Estrous activity in nulliparous heifers with divergent genetic merit for fertility traits

This observational study determined the effect of genetic merit for fertility traits on estrous activity and duration and inter-estrous interval in nulliparous dairy heifers. We also compared estrous activity between estrous events with or without conception and determined the effect of genetic merit for fertility traits on age and body weight at time of first detected estrous activity event. Activity monitoring devices (Heatime, SCR Engineers) were fitted to 7-9-mo aged Holstein-Friesian heifers with positive or negative genetic merit for fertility traits (POS FertBV: average +5%, n = 275; NEG FertBV: average -5%, n = 249) and activity data was collected to the end of the first breeding period (15-17-mo). An estrous event was defined as when the activity change index exceeded 19.2 activity units (AU) for ≥6 consecutive h. In total, 2,434 estrous events were identified (POS FertBV: n = 1454; NEG FertBV: n = 980). Estrous event duration was defined as the period when the threshold was first exceeded and when activity dropped below threshold, without another event starting within 24 h of the end of the previous event. This definition included occurrences where activity crossed the threshold multiple times in a day; these were classified as a single estrous event. A second measure, high activity duration, was defined as the total time activity exceeded the threshold. To characterize estrous activity, baseline activity was determined from the previous 7 d of activity. Peak activity and total activity (area under the curve of activity above baseline) were calculated. A fifth variable, inter-estrous interval, was calculated as a proxy for estrous cycle length. Total activity and peak activity were greater in POS than NEG FertBV heifers (total activity: 548 vs 464 AU, SED = 19.6 AU; peak activity: 72 vs 65 AU, standard error of the difference (SED) = 1.5 AU). The POS FertBV group had a mean estrous event duration and high activity duration of 15.1 h and 15.0 h, compared with 14.1 and 14.1 h for the NEG FertBV group (SED = 0.30 and 0.29 h, respectively). Inter-estrous interval did not differ between POS and NEG FertBV heifers (19.5 vs 20.0 d, SED = 0.49). Estrous events associated with conception were shorter than those not associated with conception (mean ± standard error of the mean, high activity duration: 13.0 ± 0.25 h vs 13.9 ± 0.31 h, estrous event duration: 13.1 ± 0.25 h vs 14 ± 0.32 h) and had less total activity (408 ± 15.2 vs 487 ± 18.2 AU). The POS FertBV heifers were more likely to have their first estrous activity event than NEG FertBV heifers by a given age (HR = 1.26, 95% CI = 1.0 to 1.6) or body weight (HR = 1.35, 95% CI = 1.1 to 1.6). The outcomes of this study provide evidence that positive genetic merit for fertility traits is associated with more overt estrous expression. Therefore, estrous expression traits may have potential to be used as earlier-in-life predictors of genetic merit for fertility.

Association between body condition profiles, milk production and reproduction performance in Holstein and Normande cows

Body-condition dynamics are known to affect the different steps of reproduction in cattle (cyclicity, estrus expression, fertilization, embryo development). This has led to a widespread idea that there is an ideal-target optimal body condition, but no clear profile has yet been identified. Here we investigated the relationships between body condition score (BCS) profiles and reproductive performance in dairy cows. Data were from Holstein or Normande herds in 6 French experimental farms. In the Holstein breed, we discriminated 4 BCS profiles based on combining BCS at calving (Low: around 2.6 points, or High: around 3.3 points) with BCS loss after calving (Moderate (M): ≤ 1.0 points, or Severe (S): > 1.0 points). The Low-M profile mostly included multiparous cows with higher milk yield and lower reproductive performance than cows in the 3 other profiles. Low-M cows that experienced abnormal ovarian activity had lower reproductive performance than their profile-mates. Moreover, 67% of Low-M cows kept the same profile at the following lactation. The High-S profile mostly included primiparous cows with lower milk yield and higher reproductive performance than cows in other profiles. In High-S cows, higher milk yields correlated to higher risk of failure to calf on first insemination. Moreover, 38% of High-S cows kept the same profile at the following lactation, and none changed to Low-M. The other 2 BCS profiles (Low-S and High-M) were intermediate in terms of milk yield and reproductive performance. In Normande, we discriminated 3 BCS profiles based on combining BCS at calving (Low: around 2.6 points, or High: around 3.5 points) with BCS loss after calving (Flat (F): flat with no loss, Moderate (M): around 0.5 points, or Severe (S): around 1.0 point). The Low-M and High-S profiles included cows with similar performance, even though High-S-profile cows showed better but not significantly different milk yield and reproduction performance. The High-F profile included cows that were more likely to experience abnormal ovarian activity and fail at first insemination than cows in other profiles. More than 50% of Normande cows with 2 successive lactations kept in the same BCS profile at the next lactation. Even though a low BCS at calving combined with severe BCS loss (more than 1 point) after calving was found to increase reproductive failure, there was no evidence of an optimal BCS profile for reproduction in dairy cows, and reproductive success or failure is multifactorial.

Cow activity measurements can be used to define new fertility traits for use in genetic evaluation

Cow activity measurements are widely used in herd management tools for estrus detection. The aim of this study was to examine whether a new trait based on activity measures can be useful for genetic evaluation of cow fertility in Norwegian Red dairy cattle. Data from 284 herds with Lely milking robot were collected. Daily measurements of cow activity level were available from Lely activity tags and included data from 13,224 lactations of 8,139 Norwegian Red cows. We analyzed daily activity and included records from 10 to 150 d in milk for cows with at least 50 records. The trait analyzed was interval from calving to first high activity (CFHA). In total 87% of the cows had at least one episode of high activity recorded. The mean (standard deviation) of CFHA was 42 (28) days. A linear animal repeatability model with fixed effects of month-year of calving, age-parity, and herd, and random animal and permanent environment effects was used for estimation of variance components. The trait CFHA showed significant genetic variation with a heritability of 0.05 (0.01). This trait reflects the cow's ability to return to estrus cycle and show estrus after calving, which are important aspects of cow fertility.

Estrous activity in lactating cows with divergent genetic merit for fertility traits

This observational study aimed to determine the effect of genetic merit for fertility traits on estrous expression and estrous cycle duration in grazing dairy cows, as measured by an activity monitoring device. A secondary aim was to describe changes in expression of estrus that occur during successive estrous cycles postpartum. Neck-mounted, activity-monitoring devices (Heatime, SCR Engineers Ltd.) were fitted to nulliparous Holstein-Friesian heifers with positive (POS FertBV) or negative genetic merit for fertility traits (NEG FertBV) to capture activity data during their first and second lactations (POS FertBV: n = 242, n = 188; NEG FertBV: n = 159, n = 87 in lactation 1 and 2, respectively). An estrous event was identified when the activity change index exceeded 26 activity units (AU) for 4 h. A total of 1,254 and 892 estrous events were identified in lactation 1 and 2, respectively. Estrous duration was defined as the interval between when the threshold was first exceeded and when activity dropped below the threshold, with no new event starting within 24 h of the end of the previous event. This definition of estrus included cows in which activity crossed the threshold multiple times in a day and were classified as a single estrous event. A second measure, high activity duration, was defined as the total hours that activity exceeded the threshold. To characterize estrous activity, peak activity (above baseline) and total activity (area under the curve of activity above baseline) were measured. Compared with NEG FertBV cows, POS FertBV cows had more active, longer estrous events. In lactation 1, the POS FertBV group had a mean estrous duration and a high activity duration of 12.5 and 12.4 h compared with 11.4 and 11.3 h for the NEG FertBV group [standard error of the difference (SED) = 0.5 and 0.4 h, respectively]. This significant difference also occurred in lactation 2, with a mean estrous duration of 13.1 versus 11.8 h (SED = 0.5 h) and a high activity duration of 13.0 versus 11.8 h (SED = 0.4 h) in the POS and NEG FertBV groups, respectively. Total activity and peak activity were greater in the POS compared with the NEG FertBV group in lactation 1 (peak activity: 65.5 vs. 55.8 AU, SED = 2.4 AU; total activity: 588 vs. 494 AU, SED = 25 AU) and lactation 2 (peak activity: 72.5 vs. 61.2 AU, SED = 2.9 AU; total activity: 648 vs. 541 AU, SED = 30 AU). Estrous cycle duration did not differ between the POS and NEG FertBV groups (lactation 1: 20.4 vs. 20.6 d, SED = 0.25; lactation 2: 20.8 vs. 21.0 d, SED = 0.28). Less estrous activity of the cow was associated with the first postpartum estrus. In contrast, the number of previous estrous events did not consistently affect the duration of the subsequent estrous cycle. The outcomes of this study provide evidence that positive genetic merit for fertility traits is associated with more overt estrous expression. Selection for these traits may improve estrous expression and thus estrous detection in commercial herds.

Association of estrous expression detected by an automated activity monitoring system within 40 days in milk and reproductive performance of lactating Holstein cows

The objective of this observational study was to evaluate the association of estrous expression within 40 days in milk (DIM) using a neck-mounted automated activity monitor (Heatime Pro; SCR Engineers Ltd.) with reproductive performance in lactating Holstein cows. A total of 2,077 cows (614 primiparous cows and 1,463 multiparous cows) from 5 commercial dairy farms were included in the statistical analyses. Activity data from the first 7 d after calving were excluded. An estrus event was defined as an activity change index ≥35 for more than 2 h. Cows were classified according to the number of estrus events from d 7 until d 40 postpartum into 3 categories: (1) no estrus event (Estrus0); (2) one estrus event (Estrus1), and (3) 2 or more estrus events (Estrus2). Generalized linear mixed models were used to analyze continuous and categorical data. Shared frailty models were used for time to event data. Overall, 52.7% of cows had no estrus event detected by an automated activity monitor system from d 7 until d 40 postpartum. Herd level prevalence of Estrus0 ranged from 37.5 to 58.4%. Estrous expression from d 7 until d 40 postpartum affected estrous duration and estrous intensity at first artificial insemination (AI). Cows in Estrus0 had the shortest duration (13.2 ± 0.33 h) compared with cows in Estrus1 (13.8 ± 0.36 h) and Estrus2 (14.8 ± 0.41 h). Cows in Estrus2 had a longer estrous duration at first postpartum AI compared with cows in Estrus1. Among Estrus0 cows, 46.2% had an estrus event with high intensity at first postpartum AI. Among cows in Estrus1 and Estrus2, 50.8 and 53.8% had an estrus event with high intensity at first postpartum AI, respectively. There was a significant difference between Estrus2 and Estrus0 and a tendency between Estrus0 and Estrus1. There was no difference between Estrus1 and Estrus2. For Estrus0, Estrus1, and Estrus2 cows, pregnancy per AI was 29.4, 30.9, and 37.8%, respectively. There was a significant difference between Estrus0 and Estrus2 and Estrus1 and Estrus2. There was no difference between Estrus0 and Estrus1. Estrous expression from d 7 until d 40 postpartum affected time to first AI and time to pregnancy. Compared with Estrus0 cows, cows in Estrus1 [hazard risk (HR) = 1.74] and Estrus2 (HR = 1.77) had an increased hazard of being inseminated within 100 DIM. There was no difference between Estrus1 and Estrus2. Median DIM to first AI were 70, 59, and 58 for cows in Estrus0, Estrus1, and Estrus2, respectively. Compared with Estrus0 cows, cows in Estrus1 (HR = 1.28) and Estrus2 (HR = 1.33) had an increased hazard of becoming pregnant within 200 DIM. There was no difference between Estrus1 and Estrus2. Median DIM to pregnancy were 127, 112, and 103 for Estrus0 cows, Estrus1 and Estrus2, respectively. In conclusion, cows with no estrous expression from 7 to 40 DIM had reduced estrous expression at first AI and inferior reproductive performance compared with cows that displayed estrous activity.

Short communication: Simultaneous measurements of estrus behavior and plasma concentrations of estradiol during estrus in lactating and nonlactating dairy cows

Estrus is an important behavior that can potentially be subjected to genomic selection. Circulating estradiol concentrations at estrus may be a useful phenotype if the absolute concentrations of estradiol are associated with overt phenotypes for estrus (activity, rump touches, or both; e.g., mounts, chinrests) that can be easily observed. The objective was to measure plasma estradiol concentrations at estrus and associate these measurements with the increase in activity (steps per hour) and rump touches received at estrus. We also tested the effect of lactation on the estrus traits that we measured. Cows (n = 11 lactating and n = 9 nonlactating) were treated with PGF_2α to synchronize estrus. A jugular vein was cannulated to collect blood every 2 h for plasma estradiol measurement. Plasma LH was measured during the periestrual period to determine the time of the LH surge. Cows were fitted with an accelerometer to measure activity (steps per hour) and a capacitive touch sensing device to measure the number of rump touches and total touch time. Plasma estradiol concentrations were poorly correlated with overt signs of estrus during the period leading up to maximum estrus activity. After peak estrus activity (when cows were going out of estrus and plasma estradiol concentrations were decreasing), a stronger correlation was detected between overt signs of estrus and plasma estradiol concentrations. Effective selection for improved estrus expression based on plasma estradiol concentrations will depend on whether the cow is coming into or going out of estrus at the time of blood sampling. An association existed between lactation and fewer number of hours in estrus when estrus was defined by an increase in activity (steps per hour). Lactating cows had a shorter interval from the onset of estrus to the LH surge, and the shorter interval to the LH surge may have reduced the period of elevated estradiol during estrus in the lactating cows. Understanding mechanisms that control the sensitivity of the cow to estradiol and making appropriate selection decisions based on these mechanisms will likely increase overt signs of estrus in dairy cows.

Estimates of intra- and interclass correlation coefficients for rump touches and the number of steps during estrus in postpartum cows

Estrus traits have economic value in dairy production systems and could be incorporated into genetic selection indices. In an effort to further understand selection responses, 2 studies were performed to estimate the intra- and interclass correlation coefficients for estrus traits. Holstein-Friesian cows (n = 1,197; study 1) across 5 pasture-based grazing dairy herds were fitted with a capacitive touch sensing (CTS) device on the rump (FlashMate, Farmshed Labs Limited, Hamilton, New Zealand). The daily number of rump touches were subjected to a peak detection program to objectively identify periods of increased rump touches above baseline (indicative of estrus). The number of times touched and the sum of the touch duration were used to compare farms and estimate the intraclass correlation (repeatability). For study 2, postpartum Holstein (n = 85) and Guernsey (n = 5) cows in a confinement-style dairy were used. Cows were fitted with an IceQube accelerometer (IceRobotics Ltd., Edinburgh, United Kingdom) to measure steps taken per hour and a CTS device was applied to both rumps. The interclass correlation for the number of rump touches and number of steps taken during estrus was calculated. Data collected from 5 herds (study 1) demonstrated a 2- to 3-fold difference between herds in the number of rump touches and total touch time during estrus. The intraclass correlation (repeatability; estimates of maximum heritability) for rump touches during estrus was 0.22. For study 2, the number of steps and the number of rump touches during estrus increased in a synchronous manner. The intraclass correlation (repeatability) for number of steps during estrus was 0.26. The interclass correlation (r) for the number of rump touches and the number of steps was 0.46 (R² = 0.21). Based on the R², at least 20% of the variation in the number of steps during estrus was explained by the number of touches to the rump of the cow. Selecting cows for the number of steps taken during estrus could increase the number of rump touches (mounts, chin rests, and so on, received from other cows) if a genetic correlation exists for the phenotypic correlation that we observed.

Hemodynamic changes evaluated by Doppler ultrasonographic technology in the ovaries and uterus of dairy cattle after the puerperium

The present detailed study aimed to establish for the first time the ovarian and uterine hemodynamic change in dairy cows after the end of the puerperal period to investigate a possible association between Doppler indices and volume of blood flow. Twenty cows weighing 500-600 kg (mean 400 ± 50 kg) and 4-5 years of age (mean 3.2 ± 0.5 years) categorized into two main groups (true anestrum, with corpus luteum, n = 10) and (normal cyclic, n = 10), The period of examination started from day 39 till day 70 after calving with day after day routinely examination by b-mode and Doppler performed on both ovaries with ovarian arteries (OA) and uterus with uterine arteries (MUA) in the ipsilateral (ipsi) and contralateral (contra) side to ovulation, in addition to a thickness in horns and body was measured. Estradiol and progesterone were also measured. Results showed that both Doppler indices in the OA and MUA ipsi and contra had a positive (P ≤ 0.001) correlation with contra Doppler indices, but revealed a negative (P ≤ 0.05) correlation with ipsi and contra Doppler velocities, blood flow rate and volume in anestrum cows. Both ovarian and uterine ipsi indices showed an increase (P ≤ 0.05) in the anestrum cows, and both PSV and EDV of both arteries ipsilateral showed (P ≤ 0.05) a decrease in the anestrum cows, the ipsi and contra ovarian and uterine colored % were lower in anestrum group than the normal group. Estradiol (P ≤ 0.05) decreased in anestrum cows than the normal, while progesterone increased in the anestrum group. Conclusion, although uterine and ovarian morphology were changed in anestrum cows, the vascular system of the ovary as well as uterus underwent much more marked vascular changes, the most significant being that of blood flow velocities and volume.

Genome-wide association mapping for dominance effects in female fertility using real and simulated data from Danish Holstein cattle

Exploring dominance variance and loci contributing to dominance variation is important to understand the genetic architecture behind quantitative traits. The objectives of this study were i) to estimate dominance variances, ii) to detect quantitative trait loci (QTL) with dominant effects, and iii) to evaluate the power and the precision of identifying loci with dominance effect through post-hoc simulations, with applications for female fertility in Danish Holstein cattle. The female fertility records analyzed were number of inseminations (NINS), days from calving to first insemination (ICF), and days from the first to last insemination (IFL), covering both abilities to recycle and to get pregnant in the female reproductive cycle. There were 3,040 heifers and 4,483 cows with both female fertility records and Illumina BovineSNP50 BeadChip genotypes (35,391 single nucleotide polymorphisms (SNP) after quality control). Genomic best linear unbiased prediction (BLUP) models were used to estimate additive and dominance genetic variances. Linear mixed models were used for association analyses. A post-hoc simulation study was performed using genotyped heifers’ data. In heifers, estimates of dominance genetic variances for female fertility traits were larger than additive genetic variances, but had large standard errors. The variance components for fertility traits in cows could not be estimated due to non-convergence of the statistical model. In total, five QTL located on chromosomes 9, 11 (2 QTL), 19, and 28 were identified and all of them showed both additive and dominance genetic effects. Among them, the SNP rs29018921 on chromosome 9 is close to a previously identified QTL in Nordic Holstein for interval between first and last insemination. This SNP is located in the 3’ untranslated region of gene peptidylprolyl isomerase like 4 (PPIL4), which was shown to be associated with milk production traits in US Holstein cattle but not known for fertility-related functions. Simulations indicated that the current sample size had limited power to detect QTL with dominance effects for female fertility probably due to low QTL variance. More females need to be genotyped to achieve reliable mapping of QTL with dominance effects for female fertility.

Multi-breed genome-wide association studies across countries for electronically recorded behavior traits in local dual-purpose cows

Basic bovine behavior is a crucial parameter influencing cattle domestication. In addition, behavior has an impact on cattle productivity, welfare and adaptation. The aim of the present study was to infer quantitative genetic and genomic mechanisms contributing to natural dual-purpose cow behavior in grazing systems. In this regard, we genotyped five dual-purpose breeds for a dense SNP marker panel from four different European countries. All cows from the across-country study were equipped with the same electronic recording devices. In this regard, we analyzed 97,049 longitudinal sensor behavior observations from 319 local dual-purpose cows for rumination, feeding, basic activity, high active, not active and ear temperature. According to the specific sensor behaviors and following a welfare protocol, we computed two different welfare indices. For genomic breed characterizations and multi-breed genome-wide association studies, sensor traits and test-day production records were merged with 35,826 SNP markers per cow. For the estimation of variance components, we used the pedigree relationship matrix and a combined similarity matrix that simultaneously included both pedigree and genotypes. Heritabilities for feeding, high active and not active were in a moderate range from 0.16 to 0.20. Estimates were very similar from both relationship matrix-modeling approaches and had quite small standard errors. Heritabilities for the remaining sensor traits (feeding, basic activity, ear temperature) and welfare indices were lower than 0.09. Five significant SNPs on chromosomes 11, 17, 27 and 29 were associated with rumination, and two different SNPs significantly influenced the sensor traits “not active” (chromosome 13) and “feeding” (chromosome 23). Gene annotation analyses inferred 22 potential candidate genes with a false discovery rate lower than 20%, mostly associated with rumination (13 genes) and feeding (8 genes). Mendelian randomization based on genomic variants (i.e., the instrumental variables) was used to infer causal inference between an exposure and an outcome. Significant regression coefficients among behavior traits indicate that all specific behavioral mechanisms contribute to similar physiological processes. The regression coefficients of rumination and feeding on milk yield were 0.10 kg/% and 0.12 kg/%, respectively, indicating their positive influence on dual-purpose cow productivity. Genomically, an improved welfare behavior of grazing cattle, i.e., a higher score for welfare indices, was significantly associated with increased fat and protein percentages.

Genomic merit for reproductive traits. I: Estrous characteristics and fertility in Holstein heifers

Genetic selection of dairy cattle in the United States has included reproductive traits (daughter pregnancy rate, DPR; heifer conception rate, HCR), which is believed to have partly contributed to halting the decline in reproductive performance. The objectives of the current study were to evaluate the association among genomic merit for DPR (GDPR) and HCR (GHCR) with estrous characteristics measured by an automated device. Holstein heifers (n = 1,005) were genotyped at 2 mo of age and were classified into quartiles (Q1 = lowest, Q4 = highest) according to the GDPR and GHCR values of the study population. At 10 to 11 mo of age, heifers were fitted with a collar that recorded activity and rumination and determined the occurrence of estrus according to changes in activity and rumination compared with the individual's baseline values. Estrous characteristics of spontaneous estruses (SPE) and PGF_2α-synchronized estruses (PGSE) were recorded. Heifers had their estrous cycle synchronized with PGF_2α and following detection of estrus received either artificial insemination or embryo transfer according to the herd's genetic selection program. Heifers in Q2 (17.7 ± 0.3 h) of GHCR tended to have longer SPE than heifers in Q4 (16.7 ± 0.3 h). The interaction between GDPR and GHCR was associated with the likelihood of activity peak (0 = no estrus, 100 = maximum activity) ≥80 at SPE because, among heifers in Q3 and Q4 of GHCR, those in Q1 of GDPR were less likely to have an activity peak ≥80. Heifers in Q1 and Q2 of GDPR had reduced hazard of estrus within 7 d of the first PGF_2α treatment compared with heifers in Q4 of GDPR. Heifers in Q1 (16.1 ± 0.4 h) of GDPR had shorter PGSE than heifers in Q2 (17.6 ± 0.4 h) and Q4 (17.4 ± 0.4 h) and tended to have shorter PGSE than heifers in Q3 (17.4 ± 0.4 h). Rumination nadir on the day of PGSE was greater for heifers in Q1 (-30.1 ± 0.9 min/d) of GDPR compared with heifers in Q4 (-33.7 ± 0.9 min/d). Among heifers receiving only artificial insemination, those in Q1 of GHCR (adjusted hazard ratio = 0.65; 95% confidence interval = 0.48-0.88) became pregnant at a slower rate than heifers in Q4. Genomic merit for HCR was negatively associated with SPE but tended to be positively associated with hazard of pregnancy, whereas GDPR was positively associated with PGSE and hazard of estrus. Selection of dairy cattle for DPR and HCR may improve reproductive performance through different pathways, namely estrous characteristics and pregnancy establishment.

Symposium review: The choice and collection of new relevant phenotypes for fertility selection

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Inline Progesterone Monitoring in the Dairy Industry

An inline progesterone monitoring system that works automatically and provides real-time physiological information about lactating dairy cows for making farm management decisions is not only a novel tool for scientific research but also improves productivity, food safety, animal well-being, the environment, and the public perception of the dairy industry.

Genotype by environment interaction for activity-based estrus traits in relation to production level for Danish Holstein

The objective of this study was to investigate whether genotype by environment interaction exists for female fertility traits and production of energy-corrected milk at 70d in milk (ECM70). Fertility traits considered were the activity-based estrus traits interval from calving to first high activity (CFHA), duration of high activity episode (DHA), as an indicator for first estrus duration, and strength of high activity episode (SHA), as an indicator for first estrus strength. The physical activity traits were derived from electronic activity tags for 11,522 first-parity cows housed in 125 commercial dairy herds. Data were analyzed using a univariate random regression animal model (URRM), by regressing the phenotypic performance on the average herd ECM70 as an environmental gradient. Furthermore, the genetic correlations between CFHA and ECM70 as a function of production level were estimated using a bivariate random regression animal model (BRRM). For all traits, heterogeneity of additive genetic variances and heritability estimates was observed. The heritability estimate for CFHA decreased from 0.25 to 0.10 with increasing production level and the heritability estimate for ECM70 decreased from 0.35 to 0.15 with increasing production level using URRM. The genetic correlation of the same trait in low and high production levels was around 0.74 for CFHA and 0.80 for ECM70 using URRM, but when data were analyzed using the multiple-trait analysis (MT), genetic correlation estimates between low and high production levels were not significantly different from unity. Furthermore, the genetic correlation of SHA between low and high production level was 0.22 using URRM, but the corresponding correlation estimate had large standard error when data were analyzed using MT. The genetic correlation between CFHA and ECM70 as a function of production environment was weak but unfavorable and decreased slightly from 0.09 to 0.04 with increasing production level using BRRM. Moreover, the same trend was observed when the data were analyzed using MT where the genetic correlation between CFHA and ECM70 in the low production environment was 0.29 compared with -0.13 in the high production environment, but these estimates had large standard errors. In conclusion, regardless of the trait used, in relation to average herd ECM70 production, the results indicated no clear evidence of strong genotype by environment interaction that would cause significant re-ranking of sires between low and high production environments.