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The objective of this study was to analyze the associations of body condition score (BCS) and BCS change (∆BCS) during the dry period and the first 100 d of lactation with daily milk yield. Examining the involvement of health status in the associations between BCS and milk yield was a secondary objective of this research. Data included 12,042 lactations in 7,626 Holstein cows calving between April 2019 and January 2022 in a commercial dairy operation located in Colorado, USA. BCSs were generated daily by an automated BCS camera system located at the exit of the milking parlor. The assessment points selected for this study were dry-off (BCSdry), calving (BCS1), 7 DIM (BCS7), 14 DIM (BCS14), 21 DIM (BCS21), and nadir (nBCS; defined as the lowest daily BCS from calving to 100 DIM). Subsequently, these BCS were categorized considering quartiles (Q1 = 25% lowest BCS; Q4 = 25% greatest BCS), separately for primiparous and multiparous cows. Changes in BCS were calculated from dry-off to calving (multiparous); and from calving to 7 DIM, 14 DIM, 21 DIM, and nadir and assigned into quartile categories considering Q1 as the 25% of cows with the greatest decrease of BCS. Lactations were classified based on the number of health events before nadir as healthy, affected by one event, or having multiple events. Data were examined in primiparous and multiparous cows separately using ANOVA. The least square means for daily milk at 60 DIM and 305 DIM were calculated by category of BCS and ∆BCS at multiple time points and time periods. Subsequently, lactation curves were created by BCS and ∆BCS categories and by health status. Multivariable models included calving season and BCS1 as covariables. The largest differences in milk yield among categories of BCS and ∆BCS were identified for BCS originated at nadir and for the ∆BCS between calving and nadir. The differences in average daily milk yield between cows in the lowest and the greatest nBCS category (Q1 vs. Q4) were 3.3 kg/d (60 DIM) and 3.4 kg/d (305 DIM) for primiparous cows and 2.4 kg/d (60 DIM) and 2.1 kg/d (305 DIM) for multiparous cows. During the period from calving to nadir, primiparous cows in Q1 (greatest decrease of BCS) produced 4.3 kg/d (60 DIM) and 3.8 kg/d (305 DIM) more than cows in Q4. For multiparous cows, the differences were 3.0 kg/d (60 DIM) and 1.9 kg/d (305 DIM) in favor of Q1 cows. Overall, the associations between BCS and ∆BCS categories and milk yield were not consistent across time and they depended on the parity category. Nonetheless, as the assessment of BCS and ∆BCS approached the nadir, the association between greater milk yield and lower BCS or greater reduction in BCS became more evident., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The objective of this study was to identify variables associated with the time and magnitude of nadir BCS (nBCS) during early lactation and to characterize the effects of these two measurements on the subsequent pregnancy at first artificial insemination (P/AI1) and pregnancy loss of Holstein cows. A retrospective observational study was completed using data collected from 12,042 lactations in 7,626 Holstein cows calving between April 2019 and January 2022 in a commercial dairy operation located in Colorado, USA. Scores generated by an automated BCS camera system at dry-off (BCSdry), calving (BCS1), nadir (nBCS; defined as the lowest daily BCS from calving to 100 DIM), and 21 d post nadir were selected for the analyses and subsequently categorized into quartiles (Q1 = lower nBCS). Changes in BCS were calculated from dry-off to calving (multiparous cows); from calving to nadir; and from nadir to 21 d post nadir and assigned into quartile categories considering Q1 as the 25% of cows with greater loss (pre nadir) or smaller gain (post nadir) of BCS. Data were examined using logistic regression, ANOVA, and time to event analyses. Initial univariable models were followed by multivariable models that considered parity category, calving season, BCS1, and average milk yield up to 30 DIM (M30) as covariables. Sick cows and high producing cows had increased DIM at nadir, while lower BCSdry, greater M30, and occurrence of disease were associated with lower nBCS. Cows that conceived at AI1 had their nBCS earlier (45.1 ± 0.32 d) than cows that remained open after first AI (46.4 ± 0.35 d). On the contrary, DIM at nBCS did not differ by pregnancy loss status. The logistic regression analyses reported smaller odds of P/AI1 in cows in the lower nBCS categories. Likewise, cows with larger loss in BCS between calving and nadir had smaller odds of P/AI1. Although cows that lost their pregnancy had lower nBCS, this association was not consistent across the analyses. The time to and magnitude of nBCS, together with the ∆BCS from calving to nadir could be useful measures to evaluate the transition and early lactation status of dairy cows., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The objective of this study was to characterize the associations between body condition score (BCS) and BCS change (∆BCS), determined by an automated camera system during early lactation and close to artificial insemination (AI), and the subsequent pregnancy loss (PL) in Holstein cows. A secondary objective was to determine the impact of disease on PL, considering multiple time periods relative to AI. Data from 9,430 lactations in 6,884 Holstein cows in a commercial dairy operation located in Colorado, USA were included in this retrospective observational study. Cows were subject to first AI at about 80 DIM (primiparous) and 60 DIM (multiparous), following a double OvSynch protocol. Pregnancy diagnosis was performed via transrectal ultrasonography on day 32 ± 3 after AI and reconfirmed on day 80 ± 3 after AI. Cameras mounted on the sorting gate at each exit (n = 2) of the milking parlor generated BCS on a five-point scale with 0.1 increments. The BCS at calving (BCS1), 21 DIM (BCS21), 56 DIM (BCS56), AI resulting in pregnancy (BCSAI), and 90 d post AI (BCSAI90) were selected for the analyses and subsequently categorized as low (≤ lower quartile), moderate (interquartile range), and high (≥ upper quartile). Changes in BCS were calculated by periods of interest as change from calving to 21 DIM; change from calving to 56 DIM; change from 56 DIM to AI; and change from AI to 90 d post AI and assigned into categories to facilitate the analysis. Data were examined using logistic regression, considering parity category, season at calving and AI, DIM at AI, milk yield up to 60 DIM, and occurrence of disease as covariables. The logistic regression analyses indicated that the odds of PL were greater in cows in the low BCS category relative to cows in the high BCS category at 56 DIM (OR 95% CI = 1.41 [1.12-1.79]), AI (1.31 [1.05-1.65]), and 90 d post AI (1.38 [1.10-1.74]). Likewise, cows with large loss in BCS between calving and 21 DIM (1.46 [1.10-1.94]) and loss in BCS between AI and 90 d post AI (1.44 [1.15-1.81]) had greater odds of PL compared with cows with no loss of BCS within the same period. Occurrence of disease at all the time periods considered in the analysis had a consistent detrimental impact on maintenance of the pregnancy, supporting the concept that pre and postconceptional disease affects embryonic survival. Overall, low BCS, more pronounced reductions in BCS occurring closer to AI, and occurrence of disease resulted in greater PL in this Holstein population., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society of Animal Science. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The main objective of this study was to examine the combined effect of mastitis and parity on pregnancy loss (PL) in lactating Holstein cows. A secondary objective was to estimate the cost of mastitis including that of PL attributable to mastitis. A total of 1,774 lactation periods from 1,047 Holstein cows with different parities from one dairy farm were included in a matched case-control study. All study cows were diagnosed pregnant by transrectal ultrasonography on day 33 after timed artificial insemination (TAI). Case cows (n = 222 lactations) were those later diagnosed non-pregnant by transrectal palpation on day 47 or 75 after TAI. Control cows (n = 1,552 lactations) were those confirmed pregnant by transrectal palpation on day 75 after TAI. Case cows were matched with eligible controls according to year of calving and calving-to-conception interval (CCI) ± 3 days. Cows with different parities were classified as exposed to subclinical mastitis (somatic cell score (SCS) > 4.5 in at least one Dairy Herd Improvement Association (DHIA) test day) or clinical mastitis (with or without evidence of subclinical mastitis) during two exposure periods: 1-42 days before breeding or 1-75 days during gestation (1 to PL diagnosis day in case cows, or 1-75 day in control cows). Conditional logistic regression was used to model the odds of PL as a function of previous exposure to mastitis in different parities. Cost of PL attributable to mastitis ($/case) among cows with mastitis was estimated based on attributable risk calculated in the epidemiologic analysis. We observed a higher than expected combined effect between exposure to mastitis (subclinical or clinical) before breeding and parity 3 or ≥ 4, and during gestation and parity ≥ 4 on PL. The cost of PL attributable to mastitis was highest ($196/case) in cows in parity ≥ 4 affected with clinical mastitis during gestation. Overall, study results indicate the impact of mastitis on PL is higher in older cows (parity ≥ 3). Dairy farmers and attending veterinarians can consider the combined effect of mastitis and parity when evaluating causes for PL and strategies for optimizing reproductive performance in dairy cows., (Copyright © 2019 Elsevier Inc. All rights reserved.)

An increase in stall stocking density (SSD), as measured by the number of lactating cows per stall in a freestall barn, reduces cow performance, such as milk yield and fertility, but may increase farm profitability. Our objectives were to calculate effects of varying SSD on profit per stall for a range of effects on cow performances and external farm factors and store results in regression metamodels. The literature on quantified effects of SSD on cow performance that directly affects cash flow was found to be weak. We assumed effects of SSD on milk yield, probability of conception, and probability of culling. External farm factors were probability of insemination, feed price, and milk price. A herd budget-simulation model was used which mimics the performance of cows in a herd and calculates profit per stall per year and other results. The SSD varied from 100 (no overstocking) to 150% (severe overstocking) in steps of 10%. Sensitivity analyses for effects of SSD on cow performance and effects of external farm factors were performed. Three regression metamodels were developed. The first metamodel accurately predicted profitability at 100% SSD for all variations in the external farm factors. Optimal SSD varied from 100 to 150% SSD, depending on the combination of inputs, and was very sensitive to changes in the size of the milk loss and milk and feed prices. Average optimal SSD of all 2,187 combinations of inputs was 120% SSD and average maximum increase in profit was $99/stall per year. Of the 2,187 combinations of inputs, 18% were ascending (maximum increase in profit >150% SSD), 33% were descending (maximum profit at 100% SSD), and 50% had a maximum increase in profit between 100 and 150% SSD. The second metamodel accurately captured changes in profit for all combinations of biological and external inputs and SSD. A third metamodel captured breakeven daily milk losses which would result in the same profit as at 100% SSD given the same external farm factors. In conclusion, overstocking was profitable under plausible economic conditions in the United States. The 3 metamodels accurately captured the results for a wide range of values of the input variables. A tradeoff will occur between economically optimal SSD and animal welfare in some situations., (Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Targeted reproductive management (TRM), employing automated monitoring devices (AMD), is as an alternative to the blanket adoption of ovulation synchronization protocols (OvSP) for first postpartum AI and a means of reducing the use of OvSP for re-insemination of nonpregnant cows. We hypothesized that a TRM that relies heavily on AI of cows on AMD-detected estrus improves reproductive performance and economic return. Early-postpartum estrus characteristics (EPEC) of multiparous (n = 941) cows were evaluated at 40 and 41 DIM (herds 1 and 2, respectively) and EPEC of primiparous (n = 539) cows were evaluated at 54 and 55 DIM (herds 1 and 2, respectively). Cows in the control treatment were enrolled in the Double-Ovsynch protocol and AI at a fixed time (TAI) at 82 and 83 DIM (primiparous cows in herds 1 and 2, respectively) and 68 and 69 DIM (multiparous in herds 1 and 2, respectively). Cows enrolled in the TRM treatment were managed according to EPEC as follows: (1) cows with ≥1 intense estrus (heat index ≥70; 0 = minimum, 100 = maximum) were AI upon AMD-detected estrus starting at 64 (primiparous) and 50 (multiparous) DIM and, if not AI, were enrolled in the Double-Ovsynch, (2) cows without an intense estrus were enrolled in the Double-Ovsynch at the same time as cows in the control treatment. Control cows were re-inseminated based on visual or patch-aided detection of estrus, whereas TRM cows were re-inseminated as described for control cows with the aid of the AMD. All cows received a GnRH injection 27 ± 3 d after AI and, if diagnosed as nonpregnant, completed the 5-d CoSynch protocol and received TAI 35 ± 3 d after insemination. The hazard of pregnancy was greater for cows in the TRM treatment (adjusted hazard ratio = 1.17, 95% CI = 1.05, 1.32), resulting in more cows from the TRM treatment starting a new lactation (82.6% vs. 77.2%) and fewer of them sold (15.5% vs. 20.8%). Treatments did not differ regarding total milk yield (control = 12,782.1 ± 130.6 kg, TRM = 13,054.7 ± 136.1 kg). The gross profit [(milk income + sale value + subsequent lactation calf value) − (feed cost + replacement cost + fixed cost + reproductive management cost)] of cows in the TRM treatment was $108 greater than the control treatment ($3,061.6 ± $45.9 vs. $2,953.8 ± $45.2). According to a Monte Carlo stochastic simulation, the mean (±SD) difference in gross profit was $87.8 ± 12.6/cow in favor of the TRM treatment, and 95% of the scenarios ranged from $67.2/cow to $108.5/cow (minimum = $30.2/cow, maximum = $141.1/cow). Under the conditions of the current experiment, the TRM treatment improved the gross profit of Holstein cows because the increased hazard of pregnancy changed culling dynamics, reducing replacement cost and cow sales and increasing calf value. The findings of the current experiment emphasize the importance of efficient reproductive management and its substantial economic implications, particularly in the context of high-producing Holstein cows. [ABSTRACT FROM AUTHOR]