Economic success in dairy herds is heavily reliant on obtaining pregnancies at an early stage of lactation. Our objective in this study was to attempt to predict the likelihood of conception occurring by d 100 and 150 of lactation (days in milk, DIM) by Markov chain Monte Carlo analysis using test day milk recording data and reproductive records gathered retrospectively from 8,750 cows from 33 dairy herds located in the United Kingdom. Overall, 65% of cows recalved with 30, 46, and 65% of cows conceiving by 100 DIM, 150 DIM, and beyond 150 DIM, respectively. Overall conception rate (total cows pregnant/total number of inseminations) was 27.47%. Median and mean calving to conception intervals were 123 and 105 d, respectively. The probability of conception by both 100 DIM and 150 DIM was positively associated with the average daily milk weight produced during the fourth week of lactation (W4MK) and protein percentage for test day samples collected between 0 to 30 and 31 to 60 DIM. Butterfat percentage at 0 to 30 DIM was negatively associated with the probability of conception by 100 DIM but not at 150 DIM. High somatic cell count (SCC) at both 0 to 30 and 31 to 60 DIM was negatively associated with the probability of conception by 100 DIM, whereas high SCC at 31 to 60 DIM was associated with a reduced probability of conception by 150 DIM. Increasing parity was associated with a reduced odds of pregnancy. Posterior predictions of the likelihood of conception for cows categorized as having "good" (W4MK >30kg and protein percentage at 0 to 30 and 31 to 60 DIM >3.2%) or "poor" (W4MK <25kg and protein percentage at 0 to 30 and 31 to 60 DIM <3.0%) early lactation attributes with actual observed values indicated model fit was good. The predicted likelihood of a "good" cow conceiving by 100 and 150 DIM was 0.39 and 0.57, respectively (actual observed values 0.40 and 0.59). The corresponding values for a "poor" cow were 0.28 and 0.42 (actual observed values 0.26 and 0.37). Predictions of the future reproductive success of cows may be possible using a limited number of early lactation attributes.

Accurately estimating forage biomass is essential for understanding the nutritional value of vegetation communities for wild herbivores. However, clipping, drying, and weighing vegetation by species requires substantial labor, which restricts the size and number of plots that can be sampled over a large geographical area. Labor‐intensive sampling effort can be reduced by using a double sampling strategy that pairs visual estimates of horizontal cover of vegetation with a subset of clipped plots to create equations that convert horizontal cover to biomass. However, sampling strategy and environmental covariates have rarely been considered when developing cover‐biomass equations. We evaluated environmental and sampling factors that could affect the cover‐biomass relationship using 3,404 cover‐biomass pairs measured in the Clearwater River Basin in North‐central Idaho, USA, collected from May 31–October 4 in 2016 and 2017. Our study demonstrated that when carefully applied, double sampling techniques can streamline field sampling while providing cover‐biomass conversion equations with moderate to high predictive ability (pseudo R ² = 0.25–0.99, = 0.70) for both biomass of current annual growth and high‐quality (e.g., leaves of shrubs) portion of plants (pseudo R ² = 0.65–1). Based on our results, we recommend comparing fit and predictive ability of regression types (linear, log‐linear, Gamma) and collecting >20 cover‐biomass pairs spanning a wide range of horizontal cover (1 to >50%) for each plant species. We found that accounting for overstory canopy cover and season through interaction terms improved the fit of equations by as much as 20% for over half of the 81 species‐specific and 12 structure groups. We found a modest degree of observer bias; thus, training should reduce observer bias and improve consistency but may not alleviate inconsistencies among studies. Careful classification of plant species into plant structure groups can reduce the number of equations, but species‐specific equations for the most abundant and objectively relevant plant species should be developed.

The purpose of this study was to evaluate the effect of rumination times and days spent in a close-up group before calving (DCU) on early-lactation health and reproductive outcomes in dairy cows. Data were gathered for 719 cows located in a single herd. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk; DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever, and displaced abomasum. Rumination times for each cow were downloaded daily from the herd's automated collar system used to generate heat and health alerts for each cow beginning at 21 d precalving until 14 d postcalving. During the first 30 DIM, 121 cows (18%) developed at least 1 disease-any combination of ketosis (40 cows, 5.9% of total), mastitis (17 cows, 2.5%), metritis (75 cows, 11%), milk fever (17 cows, 2.5%), or displaced abomasum (28 cows, 4.1%); 305 cows (45%) were pregnant again at 100 DIM, and an additional 139 cows (20%) were pregnant at 150 DIM. Principal component analysis was used to determine the relationship between gestation length and DCU and their association with the odds of developing disease in early lactation. We did not find any significant association between precalving rumination time and disease within the first 30 DIM. Higher rumination time in the week before calving was shown to be strongly linked to a shorter time to subsequent pregnancy, whereas rumination times postcalving were not associated with changes in the time to pregnancy. Principal component analysis showed that a curvilinear combination of gestation length and DCU (principal component 1) was significantly associated with changes in disease incidence in the first 30 DIM. Gestation length and time spent in close up are important management factors in reducing the incidence of disease in early lactation, and rumination times around calving may help predict future reproductive outcomes.

The plasma potential and the electron density and electron temperature of an rf magnetron discharge used for the ion‐assisted growth of PbTe epilayers on BaF₂ are measured using Langmuir probe diagnostics. The effect of rf potentials at the probe on the measured plasma parameters is reduced by driving the probe to follow the plasma potential. The discharge parameters are determined as a function of substrate bias voltage and substrate rf power. The ion energy and flux necessary for the epitaxial growth of (111) PbTe on (111) BaF₂ are determined.

Background: The aim of this study was to investigate the risk factors for and the impact of ultrasound‐diagnosed endometritis (UDE) on lactating dairy cows’ reproductive performance. Methods: Data were analysed from 1123 Holstein and Holstein‐Friesian cows from two Scottish dairy farms. A reproductive ultrasound examination was conducted on two occasions, at 43 ± 3 and 50 ± 3 days in milk (DIM), to screen for hyperechoic fluid in the uterus. Statistical analyses were performed using multivariable logistic regression modelling and Cox proportional hazards models. Results: The overall incidence of UDE was 8.8% (99/1123). Risk factors for UDE included calving during autumn/winter seasons, increased parity and the presence of two or more diseases in the first 50 ± 3 days postpartum. The presence of UDE was associated with a reduced odds of pregnancy after all artificial inseminations up to 150 DIM. Limitations: The retrospective design of this study led to some inherent limitations with the quality and quantity of data collected. Conclusions: The findings of this study indicate which risk factors should be monitored in postpartum dairy cows to limit the impact of UDE on future reproductive performance.

Understanding of the social environment has the potential to benefit dairy cow welfare and production. Our aim was to evaluate the associations of stocking density, calving density, days spent in a pre-partum group before calving (days spent in close-up, DCU) and the number of days from a pen filling event (addition of new cows to the pre-partum pen) on early-lactation health, production, pregnancy and culling outcomes in dairy cows. Data were gathered from 2780 cows in 2 herds. Herd management and reproductive records were analyzed for cows receiving treatment in the first 30 d of lactation (days in milk, DIM) for clinical mastitis, reproductive tract disease, ketosis, milk fever and displaced abomasum. Principal component analysis was used to account for the relationship between gestation length (GL) and DCU and their association with early lactation disease, milk production, pregnancy and culling outcomes. The effect of stocking density, the number of days from a pen filling event to calving and the calving density experienced by a cow in her week of calving was also evaluated. Causal inference was used to correct for confounding bias due to farm identity. The odds of disease in the first 30 DIM increased with stocking density before calving. A quadratic association was found between the first principal component (PC1), representing the combined effect of GL and DCU, and the odds of disease in multiparous cows only. Early lactation milk production and 305 d milk production in multiparous cows increased with PC1 score. Quadratic relationships were found between stocking density at d 8 to 2 before calving with both early lactation and 305 d milk production in multiparous cows but no associations were found in primiparous cows. Calving density showed a quadratic association with 305 d milk production in primiparous cows. The number of days from the last pen filling event to calving was not associated with changes in milk production. Disease occurrence was negatively associated with both early lactation and 305 d milk yield in multiparous cows but only with early lactation milk production in primiparous cows. The occurrence of disease was associated with a delayed time to pregnancy only in primiparous cows while both disease and being in lactation group ≥ 3 were negatively associated with time to pregnancy in multiparous cows. Week 4 milk (W4MK) was positively associated with reduced time to pregnancy in multiparous cows. For primiparous cows, increasing age at calving was associated with increased culling risk, while being in lactation group ≥ 3 was associated with increased culling risk in multiparous cows. Culling risk decreased with increasing W4MK in all cows. These results suggest that gestation length, time spent in close-up and stocking density are important factors influencing disease incidence in early lactation and subsequent lactation performance but had differing effects on primiparous versus multiparous cows. A better understanding of how pre-partum management factors influence postpartum health and milk production can help farms to plan facilities and organize the day-to-day management of cows and will assist in improving cow welfare and productivity.