This study evaluates the effectiveness and financial impact of treating anoestrus dairy cows using a modified DO protocol. Among the 350 cows included in the study, 142 (40.6%) were identified as anoestrus. The average daily milk production, days in milk at artificial insemination (AI), number of AIs, and parity were 33.8 ± 6.8 kg, 152.6 ± 24.4 days, 1.3 ± 0.2 AIs, and 1.9 ± 0.8 lactations, respectively. To assess embryo survival in anoestrus dairy cows undergoing the modified DO protocol, two groups were established. The experimental group (E group, n = 74) received the GnRH agonist gonadorelin five days after TAI as part of the DO protocol. The control group (C group, n = 68) received only the DO protocol. The pregnancy rates and cumulative pregnancy rates were significantly higher in the E group (35.1% and 56.8%) compared with the C group (26.5% and 45.6%, p < 0.05). A binary logistic regression analysis indicated that the interaction between treatment and anoestrus status considerably affected the pregnancy rate (p < 0.001) and the occurrence of accessory corpus luteum (aCL, p < 0.0001). The UW-DairyRepro$ decision support tool utilized in this study, indicated that implementing this approach could increase the net present value (NPV) by USD 54.2/anoestrus cow/year.

Sensor technology in dairy farming has revolutionized animal management by increasing productivity, health monitoring, and overall farm efficiency. However, integrating sensor data from multiple devices and brands poses considerable challenges. This article delves into the major challenges that dairy farmers encounter when using various sensor technologies, such as data compatibility, interoperability, standardization, data security, and data management problems. It also covers prospective solutions, such as standardizing data, harmonization efforts, and enhanced data integration approaches. Addressing the aforementioned challenges is a cornerstone for fully harnessing the potential of sensor technology in the dairy industry.