Kaniyamattam K, De Vries A
Department of Animal Sciences, University of Florida, Gainesville 32611.
Department of Animal Sciences, University of Florida, Gainesville 32611.
J Dairy Sci. 2014 May;97(5):2896-908. doi: 10.3168/jds.2013-7690. Epub 2014 Mar 13.
The objective of this study was to quantify the agreement between AfiLab real-time milk analyzer (Afimilk, Kibbutz Afikim, Israel) measures for fat, protein, and lactose based on near-infrared spectrum light scattering, and those collected on Dairy Herd Improvement Association (DHIA) test days and measured with the Bentley 2000 analyzer (Bentley Instruments Inc., Chaska, MN), which uses mid-infrared spectrum light. The AfiLab data were collected twice daily for each milking cow in the herd at 12-h intervals from the double-12 parlor at the University of Florida Dairy Unit (Hague, FL) from January 2010 to December 2011. Bentley data for the 23 DHIA test days in 2010 and 2011 were also obtained. Approximately 450 cows were tested each month. Tested milk was collected during 1 milking each month, alternating monthly between morning and evening milkings. AfiLab data were matched with Bentley fat and protein (n=10,273; 23 test days) and lactose (n=6,741; 16 test days). Overall means ± standard deviations (SD) of monthly mean Bentley fat, protein, and lactose were 3.74 ± 0.80%, 3.06 ± 0.37%, and 4.76 ± 0.30%, respectively. Overall means ± SD of monthly mean AfiLab minus Bentley observations were -0.08 ± 0.12 percentage points (PP) for fat (n=23), 0.02 ± 0.11 PP for protein (n=23), and -0.02 ± 0.08 PP for lactose (n=16). Overall means ± SD of monthly within-test-day SD of AfiLab minus Bentley observations were 0.66 ± 0.11 PP for fat, 0.27 ± 0.03 PP for protein, and 0.26 ± 0.03 PP for lactose. Overall means ± SD of the corresponding monthly correlations were 0.59 ± 0.09 for fat, 0.67 ± 0.04 for protein, and 0.46 ± 0.08 for lactose. Averaging the AfiLab observations from up to 6 milkings before and after the test-day milking improved the agreement for protein and lactose but not for fat. Averaging the 13 protein observations improved the mean difference to 0.01 ± 0.10 PP and the SD of the difference to 0.23 ± 0.03 PP. The correlation increased to 0.78 ± 0.04. Averaging the 13 lactose observations improved the SD of the difference to 0.23 ± 0.02 PP, but the mean of the difference decreased to -0.03 ± 0.09 PP. The correlation for lactose increased to 0.55 ± 0.05. Generally, AfiLab slightly overestimated low Bentley components and underestimated high Bentley components. We found some evidence for a systematic cow effect on lack of agreement for lactose, but not for fat and protein. The agreement between AfiLab and Bentley observations was better for protein and lactose than that for fat. Combinations of AfiLab observations from various milkings improved the agreement for protein and lactose. AfiLab real-time milk analyzers may be helpful to estimate DHIA observations.
本研究的目的是量化基于近红外光谱光散射的AfiLab实时牛奶分析仪（以色列阿菲基姆基布兹的Afimilk公司）对脂肪、蛋白质和乳糖的测量结果，与奶牛改良协会（DHIA）检测日采集并使用中红外光谱光的Bentley 2000分析仪（明尼苏达州查斯卡的Bentley Instruments Inc.公司）测量的结果之间的一致性。2010年1月至2011年12月期间，在佛罗里达大学奶牛场（佛罗里达州黑格）的双12挤奶厅，每隔12小时对牛群中的每头奶牛每天采集两次AfiLab数据。还获取了2010年和2011年23个DHIA检测日的Bentley数据。每月约有450头奶牛接受检测。每月在一次挤奶过程中采集检测用牛奶，早晚挤奶交替进行。将AfiLab数据与Bentley的脂肪和蛋白质数据（n = 10,273；23个检测日）以及乳糖数据（n = 6,741；16个检测日）进行匹配。Bentley每月平均脂肪、蛋白质和乳糖的总体均值±标准差（SD）分别为3.74 ± 0.80%、3.06 ± 0.37%和4.76 ± 0.30%。AfiLab减去Bentley观测值的每月总体均值±SD，脂肪为 -0.08 ± 0.12个百分点（PP）（n = 23），蛋白质为0.02 ± 0.11 PP（n = 23），乳糖为 -0.02 ± 0.08 PP（n = 16）。AfiLab减去Bentley观测值的每月日内SD的总体均值±SD，脂肪为0.66 ± 0.11 PP，蛋白质为0.27 ± 0.03 PP，乳糖为0.26 ± 0.03 PP。相应每月相关性的总体均值±SD，脂肪为0.59 ± 0.09，蛋白质为0.67 ± 0.04，乳糖为0.46 ± 0.08。对检测日挤奶前后最多6次挤奶的AfiLab观测值进行平均，可改善蛋白质和乳糖的一致性，但对脂肪无效。对13个蛋白质观测值进行平均，可使平均差值改善至0.01 ± 0.10 PP，差值的SD改善至0.23 ± 0.03 PP。相关性提高到0.78 ± 0.04。对13个乳糖观测值进行平均，可使差值的SD改善至0.23 ± 0.02 PP，但差值的均值降至 -0.03 ± 0.09 PP。乳糖的相关性提高到0.55 ± 0.05。一般来说，AfiLab对低Bentley成分略有高估，对高Bentley成分略有低估。我们发现有一些证据表明，奶牛对乳糖一致性的影响具有系统性，但对脂肪和蛋白质没有。AfiLab和Bentley观测值之间蛋白质和乳糖的一致性比对脂肪的更好。对来自不同挤奶的AfiLab观测值进行组合，可改善蛋白质和乳糖的一致性。AfiLab实时牛奶分析仪可能有助于估计DHIA的观测值。
