Christian-Albrechts-University Kiel, Institute of Agricultural Engineering, 24098 Kiel, Germany.
J Dairy Sci. 2010 Feb;93(2):427-36. doi: 10.3168/jds.2009-2565.
Information about constituents of milk and visual alterations can be used for management support in improving mastitis detection, monitoring fertility and reproduction, and adapting individual diets. Numerous sensors that gather this information are either currently available or in development. Nevertheless, there is still a need to adapt these sensors to special requirements of on-farm utilization such as robustness, calibration and maintenance, costs, operating cycle duration, and high sensitivity and specificity. This paper provides an overview of available sensors, ongoing research, and areas of application for analysis of milk constituents. Currently, the recognition of abnormal milk and the control of udder health is achieved mainly by recording electrical conductivity and changes in milk color. Further indicators of inflammation were recently investigated either to satisfy the high specificity necessary for automatic separation of milk or to create reliable alarm lists. Likewise, milk composition, especially fat:protein ratio, milk urea nitrogen content, and concentration of ketone bodies, provides suitable information about energy and protein supply, roughage fraction in the diet, and metabolic imbalances in dairy cows. In this regard, future prospects are to use frequent on-farm measurements of milk constituents for short-term automatic nutritional management. Finally, measuring progesterone concentration in milk helps farmers detect ovulation, pregnancy, and infertility. Monitoring systems for on-farm or on-line analysis of milk composition are mostly based on infrared spectroscopy, optical methods, biosensors, or sensor arrays. Their calibration and maintenance requirements have to be checked thoroughly before they can be regularly implemented on dairy farms.
有关牛奶成分和视觉变化的信息可用于管理支持，以提高乳腺炎检测、监测繁殖力和繁殖能力以及调整个体饮食。目前有许多收集这些信息的传感器，要么已经可用，要么正在开发中。然而，仍然需要使这些传感器适应农场利用的特殊要求，如坚固性、校准和维护、成本、运行周期持续时间以及高灵敏度和特异性。本文概述了用于分析牛奶成分的现有传感器、正在进行的研究和应用领域。目前，异常牛奶的识别和乳房健康的控制主要通过记录电导率和牛奶颜色的变化来实现。最近，人们研究了进一步的炎症指标，要么是为了满足自动分离牛奶所需的高特异性，要么是为了创建可靠的报警列表。同样，牛奶成分，尤其是脂肪：蛋白质比、牛奶尿素氮含量和酮体浓度，为奶牛的能量和蛋白质供应、饮食中的粗饲料部分以及代谢失衡提供了合适的信息。在这方面，未来的前景是使用农场中频繁的牛奶成分测量来进行短期自动营养管理。最后，测量牛奶中的孕酮浓度有助于农民检测排卵、怀孕和不孕。用于农场或在线分析牛奶成分的监测系统大多基于红外光谱、光学方法、生物传感器或传感器阵列。在它们可以在奶牛场定期实施之前，必须仔细检查它们的校准和维护要求。
