Ryotaro Miura

The objectives of this study were (1) to investigate the distribution of large (≥10 mm) follicle numbers during the estrous cycle and (2) to compare the timing of the estrus expression period after the ovarian examination between cows with one large follicle (1F) and two or more large follicles (2F) with functional corpus luteum (CL) at the ovarian examination in lactating Holstein dairy cows. In experiment 1, we performed 393 ovarian examinations by ultrasonography, addressed the existence of CL (≥20 mm) and large follicle numbers, and classified cows into 1F (n = 229) and 2F (n = 164) groups. The 1F appearance rates were beyond 75% each day during 3 to 12 d after estrus. However, 2F appearance rates were beyond 75% each day during 15 to 24 d after estrus. In experiment 2, we performed 302 ovarian examinations by ultrasonography and classified cows into the 1F (n = 168) and 2F (n = 134) groups. Estrus detection was performed for 24 d after the ovarian examination in each cow. In the 2F group, 75% of estrus occurred within 9 d of the ovarian examination. However, 75% of estrus occurred 10 d after the ovarian examination in 1F. Days from the ovarian examination to estrus were significantly shorter in the 2F (6.0 d; median, 7.2 ± 4.0 d; mean ± SD) than in the 1F (13 d, 12.4 ± 4.3 d) group. In conclusion, focusing on ≥10 mm follicle numbers with CL could be useful for predicting the estrus expression period.

In this paper, we analyze body surface temperature data of cows, and detect for the calving phase of cows. Firstly, appropriate preprocessing is applied to waveforms for analysis. Specifically, the waveform to be analyzed is extracted from the cow's body surface temperature data, and next outlier in the body surface temperature data is removed. Secondly approximate waveforms based on Fourier series expansion are generated. Additionally, a nominal waveform which does not correspond to calving phase is reconstructed, and feature parameters are extracted from the nominal waveform. Finally, by using the Mahalanobis distance, the proposed detect system for calving phase is developed. Furthermore, the extraction range of the waveform to be analyzed is discussed, and we show the effectiveness of the proposed detection system.

The objectives of this study were to assess the sequential dynamics of the endometrial polymorphonuclear cells (PMN) after calving by endometrial cytology, and clarify the factors that cause prolonged endometrial inflammation in lactating dairy cows. A total of 33 lactating Holstein dairy cows were used from -4 to 8 wk relative to calving (0 wk: the calving week). Endometrial samples were obtained sequentially from 2 to 8 wk. Body condition score and backfat thickness were obtained weekly from -4 to 8 wk. Blood samples collected from -4 to 8 wk were analyzed for indicators of energy status, hepatic function, systemic inflammation, and calcium. Blood amino acids were measured at 2 wk. Daily milk production was determined between 5 and 65 d postpartum. Based on the sequential cytological analysis, the endometrial inflammation threshold was set at ≥5.0% PMN, and the median wk of PMN% lower than 5.0% was 4.5 wk in this study; therefore, we classified the cows into the early group (cows with endometrial inflammation converged within 4 wk: n = 17) and the late group (cows with endometrial inflammation converged at or after 5 wk: n = 16). There were no differences in daily milk production, energy status, hepatic function, blood calcium concentration, and systemic inflammatory response. The late group had lower body condition scores and backfat thickness during the experimental period, and a higher blood concentration of 3-methyl histidine, indicating muscle breakdown, was observed in the late group at 2 wk. Our findings indicated that the lack of body fat reservation during the peripartum period and the increased muscle breakdown after calving were risk factors for prolonged endometrial inflammation.