstrated using a simple application to dairy cattle breeding in Ireland to quantify gains in EI reduction from existing genetic trends in milk production as well as in fertility and survival traits. Most gains were identified as coming through the dilution effect of genetic increases in milk protein per cow, although gains from genetic improvements in survival by reducing emissions from herd replacements were also significant. Emission intensities in the Irish dairy industry were estimated to be reduced by ~5% in the last 10 years because of genetic trends in production, fertility and survival traits, and a further 15% reduction was projected over the next 15 years because of an observed acceleration of genetic trends.
提出了一种方法论框架，用于推导权重，以便在选择指数中应用，以考虑遗传性状变化对温室气体排放强度（EI）的影响。虽然育种目标的排放部分被定义为总排放量与农场产出加权组合的比值，但由此产生的性状加权因素可以作为线性权重应用，在考虑 EI 之前，增加任何现有的育种目标。微积分被用来定义将每个性状变化与动物生产系统的预期 EI 变化联系起来所需的参数和假设。确定了四个关键组成部分。性状对每头繁殖母畜排放动物数量的潜在影响首先对排放输出有直接影响，但其次，由于与额外动物相关的额外产出，也有稀释效应。第三，每个遗传性状都有可能改变每头动物产生的排放量，最后，还要考虑性状对产品产出的潜在影响。从该方程得出的排放强度权重需要进一步修改，以便将其纳入现有的育种目标。这些修改包括考虑性状表达的不同时间和频率，以及一个权重因子，以确定从提高农场盈利能力转向实现 EI 增益的选择重点程度。该方法使用爱尔兰奶牛养殖的简单应用进行了演示，以量化现有遗传趋势在牛奶生产以及在繁殖力和存活率性状方面对 EI 减少的收益。最大的收益被认为来自每头牛牛奶蛋白遗传增加的稀释效应，尽管由于减少畜群更替的排放而提高存活率的遗传改进也有显著收益。由于生产、繁殖力和存活率性状的遗传趋势，爱尔兰乳制品行业的排放强度在过去 10 年中降低了约 5%，预计在未来 15 年内还将再降低 15%，因为遗传趋势的加速。
