Invited review: Contribution of milk harvesting research to optimal interaction between biology and milking technology

The broad focus of this review is on milk harvesting in machine-milked herds. With particular emphasis on: (1) milk secretion and storage dynamics in the udder, (2) milk ejection, (3) milk flow profiles and their effect on milking efficiency, (5) immunological activity and milking efficiency, (5) milking machine aspects of milk removal, and (6) the future potential of milking technology. Machine milking has evolved from its early mechanical beginnings into a technologically advanced, data-driven process that must balance speed, chosen completeness, and gentleness on teat tissue to support efficient milk removal and optimal udder health. This review summarizes the current understanding of milk harvesting from a physiological, mechanical, and managerial perspective and outlines the key factors shaping its future development. Fundamentally, milk harvesting is built upon a biological sequence involving milk synthesis, ejection, and removal. Milk synthesis occurs at the alveolar level and is influenced by local quarter-specific physiology. Milk ejection is driven by the oxytocin-mediated contraction of myoepithelial cells, a process sensitive to the degree of udder filling, familiarity with the milking environment, and cow-operator interactions. Milk flow profiles, shaped by these biological processes, provide crucial insights into milking efficiency and udder health outcomes. At the machine level, key variables include milking vacuum, pulsation characteristics, liner properties, and teatcup removal strategies. Optimal settings for each of these parameters depend on dynamic interactions with cow physiology and milking stage. Recent research highlights the need to consider these factors not in isolation but as part of an integrated milking system, where vacuum, pulsation, liner design, and timing of teatcup removal interact to affect milking speed, teat condition, and udder health. Automation of milking systems and indeed automated milking systems have driven a shift toward individualized milking at the quarter level, enabling more precise control of extraction timing and flow rate. The integration of real-time sensor data, machine learning, and adaptive milking parameters represents a major step forward in the optimization of milking systems. In the near future, distinctions between automated milking systems and conventional systems will become increasingly blurred, as both adopt automation and intelligent controls tailored to individual cows and quarters. This review also explores the role of immunological activity in shaping milking efficiency. Elevated SCC has been associated with altered milk flow curves and decreased productivity. There is emerging evidence suggesting that modern selection and management strategies may reduce the historical link between fast milking and mastitis risk. This relationship remains complex and context dependent. The detection and management of abnormal milk (supported by more advanced inline sensor systems) is expected to become a cornerstone of future milking technology. Looking forward, the drivers of change in milk harvesting will include labor availability, economic pressures, environmental concerns, animal health, and consumer expectations. A new era of biologically aware, data-informed, and precision-engineered milking systems is emerging. These systems will support the gentle, efficient removal of milk to a user-defined end point, tailored to each animal and each milking event.