Özkan Gülzari Şeyda, Vosough Ahmadi Bouda, Stott Alistair W
Department of Animal and Aquacultural Sciences, Faculty of Veterinary Medicine and Biosciences, Norwegian University of Life Sciences, P.O. Box 5003, Ås, 1430 Norway; Norwegian Institute of Bioeconomy Research, Post Box 115, Ås 1431 Norway.
Scotland's Rural College (SRUC), West Mains Road, Edinburgh, EH9 3JG, United Kingdom; European Commission, Joint Research Centre, Seville, Spain.
Prev Vet Med. 2018 Feb 1;150:19-29. doi: 10.1016/j.prevetmed.2017.11.021. Epub 2017 Nov 27.
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subclinical mastitis as an exemplar to benchmark alternative scenarios against an economic optimum and adjusted herd structure to estimate the GHG emissions intensity associated with varying levels of disease. Five levels of somatic cell count (SCC) classes were considered namely 50,000 (i.e. SCC50), 200,000, 400,000, 600,000 and 800,000cells/mL (milliliter) of milk. The effects of varying levels of SCC on milk yield reduction and consequential milk price penalties were used in a dynamic programming (DP) model that maximizes the profit per cow, represented as expected net present value, by choosing optimal animal replacement rates. The GHG emissions intensities associated with different levels of SCC were then computed using a farm-scale model (HolosNor). The total culling rates of both primiparous (PP) and multiparous (MP) cows for the five levels of SCC scenarios estimated by the model varied from a minimum of 30.9% to a maximum of 43.7%. The expected profit was the highest for cows with SCC200 due to declining margin over feed, which influenced the DP model to cull and replace more animals and generate higher profit under this scenario compared to SCC50. The GHG emission intensities for the PP and MP cows with SCC50 were 1.01kg (kilogram) and 0.95kg carbon dioxide equivalents (COe) per kg fat and protein corrected milk (FPCM), respectively, with the lowest emissions being achieved in SCC50. Our results show that there is a potential to reduce the farm GHG emissions intensity by 3.7% if the milk production was improved through reducing the level of SCC to 50,000cells/mL in relation to SCC level 800,000cells/mL. It was concluded that preventing and/or controlling subclinical mastitis consequently reduces the GHG emissions per unit of product on farm that results in improved profits for the farmers through reductions in milk losses, optimum culling rate and reduced feed and other variable costs. We suggest that further studies exploring the impact of a combination of diseases on emissions intensity are warranted.
动物健康受损会导致奶牛场的生产力和盈利能力下降，造成投入使用效率低下，并增加单位产品产生的温室气体（GHG）排放量（即排放强度）。在此，我们以亚临床型乳腺炎为例，将替代方案与经济最优方案进行对比，并调整畜群结构，以估算与不同疾病水平相关的温室气体排放强度。我们考虑了五个体细胞计数（SCC）等级，即每毫升牛奶中含50,000个（即SCC50）、200,000个、400,000个、600,000个和800,000个细胞。不同SCC水平对产奶量减少和相应牛奶价格惩罚的影响被用于一个动态规划（DP）模型中，该模型通过选择最优的动物替换率，使每头奶牛的利润最大化，以预期净现值表示。然后使用农场规模模型（HolosNor）计算与不同SCC水平相关的温室气体排放强度。该模型估计的五个SCC水平情景下初产（PP）和经产（MP）奶牛的总淘汰率从最低的30.9%到最高的43.7%不等。对于SCC200的奶牛，预期利润最高，这是由于饲料利润率下降，这影响了DP模型在此情景下淘汰和替换更多动物并产生更高利润，相比SCC50而言。SCC50的PP和MP奶牛每千克脂肪和蛋白质校正乳（FPCM）的温室气体排放强度分别为1.01千克和0.95千克二氧化碳当量（COe），SCC50实现了最低排放。我们的结果表明，如果通过将SCC水平降低至每毫升50,000个细胞相对于每毫升800,000个细胞的SCC水平来提高牛奶产量，那么农场的温室气体排放强度有潜力降低3.7%。得出结论认为，预防和/或控制亚临床型乳腺炎会相应减少农场单位产品的温室气体排放，通过减少牛奶损失、优化淘汰率以及降低饲料和其他可变成本，为奶农带来更高利润。我们建议有必要进一步研究探索多种疾病组合对排放强度的影响。
