Improving nutrition efficiency and milk quality in dairy production

牛奶是最有营养的单一食物，也是英国饮食中饱和脂肪酸（SFA）的主要提供者。某些SFA可能会增加心血管疾病（CVD）的风险，卫生组织已紧急建议用顺式不饱和FA（乌法）替代膳食SFA，以减少CVD相关疾病。牛奶是人类饮食中脂肪酸（FA）的主要单一来源，生产具有更多乌法和更少SFA的牛奶有助于实现这一目标，而不需要改变消费者的饮食习惯。此外，全球对牛奶和乳制品的需求不断增长，以及对食品、饲料和燃料资源的竞争，要求在乳制品生产的各个方面最佳利用资源。提高饲料利用效率（FUE;每给定的饲料摄入量更多的牛奶）和能量利用效率（埃厄;更高的摄入能量保留在体内的百分比）增加农场的盈利能力（降低饲养成本）并减少牛奶生产的环境足迹（降低甲烷排放）。因此，开发双赢的管理方案，同时提高效率和牛奶营养质量，对于未来的可持续发展和改善消费者对乳制品行业的看法至关重要。因此，拟议计划的目的是确定动物、饮食和管理因素，以提高奶牛的FUE和埃厄，并提高牛奶的营养质量。这将通过以下研究来实现：1）调查主要膳食参数对FUE，NUE和甲烷排放的影响及其相互作用。将从现有数据（URE、AFBI）中开发一个包含>100项奶牛代谢研究的数据集，并使用已发表的数据进行增强，使用的研究最好包含与饮食、动物、饲料摄入量、生产、能量摄入/输出和甲烷排放相关的变量。采用线性混合效应模型的方差分析将评估养分参数对肥料利用率、埃厄和甲烷排放量的影响。多变量冗余分析（RDA）将评估相对影响，并以图形方式表示饮食参数之间的关系，以及它们对FUE、埃厄、甲烷排放和牛奶质量的反应。2)调查畜牧业实践（育种，饲养，管理）对FUE和牛奶营养质量在牛群水平的相对影响。2019年1月至12月进行了一项农场调查，包括25个有机农场和45个传统农场（URE）。本研究每月从农场的大罐收集牛奶样本，并通过农民问卷记录饲养实践和生产变量（牛奶产量，基本成分，FUE）。在拟议的方案期间，将通过气相色谱法分析牛奶样品的FA概况。ANOVA LME将评估生产系统（有机、常规）和系统内养殖群体（例如，高放牧与低放牧）对FUE和牛奶质量的影响。将进行RDA以评估相对影响，并以图形方式表示饲养参数之间的关系，以及它们对FUE、生产力和牛奶质量的反应。3)揭示了在不同日粮条件下，瘤胃微生物如何影响与FUE、埃厄、甲烷排放和乳品质相关的代谢途径。将在AFBI中对12头泌乳奶牛进行实验，采用3（日粮）× 3（周期）拉丁方设计，使用含白色三叶草的三种不同日粮。在每个阶段，奶牛将在隔间中饲养21天，然后在间接开路呼吸热量计室中饲养最后7天，以测量摄食量、产奶量、尿/粪便排出量、气体交换（O2、CO2和CH 4）并收集瘤胃液和乳汁样本。本研究将利用乳/瘤胃FA谱（URE）和宏基因组学技术（QUB）来鉴定促进FUE、埃厄和乳品质的瘤胃微生物及其基因。通过500 MHz NMR（URE）分析瘤胃液和乳中的代谢产物谱，将突出与代谢途径相关的代谢产物谱。

Milk is the most nutritious single food but also a major provider of saturated fatty acids (SFA) in the UK diets. Certain SFA may increase risk of cardiovascular disease (CVD), and health organisations have urgently recommended substitution of dietary SFA with cis-unsaturated FA (UFA), to reduce CVD-related illness. Producing milk, the main single source of fatty acids (FA) in human diets, with more UFA and less SFA couldcontribute to this aim without requiring changes to consumer dietary habits. Additionally, the increasing global demand for milk and dairy products, and the competition for resources for food, feed and fuel require optimum use of resources in all aspects of dairy production. Improving feed use efficiency (FUE; more milk per given feed intake) and energy use efficiency (EUE; higher % of ingested energy retained inthe body) increase farm profitability (lower feeding costs) and reduce environmental footprint (lower methane emissions) of milk production. Therefore, developing win-win management scenarios that simultaneously improve efficiency and milk nutritional quality are of paramount importance for future sustainability, and improving consumer perception, of the dairy sector. The aim of the proposed programme is therefore to identify the animal, dietary, and management factors that improve FUE and EUE in dairy cows and enhance the nutritional quality of milk. This will be achieved via the following studies:1) Investigate the effects of, and interactions between, the main dietary parameters on FUE, NUE and methane emissions. A dataset of >100 cow metabolism studies, will be developed from existing data (URE, AFBI), and enhanced with published data, using studies that preferably contain variables related to diet, animal, feed intake, production, energy intake/outputs, and methane emissions. Analysis of variance (ANOVA) using linear mixed effects models (LME) will assess the effect of nutrient parameters on FUE, EUE and methane emissions. Multivariate redundancy analyses (RDA) will assess the relative impact and graphically represent relationships between dietary parameters, and the responses they evoke on FUE, EUE, methane emissions and milk quality. 2) Investigate the relative impact of husbandry practices (breeding, feeding, management) on FUE and milk nutritional quality at herd level. A farm survey including 25 organic and 45 conventional farms was conducted January-December 2019 (URE). This study collected monthly milk samples from farms' bulk-tank and recorded husbandry practices and production variables (milk yield, basic composition, FUE) via farmers' questionnaires. During the proposed programme, milk samples will be analysed for FA profiles by gas chromatography. ANOVA LME will assess the effect of production system (organic, conventional) and within-system husbandry-groups (e.g. high-grazing vs lowgrazing) on FUE and milk quality. RDA will be performed to assess the relative impact and graphically represent the relationships between husbandry parameters, and the responses they evoke on FUE, productivity and milk quality. 3) Reveal how rumen microbes influence metabolic pathways related to FUE, EUE, methane emissions and milk quality under different dairy diets. An experiment with 12 lactating dairy cows will be performed in AFBI, using three different diets containing white clover under a 3(diets)x3(periods) Latin-Square design. In each period, cows will be housed in cubicle accommodation for 21 days and then in indirect open-circuit respiration calorimeter chambers for the final 7 days, to measure feed intakes, milk production, urine/faeces output, gaseous exchange (O2, CO2 and CH4) and collect rumen fluid and milk samples. Milk/rumen FA profiling (URE) and metagenomics techniques (QUB) will be used to identify rumen microbes, and their genes, which promote FUE, EUE and milk quality. The metabolite profile in rumen fluid and milk, by 500MHz NMR (URE), will highlight the metabolic pathways related