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The preovulatory intrafollicular environment plays a major role in determining oocyte competence. The basis of this review is to highlight the importance of the preovulatory follicle's physiological status prior to the preovulatory luteinizing hormone (LH) surge and onset of oocyte maturation to promote an optimal follicular microenvironment and optimal oocyte developmental competence in cattle. While the underlying mechanisms remain unclear, and are likely multifactorial, the preovulatory follicle's physiological status prior to the preovulatory LH surge is highly influential on the oocyte's capacity to undergo postfertilization embryo development. Changes in the intrafollicular environment of the preovulatory follicle including steroid hormone production, metabolome profiles, and proteome profiles likely support the oocyte's developmental and metabolic competency. This review focuses on the relationship between bovine oocyte developmental competency and antral follicle progression to the preovulatory phase, the role of the preovulatory follicle in improving oocyte developmental competence in cattle, and the importance of the ever-evolving preovulatory intrafollicular environment for optimal fertility.Bovine pregnancy rates and oocyte developmental competence are heavily influenced by the periovulatory follicular environment. It is well known that the status of the preovulatory follicle at the time of the luteinizing hormone (LH) surge is related to both circulating and intrafollicular hormone concentrations during the follicular phase. Additional relationships between follicle status at the time of the LH surge and oocyte metabolic capacity or modifications in the follicular fluid metabolome and proteome have recently been established. Such studies suggest that critical, multifaceted modifications to the intrafollicular components occur leading up to the LH surge, and that such modifications contribute to the optimal preparation of both the oocyte and intrafollicular environment for oocyte maturation. This review focuses on intrafollicular changes that occur within the dominant follicle from luteolysis to the LH surge and discusses recent advancements in the literature related to how such changes support oocyte competence.

Development of the corpus luteum (CL) requires the growth of a new capillary network from preexisting vasculature, a process known as angiogenesis. Successful building of this capillary network occurs through a sequence of cellular events-differentiation, proliferation, migration, and adhesion-which are regulated by a suite of angiogenic proteins that includes cellular communication network factor 1 (CCN1). We previously reported that the expression of CCN1 was highest in luteal tissue obtained from the early-cycle, 4-d-old bovine CL (i.e., corpus hemorrhagicum) compared to the mid- and late-cycle CL. In the present study, we treated steroidogenic bovine luteal cells from early-cycle CL with luteinizing hormone (LH), but it had no effect on CCN1 expression. Direct stimulation of the canonical LH pathway with forskolin and dibutyryl-cyclic adenosine monophosphate (cAMP), however, inhibited CCN1 mRNA expression. In endothelial cells, stimulation of Ras homolog family member A (RhoA) induces CCN1 expression, whereas RhoA inactivation inhibits it. Yet, it is unknown if regulation of CCN1 in steroidogenic luteal cells works likewise. We hypothesized that a similar mechanism of CCN1 regulation exists in bovine luteal cells and that thrombin, a known RhoA activator, may be a physiologic trigger for this mechanism in the early-cycle CL. To test this hypothesis, ovaries were collected from lactating dairy cows on days 3 or 4 of the estrous cycle, and corpora lutea were dissected and dissociated. Steroidogenic luteal cells were suspended in defined Ham's F12 medium, supplemented with insulin/transferrin/selenium and gentamicin, and seeded into 6-well plates. After 24 h, spent medium was replaced with fresh Ham's F12, and the cells were cultured for 24 to 48 h. Cells were treated for 2 h with defined medium, 10% fetal bovine serum (FBS), thrombin (1, 5, 10 U/mL), or Rho Activator II (0.25, 1, 2 μg/mL). Cells were then lysed for RNA extraction, followed by cDNA generation, and quantitative polymerase chain reaction (qPCR). Thrombin (1, 5, 10 U/mL; n = 3) and Rho Activator II (0.25, 1, 2 μg/mL; n = 6) increased (P0.05) CCN1 mRNA expression. In summary, CCN1 in bovine steroidogenic luteal cells was induced by thrombin and appeared to be regulated in a Rho-dependent manner. Future work will elucidate the signaling partners downstream of Rho which leads to CCN1 gene expression.The corpus luteum (CL) is a transient ovarian endocrine gland that secretes progesterone, the hormone of pregnancy. Development of an optimally functioning CL requires the creation of a dense capillary bed through growth of new blood vessels, which is an intricate process called angiogenesis. A myriad of factors regulates angiogenesis, including the angiogenic inducer protein, cellular communication network factor 1 (CCN1). Although it is highly expressed in the early-cycle bovine CL, the mechanisms of CCN1 regulation have not been fully elucidated. In the present study, we showed that CCN1 expression in steroidogenic luteal cells from the early-cycle bovine CL was induced by Ras homolog family member A (RhoA) and by thrombin, but not by luteinizing hormone (LH). To the best of our knowledge, the involvement of thrombin and its signaling partner, RhoA, in regulating CCN1 in bovine steroidogenic luteal cells has not been previously reported. These findings will inform our future work to determine how RhoA activation by thrombin leads to increased expression of CCN1.

Embryonic or fetal loss in cattle is associated with problems that occur during oocyte maturation, early embryonic development, conceptus elongation, maternal recognition of pregnancy (MRP), and/or placental attachment and implantation. Many of these problems manifest as inadequate or asynchronous communication between the developing conceptus and endometrium, resulting in pregnancy failure. This review will provide an overview of how various conceptus-endometrial paracrine signaling systems control the fate of early pregnancy in cattle and other ruminants. We begin by summarizing the actions of interferon-tau, the classic MRP signal in ruminates, and then explore how other secretory factors derived from either the conceptus or endometrium influence establishment and maintenance of pregnancy. Insight into how the endometrium responds to male vs. female conceptuses or conceptuses produced by in vitro methods will also be described. Specific focus will be placed on describing how "omic" technologies and other cutting-edge techniques have assisted with identifying novel conceptus and/or endometrial factors and their functions. Recent findings indicate that the endometrial transcriptome and histotroph are altered by conceptus sex, quality, and origin, suggesting that the endometrium is a sensor of conceptus biochemistry. Although the endometrium has a certain level of flexibility in terms of conceptus-maternal interactions, this interplay is not sufficient to retain some pregnancies. However, new information inspires us to learn more and will help develop technologies that mitigate early embryonic loss and reproductive failure in ruminants and other animals.Early pregnancy losses are common in cattle. This review describes how critical the interplay between the developing conceptus (embryo and extraembryonic membranes) and endometrium is to maintaining pregnancies in cattle and other ruminants. The discovery of interferon-tau more than 40 yr ago initiated a new field of reproductive biology focused on describing how the conceptus and endometrium communicate with one another through the secretion of paracrine factors, extracellular vesicles, and other molecules. The use of “omic” and gene editing technologies has assisted with identifying novel functions for many conceptus and endometrial secreted factors. This review provides examples of how conceptus sex, quality, and in vitro vs. in vivo development influences endometrial function. The endometrium appears to have some flexibility in its response to conceptuses, and this insight could be used to our advantage as we work towards developing schemes to rescue conceptuses that are in danger of experiencing pregnancy loss.

A study was conducted to determine the standardized total tract digestible phosphorus (STTD P) requirement for 24- to 130-kg finishing pigs housed under commercial conditions. A total of 1,130 barrows and gilts (PIC 359 × 1050, Hendersonville, TN; initially 24.2 kg) were used, with 26 to 27 pigs per pen with 7 replicates per treatment. Pens of pigs were allotted to treatments in a randomized complete block design with body weight (BW) as the blocking factor. The dietary treatments were fed in 4 phases and were formulated to contain 80%, 90%, 100%, 115%, 130%, and 150% of the National Research Council (NRC) requirement estimate for finishing pigs within each phase. Weight ranges for each phase were: 27 to 49, 49 to 76, 76 to 90, and 90 to 130 kg. Treatments were achieved by increasing the amount of monocalcium phosphate at the expense of corn in the diet with no added phytase. All diets were formulated to contain a similar 1.14:1 to 1.16:1 total Ca:P ratio across treatments in all phases. Increasing STTD P resulted in a quadratic response (P < 0.05) in average daily gain (ADG), gain-to-feed ratio (G:F), and final BW. The greatest improvement was observed with STTD P at 130% of NRC for ADG and final BW and at 115% STTD P for G:F. Average daily feed intake increased linearly (linear, P < 0.05) with the inclusion of STTD P. Increasing STTD P resulted in an increase (quadratic, P < 0.05) in hot carcass weight (HCW) and carcass ADG with the greatest response observed with STTD P at 130% of NRC. There was a marginally significant response (quadratic, P < 0.10) in carcass G:F, with the greatest improvement with STTD P at 115% of NRC. Carcass yield decreased (linear, P < 0.05) with increasing STTD P, while there was a marginally significant (linear, P < 0.10) decrease in backfat and increase in fat-free lean. At the end of the study, a metacarpal was collected and analyzed for bone ash. Increasing STTD P resulted in an increase (linear, P < 0.05) in bone ash weight and percentage ash. For ADG and G:F, the quadratic model demonstrated the best fit. The maximum response in ADG and G:F was estimated at 122% and 116% of NRC STTD P, respectively. The broken-line linear model best fit the data for percentage bone ash, with a plateau achieved at 131% of the NRC STTD P. In conclusion, the estimated STTD P requirement of 24 to 130 kg ranged from 116% to 131% of the NRC publication (2012) requirement estimate.

This paper outlines typical terminology for modeling and highlights key historical and forthcoming aspects of mathematical modeling. Mathematical models (MM) are mental conceptualizations, enclosed in a virtual domain, whose purpose is to translate real-life situations into mathematical formulations to describe existing patterns or forecast future behaviors in real-life situations. The appropriateness of the virtual representation of real-life situations through MM depends on the modeler’s ability to synthesize essential concepts and associate their interrelationships with measured data. The development of MM paralleled the evolution of digital computing. The scientific community has only slightly accepted and used MM, in part because scientists are trained in experimental research and not systems thinking. The scientific advancements in ruminant production have been tangible but incipient because we are still learning how to connect experimental research data and concepts through MM, a process that is still obscure to many scientists. Our inability to ask the right questions and to define the boundaries of our problem when developing models might have limited the breadth and depth of MM in agriculture. Artificial intelligence (AI) has been developed in tandem with the need to analyze big data using high-performance computing. However, the emergence of AI, a computational technology that is data-intensive and requires less systems thinking of how things are interrelated, may further reduce the interest in mechanistic, conceptual MM. Artificial intelligence might provide, however, a paradigm shift in MM, including nutrition modeling, by creating novel opportunities to understand the underlying mechanisms when integrating large amounts of quantifiable data. Associating AI with mechanistic models may eventually lead to the development of hybrid mechanistic machine-learning modeling. Modelers must learn how to integrate powerful data-driven tools and knowledge-driven approaches into functional models that are sustainable and resilient. The successful future of MM might rely on the development of redesigned models that can integrate existing technological advancements in data analytics to take advantage of accumulated scientific knowledge. However, the next evolution may require the creation of novel technologies for data gathering and analyses and the rethinking of innovative MM concepts rather than spending resources in collecting futile data or amending old technologies.

Management and policy decisions are continually made to mitigate disease introductions in animal populations despite often limited surveillance data or knowledge of disease transmission processes. Science-based management is broadly recognized as leading to more effective decisions yet application of models to actively guide disease surveillance and mitigate risks remains limited. Disease-dynamic models are an efficient method of providing information for management decisions because of their ability to integrate and evaluate multiple, complex processes simultaneously while accounting for uncertainty common in animal diseases. Here we review disease introduction pathways and transmission processes crucial for informing disease management and models at the interface of domestic animals and wildlife. We describe how disease transmission models can improve disease management and present a conceptual framework for integrating disease models into the decision process using adaptive management principles. We apply our framework to a case study of African swine fever virus in wild and domestic swine to demonstrate how disease-dynamic models can improve mitigation of introduction risk. We also identify opportunities to improve the application of disease models to support decision-making to manage disease at the interface of domestic and wild animals. First, scientists must focus on objective-driven models providing practical predictions that are useful to those managing disease. In order for practical model predictions to be incorporated into disease management a recognition that modeling is a means to improve management and outcomes is important. This will be most successful when done in a cross-disciplinary environment that includes scientists and decision-makers representing wildlife and domestic animal health. Lastly, including economic principles of value-of-information and cost-benefit analysis in disease-dynamic models can facilitate more efficient management decisions and improve communication of model forecasts. Integration of disease-dynamic models into management and decision-making processes is expected to improve surveillance systems, risk mitigations, outbreak preparedness, and outbreak response activities.

Twelve adult beagle dogs (10.6 ± 1.4 kg) were fed extruded dog diets in which the starch sources were whole sorghum, sorghum flour, sorghum mill-feed, or an equal combination of rice, corn, and wheat. The experiment was conducted as a replicated Latin square design digestibility study. Estimates of fecal organic matter (OM), crude protein (CP), crude fat (CF), and gross energy (GE) outputs were determined by four methods: total fecal collection (TFC), chromic oxide (Cr2O3), titanium dioxide (TiO2), and acid insoluble ash (AIA). The correlation among the fecal output estimates by the four methods by partial correlation coefficients from the Error SSCP Matrix (Pearson) were considered significant at P < 0.05. The external markers, Cr2O3 and TiO2, had a higher (P < 0.05) OM fecal output Pearson correlation to TFC than the intrinsic marker AIA (R = 0.931 for Cr2O3 vs. TiO2; R = 0.559 for TFC vs. Cr2O3; R = 0.592 for TFC vs. TiO2; R = 0.291 for AIA vs. TFC). Interestingly, TiO2 highly correlated (P < 0.05) to Cr2O3 (R = 0.93 for OM), and was also correlated highly to TFC and AIA. The study suggests that TiO2 may be a preferred marker to estimate fecal output in dogs vs. Cr2O3. The use of AIA represents a potential option for determining digestibility for diets in which external markers are impractical.

Maintaining optimal body condition is an important concern for horse owners and managers as it can affect reproductive efficiency, athletic ability, and overall health of the horse; however, information regarding dietary requirements to maintain or alter BCS in the horse is limited. A recently developed model had high accuracy in predicting the energy required to alter BCS in the horse. However, the model was restricted to sedentary mares, while many horses are subject to physical work. The objective of this study was to expand the scope of that model to include exercising horses by incorporating previously published estimates of exercise energy expenditure and then testing the expanded model. Stock type horses (n = 24) were grouped by initial BCS (3.0 to 6.5) and assigned to treatments of light (L), heavy (H), or no-exercise control (C). Horses were fed according to the model recommendations to increase (I) or decrease (D) two BCS within 60 d. Thus, six treatments were obtained: HD, HI, LD, LI, CD, CI. Mean DE intake Mcal/d for each group was HD = 19.3 ± 0.90, HI = 29 ± 0.84, LD = 13.2 ± 0.54, LI = 23.1 ± 1.39, CD = 12.1 ± 0.79, and CI = 21.9 ± 0.94. BCSs were evaluated by three independent appraisers, days 0 and 60 values were used to calculate the average BCS change for HD = −0.88 ± 0.24, HI = 1.13 ± 0.24, LD = −1.5 ± 0.29, LI = 0.88 ± 0.38, CD = −1.38 ± 0.13, and CI = 1.35 ± 0.14. Statistical comparison of final observed and model predicted values revealed acceptable precision when predicting BCS and BW respectively in control horses (r(2) = 0.91, 0.98) but less precision when predicting body fat (BF) (r(2) = 0.51). Model precision for BCS, BW, and BF respectively in lightly (r(2) = 0.29, 0.85, 0.57) and heavily (r(2) = 0.04, 0.84, 0.13) exercised horses was low. Model accuracy was acceptable across all treatments when predicting BW (C(b) = 0.97, 0.96, 0.98). However, accuracy varied when predicting BCS (C(b) = 0.82, 0.89, 0.41) and BF (C(b) = 0.80, 0.55, 0.87) for the control, light, and heavy exercise groups, respectively. These results indicate that the revised model is acceptable for sedentary horses but the predictability of the model was insensitive to the exercising horse, therefore the exercise energy expenditure formulas incorporated into the model require revision. Packaging this model in a format that facilitates industry application could lead to more efficient feeding practices of sedentary horses, generating health, and economic benefit. Further investigation into energy expenditure of exercising horses could yield a model with broader applications.

Twelve Angus steers (BW 452.8 ± 6.1 kg) fitted with ruminal cannulae were used to determine the impact of trace mineral (TM) source on digestibility, ruminal volatile fatty acid (VFA) composition, ruminal soluble concentrations of Cu, Zn, and Mn, and relative binding strength of trace minerals located in the rumen insoluble digesta fraction. Steers were fed a medium-quality grass hay diet (DM basis: 10.8% CP, 63.1% neutral detergent fiber [NDF], 6.9 mg Cu/kg, 65.5 mg Mn/kg, and 39.4 mg Zn/kg) supplemented with protein for 21 d. Treatments consisted of either sulfate (STM) or hydroxy (HTM) sources (n = 6 steers/treatment) to provide 20, 40, and 60 mg supplemental Cu, Mn, and Zn/kg DM, respectively. Following a 21-d adaptation period, total fecal output was collected for 5 d. Dry matter (P < 0.07) and CP (P < 0.06) digestibility tended to be reduced, and NDF (P < 0.04) and acid detergent fiber (ADF) (P < 0.05) digestibility were reduced in STM- vs. HTM-supplemented steers. On day 6, ruminal fluid was collected at 0, 2, and 4 h post-feeding and analyzed for VFA. There were no treatment x time interactions for VFA. Steers receiving HTM had less (P < 0.02) molar proportions of butyric acid and greater (P < 0.05) total VFA concentrations than STM-supplemented steers. Steers were then fed the same diet without supplemental Cu, Zn, or Mn for 14 d. On day 15 steers received a pulse dose of 20 mg Cu, 40 mg Mn, and 60 mg Zn/kg DM from either STM or HTM (n = 6 steers/treatment). Ruminal samples were obtained at 2-h intervals starting at −4 and ending at 24 h relative to dosing. There was a treatment x time interaction (P < 0.03) for ruminal soluble Cu, Mn, and Zn concentrations. Ruminal soluble mineral concentrations were greater (P < 0.05) for Cu at 4, 6, 8, 10, 12, and 14 h; for Mn at 4 and 6 h; and for Zn at 4, 6, and 8 h post-dosing in STM compared with HTM-supplemented steers. Copper concentrations were greater (P < 0.05) at 12 and 24 h and Zn concentrations in ruminal solid digesta were greater at 24 h in HTM-supplemented steers. Upon dialysis against Tris-EDTA, the percent Zn released from digesta was greater (P < 0.05) at 12 h (P < 0.03) and 24 h (P < 0.05), and the percent Cu released was greater (P < 0.02) at 24 h post-dosing in HTM steers when compared with STM-supplemented steers. Results indicate that Cu and Zn from HTM have low solubility in the rumen and appear to be less tightly bound to ruminal solid digesta than Cu and Zn from STM. The lower ruminal soluble concentrations of Cu and Zn in steers given HTM were associated with greater fiber digestibility.

Monitoring, recording, and predicting livestock body weight (BW) allows for timely intervention in diets and health, greater efficiency in genetic selection, and identification of optimal times to market animals because animals that have already reached the point of slaughter represent a burden for the feedlot. There are currently two main approaches (direct and indirect) to measure the BW in livestock. Direct approaches include partial-weight or full-weight industrial scales placed in designated locations on large farms that measure passively or dynamically the weight of livestock. While these devices are very accurate, their acquisition, intended purpose and operation size, repeated calibration and maintenance costs associated with their placement in high-temperature variability, and corrosive environments are significant and beyond the affordability and sustainability limits of small and medium size farms and even of commercial operators. As a more affordable alternative to direct weighing approaches, indirect approaches have been developed based on observed or inferred relationships between biometric and morphometric measurements of livestock and their BW. Initial indirect approaches involved manual measurements of animals using measuring tapes and tubes and the use of regression equations able to correlate such measurements with BW. While such approaches have good BW prediction accuracies, they are time consuming, require trained and skilled farm laborers, and can be stressful for both animals and handlers especially when repeated daily. With the concomitant advancement of contactless electro-optical sensors (e.g., 2D, 3D, infrared cameras), computer vision (CV) technologies, and artificial intelligence fields such as machine learning (ML) and deep learning (DL), 2D and 3D images have started to be used as biometric and morphometric proxies for BW estimations. This manuscript provides a review of CV-based and ML/DL-based BW prediction methods and discusses their strengths, weaknesses, and industry applicability potential.

Thermal stress can result in productivity losses, morbidity, and mortality if proper management practices are not employed. A basic understanding of the relationship between animals and the thermal environment is crucial to assess the environment’s impact on livestock performance. Therefore, the study objective was to evaluate whether different early life thermal stressors (ELTS) altered the temperature preference of pigs later in life. Twelve sows and their litters were randomly exposed to 1 of 3 ELTS treatments from 7 to 9 d of age: early life heat stress (ELHS; cycling 32 to 38 °C; n = 4), early life cold stress (ELCS; 25.4±1.1 °C without heating lamp; n = 4), or early life thermoneutral (ELTN; 25.4±1.1 °C with a heating lamp; n = 4) conditions. From 10 to 20 d, (weaning) all piglets were exposed to ELTN conditions. At weaning, pigs were randomly assigned to groups of 4 of the same sex and ELTS treatment. Temperature preference, where pigs freely choose a temperature, was assessed in 21 groups (n = 7 groups per ELTS treatment) using 1 of 3 thermal gradient apparatuses (22 to 40 °C). Testing began at 26 ± 1.3 d of age to give pigs time to acclimate to solid food after weaning and 1 group per ELTS treatment were tested simultaneously in each apparatus. Pigs were given 24 h to acclimate followed by a 24-h testing period. Behavior (active and inactive), posture (upright, sternal, and lateral lying), and location were documented every 20 min using instantaneous scan samples. Preferred feeding temperature was determined by the latency to empty a feeder in each location. Data were analyzed using PROC MIXED in SAS 9.4. A cubic regression model was used to calculate the peak temperature preference of pigs based on the temperature pigs spent most of their time. The preference range was calculated using peak temperature preference ±SE for each ELTS treatment group. Early life thermal stress altered where pigs spent most of their time within the thermal gradient (P = 0.03) with ELTN pigs preferring cooler temperatures (peak preference of 23.8 °C) compared with their ELCS exposed counterparts (peak preference of 26.0 °C; P < 0.01). However, ELHS exposed pigs (peak preference of 25.6 °C) did not differ in their temperature preference compared with ELTN or ELCS exposed counterparts (P > 0.05). In summary, ELCS exposure altered pig temperature preference later in life indicating that ELTS can alter temperature preference in pigs.

The objective of this experiment was to evaluate the impact of complexed trace mineral supplementation on ovum pick-up (OPU) and in vitro embryo production in lactating beef cows. Thirty days prior to fixed-time artificial insemination (FTAI; day −30), 68 postpartum cows were stratified by BW, BCS, and parity before being randomly assigned to 10 pens of either a treatment (TRT; n = 5) or a control (CNT; n = 5) group. Each group received a weekly mineral supplement allotment of 1.16 kg × week−1 × cow–calf pair−1 for 14 wk. Cows assigned to the TRT group received a mineral supplement that contained amino acid complexes of zinc, copper, and manganese, as well as cobalt glucoheptonate (Availa Plus; Zinpro Corp., Eden Prairie, MN, USA), while cows assigned to the CNT group received a mineral supplement that was formulated to contain similar concentrations of these trace minerals from inorganic sources. All cows were submitted to a 7 d CO-Synch + CIDR protocol on day −10 and bred using FTAI on day 0. Pregnancy diagnosis was performed on day 28 and nonpregnant cows were removed. All pregnant cows were subjected to ovum pick-up (OPU) on day 52 and 67 of gestation. Cumulus-oocyte complexes (COCs) were evaluated and graded prior to in vitro fertilization (IVF). Analysis of variance was conducted to determine effects of treatment on response variables, and pen was considered the experimental unit. Supplement consumption did not differ (P = 0.48) between treatments (1.16 ± 0.12 vs. 1.07 ± 0.15 kg of DM × week−1 × cow–calf pair−1 for TRT and CNT, respectively). Total COC recovery was greater (P = 0.03) from TRT when compared with CNT cows (22.4 ± 2.0 vs. 16.4 ± 1.4 COCs × pen−1, respectively) and the number of COCs meeting maturation criteria was increased in TRT cows (P = 0.05) when compared with CNT cows (15.9 ± 1.6 vs. 11.8 ± 1.0 COCs × pen−1, respectively). Production of transferable embryos tended to be greater (P = 0.06) for TRT than CNT cows (4.7 ± 0.6 vs. 2.7 ± 0.7 embryos × pen−1, respectively). Furthermore, when expressed as a ratio, the number of recovered COCs meeting maturation criteria that were required to produce a transferable embryo tended to be lower for TRT than CNT cows (3.10 ± 0.93 vs. 7.02 ± 1.60; P = 0.06). In summary, complete replacement with complexed trace mineral improved COC recovery and in vitro embryo production when compared with inorganic forms of these trace minerals in beef cows.