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Relationships between odd- and branched-chain fatty acid profiles in milk and calculated enteric methane proportion for lactating dairy cattle

机译:泌乳奶牛的牛奶中奇数和支链脂肪酸谱与计算出的肠甲烷比例之间的关系

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The purpose of this study was to explore the relationships between odd- and branched-chain fatty acids (OBCFA) in milk with calculated enteric CH4 production for lactating dairy cows using multiple linear regression (MLR), partial least squares regression (PLS) and a genetic algorithm approach (GA). A dataset collected from 13 experiments containing 224 paired observations of measured acetate, propionate and butyrate proportions in rumen fluid VFA and 7 measured OBCFA was used. Methane proportion (mmol/mol VFA) was calculated from acetate, propionate and butyrate and expressed relative to the sum of these volatile fatty acids (VFA). Calculated CH4 production was related to milk OBCFA using MLR and PLS, resulting in a linear prediction model. The GA approach resulted in a model which predicted rumen VFA proportions of total VFA from milk OBCFA. Methane proportion was calculated from predicted acetate, propionate and butyrate proportions in total VFA based on rumen stoichiometry and compared with CH4 proportion calculated from measured VFA proportions. The prediction error was low (i.e., root mean square prediction error < 5%), and models captured up to 66% of the variance in the data and the concordance correlation coefficient was close to 0.8. The variance of the prediction error was less than 40% of the variance of the calculated CH4 proportion. Seven milk OBCFA were initially considered as predictors, from which the branched-fatty acids iso C14:0, iso C15:0, iso C16:0 were positively related to calculated enteric CH4 production and the odd-fatty acids C15:0 and the sum of C17:0 and C17:1 cis-9 were negatively related to it. Relationships in this large data set identify the most relevant OBCFA in milk as potential predictors of rumen methanogenesis.This paper is part of the special issue entitled: Greenhouse Gases in Animal Agriculture Finding a Balance between Food and Emissions. Guest Edited by T.A. McAllister, Section Guest Editors: K.A. Beauchemin, X. Hao, S. McGinn and Editor for Animal Feed Science and Technology, P.H. Robinson
机译:这项研究的目的是使用多重线性回归(MLR),偏最小二乘回归(PLS)和线性回归分析(MLR)和泌乳奶牛探索牛奶中奇数和支链脂肪酸(OBCFA)与计算出的肠内CH4产量之间的关系。遗传算法方法(GA)。使用从13个实验中收集的数据集,其中包含224对配对的瘤胃液VFA中的乙酸盐,丙酸盐和丁酸盐比例的测量值,以及7个测量的OBCFA。由乙酸盐,丙酸盐和丁酸盐计算甲烷比例(mmol / mol VFA),并相对于这些挥发性脂肪酸(VFA)的总和表示。使用MLR和PLS计算得出的CH4产量与牛奶OBBCA相关,从而产生线性预测模型。 GA方法产生了一个模型,该模型可以预测牛奶OBCFA中总VFA的瘤胃VFA比例。根据瘤胃化学计量从总VFA中预测的乙酸根,丙酸根和丁酸根的比例计算甲烷比例,并将其与从测量的VFA比例计算得到的CH4比例进行比较。预测误差很低(即均方根预测误差<5%),并且模型捕获了数据中高达66%的方差,并且一致性相关系数接近0.8。预测误差的方差小于所计算的CH4比例方差的40%。最初将七种牛奶OBCFA用作预测指标,从中预测支链脂肪酸iso C14:0,iso C15:0,iso C16:0与计算得出的肠CH4产生正相关,而奇数脂肪酸C15:0和总和C17:0和C17:1的顺式9与之负相关。大量数据之间的关系确定了牛奶中最相关的OBCFA可能是瘤胃甲烷生成的潜在预测因素。本文是《动物农业中的温室气体在食物与排放之间找到平衡》这一特刊的一部分。来宾由T.A.编辑麦卡利斯特(McAllister),客座编辑:K.A。 Beauchemin,X. Hao,S.McGinn和动物饲料科学与技术编辑,P.H。罗宾逊

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