Suppr超能文献

应用漫反射近红外光谱技术在线分析牛奶成分的准确性。

Accuracy of in-line milk composition analysis with diffuse reflectance near-infrared spectroscopy.

机构信息

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

出版信息

J Dairy Sci. 2012 Nov;95(11):6465-76. doi: 10.3168/jds.2012-5388. Epub 2012 Sep 7.

Abstract

Knowledge of daily milk composition changes can assist in monitoring dairy cow health and can help to detect nutritional imbalances. An analytical tool offering the possibility of analyzing milk during the daily milking routine would provide such information. Near-infrared (NIR) spectroscopy can analyze multiple constituents in a given substrate at the same time. In this study, a special NIR in-line milk-analyzing device was designed, and its ability to predict the contents of fat, protein, lactose, and urea and the somatic cell count in milk during the milking process was evaluated. The NIR spectra were acquired with a diode array spectrometer in diffuse reflection in the wavelength range 851 to 1649 nm. The spectra originated from a total of 785 partial milkings out of 84 composite milkings. Corresponding subsamples of the composite milkings were used for reference analysis (n=785). Excellent validation results were obtained with regard to the coefficients of determination (R(2)=0.99, 0.98, and 0.92), and standard errors of prediction (0.09, 0.05, and 0.06) for fat (%), protein (%), and lactose (%), respectively. Satisfying results were achieved for urea content (mg/L) and logarithmically transformed SCC in milk, with R(2) of 0.82 and 0.85 and standard errors of prediction of 19.3 and 0.18, respectively. The accuracy of predicting protein, lactose, and urea contents was in accordance with international recommendations for reproducibility specified for in-line analytical devices.

摘要

对日常牛奶成分变化的了解有助于监测奶牛的健康状况,并有助于发现营养失衡。一种能够在日常挤奶过程中分析牛奶的分析工具可以提供这些信息。近红外(NIR)光谱学可以同时分析给定基质中的多种成分。在这项研究中,设计了一种特殊的 NIR 在线牛奶分析装置,并评估了其在挤奶过程中预测牛奶中脂肪、蛋白质、乳糖和尿素含量以及体细胞计数的能力。NIR 光谱是在漫反射中使用二极管阵列分光光度计在 851 到 1649nm 的波长范围内获得的。这些光谱来自总共 785 次部分挤奶中的 84 次复合挤奶。复合挤奶的相应副样用于参考分析(n=785)。对于脂肪(%)、蛋白质(%)和乳糖(%),得到了出色的验证结果,决定系数(R(2)=0.99、0.98 和 0.92)和预测标准误差(0.09、0.05 和 0.06)分别为 0.99、0.98 和 0.92。对于牛奶中的尿素含量(mg/L)和对数转换的体细胞计数,也获得了令人满意的结果,R(2)分别为 0.82 和 0.85,预测标准误差分别为 19.3 和 0.18。预测蛋白质、乳糖和尿素含量的准确性符合国际上对在线分析装置再现性的建议。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验