...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of dairy science >Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk
【24h】

Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk

机译：使用牛奶的中红外光谱对丹麦泌乳奶牛的剩余饲料摄入量和干物质摄入量进行预测和验证

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24 kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R~2 increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83 kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R~2 = 0.30 and RMSEP = 2.91 kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R~2 increased to 0.81 and RMSEP decreased to 1.49 kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R~2 = 0.46 and RMSEP = 1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region.
机译：本研究探讨了傅立叶变换中红外（FT-IR）光谱图作为干物质摄入量（DMI）和残留饲料摄入量（RFI）的预测指标的有效性。偏最小二乘回归方法用于建立预测模型。使用不同的外部测试集对模型进行了验证，一个随机删除了20％的记录（验证A），第二个随机删除了20％的奶牛（验证B），第三个（对于DMI预测模型）随机删除了一头母牛（验证C）。数据包括来自140头母牛的1,044条记录； 97名是丹麦霍尔斯坦，43名是丹麦球衣。结果显示，与其他验证方法相比，验证A的准确性更高。牛奶产量（MY）在DMI预测中起很大作用； MY解释了59％的变化，验证的模型误差预测均方根误差（RMSEP）为2.24 kg。通过添加活重（LW）作为附加的预测性状对模型进行了改进，其中精度R〜2从0.59增大到0.72，误差RMSEP从2.24 kg减小到1.83 kg。当仅将牛奶的FT-IR光谱图用于DMI预测时，获得的预测能力较低，R〜2 = 0.30，RMSEP = 2.91 kg。但是，一旦添加了光谱信息，再加上MY和LW作为预测因子，模型精度就会提高，R〜2增加到0.81，RMSEP减少到1.49 kg。 RFI的预测准确性在整个泌乳期都会发生变化。与哺乳期或泌乳中期和晚期相比，泌乳早期的RFI预测模型更好，R〜2 = 0.46，RMSEP = 1.70。有助于DMI和RFI预测模型的最重要的光谱波数包括脂肪，蛋白质和乳糖峰。当使用红外预测的脂肪，蛋白质和乳糖代替全光谱时，获得了可比的预测结果，表明FT-IR光谱数据并未添加可改善DMI和RFI预测模型的重要新信息。因此，实际上，如果未存储完整的FT-IR光谱数据，则可以基于标准牛奶控制数据获得相似的DMI或RFI预测结果。对于DMI，牛奶脂肪区域是牛奶光谱的主要变化原因。对于RFI，牛奶光谱的主要变化是在牛奶蛋白质区域内。

著录项

  • 来源
    《Journal of dairy science》 |2017年第1期|253-264|共12页
  • 作者

    N. Shetty; P. Lovendahl; M. S. Lund; A. J. Buitenhuis;

  • 作者单位

    Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, DK 8830 Tjele, Denmark;

    Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, DK 8830 Tjele, Denmark;

    Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, DK 8830 Tjele, Denmark;

    Department of Molecular Biology and Genetics, Center for Quantitative Genetics and Genomics, Aarhus University, DK 8830 Tjele, Denmark;

  • 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

    dry matter intake; residual feed intake; spectroscopy; prediction; validation;

    机译：干物质摄入量;剩余饲料摄入量;光谱学预测;验证;

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