Modelling impacts of performance on the probability of reproducing, and thereby on productive lifespan, allow prediction of lifetime efficiency in dairy cows

Association of Metabolic and Endocrine Disorders with Bovine Ovarian Follicular Cysts

After estrus, when mature follicles fail to ovulate, they may further develop to form follicular cysts, affecting the normal function of ovaries, reducing the reproductive efficiency of dairy cows and causing economic losses to cattle farms. However, the key points of ovarian follicular cysts pathogenesis remain largely unclear. The purpose of the current research was to analyze the formation mechanism of ovarian follicular cysts from hormone and gene expression profiles. The concentrations of progesterone (P4), estradiol (E2), insulin, insulin-like growth factor 1 (IGF1), leptin, adrenocorticotropic hormone (ACTH) and ghrelin in follicle fluid from bovine follicular cysts and normal follicles were examined using enzyme-linked immunosorbent assay (ELISA) or 125I-labeled radioimmunoassay (RIA); the corresponding receptors' expression of theca interna cells was tested via quantitative reverse transcription polymerase chain reaction (RT-qPCR), and the mRNA expression profiling was analyzed via RNA sequencing (RNA-seq). The results showed that the follicular cysts were characterized by significant lower E2, insulin, IGF1 and leptin levels but elevated ACTH and ghrelin levels compared with normal follicles (p < 0.05). The mRNA expressions of corresponding receptors, PGR, ESR1, ESR2, IGF1R, LEPR, IGFBP6 and GHSR, were similarly altered significantly (p < 0.05). RNA-seq identified 2514 differential expressed genes between normal follicles and follicular cysts. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis linked the ovarian steroidogenesis pathway, especially the STAR, 3β-HSD, CYP11A1 and CYP17A1 genes, to the formation of follicular cysts (p < 0.01). These results indicated that hormone metabolic disorders and abnormal expression levels of hormone synthesis pathway genes are associated with the formation of bovine ovarian follicular cysts.

Estimation of Dairy Cow Survival in the First Three Lactations for Different Culling Reasons Using the Kaplan-Meier Method

The aims of the study were: (i) to compare survival curves for cows culled for different reasons over three successive lactations using the Kaplan-Meier estimator; (ii) to determine the effects of breeding documentation parameters on cow survival; (iii) to investigate the similarity between culling categories. The survival times for a subset of 347,939 Holstein-Friesian cows culled between 2017 and 2018 in Poland were expressed in months from calving to culling or the end of lactation. The survival tables were constructed for each culling category and lactation number. The survival curves were also compared. The main culling categories were reproductive disorders-40%, udder diseases-13 to 15%, and locomotor system diseases-above 10%. The survival curves for cows from individual culling categories had similar shapes. A low probability of survival curves for metabolic and digestive system diseases and respiratory diseases was observed in each of the three lactations. The contagious disease category was almost non-existent in the first lactation. The greatest influence on the relative culling risk was exerted by age at first calving, lactation length, calving interval, production subindex, breeding value for longevity, temperament, and average daily milk yield. A more accurate method of determining culling reasons would be required.

Effect of hydrogenated fat-embedded calcium gluconate on lactation performance in dairy cows

Hydrogenated fat-embedded calcium gluconate (HFCG), a prebiotic mixture designed to target the hindgut, has improved milk and component yields when supplemented in mid-lactation cows, likely due to improved hindgut health. The objective of this study was to evaluate production responses to HFCG when fed to lactating dairy cattle over a full lactation. Seventy-four Holstein cows (21 primiparous, 53 multiparous) were used in a randomized complete block design comparing supplementation with either HFCG (approximately 16 g/d of supplement delivering approximately 6.4 g of active ingredient) or a negative control from approximately 21 days prior to calving until the end of lactation. In multiparous cattle supplemented with HFCG, average daily milk protein yield (P = 0.037) was increased during the first 8 weeks of lactation, while average daily yields of milk fat, fat- and energy-corrected milk tended (P ≤ 0.075) to increase over the same period of time. Increased yields were likely supported by the concurrent increase in dry matter intake (P = 0.036). Future work is needed to characterize the mode of action of this product within both the hindgut lumen and host, as well as investigate the potential differential responses between primiparous and multiparous animals over the course of lactation.

Associations between feed efficiency and aspects of lactation curves in primiparous Holstein dairy cattle

Genetic selection for improved feed efficiency in dairy cattle has received renewed attention over the last decade to address the needs of a growing global population. As milk yield is a critical component of feed efficiency metrics in dairy animals, our objective was to evaluate the associations between feed efficiency in primiparous Holstein cattle and parameters of a mathematical model describing individual lactation curves. The Dijkstra lactation curve model was fit to individual lactation records from 34 Holstein heifers with previously estimated measures of feed efficiency. We found that the optimal fit of the Dijkstra model was achieved using daily milk yield records up to 21 d in milk to capture the rise to peak milk yield and using monthly dairy herd improvement records for the remainder of lactation to accurately characterize lactation persistency. In the period of lactation before peak milk yield, improved feed efficiency was associated with a faster increase in daily milk yield over a shorter period of time at the expense of increased mobilization of body reserves; this serves to reinforce the concept that dairy cattle are primarily capital breeders versus income breeders. Feed efficiency in the period following peak lactation, as measured by gross feed efficiency, return over feed costs, and net energy efficiency of lactation, was positively associated with higher peak milk yield. The findings in early lactation suggest that estimates of feed efficiency could be improved by evaluating feed efficiency relative to conception, rather than parturition and lactation, to better account for the energy stored and released from body reserves in capital breeding.

Review: extended lactation in dairy cattle

This paper reviews the effects of extended lactation (EXT) as a strategy in dairy cattle on milk production and persistency, reproduction, milk quality, lifetime performance of the cow and finally the economic effects on herd and farm levels as well as the impact on emission of greenhouse gas at product level. Primiparous cows are able to produce equal or more milk per feeding day during EXT compared with a standard 305-d lactation, whereas results for multiparous cows are inconsistent. Cows managed for EXT can achieve a higher lifetime production while delivering milk with unchanged or improved quality properties. Delaying insemination enhances mounting behaviour and allows insemination after the cow's energy balance has become positive. However, in most cases EXT has no effect or a non-significant positive effect on reproduction. The EXT strategy sets off a cascade of effects at herd and farm level. Thus, the EXT strategy leads to fewer calvings and thereby expected fewer diseases, fewer replacement heifers and fewer dry days per cow per year. The optimal lifetime scenario for milk production was modelled to be an EXT of 16 months for first parity cows followed by an EXT of 10 months for later lactations. Modelling studies of herd dynamics indicate a positive effect of EXT on lifetime efficiency (milk per dry matter intake), mainly originating from benefits of EXT on daily milk yield in primiparous cows and the reduced number of replacement heifers. Consequently, EXT also leads to reduced total meat production at herd level. For the farmer, EXT can give the same economic return as a traditional lactation period. At farm level, EXT can contribute to a reduction in the environmental impact of dairy production, mainly as a consequence of the reduced production of beef. A wider dissemination of the EXT concept will be supported by methods to predict which cows may be most suitable for EXT, and clarification of how milking frequency and feeding strategy through the lactation can be organised to support milk yield and an appropriate body condition at the next calving.

Coupling a reproductive function model to a productive function model to simulate lifetime performance in dairy cows

Reproductive success is a key component of lifetime performance in dairy cows but is difficult to predict due to interactions with productive function. Accordingly, this study introduces a dynamic model to simulate the productive and reproductive performance of a cow during her lifetime. The cow model consists of an existing productive function model (GARUNS) which is coupled to a new reproductive function model (RFM). The GARUNS model simulates the individual productive performance of a dairy cow throughout her lifespan. It provides, with a daily time step, changes in BW and composition, fetal growth, milk yield and composition and food intake. Genetic-scaling parameters are incorporated to scale individual performance and simulate differences within and between breeds. GARUNS responds to the discrete event signals 'conception' and 'death' (of embryo or fetus) generated by RFM. In turn, RFM responds to the GARUNS outputs concerning the cow's energetic status: the daily total processed metabolizable energy per kg BW (TPEW) and the net energy balance (EB). Reproductive function model models the reproductive system as a compartmental system transitioning between nine competence stages: prepubertal (PRPB), anestrous (ANST), anovulatory (ANOV), pre-ovulating (PREO), ovulating (OVUL), post-ovulating (PSTO), luteinizing (LUTZ), luteal (LUTL) and gestating (GEST). The transition from PRPB to ANST represents the start of reproductive activity at puberty. The cyclic path through ANST, PREO, OVUL, PSTO, LUTZ and LUTL forms the regime of ovulatory cycles, whereas ANOV and GEST are transient stages that interrupt this regime. Anovulatory refers explicitly to a stage in which ovulation cannot occur (i.e. interrupted cyclicity), whereas ANST is a pivotal stage within ovulatory cycles. Reproductive function model generates estradiol and progesterone hormonal profiles consistent with reference profiles derived from literature. Cyclicity is impacted by the GARUNS output EB and clearance of estradiol is impacted by TPEW. A farming system model was designed to describe different farm protocols of heat detection, insemination, feeding (amount and energy density), drying-off and culling. Results of model simulation (10 000 simulations of individual cows over 5000 days lifetime period, with randomly drawn genetic-scaling parameters and standard diet) are consistent with literature for reproductive performance. This model allows simulation of deviations in reproductive trajectories along physiological stages of the cow reproductive cycle. It thus provides the basis for evaluation of the relative importance of different factors affecting fertility at individual cow and herd levels across different breeds and management environments.

Evaluating the ability of a lifetime nutrient-partitioning model for simulating the performance of Australian Holstein dairy cows

The present study determined the ability of a lifetime nutrient-partitioning model to simulate individual genetic potentials of Australian Holstein cows. The model was initially developed in France and has been shown to be able to accurately simulate performance of individual cows from various breeds. Generally, it assumes that the curves of cow performance differ only in terms of scaling, but the dynamic shape is universal. In other words, simulations of genetic variability in performance between cow genotypes can be performed using scaling parameters to simply scale the performance curves up or down. Validation of the model used performance data from 63 lactations of Australian Holstein cows offered lucerne cubes plus grain-based supplement. Individual cow records were used to derive genetic scaling parameters for each animal by calibrating the model to minimise root mean-square errors between observed and fitted values, cow by cow. The model was able to accurately fit the curves of bodyweight, milk fat concentration, milk protein concentration and milk lactose concentration with a high degree of accuracy (relative prediction errors <5%). Daily milk yield and weekly body condition score were satisfactorily predicted, although slight under-predictions of milk yield were identified during the last stage of lactation (relative prediction errors ≈11.1–15.6%). The prediction of feed intake was promising, with the value of relative prediction error of 18.1%. The results also suggest that the current recommendation of energy required for maintenance of pasture-based cows might be under-estimated. In conclusion, this model can be used to simulate genetic variability in the production potential of Australian cows. Thus, it can be used for simulation of consequences of future genetic-selection strategies on lifetime performance and efficiency of individual cows.

Disentangling the relative roles of resource acquisition and allocation on animal feed efficiency: insights from a dairy cow model

Background

Feed efficiency of farm animals has greatly improved through genetic selection for production. Today, we are faced with the limits of our ability to predict the effect of selection on feed efficiency, partly because the relative importance of the components of this complex phenotype changes across environments. Thus, we developed a dairy cow model that incorporates the dynamic interplay between life functions and evaluated its behaviour with a global sensitivity analysis on two definitions of feed efficiency. A key model feature is to consider feed efficiency as the result of two processes, acquisition and allocation of resources. Acquisition encapsulates intake and digestion, and allocation encapsulates partitioning rules between physiological functions. The model generates genetically-driven trajectories of energy acquisition and allocation, with four genetic-scaling parameters controlling these processes. Model sensitivity to these parameters was assessed with a complete factorial design.

Results

Acquisition and allocation had contrasting effects on feed efficiency (ratio between energy in milk and energy acquired from the environment). When measured over a lactation period, feed efficiency was increased by increasing allocation to lactation. However, at the lifetime level, efficiency was increased by decreasing allocation to growth and increasing lactation acquisition. While there is a strong linear increase in feed efficiency with more allocation to lactation within a lactation cycle, our results suggest that there is an optimal level of allocation to lactation beyond which increasing allocation to lactation negatively affects lifetime feed efficiency.

Conclusions

We developed a model to predict lactation and lifetime feed efficiency and show that breaking-down feed conversion into acquisition and allocation, and introducing genetically-driven trajectories that control these mechanisms, permitted quantification of their relative roles on feed efficiency. The life stage at which feed efficiency is evaluated appears to be a key aspect for selection. In this model, body reserves are also a key component in the prediction of lifetime feed efficiency since they integrate the feedback of acquisition and allocation on survival and reproduction. This modelling approach provided new insights into the processes that underpin lifetime feed efficiency in dairy cows.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-016-0251-8) contains supplementary material, which is available to authorized users.