首页> 外文期刊>Journal of dairy research >Accuracy and application of milk fatty acid estimation with diffuse reflectance near-infrared spectroscopy
【24h】

Accuracy and application of milk fatty acid estimation with diffuse reflectance near-infrared spectroscopy

机译:漫反射近红外光谱法测定牛奶脂肪酸的准确性和应用

获取原文
获取原文并翻译 | 示例
           

摘要

Near infrared spectroscopy (NIRS) has the potential to estimate contents of fatty acids (FA) in milk frequently at-farm or during daily milking routine. In this study, a total of 738 raw milk spectra collected from 33 Holstein cows over a period of 30 weeks were recorded. Reference data on FA composition in milk and in milk fat were analysed in laboratory. Calibration models were calculated for single FA and groups of FA in milk and in milk fat. Validation resulted in sufficient Ratio of Prediction to Deviation (RPD) values for some single FA and in higher RPD values for groups of FA when concentrations of FA in milk were predicted. Since the concentrations of most FA in milk are highly correlated with milk fat content, the prediction of FA contents in milk fat is more meaningful when independent predictions are intended. The accuracy of predicting single FA concentrations in milk fat is rather poor for most FA but still comparable to alternative analysing methods such as MIR analysis. The estimation of different groups of FA in milk fat resulted in an improved accuracy based on higher RPD values, which was sufficient to mirror the development in the different lactation phases. The course of cow individual long chain fatty acid (LCFA) concentration in the early lactation stage can be an indicator for body fat mobilisation. The accurate estimation of the extent and duration of body fat mobilisation in cow individuals was rather difficult with NIR predicted LCFA concentrations and would require a higher measuring frequency than applied in this study.
机译:近红外光谱法(NIRS)可以估计农场或日常挤奶过程中经常出现的牛奶中脂肪酸(FA)的含量。在这项研究中,记录了在30周内从33头荷斯坦奶牛收集的738张原始奶谱。在实验室中分析了牛奶和乳脂中脂肪酸成分的参考数据。计算牛奶和乳脂中单个FA和FA组的校准模型。当预测牛奶中的FA浓度时,对于某些单个FA而言,验证会产生足够的预测偏差与偏差(RPD)值,对于FA组,则会产生更高的RPD值。由于牛奶中大多数FA的浓度与乳脂含量高度相关,因此,当需要进行独立预测时,对乳脂中FA含量的预测更有意义。对于大多数脂肪酸,预测乳脂中单一脂肪酸浓度的准确性相当差,但仍可与替代分析方法(如MIR分析)相比。基于较高的RPD值,对乳脂中FA的不同组的估计可以提高准确性,这足以反映出不同泌乳阶段的发育情况。泌乳早期奶牛个体长链脂肪酸(LCFA)浓度的变化过程可能是人体脂肪动员的指标。用NIR预测的LCFA浓度很难准确估计牛体内脂肪运动的程度和持续时间,并且需要比本研究中应用的频率更高的测量频率。

著录项

  • 来源
    《Journal of dairy research》 |2018年第2期|212-221|共10页
  • 作者单位

    Institute of Agricultural Engineering, Christian-Albrechts-University Kiel, 24098 Kiel, Germany;

    Institute of Animal Nutrition and Physiology, Christian-Albrechts-University Kiel, 24098 Kiel, Germany;

    Institute of Agricultural Engineering, Christian-Albrechts-University Kiel, 24098 Kiel, Germany;

    Department of Safety and Quality of Milk and Fish Products, Max Rubner-lnstitute, 24103 Kiel, Germany;

    Institute of Animal Nutrition and Physiology, Christian-Albrechts-University Kiel, 24098 Kiel, Germany;

    Institute of Agricultural Engineering, Christian-Albrechts-University Kiel, 24098 Kiel, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    NIRS; milk analysis; body fat mobilisation; long chain fatty acids;

    机译:NIRS;牛奶分析;动员体内脂肪;长链脂肪酸;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号