Comparison of sheep and dairy cows for in vivo digestibility of perennial ryegrass

Sheep are often used as a proxy for dairy cows when measuring the digestibility of a feed. In recent years grassland management guidelines for ruminant animals have been re-evaluated in accordance with the progression in animal genetics and the acknowledgement that genetic potential has an influence on both feed intake and digestibility. Recommended pre-grazing herbage mass (HM) targets are now much lower with improved perennial ryegrass varieties available for grazing swards. The objective of this study was to compare the in vivo digestibility of perennial ryegrass in wether sheep and lactating dairy cows. The experimental design was selected to measure the effect of animal species (cows, sheep), sward HM measured cutting herbage at 4 cm above ground level (low: 1 700 kg DM/ha and high: 4 000 kg DM/ha) and season (Spring: Apr–May, Summer: Jul–Aug) on the digestibility of perennial ryegrass. Each HM treatment was offered to each animal within species and season for 12 d using a 2 HM × 2 period changeover Latin square design. There were eight cows and eight sheep, so there were four 2 × 2 Latin squares for each animal species (two) at each season (two), giving 64 observations. During each 12 d experimental period, the first 6 d were used for adaptation (adaptation phase) and the final 6 d were used for measurement (measurement phase). In vivo organic matter digestibility (OMD) in spring did not differ between animal species but in summer sheep had higher in vivo OMD than cows. The results described herein highlight the suitability of wether sheep as an alternative to dairy cows for determining the digestibility of perennial ryegrass in spring but not in summer. Stage of growth of the plant, which is intrinsically linked to season, should be considered as results show that digestibility in the ruminant was affected by season but not differentially affected by changing sward HM.     

An approximate multitrait model for genetic evaluation in dairy cattle with a robust estimation of genetic trends (Open Access publication)

In a stochastic simulation study of a dairy cattle population three multitrait models for estimation of genetic parameters and prediction of breeding values were compared. The first model was an approximate multitrait model using a two-step procedure. The first step was a single trait model for all traits. The solutions for fixed effects from these analyses were subtracted from the phenotypes. A multitrait model only containing an overall mean, an additive genetic and a residual term was applied on these preadjusted data. The second model was similar to the first model, but the multitrait model also contained a year effect. The third model was a full multitrait model. Genetic trends for total merit and for the individual traits in the breeding goal were compared for the three scenarios to rank the models. The full multitrait model gave the highest genetic response, but was not significantly better than the approximate multitrait model including a year effect. The inclusion of a year effect into the second step of the approximate multitrait model significantly improved the genetic trend for total merit. In this study, estimation of genetic parameters for breeding value estimation using models corresponding to the ones used for prediction of breeding values increased the accuracy on the breeding values and thereby the genetic progress.     

Genetic evaluation of Ethiopian Boran cattle and their crosses with Holstein Friesian in central Ethiopia: milk production traits

Breed additive and non-additive effects, and genetic parameters of lactation milk yield (LYD), 305-day milk yield (305YD), lactation length (LL), milk yield per day of lactation (DM) and lifetime milk yield (LTYD) were estimated in Ethiopian Boran cattle and their crosses with Holstein in central Ethiopia. The data analyzed included 2360 lactation records spread over 15 years. Ethiopian Boran cattle were consistently inferior (P < 0.01) to the Ethiopian Boran-Holstein crosses for the dairy traits studied. When the crosses were compared, LYD, 305YD and DM were higher (P < 0.01) for 75% and 87.5% crosses compared to 50% and 62.5% ones. However, the 50% crosses had higher (P < 0.01) LTYD than the other genetic groups. The individual additive genetic breed differences for milk production traits were all significant (P < 0.01). The estimates, in favor of Holstein, were 2055 ± 192 kg for LYD, 1776 ± 142 kg for 305YD, 108 ± 24 days for LL, 5.9 ± 0.5 kg for DM and 3353 ± 1294 kg for LTYD. Crossbreeding of the Holstein with the Ethiopian Boran resulted in desirable and significant (P < 0.01) individual heterosis for all milk production traits. The heterosis estimates were, 529 ± 98, 427 ± 72 kg, 44 ± 12 days 1.47 ± 0.23 kg and 3337 ± 681 kg, for LYD, 305YD, LL, DM and LTYD, respectively. The maternal heterotic effects were non-significant (P > 0.05) for all traits. Heritabilities of LYD, 305YD, LL, DM and LTYD for Ethiopian Boran were 0.20 ± 0.03, 0.18 ± 0.03, 0.26 ± 0.03, 0.13 ± 0.03 and 0.02 ± 0.04, respectively. The corresponding estimates for crosses were 0.10 ± 0.002, 0.11 ± 0.003, 0.63 ± 0.02, 0.45 ± 1.05 and 0.24 ± 0.11, respectively. Selection within each of the genetic groups and crossbreeding should substantially improve the milk production potential of the Ethiopian Boran breed under such production system.     

Developing a predictive model for the energy content of goat milk as the basis for a functional unit formulation to be used in the life cycle assessment of dairy goat production systems

Recent reports on livestock environmental impact based on life cycle assessment (LCA) did not fully consider the case of the dairy goat. Assignment of an environmental impact (e.g. global warming potential) to a specific product needs to be related to the appropriate ‘unitary amount’ or functional unit (FU). For milk, the energy content may provide a common basis for a definition of the FU. To date, no ad hoc formulations for the FU of goat milk have been proposed. For these reasons, this study aimed to develop and test one or more predictive models (DPMs) for the gross energy (GE) content of goat milk, based on published compositional data, such as fat (F), protein, total solids (TS), solid non-fat matter (SNF), lactose (Lac) and ash. The DPMs were developed, selected and tested using a linear regression approach, as a meta-analysis (i.e. meta-regression) was not applicable. However, in the final stage, a control procedure for spurious findings was carried out using a Monte Carlo permutation test. Because several published predictive models (PPMs) for GE in cow milk and goat milk were found in the literature, they were tested on the same data set with which the DPMs were developed. The best-performing DPMs and PPMs were compared directly with a subset of the individual data retrieved from the literature. Overall, the paucity of direct measurements of the GE in goat milk was a limiting factor in collecting data from the literature; thus, only a small data set (n=26) was established, even though it was considered sufficiently representative of milks from different goat breeds. The three best PPMs based on F alone gave more biased estimates of the GE content of the goat milk than the three new DPMs based on F, F and SNF and F and TS, respectively. Accordingly, three different formulations of FU are proposed, depending on the availability of data including both F and TS (or F and SNF) or F alone. Even though several metrics can be used in defining the FU for milk to be used in LCAs of goat farming systems, the proposed FU formulations should be adopted in place of the similar energy-based ones developed for other dairy species.     

Alkaline pre-treatment of oilseed rape straw for bioethanol production: evaluation of glucose yield and pre-treatment energy consumption

The objective of the research was to investigate the effect of biomass loading, alkali (NaOH) concentration and pre-treatment time on the yield of glucose obtained following alkaline pre-treatment and enzymatic hydrolysis of oilseed rape (OSR) straw. A maximum glucose yield of (440.6 ± 14.9) g glucose kg⁻¹ biomass was obtained when OSR straw was pre-treated at a biomass loading of 50 g kg⁻¹ and an alkali concentration of 0.63 mol dm⁻³ NaOH for 30 min. The energy efficiency of glucose extraction (0.39 kg glucose MJ⁻¹ consumed) was highest when OSR straw was pre-treated at a biomass loading of 50 g kg⁻¹ and an alkali concentration of 0.63 or 0.75 mol dm⁻³ for 30 min. The study demonstrated alkaline pre-treatment of OSR straw is superior to acid pre-treatment in terms of glucose yield and energy efficiency.     

Genotype by production environment interaction for birth and weaning weights in a population of composite beef cattle

The objectives of the present study were: (1) to evaluate the importance of genotype×production environment interaction for the genetic evaluation of birth weight (BW) and weaning weight (WW) in a population of composite beef cattle in Brazil, and (2) to investigate the importance of sire×contemporary group interaction (S×CG) to model G×E and improve the accuracy of prediction in routine genetic evaluations of this population. Analyses were performed with one, two (favorable and unfavorable) or three (favorable, intermediate, unfavorable) different definitions of production environments. Thus, BW and WW records of animals in a favorable environment were assigned to either trait 1, in an intermediate environment to trait 2 or in an unfavorable environment to trait 3. The (co)variance components were estimated using Gibbs sampling in single-, bi- or three-trait animal models according to the definition of number of production environments. In general, the estimates of genetic parameters for BW and WW were similar between environments. The additive genetic correlations between production environments were close to unity for BW; however, when examining the highest posterior density intervals, the correlation between favorable and unfavorable environments reached a value of only 0.70, a fact that may lead to changes in the ranking of sires across environments. The posterior mean genetic correlation between direct effects was 0.63 in favorable and unfavorable environments for WW. When S×CG was included in two- or three-trait analyses, all direct genetic correlations were close to unity, suggesting that there was no evidence of a genotype×production environment interaction. Furthermore, the model including S×CG contributed to prevent overestimation of the accuracy of breeding values of sires, provided a lower error of prediction for both direct and maternal breeding values, lower squared bias, residual variance and deviance information criterion than the model omitting S×CG. Thus, the model that included S×CG can therefore be considered the best model on the basis of these criteria. The genotype×production environment interaction should not be neglected in the genetic evaluation of BW and WW in the present population of beef cattle. The inclusion of S×CG in the model is a feasible and plausible alternative to model the effects of G×E in the genetic evaluations.     

Adaptation and evaluation of the GrazeIn model of grass dry matter intake and milk yield prediction for grazing dairy cows

The prediction of grass dry matter intake (GDMI) and milk yield (MY) are important to aid sward and grazing management decision making. Previous evaluations of the GrazeIn model identified weaknesses in the prediction of GDMI and MY for grazing dairy cows. To increase the accuracy of GDMI and MY prediction, GrazeIn was adapted, and then re-evaluated, using a data set of 3960 individual cow measurements. The adaptation process was completed in four additive steps with different components of the model reparameterised or altered. These components were: (1) intake capacity (IC) that was increased by 5% to reduce a general GDMI underprediction. This resulted in a correction of the GDMI mean and a lower relative prediction error (RPE) for the total data set, and at all stages of lactation, compared with the original model; (2) body fat reserve (BFR) deposition from 84 days in milk to next calving that was included in the model. This partitioned some energy to BFR deposition after body condition score nadir had been reached. This reduced total energy available for milk production, reducing the overprediction of MY and reducing RPE for MY in mid and late lactation, compared with the previous step. There was no effect on predicted GDMI; (3) The potential milk curve was reparameterised by optimising the rate of decrease in the theoretical hormone related to secretory cell differentiation and the basal rate of secretory cell death to achieve the lowest possible mean prediction error (MPE) for MY. This resulted in a reduction in the RPE for MY and an increase in the RPE for GDMI in all stages of lactation compared with the previous step; and (4) finally, IC was optimised, for GDMI, to achieve the lowest possible MPE. This resulted in an IC correction coefficient of 1.11. This increased the RPE for MY but decreased the RPE for GDMI compared with the previous step. Compared with the original model, modifying this combination of four model components improved the prediction accuracy of MY, particularly in late lactation with a decrease in RPE from 27.8% in the original model to 22.1% in the adapted model. However, testing of the adapted model using an independent data set would be beneficial and necessary to make definitive conclusions on improved predictions.     

LiGAPS-Beef,a mechanistic model to explore potential and feed-limited beef production 2: sensitivity analysis and evaluation of sub-models

The model LiGAPS-Beef (Livestock simulator for Generic analysis of Animal Production Systems – Beef cattle) has been developed to assess potential and feed-limited growth and production of beef cattle in different areas of the world and to identify the processes responsible for the yield gap. Sensitivity analysis and evaluation of model results with experimental data are important steps after model development. The first aim of this paper, therefore, is to identify which parameters affect the output of LiGAPS-Beef most by conducting sensitivity analyses. The second aim is to evaluate the accuracy of the thermoregulation sub-model and the feed intake and digestion sub-model with experimental data. Sensitivity analysis was conducted using a one-at-a-time approach. The upper critical temperature (UCT) simulated with the thermoregulation sub-model was most affected by the body core temperature and parameters affecting latent heat release from the skin. The lower critical temperature (LCT) and UCT were considerably affected by weather variables, especially ambient temperature and wind speed. Sensitivity analysis for the feed intake and digestion sub-model showed that the digested protein per kg feed intake was affected to a larger extent than the metabolisable energy (ME) content. Sensitivity analysis for LiGAPS-Beef was conducted for ¾ Brahman×¼ Shorthorn cattle in Australia and Hereford cattle in Uruguay. Body core temperature, conversion of digestible energy to ME, net energy requirements for maintenance, and several parameters associated with heat release affected feed efficiency at the herd level most. Sensitivity analyses have contributed, therefore, to insight which parameters are to be investigated in more detail when applying LiGAPS-Beef. Model evaluation was conducted by comparing model simulations with independent data from experiments. Measured heat production in experiments corresponded fairly well to the heat production simulated with the thermoregulation sub-model. Measured ME contents from two data sets corresponded well to the ME contents simulated with the feed intake and digestion sub-model. The relative mean absolute errors were 9.3% and 6.4% of the measured ME contents for the two data sets. In conclusion, model evaluation indicates the thermoregulation sub-model can deal with a wide range of weather conditions, and the feed intake and digestion sub-model with a variety of feeds, which corresponds to the aim of LiGAPS-Beef to simulate cattle in different beef production systems across the world.     

Comparison of three systems for predicting the digestible energy value of natural grassland and lucerne hays for horses

The accuracy and precision of the National Research Council (NRC), Gesellschaft für Ernährungsphysiologie (GfE) and Institut National de la Recherche Agronomique (INRA) systems for predicting the digestible energy (DE) value of hays were determined from the results of 15 digestibility trials with natural grassland hays and 9 digestibility trials with lucerne hays that all met strict experimental and a tight corpus of methods. The hays were harvested in the temperate zone. They covered broad ranges of chemical composition and DE value. The INRA system was more accurate than the other two systems, with the bias between the predicted and measured DE values of natural grassland and lucerne hays averaging −0.11 and −0.04 MJ/kg DM with the INRA system, 0.34 and −0.70 MJ/kg DM with the NRC system and −0.50 and −1.69 MJ/kg DM with the GfE system (P < 0.05). However, the precision of the three systems was similar; the standard error of prediction corrected by bias was not significantly different (P > 0.05). The GfE system underestimated the DE value of hays, especially of lucerne hays. The differences between the predicted and measured DE values resulted mainly from the errors in the prediction of organic matter digestibility and energy digestibility for both natural grassland and lucerne hays. Discrimination according to botanical family (grassland v. lucerne) can help improve the prediction of the DE value of hays. The choice of appropriate predictive variables is discussed in the light of differences in chemical composition and digestibility of the various cell wall components of grassland and lucerne hays. Neutral detergent fiber (NDF) may thus be preferable to ADF in the prediction equation of the DE value of lucerne hays, whereas ADF and NDF may both be relevant for natural grassland hays.     

Detection of QTL for milk production traits in cattle by application of a specifically developed marker map of BTA6

Interval mapping was carried out to identify quantitative trait loci (QTL) for milk production traits in five granddaughter design families of the German Holstein population. Fourteen randomly generated markers spanning the whole of BTA6 and six targeted microsatellite markers from BTA6q21-31 were included in the analysis. In one family a QTL with effects on milk fat yield and milk protein yield was mapped to the interval TGLA37-FBN13 (3 CM proximal to FBN13, lodscore 3.22) in the middle part of the chromosome. Although there are several reports about QTL with effects on milk production traits on BTA6 in the literature, a QTL with effects on milk fat and milk protein yield has not been previously described.     

Genotype by environment interaction due to heat stress during gestation and postpartum for milk production of Holstein cattle

Remarkable increases in the production of dairy animals have negatively impacted their tolerance to heat stress (HS). The evaluation of the effect of HS on milk yield is based on the direct impact of HS on performance. However, in practical terms, HS also exerts its influence during gestation (indirect effect). The main purpose of this study was to identify and characterize the genotype by environment interaction (G × E) due to HS during the last 60 days of gestation (THI_g) and also the HS postpartum (THI_m) over first lactation milk production of Brazilian Holstein cattle. A total of 389 127 test day milk yield (TD) records from 1572 first lactation Holstein cows born in Brazil (daughters of 1248 dams and 70 sires) and the corresponding temperature–humidity index (THI) obtained between December 2007 and January 2013 were analyzed using different random regression models. Cows in the cold environment (THI_g = 64 to 73) during the last 60 days of gestation produced more milk than those cows in a hot environment (THI_g = 74 to 84), particularly during the first 150 days of lactation (DIM). The heritabilities (h²) of TD were similar throughout DIM for cows in THI_g hot (0.11 to 0.20) or (0.10 to 0.22), while the genetic correlations (r_g) for TD between these two environments ranged from 0.11 to 0.52 along the first 250 DIM. The h² estimates for TD across THI_m were similar for cows in THI_g hot (0.07 to 0.25) and THI_g cold (0.08 to 0.19). The r_g estimates ranged from 0.17 to 0.42 along THI_m between TD of cows in cold and hot THI_g. The results were consistent in demonstrating the existence of an additional source of G × E for TD due to THI_g and THI_m. The present study is probably the first to provide evidence of this source of G × E; further research is needed because of its importance when the breeding objective is to select animals that are more tolerant to HS.     

A teleonomic model describing performance (body, milk and intake) during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. 2. Voluntary intake and energy partitioning

This is the second of two papers describing a teleonomic model of individual performance during growth and over repeated reproductive cycles throughout the lifespan of dairy cattle. The model described in the first paper is based on the coupling of a regulating sub-model of the dynamic partitioning of a female mammal's priority over a lifetime with an operating sub-model of whole-animal performance. The model provides a reference pattern of performance under normal husbandry and feed regimen, which is expressed in this paper in a reference dynamic pattern of energy partitioning adapted to changes in nutrient supply. This paper deals with the representation of deviations from the reference pattern of performance. First, a model of intake regulation, accounting for feed allowance, physical limitation of the digestive tract and energy demand, is used to determine the actual intake, which may generate a deviation from the energy input under the reference pattern of partitioning. Second, a theoretical model is proposed to apportion the energy deviation between flows involved in performance and thus simulate lifetime performance when actual intake is above or below requirements. The model explicitly involves a homeorhetic drive by way of the tendency to home on to the teleonomic trajectory and a homeostatic control by way of the tendency to maintain an energy equilibrium in response to nutritional constraints. The model was evaluated through simulations reproducing typical feeding trials in dairy cows. Model simulations shown in graphs concern the effect of dietary energy content on intake, body weight and condition score, and milk yield. Results highlight the ability of the model to simulate the combination of physical and energetic regulation of intake, the accelerated, retarded and compensatory patterns of growth and the short- and long-term residual effects of pre-partum feeding on lactation.     

Assessment of a dry and a wet route for the production of biofuels from microalgae: energy balance analysis

In this study, the energy balance of two microalgae-to-biofuel concepts, one via a so called “dry route” (oil extraction from dried algae) and one via a “wet route” (oil extraction in the water phase), are assessed. Both routes are intended to convert the chemical energy contained in the microalgae into high-value biofuels with minimal fossil energy consumption. The analysis shows that the drying process in the dry route and the oil extraction process in the wet route consume a significant amount of energy. By coupling waste heat from a nearby power plant to the process, the energy balance can be improved and a potential fossil energy ratio (FER) up to 2.38 and 1.82 can be reached for the dry and wet route, respectively. The results indicate that based on current available technologies, the dry route has higher FER and the wet route has more potential in producing high valuable biofuels.     

气雾攻击法感染结核病小鼠模型的建立及其综合评价

目的 模拟自然感染方式建立结核病小鼠模型,并对其病理变化进行综合评价.方法 通过气雾攻击方式将结核分枝杆菌H37Rv接种至C57BL/6J小鼠体内.在感染后的4周、6周、8周对小鼠进行micro-CT活体动态扫描,无菌分离肺脏和脾脏,肉眼观察病变情况,活菌菌落计数,组织病理检测(HE和抗酸染色).结果 肉眼观察和micro-CT扫描发现,不同时间小鼠肺部感染情况逐渐加重,至感染后第8周时病变弥漫至整个肺部;HE染色肺组织出现弥漫性肉芽肿样实变;抗酸染色可见结核分枝杆菌.结论 通过大体病变、病理、影像、菌落计数几个方面对建立的小鼠模型进行综合分析,证明利用气雾攻击法感染的结核病小鼠模型建立成功;该模型在形成病变时与结核患者的情况存在一定差异,对其完善的综合评价有助于在相关研究中对该小鼠模型的合理应用.     

Design of a data model for developing laboratory information management and analysis systems for protein production

Data management has emerged as one of the central issues in the high-throughput processes of taking a protein target sequence through to a protein sample. To simplify this task, and following extensive consultation with the international structural genomics community, we describe here a model of the data related to protein production. The model is suitable for both large and small facilities for use in tracking samples, experiments, and results through the many procedures involved. The model is described in Unified Modeling Language (UML). In addition, we present relational database schemas derived from the UML. These relational schemas are already in use in a number of data management projects.     

Empirical evaluation of selective DNA pooling to map QTL in dairy cattle using a half-sib design by comparison to individual genotyping and interval mapping

This study represents the first attempt at an empirical evaluation of the DNA pooling methodology by comparing it to individual genotyping and interval mapping to detect QTL in a dairy half-sib design. The findings indicated that the use of peak heights from the pool electropherograms without correction for stutter (shadow) product and preferential amplification performed as well as corrected estimates of frequencies. However, errors were found to decrease the power of the experiment at every stage of the pooling and analysis. The main sources of errors include technical errors from DNA quantification, pool construction, inconsistent differential amplification, and from the prevalence of sire alleles in the dams. Additionally, interval mapping using individual genotyping gains information from phenotypic differences between individuals in the same pool and from neighbouring markers, which is lost in a DNA pooling design. These errors cause some differences between the markers detected as significant by pooling and those found significant by interval mapping based on individual selective genotyping. Therefore, it is recommended that pooled genotyping only be used as part of an initial screen with significant results to be confirmed by individual genotyping. Strategies for improving the efficiency of the DNA pooling design are also presented.     

Effect of a negative energy balance induced by feed restriction in lactating sows on hepatic lipid metabolism,milk production and development of litters

In rodents, forced activation of hepatic peroxisome proliferator-activated receptor α (PPARα) by administration of exogenous PPARα activators during lactation leads to a reduction of milk triacylglycerol (TAG) production. Herein, we investigated whether a negative energy balance (NEB) induced by feed restriction (about 18% lower feed and energy intake) during lactation by increasing the release of fatty acids, which act as PPARα agonists, causes a disruption of hepatic lipid metabolism and thereby impairs milk TAG production in sows. Nutrient and energy content of the milk on day 20 of lactation and gains of litters during the first 14 d and the whole 21 d suckling period did not differ between Control and feed-restricted sows. The mRNA concentrations of several sterol regulatory element-binding protein target genes involved in lipid synthesis in the liver and the plasma concentration of TAG were reduced in the feed-restricted sows, whereas the mRNA concentrations of PPARα target genes involved in fatty acid oxidation in liver and skeletal muscle were not different between groups. In conclusion, it was shown that an NEB during lactation does not adversely affect milk composition and gains of litters, despite inhibiting hepatic expression of genes involved in lipid synthesis and reducing plasma TAG concentration. The finding that PPARα target genes involved in fatty acid utilisation in liver and muscle of sows are not induced by the NEB during lactation may explain that fatty acid availability in the mammary gland is sufficient to maintain milk TAG production and to allow normal litter gain.     

Use of AI technician scores for body condition, uterine tone and uterine discharge in a model with disease and milk production parameters to predict pregnancy risk at first AI in Holstein dairy cows

Technicians recorded body condition score (BCS) and several parameters related to estrus and/or metritis for 1694 first insemination cows on 23 farms. Additional variables for modeling the adjusted odds ratios (OR) for pregnancy were data on disease prior to or within 21 days of AI and test day milk yields. Significant predictors for pregnancy were farm, year and season, BCS, uterine tone, contaminated insemination gun after AI, fat-protein corrected kilograms milk (FPCM), days in milk (DIM), and diseases. Vaginal mucus, ease of cervical passage, and lameness were not significant predictors for pregnancy. Pregnancy risk at AI increased with increasing DIM, reaching a near optimum after 82 days. Lack of uterine tone was associated with a lowered pregnancy risk (OR = 0.69) as was contaminated insemination gun (OR = 0.67), first-parity lactation, FPCM >33 kg (OR = 0.71), BCS 2.5 at AI (OR = 0.65), clinical mastitis (OR = 0.53), cystic ovarian disease (OR = 0.53), and metritis (OR = 0.74). It was concluded that data on BCS and uterine findings, as collected by AI technicians, are significant predictors of AI outcome. Dairy producers and veterinarians should jointly examine the potential costs and value of such AI technician-based data to improve herd fertility.