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The list of standard abbreviations for JDS is available at adsa.org/jds-abbreviations-24. Nonstandard abbreviations are available in the Notes. Dairy cow fertility is a complex trait that depends on the cow's physiological status, the farm's environmental and management conditions, and their interactions. Already the slightest improvement in fertility can positively impact a farm's profitability and sustainability. In research, milk progesterone (P4) has often been used as an accurate and feasible way to identify a dairy cow's reproduction status. Moreover, in Europe and Canada, it has been used to improve fertility management on commercial farms as it allows to accurately identify reproduction issues, pregnancy, and the optimal insemination window. An on-farm P4 device (OPD) automatically samples, measures, and monitors the milk P4 concentration of individual cows. To this end, the P4 data are smoothed to be robust for measurement errors and outliers, and fixed thresholds are used to estimate the time of luteolysis preceding ovulation, thereby generating a luteolysis alert (LA). By smoothing the P4 data, the OPD introduces a time lag on the LA. Variation in this time lag is not considered in the estimation of the optimal insemination window that is advised to the farmer. Ignoring this variation might decrease the accuracy of the optimal insemination window and, therefore, decreases the likelihood of conception. We hypothesize that considering the length of the time lag and adapting the advice accordingly improves the conception rate. This observational retrospective study uses an extensive dataset from 17 commercial dairy farms that are equipped with an OPD. We estimated the time lag on the alerts and evaluated their relationship with the interval from LA to insemination for successful (n = 3,721) and unsuccessful inseminations (n = 3,896) separately. Results showed that the probability of conception increases when a longer LA time lag is compensated with a shorter interval from LA to insemination and vice versa. In addition, for successful inseminations, we found a clear negative relation between the time lag and the interval from LA to insemination and the interval was significantly shorter when the time lag of the LA was longer. This negative relation between time lag and interval from LA to insemination was less pronounced for unsuccessful inseminations. Additionally, we evaluated the conception rates for inseminations that are performed too early, in time, or too late with respect to the optimal insemination window advised by the OPD, in function of their associated time lags. We found that, for inseminations that were preceded by a short time lag (<8 h), the conception rate was 17.5 percentage points higher when cows were inseminated later than advised. Likewise, when inseminations were preceded by a long time lag (≥24 h), we found that the conception rate was 13 percentage points higher when cows were inseminated earlier than advised. Our results suggest that farmers using an OPD could potentially increase their conception success by compensating the variable time lag on the LA by adapting the interval from alert to insemination accordingly. This could be used to develop reproductive management strategies to improve reproductive performance on those farms, which can positively affect their sustainability. [ABSTRACT FROM AUTHOR]

Automated monitoring of fertility in dairy cows using milk progesterone is based on the accurate and timely identification of luteolysis. In this way, well-adapted insemination advice can be provided to the farmer to further optimize fertility management. To properly evaluate and compare the performance of new and existing data-processing algorithms, a test data set of progesterone time-series that fully covers the desired variability in progesterone profiles is needed. Further, the data should be measured with a high frequency to allow rapid onset events, such as luteolysis, to be precisely determined. Collecting this type of data would require a lot of time, effort, and budget. In the absence of such data, an alternative was developed using simulated progesterone profiles for multiple cows and lactations, in which the different fertility statuses were represented. To these, relevant variability in terms of cycle characteristics and measurement error was added, resulting in a large cost-efficient data set of well-controlled but highly variable and farm-representative profiles. Besides the progesterone profiles, information on (the timing of) luteolysis was extracted from the modeling approach and used as a reference for the evaluation and comparison of the algorithms. In this study, 2 progesterone monitoring tools were compared: a multiprocess Kalman filter combined with a fixed threshold on the smoothed progesterone values to detect luteolysis, and a progesterone monitoring algorithm using synergistic control, PMASC, which uses a mathematical model based on the luteal dynamics and a statistical control chart to detect luteolysis. The timing of the alerts and the robustness against missing values of both algorithms were investigated using 2 different sampling schemes: one sample per cow every 8 h versus 1 sample per day. The alerts for luteolysis of the PMASC algorithm were on average 20 h earlier compared with the ones of the multiprocess Kalman filter, and their timing was less sensitive to missing values. This was shown by the fact that, when 1 sample per day was used, the Kalman filter gave its alerts on average 24 h later, and the variability in timing of the alerts compared with simulated luteolysis increased with 22%. Accordingly, we postulate that implementation of the PMASC system could improve the consistency of luteolysis detection on farm and lower the analysis costs compared with the current state of the art. [ABSTRACT FROM AUTHOR]

The progesterone (P4) monitoring algorithm using synergistic control (PMASC) uses luteal dynamics to identify fertility events in dairy cows. This algorithm employs a combination of mathematical functions describing the increasing and decreasing P4 concentrations during the development and regression of the corpus luteum and a statistical control chart that allows identification of luteolysis. The mathematical model combines sigmoidal functions from which the cycle characteristics can be calculated. Both the moment at which luteolysis is detected and confirmed by PMASC, as well as the model features themselves, can be used to inform the farmer on the fertility status of the cows. [ABSTRACT FROM AUTHOR]

• Cows with endometritis had increased risk of atypical progesterone profiles. • Prolonged luteal activity was the principal cyclicity problem associated with endometritis. • Cows with endometritis had a 3-day delay in the onset of luteal activity. • Endometritis was not associated with adverse effects on delayed first ovulation or cessation of cyclicity. • The effect of endometritis on ovarian cyclicity was dependent on the grade of endometritis. Endometritis in dairy cows is a major global issue and has been associated with a decrease in reproductive performance. The aim of this study was to quantify the effect of endometritis (as defined by the presence of any abnormal vaginal discharge after 21 days post-partum) on post-partum ovarian cyclicity in dairy cows. Milk progesterone analysis was used to monitor reproductive cyclicity in 170 dairy cows across three different commercial herds. Associations between the occurrence of endometritis and the incidence risk of a variety of atypical cycle profiles during the calving to conception period were investigated to establish the importance of endometritis on post-partum ovarian activity. Endometritis increased the incidence odds of atypical ovarian profiles (P < 0.05) with prolonged luteal activity being the most affected (P < 0.05), but also showed prolonged time (3 days) to onset of luteal activity after parturition (P < 0.05). Using milk progesterone analysis, we found a relatively low incidence odds for reproductive cycle problems in healthy cows during the calving to conception period. However, the incidence odds of cycle problems, in particular prolonged luteal activity, were high in cows that had experienced endometritis, which would have significantly impaired reproductive function. [ABSTRACT FROM AUTHOR]

Research on estrus synchronization, progesterone profiles of post-synchronization and early pregnancyhas been conducted using 16 Holstein Frisian dairy cows. Treated cows were divided into 2 groups. Cowsin group I were synchronized with double injection of prostaglandin F2á (PGF2á, Lutalyse®) 25 mg / head at11 days apart, then were inseminated twice at 72 hours and 96 hours after the second injection of PGF2á(FTAI = fixed timed insemination). Group II were synchronized with progesterone implant-CIDR® for 11days. At the time of progesterone implant withdrawal the animals were injected with PGF2á at 25 mg /head then inseminated twice at 48 hours and 72 hours. Milk samples were collected on the day before, atthe treatment day and at day 1st, 3rd, 5th, 7th following the first insemination in order to determine theprofile of progesterone after synchronization, while for early pregnancy examinations, sampling of milkwere collected at day 21th, 24th and 27th after the first insemination. The milk samples were analyzed byRadioimmunoassay (RIA) method. Rectal palpation to confirm pregnancy was undertaken at day 60thafter the first insemination. The results showed a marked decrease in milk progesterone (nmol / l) at thefirst insemination (H0) in both group PGF2á and CIDR® (0.84; 0.49 vs. 0.92; 0.32), which indicated theoccurrence of estrus. Gradually increased of milk progesterone level (0.52; 0.68; 1.17; 1.69, respectively)started from day 1st, 3rd, 5th, 7th was seen in animals PGF2á group, whereas in the CIDR® group the milkprogesterone level was found fluctuate (0.21; 0.39; 0.33; 1.61). However, at day 7th the concentration ofprogesterone in both groups was significantly increased which indicated functional activity of the corpusluteum. Meanwhile the progesterone concentrations (nmol/l) of pregnant cows at day 21st, 24th and 27th ingroup PGF2á were 3.63; 3.51; 1.58 and in CIDR® group were 2.50; 2,79; 4.35, respectively. In non-pregnantcows, the progesterone concentrations (nmol/l) were lower (0.63; 0.42; 1.41 vs. 0.20; 0.27; 1.33), than thoseof pregnant cows. The results of rectal palpation after 60 days of the first Artificial Insemination (AI)confirmed that 5 cows with higher milk progesterone concentrations at day H21, H24, H27 from the firstinsemination were pregnant, with the possibilities at 62.5% in each group. It is concluded that estroussynchronization using either PGF2á or CIDR® in lactating dairy cows will give the same response and thiscould be detected using the milk progesterone profiles. Measurement of milk progesterone concentrationsby RIA began at day 21 of the first AI was effective for early pregnancy diagnosis.

The aim of the current instant study was to evaluate relative at-line milk progesterone dynamic changes according to parity and status of reproduction and to estimate the relationship with productivity in dairy cows by at-line milk analysis system Herd NavigatorTM. According to the progesterone assay, experimental animals were divided into three periods: postpartum, after insemination, and pregnancy. In the first stage of the postpartum period, progesterone levels in milk were monitored every 5 days. This period of reproductive cycle recovery was followed for 30 days (days 0–29). The second stage of the postpartum period (30–65 days) lasted until cows were inseminated. In the period (0–45 days) after cow insemination, progesterone levels were distributed according to whether or not cows became pregnant. For milk progesterone detection, the fully automated real-time progesterone analyzer Herd NavigatorTM (Lattec I/S, Hillerød, Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). We found that an at-line progesterone concentration is related to different parities, reproductive statuses, and milk yield of cows: the 12.88% higher concentration of progesterone in milk was evaluated in primiparous cows. The average milk yield in non-pregnant primiparous cows was 4.64% higher, and in non-pregnant multiparous cows 6.87% higher than in pregnant cows. Pregnancy success in cows can be predicted 11–15 days after insemination, when a significant increase in progesterone is observed in the group of pregnant cows.

Timely identification of a cow's reproduction status is essential to minimize fertility-related losses on dairy farms. This includes optimal estrus detection, pregnancy diagnosis, and the timely recognition of early embryonic death and ovarian problems. On-farm milk progesterone (P4) analysis can indicate all of these fertility events simultaneously. However, milk P4 measurements are subject to a large variability both in terms of measurement errors and absolute values between cycles. The objective of this paper is to present a newly developed methodology for detecting luteolysis preceding estrus and give an indication of its on-farm use. The innovative monitoring system presented is based on milk P4 using the principles of synergistic control. Instead of using filtering techniques and fixed thresholds, the present system employs an individually on-line updated model to describe the P4 profile, combined with a statistical process control chart to identify the cow's fertility status. The inputs for the latter are the residuals of the on-line updated model, corrected for the concentration-dependent variability that is typical for milk P4 measurements. To show its possible use, the system was validated on the P4 profiles of 38 dairy cows. The positive predictive value for luteolysis followed by estrus was 100%, meaning that the monitoring system picked up all estrous periods identified by the experts. Pregnancy or embryonic mortality was characterized by the absence or detection of luteolysis following an insemination, respectively. For 13 cows, no luteolysis was detected by the system within the 25 to 32 d after insemination, indicating pregnancy, which was confirmed later by rectal palpation. It was also shown that the system is able to cope with deviating P4 profiles having prolonged follicular or luteal phases, which may suggest the occurrence of cysts. Future research is recommended for optimizing sampling frequency, predicting the optimal insemination window, and establishing rules to detect problems based on deviating P4 patterns. [ABSTRACT FROM AUTHOR]

The main objective of this study was to investigate the benefit of accuracy of genomic prediction when combining records for an intermediate physiological phenotype in a training population with records for a traditional phenotype. Fertility was used as a case study, where commencement of luteal activity (C-LA) was the physiological phenotype, whereas the interval from calving to first service and calving interval were the traditional phenotypes. The potential accuracy of across-country genomic prediction and optimal recording strategies of C-LA were also investigated in terms of the number of farms and number of repeated records for C-LA. Predicted accuracy was obtained by estimating population parameters for the traits in a data set of 3,136 Holstein Friesian cows with 8,080 lactations and using a deterministic prediction equation. The effect of genetic correlation, heritability, and reliability of C-LA on the accuracy of genomic prediction were investigated. When the existing training population was 10,000 bulls with reliable estimated breeding value for the traditional trait, predicted accuracy for the physiological trait increased from 0.22 to 0.57 when 15,000 cows with C-LA records were added to the bull training population; but, when the interest was in predicting the traditional trait, we found no benefit from the additional recording. When the genetic correlation was higher between the physiological and traditional traits (0.7 instead of 0.3), accuracy increased less when adding the 15.000 cows with C-LA (from 0.51 to 0.63). In across-country predictions, we observed little to no increase in accuracy of the intermediate physiological phenotype when the training population from Sweden was large, but when accuracy increased the training population was small (200 cows), from 0.19 to 0.31 when 15,000 cows were added from the Netherlands (genetic correlation of 0.5 between countries), and from 0.19 to 0.48 for genetic correlation of 0.9. The predicted accuracy initially increased substantially when recording on the same farm was extended and multiple C-LA records per cow were used in prediction compared with single records; that is, accuracy increased from 0.33 with single records to 0.38 with multiple records (on average 1.6 records per cow) from 2 yr of recording C-LA. But, when the number C-LA per cow increased beyond 2 yr of recording, we noted no substantial benefit in accuracy from multiple records. For example, for 5 yr of recording (on average 2.5 records per cow), accuracy was 0.47; on doubling the recording period to 10 yr (on average 3.1 records per cow), accuracy increased by 0.07 units, whereas when C-LA was recorded for 15 yr (on average 3.3 records per cow) accuracy increased only by 0.05 units. Therefore, for genomic prediction using expensive equipment to record traits for training populations, it is important to optimize the recording strategy. The focus should be on recording more cows rather than continuous recording on the same cows. [ABSTRACT FROM AUTHOR]

Despite the importance of progesterone on the fertility of lactating dairy cows, the factors that affect post ovulatory progesterone concentration are still unclear. Thus, the aim of the present study was to identify factors associated with the post ovulatory progesterone rise following 1st insemination in lactating dairy cows. Data collected across a number of complimentary studies were compiled to produce a single database of 168 lactating Holstein Friesian dairy cows maintained under commercial conditions. In all animals a number of variables were measured during the insemination period and related to milk progesterone measured on day 5 following 1st artificial insemination (AI). Overall, 44% of cows conceived to 1st AI and while mean day 5 progesterone was not significantly higher in these cows, there was a significant quadratic relationship between milk progesterone concentration and conception rate. While a number of variables showed some association with progesterone concentration, the only variable showing a strong and repeatable relationship was plasma leptin concentration. We conclude that adequate but not excessive progesterone levels on day 5 bring about a better fertility, and plasma leptin concentration may be a much better indicator of metabolic status in lactating dairy cows. [ABSTRACT FROM AUTHOR]

Endocrine fertility traits, defined from progesterone concentration levels in milk, have been suggested as alternative indicators for fertility in dairy cows because they are less biased by farm management decisions and more directly reflect a cow's reproductive physiology than classical traits derived from insemination and calving data. To determine the potential use of endocrine fertility traits in genomic evaluations, the improvement in accuracy from using endocrine fertility traits concurrent with classical traits in the genomic prediction of fertility was quantified. The impact of recording all traits on all training animals was also investigated. Endocrine and classical fertility records were available on 5,339 lactations from 2,447 Holstein cows in Ireland, the Netherlands, Sweden, and the United Kingdom. The endocrine traits were commencement of luteal activity (C-LA]) and proportion of samples with luteal activity (PLA); the classical trait was the interval from calving to first service (CFS). The interval from C-LA to first service (C-LAFS), which is a combination of an endocrine trait and a classical trait, was also investigated. The target (breeding goal) trait for fertility was CFS or C-LAFS, whereas C-LA and PLA served as predictor traits. Genomic EBV (GEBV) for fertility were derived using genomic BLUP in bivariate models with 85,485 SNP. Genomic EBV for the separate fertility traits were also computed, in univariate models. The accuracy of GEBV was evaluated by 5-fold cross-validation. The highest accuracy of GEBV was achieved using bivariate predictions, where both an endocrine fertility trait and the classical fertility trait were used. Accuracy of GEBV for predicting adjusted phenotypes for CFS in the univariate model was 0.04, but when predicting CFS using a bivariate model with C-LA, the accuracy increased to 0.14 when all training animals were phenotyped for C-LA and (or not) for CFS. On phenotyping all training animals for both C-LA and CFS, accuracy for CFS increased to 0.18; however, when validation animals were also phenotyped for C-LA, there was no substantial increase in accuracy. When predicting CFS in bivariate analysis with PLA, accuracy ranged from 0.07 to 0.14. This first study on genomic predictions for fertility using endocrine traits suggests some improvement in the accuracy of prediction over using only the classical traits. Further studies with larger training populations may show greater improvements. [ABSTRACT FROM AUTHOR]

The aim of this study was to gain a better understanding of the variability in shape and features of all progesterone profiles during estrus cycles in cows and to create templates for cycle shapes and features as a base for further research. Milk progesterone data from 1418 estrus cycles, coming from 1009 lactations, was obtained from the Danish Cattle Research Centre in Foulum, Denmark. Milk samples were analyzed daily using a Ridgeway ELISA-kit. Estrus cycles with less than 10 data points or shorter than 4 days were discarded, after which 1006 cycles remained in the analysis. A median kernel of three data points was used to smooth the progesterone time series. The time between start of progesterone rise and end of progesterone decline was identified by fitting a simple model consisting of base length and a quadratic curve to progesterone data, and this luteal-like phase (LLP) was used for further analysis. The data set of 1006 LLP's was divided into five quantiles based on length. Within quantiles, a cluster analysis was performed on the basis of shape distance. Height, upward and downward slope, and progesterone level on Day 5 were compared between quantiles. Also, the ratio of typical versus atypical shapes was described, using a reference curve on the basis of data in Q1–Q4. The main results of this article were that (1) most of the progesterone profiles showed a typical profile, including the ones that exceeded the optimum cycle length of 24 days; (2) cycles in Q2 and Q3 had steeper slopes and higher peak progesterone levels than cycles in Q1 and Q4 but, when normalized, had a similar shape. Results were used to define differences between quantiles that can be used as templates. Compared to Q1, LLP's in Q2 had a shape that is 1.068 times steeper and 1.048 times higher. Luteal-like phases in Q3 were 1.053 times steeper and 1.018 times higher. Luteal-like phases in Q4 were 0.977 times steeper and 0.973 times higher than LLP's in Q1. This article adds to our knowledge about the variability of progesterone profiles and their shape differences. The profile clustering procedure described in this article can be used as a means to classify progesterone profiles without recourse to an a priori set of rules, which arbitrarily segment the natural variability in these profiles. Using data-derived profile shapes may allow a more accurate assessment of the effects of, e.g., nutritional management or breeding system on progesterone profiles. [ABSTRACT FROM AUTHOR]

Endocrine fertility traits, which are defined from progesterone concentration levels in milk, are interesting indicators of dairy cow fertility because they more directly reflect the cows own reproductive physiology than classical fertility traits, which are more biased by farm management decisions. The aim of this study was to detect quantitative trait loci (QTL) for 7 endocrine fertility traits in dairy cows by performing a genomewide association study with 85k single nucleotide polymorphisms (SNP), and then fine-map targeted QTL regions, using imputed sequence variants. Two classical fertility traits were also analyzed for QTL with 85k SNP. The association between a SNP and a phenotype was assessed by single-locus regression for each SNP, using a linear mixed model that included a random polygenic effect. A total of 2,447 Holstein Friesian cows with 5,339 lactations with both phenotypes and genotypes were used for association analysis. Heritability estimates ranged from 0.09 to 0.15 for endocrine fertility traits and 0.03 to 0.10 for classical fertility traits. The genome-wide association study identified 17 QTL regions for endocrine fertility traits on Bos taurus autosomes (BTA) 2, 3, 8, 12, 15, 17, 23, and 25. The highest number (5) of QTL regions from the genome-wide association study was identified for the endocrine trait "proportion of samples with luteal activity." Overlapping QTL regions were found between endocrine traits on BTA 2, 3, and 17. For the classical trait calving to first service, 3 QTL regions were identified on BTA 3, 15, and 23, and an overlapping region was identified on BTA 23 with endocrine traits. Fine-mapping target regions for the endocrine traits on BTA 2 and 3 using imputed sequence variants confirmed the QTL from the genome-wide association study, and identified several associated variants that can contribute to an index of markers for genetic improvement of fertility. Several potential candidate genes underlying endocrine fertility traits were also identified in the target regions and are discussed. However, due to high linkage disequilibrium, it was not possible to specify genes or polymorphisms as causal factors for any of the regions. [ABSTRACT FROM AUTHOR]

In this study, the use of milk progesterone assay for oestrus detection and early pregnancy diagnosis in Nili-Ravi buffaloes was investigated. For this purpose, 100 milking buffaloes with clinically normal reproductive tract were used. Oestrus was detected on the basis of visual signs and uterine changes observed through rectal palpation. These buffaloes were then inseminated on day of oestrus. Three milk samples were taken from each buffalo, one each on day of insemination and then on 10-12 and 21-22 days post insemination. These animals were rectally examined for pregnancy 60 days after insemination. The milk samples were analyzed for progesterone concentrations through RIA. Out of 100 buffaloes observed to be in oestrus on the basis of visual signs and rectal examination, 94% showed the milk progesterone concentrations ranging from 0.01 to 0.90 ng/ml, whereas in only 6% animals, milk progesterone concentrations ranged from 3.31 to 7.44 ng/ml. Thus, 6% buffaloes seemed to have been inseminated during luteal phase. On day 21-22, out of 84 buffaloes examined, 50(59.52%) showed the milk progesterone concentrations >2.0 ng/ml and were assumed to be pregnant. However, when 41 out of these 50 animals were rectally examined 60 days post insemination, 36(87.81%) were found pregnant. Perhaps there was early embryonic death in the remaining 5(12.19%) buffaloes. It was concluded that milk progesterone assay may be used to evaluate the accuracy of clinically diagnosed oestrus, as well as for early pregnancy diagnosis in Nili-Ravi buffaloes.

The main objective of this study was to identify the factors that affect the success of artificial insemination (A.I) services under field conditions. The data from a total of 459 inseminations were analyzed. The effects of farm, animal, semen/bull and A.I. technician on conception rate were studied. Milk progesterone concentration was used as an indicator of conception. Milk samples were collected from animals at day 0, 11 and 22 post-insemination and analysed for progesterone (P4) concentrations using radioimmunoassay (RIA) kits. Results indicated that the overall conception rate through A.I. under field condition was 29%. Among the farm-related factors, only region had a significant effect on conception rate (P0.05). Animals inseminated within 24 hours after the onset of estrus had a higher, though statistically insignificant, conception rate than those inseminated after 24 hours. Among the animal-related factors, species, milk production, body condition score (BCS), lactation state, heat signs and uterine tone had a significant effect on conception rate. The conception rate in buffaloes was higher than in cattle (P

The interval from calving to commencement of luteal activity (CLA) was determined by progesterone measurements from milk samples obtained once a week until the 14th week post-partum in 513 German Holstein cows in first to third parity. Milk samples were analyzed by an “on-farm” device (eProCheck ® , Minitüb, Germany) and simultaneously by RIA. The objective of this study was to examine the effect of milk yield, protein content and body condition of a cow on the CLA post-partum. Milk progesterone concentrations of “on-farm” measurements correlated with measurements done by the RIA-method significantly ( r = 0.72; P < 0.001). Within the analyzed herd the interval from calving until the first rise of progesterone averaged 5.6 ± 2.4 weeks. The 100-days milk yield was not associated with CLA. Cows with a milk protein content at 1st milk recording of ≤3.5% revealed first luteal activity 1.3 ± 0.3 weeks later than cows that had a content of >3.75% protein ( P < 0.01). Furthermore cows with assisted calving or dystocia presented significantly later CLA than cows which required no help during the calving process ( P < 0.05). The change in back fat thickness from 1st to 2nd milk recording had a significant influence on CLA ( P < 0.05). In conclusion the phenotypic impact of milk yield on fertility cannot be confirmed regarding to CLA. The negative energy balance after calving, caused by the high milk yields, is more detrimental for the cyclical activity as was shown by the parameters milk protein content and change in BFT. [ABSTRACT FROM AUTHOR]

To improve the detection of ovulation and early diagnosis of pregnancy on dairy farms, a disposable electrochemical immunosensor was developed using indirect competitive immunoassays and screen-printed carbon electrodes. After optimisation of the assay conditions, the linear range was from 0.16 to 50 ng/ mL. The limit of detection was 0.16 ng/ mL. There was no cross-reactivity with testosterone, 17-β-estradiol and estriol. The intra-assay coefficient of variation was less than 13% and interassay coefficient of variation was < 9%. The percentage recovery was from 95.8% to 115.7%. Stability lasts 4 days at 4 °C. The results of preliminary application trials indicate that the method could have practical potential. [ABSTRACT FROM AUTHOR]

A study on the augmentation of postpartum reproductive efficiency in Holstein Friesian crossbred cattle through supplementation with ragi (Eleusine corocana) grain during the transition period is presented. It is said that postpartum reproductive inefficiency is caused by nutritional mismanagement during the transition period when the demand for energy increases due to the onset of lactation. The researchers monitored the sample's milk urea nitrogen (MUN) and milk total protein.

Abstract: The objectives of this study were to derive a useful case definition of delayed resumption of ovarian activity, based on factors associated with reduced fertility, and to assess its impact on subsequent reproductive performance in Holstein cows (Bos taurus). Milk samples were collected twice weekly from 219 cows from four commercial herds, and whole-milk progesterone concentrations were determined with an enzyme-linked immunosorbent assay. Ovulation was considered to have occurred 5 d before the first rise of milk progesterone concentration above the basal level. Survival analysis was used to derive a case definition of delayed resumption of ovarian activity postpartum based on factors that were predictive of reduced pregnancy rate. First postpartum ovulation occurring beyond 35 d postpartum was associated with a reduced pregnancy rate (hazard ratio [HR]=0.50; P<0.001) and was defined as delayed resumption of ovarian activity; overall, 75 (34.9%) cows were in this category. These cows were more likely not to conceive on first artificial insemination (odds ratio [OR]=2.85; P=0.01) and more likely not to become pregnant within 100 d (OR=3.30; P=0.001) and 210 d (OR=3.20; P<0.001) postpartum compared with cows with normal resumption of ovarian activity. Furthermore, 13 (6%) cows that ovulated within 35 d postpartum had a prolonged (≥14 d) interval between either first and second or second and third luteal phases postpartum. A prolonged interluteal interval was also associated with a reduced pregnancy rate (HR=0.35; P=0.02). Days open (mean ± SEM) were greater (P=0.0002) in cows with delayed resumption of ovarian activity (213±13 d) and in cows with prolonged interluteal interval (220±37 d) than in cows with normal resumption of ovarian activity (152±9 d). In conclusion, first ovulation occurring beyond 35 d postpartum was defined as delayed resumption of ovarian activity, and the first ovulation occurring within 35 d postpartum but the absence of luteal activity ≥14 d between two consecutive luteal phases was defined as a prolonged interluteal interval; both abnormalities adversely affected the subsequent reproductive performance of Holstein cows. [Copyright &y& Elsevier]

Supplementary feeding of Desert ewes at mating time or for 45 days pre-lambing, or both combined, increased lambing and twinning, gave heavier lambs and gave farmers a greater monetary return. The best return was with the two supplements combined. Supplementing the diet of weaned lambs for four months gave increased growth, advanced puberty, and gave higher conception and lambing rates. Copyright © 2006 John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

Abstract: Milk progesterone concentration (P4), milk yield, milk composition, ovarian structures and pregnancy status were studied in 108 cows treated with two doses of PGF 14 days apart and inseminated at fixed time (TAI) 80–82h later. The synchronization protocol was started at 70±1.4 days after parturition. Milk P4 profiles revealed that anestrus, failure of luteolysis following treatment with PGF and failure to ovulate following luteolysis were the main reasons for low pregnancy rate with TAI. Anestrous cows had a higher percentage of milk fat (P <0.05) and higher fat to protein ratio (P <0.01), and cows that did not undergo luteolysis had higher milk yield (P <0.05) and lower percentage of milk protein (P <0.05) than cows that responded to PGF treatment. Cows that did not undergo luteolysis and cows that did not ovulate following luteolysis had lower milk P4 during the luteal phase preceding the second PGF injection (P <0.01 and P <0.05, respectively). Pregnancy rates 24 and 47 days after TAI in cows that responded as expected to the synchronization treatment were 62% and 54%, respectively. Pregnancy was precluded in non-responsive cows. The largest follicle at the time of TAI in cows experiencing late embryonic mortality was smaller (P =0.02) than in cows that successfully maintained pregnancy. Results suggest that a primary reason for low pregnancy rate in dairy cows after administration of PGF and TAI is inappropriate ovarian function prior to, or following treatment. [Copyright &y& Elsevier]

Abstract: Logistic regression analysis was used to evaluate the relationship between post-insemination milk progesterone concentration and embryo survival, and between milk yield and milk progesterone concentration. Milk samples were collected on Days 1, 4, 5, 6, and 7 (insemination=Day 0) following 871 inseminations in spring-calving dairy cows. Milk progesterone concentrations were measured by enzyme-immunoassay and pregnancy diagnosis was conducted with transrectal ultrasonography at approximately Day 30. There was a negative linear relationship (P &#60;0.01) between milk progesterone concentration on Day 4 and embryo survival while, in contrast, there was a positive linear and quadratic relationship between milk progesterone concentration on Days 5, 6 and 7 (P &#60;0.05) and also between the rate of change in progesterone concentrations between Days 4 and 7 inclusive and embryo survival (P &#60;0.05). There was a weak negative linear relationship between average daily milk yield at the time of insemination and milk progesterone concentrations (P &#60;0.001). There was no association between many production parameters, including liveweight and body condition score measured at various stages between calving and insemination, and milk progesterone concentration between Days 4 and 7 inclusive (P >0.05). In conclusion, low progesterone during Days 5–7 (after insemination) was associated with low fertility in dairy cows and there were indications of a range of progesterone concentrations within which embryo survival was maximal. [Copyright &y& Elsevier]

Abstract: We have used milk progesterone analysis to monitor reproductive function in lactating dairy cows and have then related this reproductive function to a variety of metabolic variables. Monitoring of cows (n =41) during the period of onset of luteal function (first milk progesterone reading>5ng/ml) revealed that delayed onset was associated with increased milk yield and greater loss of body weight and body condition but was not related to plasma metabolite or leptin concentrations. Further monitoring of reproductive function in these 41 cows and an additional 33 cows (total n =74) during the mating period (from weeks 6 to 14 post partum) identified reproductive cycle abnormalities in 29 (39.2% of animals). The occurrence of cycle abnormalities was associated with increased milk yield (P &#60;0.05), elevated plasma beta hydroxybutyrate (P &#60;0.05) and reduced plasma leptin (P &#60;0.01) concentrations as well as a lower (P &#60;0.05) rate of gain of body weight and condition score but was not associated with plasma urea or glucose concentrations. Furthermore, cows exhibiting cycle abnormalities had a longer (P &#60;0.01) interval to first service and a smaller percentage had conceived by 100 days post partum (34.5% versus 66.7%; P &#60;0.01). These results provide further evidence that impaired reproductive function during the post partum period in dairy cows is caused by a poor energy status and not elevated urea concentrations. Reduced plasma leptin concentrations in animals suffering reproductive dysfunction further supports this view. [Copyright &y& Elsevier]

Three strains of Holstein-Friesian (HF): high production North American (HP), high durability North American (HD) and New Zealand (NZ) cows were assigned, within strain, to one of three pasture-based feeding systems: (1) the Moorepark (control) system (MP), (2) a high concentrate system (HC), (3) a high stocking rate system (HS). Ovarian function was assessed using milk progesterone samples, collected from 117 cows in each of two successive years, with 81 animals being common to both years. Milk samples were collected thrice weekly, beginning day 5 post-calving and continued to day 26 after first AI. Data from animals subsequent to reproductive hormonal treatment were removed from the analysis. Feed system and strain of HF by feeding system interaction had no significant effect on re-establishment of ovarian activity and subsequent conception rate to first AI. Strain of HF had no significant effect on interval to commencement of luteal activity (CLA). The mean interval to CLA was 32.9 days (S.E. 1.18), ranged from 6 to 100 days, with 42 and 85% of cows ovulating by day 26 and 60, respectively. The HD (62%) and NZ (57%) strains had a higher conception rate to first AI than the HP strain (40%), (P < 0.05). Retrospective analysis categorised all cows into four quartiles based on interval to CLA (<20 days, 20–26 days, 27–44 days and >44 days). Cows in the first and fourth CLA quartiles had a longer calving to conception interval (P < 0.05). Cows with abnormal progesterone profiles (38.4%) had an earlier mean calving date, with a similar submission rate and conception rate to first service compared to cows with normal hormonal profiles. There was no significant difference in luteal activity or reproduction performance, apart from calving to conception interval, between cows that conceived or did not conceive to first service. These results indicate that while conception rate to first service differed between strains of HF cow, this was not associated with differences in the onset and pattern of luteal activity post partum. [Copyright &y& Elsevier]

Presents abstracts of several studies on animal reproductive technologies and management. "Development of a Boar Semen Mobility Assay," by A. A. Olivera, D. L. Fernandez and E. S. Fonda; "Effects of Holding Time Prior to Freezing on the Motility, Viability and Membrane Binding Ability of Ram Sperm," by P. H. Purdy; "Deep Uterine Horn AI Improves Fertility of Lactating Dairy Cows," by J. R. Pursley.

Presents abstracts of several studies on animal reproductive technologies and management. "Development of a Boar Semen Mobility Assay," by A. A. Olivera, D. L. Fernandez and E. S. Fonda; "Effects of Holding Time Prior to Freezing on the Motility, Viability and Membrane Binding Ability of Ram Sperm," by P. H. Purdy; "Deep Uterine Horn AI Improves Fertility of Lactating Dairy Cows," by J. R. Pursley.

Presents abstracts of several studies on animal reproductive technologies and management. "Development of a Boar Semen Mobility Assay," by A. A. Olivera, D. L. Fernandez and E. S. Fonda; "Effects of Holding Time Prior to Freezing on the Motility, Viability and Membrane Binding Ability of Ram Sperm," by P. H. Purdy; "Deep Uterine Horn AI Improves Fertility of Lactating Dairy Cows," by J. R. Pursley.

The interval from calving to first luteal activity (CLA) has been suggested as an unbiased and, therefore, preferable measure for selection on female fertility in dairy cattle. However, measurement of this interval for individual cows is not feasible for reasons of cost and labor associated with the necessary frequent (milk) progesterone measurements. The objective of this study was to test the hypothesis that mean sire progesterone profiles based on individual progesterone measurements of daughters at 3- to 6-wk intervals have prospects as a measure for female fertility when selecting sires in a progeny testing scheme. In this study, progesterone concentrations were measured in milk samples collected at routinely performed milk recordings during the first 100 d of lactation of daughters of 20 test bulls. It is demonstrated that a) mean progesterone profiles can be used to calculate the earliest stage of lactation at which at least 50% of the daughters of a test bull has a milk progesterone level >3 ng/mL (indicating luteal activity) and that b) this stage, at which 50% of the daughters of a bull have an active corpus luteum (CLA50%), varies largely between test bulls. We conclude that selecting sires based on daughter CLA50% may improve female fertility. [ABSTRACT FROM AUTHOR]

Milk progesterone level is a good marker to evaluate the functional status of the corpus luteum in all farm animals. The present study was conducted to monitor changes in milk progesterone concentrations at the time of oestrus and post-mating for diagnosing early pregnancy in Anatolian water buffaloes. Twenty-one buffaloes reared at the Kocatepe Agricultural Research Institute, Afyon, Turkey, were used. Milk samples were collected on Days 0 (D0: oestrus-mating), 11, 19, 21 and 24, and then every 3-4 days until Day 45. They were stored at 4 °C and analysed by the enzyme immunoassay (EIA) method. Rectal palpation was performed on Day 60 to confirm pregnancy. Although 16 animals had elevated levels of progesterone on Day 19 and Day 24, pregnancy was only confirmed in 12 of them on Day 60. Although the other 4 buffaloes had elevated levels of progesterone and did not return to oestrus during Day 19 and Day 24, they were confirmed non-pregnant on Day 60. Two of these non-pregnant buffaloes with elevated progesterone levels had increased progesterone levels even on Day 45 and did not return to oestrus. In the remaining 2 non-pregnant buffaloes with elevated progesterone levels, progesterone concentrations declined gradually (1.2 ng/ml on Day 31 and 0.88 ng/ml on Day 45). The other 5 buffaloes were diagnosed non-pregnant based upon the milk progesterone assay. Mean progesterone concentration in these non-pregnant buffaloes was 0.88 ± 0.37 ng/ml between Days 19 and 24. The accuracy rate, sensitivity, specificity and the detection rate of pregnancy and non-pregnancy of progesterone assay were 81.0, 100.0, 56.0, 75.0 and 100.0%, respectively. In conclusion, milk progesterone assay is a fast and reliable tool to detect oestrus time and non-pregnant buffaloes with a 100.0% accuracy rate. In addition, this assay may also give an idea about early pregnancy during Days 19-24 of gestation and may be used to predict some reproductive disorders which cause infertility ... [ABSTRACT FROM AUTHOR]

The milk progesterone test; a means to improve fertility in dairy herds The blood progesterone concentration, depending on corpus luteum activity, is reflected by the amount of progesterone in the milk. Since this was discovered in the seventies, dairy farmers and veterinarians are utilizing this fact by having progesterone concentrations determined in milk samples with the purpose of recognizing the respective physiological or pathological state of a cow's ovaries. The practicability of the test is facilitated by the recent availability of quick, cheap methods for determining milk progesterone concentrations. The test may be applied by dairy farmers to examine the proper time of insemination, check for cyclicity and recognize return cows. More complex physiological or pathological ovarian conditions are usually monitored by analysing progesterone concentrations in a sequence of samples usually collected under supervision of a veterinarian. In this context the milk progesterone test may serve as a valuable diagnostic tool to recognize conditions such as silent heat, lack of cyclicity, cystic follicles, retained corpora lutea and irregular cycles. It may also serve to monitor the ovarian response to therapeutical or biotechnical measures or to improve the accuracy of fertility parameters. Zusammenfassung Die vom Vorhandensein eines funktionellen Gelbkörpers am Ovar abhängige Progesteronkonzentration im Blut spiegelt sich deutlich in der Milch wider. Seit den 70er Jahren machen sich in zunehmendem Maße Tierhalter und Tierärzte diese Erkenntnis zunutze, indem sie Milchproben auf ihren Progesteroninhalt hin untersuchen lassen, um daraus Rückschlüsse auf Funktionszustand und etwaige pathologische Zustände am Eierstock zu ziehen. Den eigentlichen Durchbruch erlangte der Milchprogesterontest mit der Verfügbarkeit schneller preiswerter Progesteronanalyseverfahren. Vom Landwirt wird der Test in erster Linie zur Überprüfung des Besamungszeitpunkts, zur Feststellung von zyklischer Ovaraktivität und zur Erkennung von umrindernden Tieren genutzt. Die Aufklärung komplexerer physiologischer oder pathologischer Zusammenhänge erfordert meist Einsendung mehrerer Proben und geht in der Regel vom Tierarzt aus. In diesem Zusammenhang kann der Milchprogesterontest bei Unregelmäßigkeiten wie Anaphrodisie, Azyklie, Follikel-Theka-Zysten, persistierendem Gelbkörper und unregelmäßigem Umrindern als wertvolle Diagnosehilfe dienen. Er bietet auch die Möglichkeit einer Verlaufskontrolle bei therapeutischen und biotechnischen Maßnahmen sowie der Verbesserung der Aussagegenauigkeit von Fruchtbarkeitsparametern und deren Verwendbarkeit im Rahmen züchterischer Maßnahmen. [ABSTRACT FROM AUTHOR]

Simple Summary: According to the literature, the at-line progesterone monitoring system Herd NavigatorTM (Lattec I/S, Hillerød, Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). It works automatically and provides real-time physiological information about lactating dairy cows. For making farm-management decisions, it is not only a novel tool for scientific research, but also a mechanism for improving productivity, food safety, animal well-being, the environment, and the public perception of the dairy industry. It has been hypothesized that the progesterone concentration determined by the at-line milk analysis system and changes in its dynamics correlate with the parity, reproductive status, and milk yield of cows. The aim of the current study was to evaluate relative at-line milk progesterone (mP4) dynamic changes, according to the parity and status of reproduction, and to estimate the relationship with productivity in dairy cows. Frequent automated mP4 sampling can help identify characteristics of mP4 dynamic changes associated with successful pregnancies, pregnancy losses, and potential differences in mP4 dynamics among parity groups, which have not been studied previously. The aim of the current instant study was to evaluate relative at-line milk progesterone dynamic changes according to parity and status of reproduction and to estimate the relationship with productivity in dairy cows by at-line milk analysis system Herd NavigatorTM. According to the progesterone assay, experimental animals were divided into three periods: postpartum, after insemination, and pregnancy. In the first stage of the postpartum period, progesterone levels in milk were monitored every 5 days. This period of reproductive cycle recovery was followed for 30 days (days 0–29). The second stage of the postpartum period (30–65 days) lasted until cows were inseminated. In the period (0–45 days) after cow insemination, progesterone levels were distributed according to whether or not cows became pregnant. For milk progesterone detection, the fully automated real-time progesterone analyzer Herd NavigatorTM (Lattec I/S, Hillerød, Denmark) was used in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). We found that an at-line progesterone concentration is related to different parities, reproductive statuses, and milk yield of cows: the 12.88% higher concentration of progesterone in milk was evaluated in primiparous cows. The average milk yield in non-pregnant primiparous cows was 4.64% higher, and in non-pregnant multiparous cows 6.87% higher than in pregnant cows. Pregnancy success in cows can be predicted 11–15 days after insemination, when a significant increase in progesterone is observed in the group of pregnant cows. [ABSTRACT FROM AUTHOR]

The lateral flow test (LFT) is an immunochromatographic method that utilises an immunostrip for non-laboratory diagnostic purposes. The present study evaluated a milk progesterone LFT against the enzyme immunoassay (EIA) to confirm oestrus and a non-pregnancy diagnosis. In total, 277 milk samples from 70 cows were analysed, collected on the day of artificial insemination and at 19 days, 21 days and 24 days post insemination. The level of accuracy of the LFT compared with the EIA was 95.0 per cent for milk samples containing <2 ng/ml progesterone and 97.0 per cent for milk samples containing >10 ng/ml progesterone. The validation of oestrus by the LFT was 98.6 per cent accurate using 2 ng/ml progesterone as the EIA estimate for oestrus. The test performance for a non-pregnancy diagnosis was subject to the day of milk sampling, showing the highest accuracy on day 24 post insemination for both tests. When optimised for maximum specificity, and compared with rectal palpation, the LFT had a sensitivity and specificity for non-pregnancy diagnosis on day 24 post insemination of 75.0 per cent and 100.0 per cent, respectively, with an overall accuracy of 84.4 per cent. The corresponding characteristics for the quantitative EIA were 85.0 per cent, 100.0 per cent and 90.6 per cent, respectively. The LFT results compared favourably with the quantitative milk progesterone EIA., (British Veterinary Association.)

An observational study was conducted in 18 Ontario Dairy herds between January 2004 and April 2005. Milk samples were collected at 46 and 60 (± 7) DIM for progesterone (P4) analysis. Anestrus was defined as P4 < 1ng/ml in both skim milk samples. A total of 1341 animal had complete data for analysis with logistic regression and survival analysis controlling for the effects of clustering at the herd level. Overall, the prevalence of anestrus was 19.5% (95% confidence interval = 17.4 to 21.6%). The estimated herd specific prevalence varied from 5% to 44%. The prevalence of anestrus was not different among parities. Calving in the spring increased the odds of anestrus 1.7 times (p=0.02) relative to animals calving in the summer. In a representative subset of 1046 animals, milk b-hydroxybutyrate (BHBA) was measured once in each of the first two weeks after calving. Among these, 26% had subclinical ketosis (≥ 100 mmol/ml BHBA) in week 1 (range among herds, 5 to 82%) and 25% (range, 5 to 84%) in week 2 of lactation. Accounting for season and clustering at the herd level, cows with ketosis in week 1 were 1.5 times more likely (P=0.02) than non-ketotic animals to be classified as anestrus. Ketosis in the second week was not a significant risk factor. Other risk factors included displaced abomasum (OR 2.5; 95% CI 1.2 -5.0), twins (OR 2.1; 95% CI 1.1-3.9), and dystocia (OR 1.3, 95%CI 1.1 - 1.7). The risk of anestrus decreased as first DHI test projected 305ME increased to 9500 kg (OR= 0.9998/kg milk; p=0.03) while there was no change in the risk of anestrus associated with first projection > 9500 kg. Controlling for parity, season of calving and the impact of clustering at the farm level. Anovulatory cows were inseminated 3 days later than cycling animals (76 vs. 73; HR 0.8, p=0.03), and they were 40% less likely to conceive at first insemination (OR 0.6; 95% CI .42 - .83). Conception was delayed by 27 days (156 vs. 129) in anestrus cows. Anestrus animals were 1.4 times (95% CI 1.1 - 1.9) more likely to be culled than cycling cows at 60 DIM. [ABSTRACT FROM AUTHOR]