A randomized study on the effect of extended voluntary waiting period in primiparous dairy cows on milk yield during first and second lactation

Extending the voluntary waiting period (VWP) for primiparous cows can have a positive impact on fertility without a negative impact on milk production per day in the calving interval (CInt). We investigated the effect of extended VWP during first lactation on milk yield (MY) during 2 consecutive lactations in primiparous cows. The study involved 16 commercial herds in southern Sweden. A total of 533 Holstein and Red dairy cattle (Swedish Red, Danish Red, Ayrshire) dairy cows were randomly assigned to a conventional 25 to 95 d VWP (n = 252) or extended 145 to 215 d VWP (n = 281). Data on calvings, inseminations, and test-day yields were retrieved from the Swedish Milk Recording System. Cows with VWP according to plan and completing 1 or 2 CInt with a second or third calving were included in the data analysis. Whole lactation and 305-d energy-corrected milk (ECM) yield were higher for the extended VWP group than the conventional VWP group in both the first lactation (12,307 vs. 9,587 and 9,653 vs. 9,127 kg ECM) and second lactation (12,817 vs. 11,986 and 11,957 vs. 11,304 kg ECM). We found no difference between the VWP groups in MY per day during the first CInt or during the first and second CInt combined, although MY per day during the second CInt was around 1.5 kg higher for cows with extended VWP than for cows with conventional VWP. Thus extended VWP for primiparous cows can be used as a management tool without compromising MY.

ASAS-NANP SYMPOSIUM: MATHEMATICAL MODELING IN ANIMAL NUTRITION: Opportunities and Challenges of Confined and Extensive Precision Livestock Production

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confined operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative five-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSMs). This five-step process acts as a guide to realize anticipated benefits from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confined and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in more challenging and harsh, extensive systems, it is likely that confined operations will benefit from required advances in precision technology and PSMs, ultimately strengthening the benefits from precision technology to achieve short- and long-term goals.

Validation of a novel milk progesterone-based tool to monitor luteolysis in dairy cows: Timing of the alerts and robustness against missing values

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.

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.

Symposium review: Characterization of the bovine milk protein profile using proteomic techniques

Identification and characterization of the comprehensive bovine milk proteome has historically been limited due to the dichotomy of protein abundances within milk. The high abundance of a select few proteins, including caseins, α-lactalbumin, β-lactoglobulin, and serum albumin, has hindered intensive identification and characterization of the vast array of low-abundance proteins in milk due to limitations in separation techniques and protein labeling capacity. In more recent years, the development and advancement of proteomics techniques have yielded valuable tools for characterization of the protein profile in bovine milk. More extensive fractionation and enrichment techniques, including the use of combinations of precipitation techniques, immunosorption, gel electrophoresis, chromatography, ultracentrifugation, and hexapeptide-based binding enrichment, have allowed for better isolation of lower abundance proteins for further downstream liquid chromatography-tandem mass spectrometry approaches. The different milk subfractions isolated during these processes can also be analyzed as individual entities to assess the protein profile unique to the different fractions-for instance, investigation of the skim milk-associated proteome versus the milk fat globule membrane-associated proteome. Updates to high-throughput methods, equipment, and software have also allowed for greater interpretation and visualization of the data. For instance, labeling techniques have enabled analysis of multiplexed samples and more accurate comparison of specific protein abundances and quantities across samples, and integration of gene ontology analysis has allowed for a more in-depth and visual representation of potential relationships between identified proteins. Inclusively, these developments in proteomic techniques have allowed for a rapid increase in the number of milk-associated proteins identified and a better grasp of the relationships and potential functionality of the proteins within the milk proteome.

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.