Prediction of 24-hour milk yield and composition in dairy cows from a single part-day yield and sample

IF 0.9 4区农林科学 Q3 AGRICULTURE, MULTIDISCIPLINARY

Irish Journal of Agricultural and Food Research Pub Date : 2019-01-01 DOI:10.2478/ijafr-2019-0007

S. McParland, B. Coughlan, B. Enright, M. O'keeffe, R. O’Connor, L. Feeney, D. Berry

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引用次数: 4

Abstract

Abstract The objective was to evaluate the accuracy of predicting 24-hour milk yield and composition from a single morning (AM) or evening (PM) milk weight and composition. A calibration dataset of 37,481 test-day records with both AM and PM yields and composition was used to generate the prediction equations; equations were validated using 4,644 test-day records. Prediction models were developed within stage of lactation and parity while accounting for the inter-milking time interval. The mean correlation between the predicted 24-hour yields and composition of milk, fat and protein and the respective actual values was 0.97 when based on just an AM milk yield and composition with a mean correlation of 0.95 when based on just a PM milk yield and composition. The regression of predicted 24-hour yield and composition on the respective actual values varied from 0.97 to 1.01 with the exception of 24-hour fat percentage predicted from a PM sample (1.06). A single AM sample is useful to predict 24-hour milk yield and composition when the milking interval is known.

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从单日产量和样本预测奶牛24小时产奶量和成分

摘要目的是评估从一个上午（AM）或晚上（PM）的牛奶重量和成分预测24小时产奶量和成分的准确性。使用37481个测试日记录的校准数据集，包括AM和PM产量和成分，以生成预测方程；使用4644个测试日记录对方程进行了验证。预测模型是在哺乳期和产程内建立的，同时考虑了挤奶间隔时间。当仅基于AM牛奶产量和成分时，预测的24小时产量和牛奶、脂肪和蛋白质的成分与各自的实际值之间的平均相关性为0.97，而当仅基于PM牛奶产量和组成时，平均相关性为0.95。预测的24小时产量和成分与各自实际值的回归从0.97到1.01不等，PM样本预测的24 h脂肪百分比除外（1.06）。当挤奶间隔已知时，单个AM样本可用于预测24 h产奶量和成分。

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来源期刊

Irish Journal of Agricultural and Food Research 农林科学-农业综合

CiteScore

2.50

自引率

20.00%

发文量

审稿时长

>36 weeks

期刊介绍： The Irish Journal of Agricultural and Food Research is a peer reviewed open access scientific journal published by Teagasc (Agriculture and Food Development Authority, Ireland). Manuscripts on any aspect of research of direct relevance to Irish agriculture and food production, including plant and animal sciences, food science, agri environmental science, soils, engineering, buildings, economics and sociology, will be considered for publication. The work must demonstrate novelty and relevance to the field of research. Papers published or offered for publication elsewhere will not be considered, but the publication of an abstract does not preclude the publication of the full paper in this journal.