Dairy Operations Research Articles

Net zero initiative in U.S. beef and dairy systems: integrative on-farm recommendations for greenhouse gas reduction

Abstract Beef and dairy production systems play an important role in society, providing a variety of ecosystem services. U.S. beef and dairy production systems require being aligned with the global and national effort to stabilize the anthropogenic greenhouse gas (GHG) emissions in the atmosphere. This study adapted the nominal group technique framework to design a roadmap to achieving a net-zero GHG cattle supply chain in the U.S. with an emphasis on farm recommendations. Scientists with diverse expertise in sustainable beef and dairy production proposed, categorized, described, defined, and prioritized strategies that have the potential to significantly reduce GHG emissions, improve production system efficiencies, and promote sustainability. These strategies were presented to different stakeholders and classified according to the marginal GHG reduction, expected return on investment, and market readiness. Thus, strategies were defined for cow-calf and stocker, feedlot, and dairy operations, according to the characteristics of the cattle systems in the U.S. This net-zero roadmap presents a broad range of options for promoting sustainable cattle production in the U.S. Priority items for a research agenda to facilitate progress towards implementing this net-zero roadmap are described according to the dairy or beef production system and including the modulation of rumen fermentation, precision diet management, manure management, increasing animal and system efficiency, and genetic evaluation and selecting of efficient animals. The expected return on investment and market readiness of the proposed strategies depend on the technology type and system localization. Progress toward the net-zero goal depends on the widespread adoption of appropriate mitigation strategies. Future research programs must prioritize identified research needs to promote the wide adoption of the proposed strategies.

Nitrogen excretion and utilisation of dairy cows grazing temperate semi-natural grasslands

Diets reliant on grazed, temperate herbage are prone to greater nitrogen (N) losses via urine than balanced stall-fed diets which poses a greater risk for N emissions. Measures for improving the N utilisation in grazing-based dairy cattle systems are predominantly investigated on homogenous clover-ryegrass pastures with high herbage yields and nutritional quality. In contrast, grazing-based systems reliant on less external inputs (e.g., synthetic fertilisers or concentrates) using semi-natural grassland as main feed source, such as in large parts of Central Europe, received less attention. The N utilisation and excretion of grazing cows in low-input dairy farms was, thus, investigated on nine commercial organic dairy farms in South Germany across one to four periods per farm. The dataset captured a diverse set of dairy production systems comprising 323 individual animal observations. A mean (± one standard deviation) milk production, DM intake (DMI), and pasture DMI of 23.9 kg (± 5.35), 21.0 kg (± 3.21), and 11.3 kg/d (± 4.83), respectively, was determined using titanium dioxide and faecal crude protein concentration as markers of faecal excretion and diet digestibility, respectively. Milk N use efficiency (MNE; i.e., milk N secretion as share of N intake) averaged 24.7 g/100 g N intake (± 5.91), which is greater than observations in temperate, high-input grazing systems but lower than in cows receiving balanced diets in the barn. The MNE and another seven indicators of N utilisation and excretion displayed a wide range of values. The grazing management factors explaining this variation were, thus, identified via backward elimination. The supplementation strategy had the greatest potential for manipulating N utilisation and excretion of dairy cows. Increasing shares of fresh forages (i.e., meadow grass or clover-grass leys) as well as of hay in supplement DMI increased N utilisation (e.g., MNE) and decreased urinary N excretion (e.g., urinary N to creatinine ratio), while increasing shares of concentrates in supplement DMI are related to lower N losses via urine. At the same time, increases in total supplement DMI reduced N utilisation and increased urinary N excretion. Hence, full-time grazing combined with supplementation of fresh forage and hay in the barn is a viable option for low-input, grazing-based dairy operations with moderate levels of N losses.

Effect of dairy manure‐based fertilizers on nitrous oxide emissions in a semi‐arid climate

AbstractManure treatment technologies are of interest to dairy operations to improve nutrient management, although there are little data related to nutrient availability and environmental impacts of these manure‐based fertilizer products. This field trial experiment investigated the impact of two manure‐based fertilizer sources (phosphorus enriched solids [PE] and mechanical vapor recompression solids [VR]) on soil nutrients, crop yields, and N2O emissions in a forage rotation. The study was a factorial random complete block design, with two main factors: manure history (with [M]; without [NM]) and manure‐based fertilizer product (control [Con], PE, VR), under a continuous corn and triticale rotation. M had greater soil organic carbon, total carbon, total nitrogen, and M3‐P (30%–128%) and reduced NH4‐N (15%) than NM, with no other treatment differences. Corn silage yields were greater in NM versus M (7%) treatments only in 2021, while in 2022 VRNM was 17% greater than ConNM only. Triticale yields were 14% greater in M plots versus NM treatments only in 2021. In 2022, triticale yields were 1.7 times lower in ConNM versus all other treatments, and PENM was 71% greater than ConM. The greatest N2O fluxes occurred in May, June, and July with M having 69% greater average cumulative fluxes than NM, while average VR cumulative fluxes were 102% greater than PE and Con. Over both years, net loss of Napplied as N2O‐N was 1.9%–2.2% for VR and 0.4%–0.8% for PE solids. While manure‐based fertilizers performed well as a nutrient source, their susceptibility to N2O loss needs to be considered in management strategies.

420 Automated identification and behavioral estrus detection in freestall-housed dairy cows using computer vision and machine learning: A two-layered algorithm approach

Abstract A critical aspect of dairy management involves maintaining accurate records of individual animals and promptly detecting estrus behavior, which is vital for successful breeding and reproductive outcomes. Recent advancements in precision livestock management, utilizing computer vision and machine learning technologies, have paved the way for automated and precise solutions in these areas. The objective of this study is to investigate the application of computer vision and machine learning for animal identification and behavioral estrus detection in dairy cows housed in freestall settings, employing a two-layered algorithmic approach. The research was conducted at the Joe Bearden Dairy Research Center, where a total of 10 lactating Holstein-Friesian cows were assessed across a 7-d trial period. For synchronization efforts, cows were provided a single injection of Prostaglandin F2α at trial initiation with expected estrus behaviors to be exhibited within the following 56 h. Continuous video was captured in 4k resolution using a five-camera closed caption media recording system strategically placed in the pen corners and over the feed bunk alleyway to capture multiple perspectives. Video data extrapolated into frames and manual annotation was utilized to generate the machine learning algorithm’s training data. Frames were randomly selected from a scattering of 56 h of video across all five camera viewpoints and down sampled to 384 x 640 p for both layers. A two-layer approach was employed utilizing an algorithm for each aspect of the study with the first model detecting the behavior, and the second model using the detected region of interest to identify specific cows. The first layer was trained on 682 frames and validated against 123 manually annotated frames. The second layer was trained on 102 frames and validated against 16 frames manually annotated for individual animals. Results demonstrated that the model used for mounting behavior identification has high precision (0.819) and recall (0.89), achieving a 0.926 mAP at an IoU of 0.5. This model achieved an F1 score of 0.86 at a confidence threshold of 0.268. The results demonstrated that the model used for individual animal identification across different classes achieved high precision (0.861) and recall (0.842), with a mAP of 0.897 at an IoU of 0.5. The F1 score for all classes was 0.89 at a confidence threshold of 0.788. In conclusion, these promising findings underscore the potential of computer vision and machine learning technologies to revolutionize dairy cow management practices. This innovative approach not only has potential to enhance operational efficiency, but also contributes significantly to improved reproductive management, thereby advancing precision and productivity in dairy operations.

Genomic Profiling of Antimicrobial Resistance Genes in Clinical Salmonella Isolates from Cattle in the Texas Panhandle, USA.

Rising antimicrobial resistance (AMR) in Salmonella serotypes host-adapted to cattle is of increasing concern to the beef and dairy industry. The bulk of the existing literature focuses on AMR post-slaughter. In comparison, the understanding of AMR in Salmonella among pre-harvest cattle is still limited, particularly in Texas, which ranks top five in beef and dairy exports in the United States; inherently, the health of Texas cattle has nationwide implications for the health of the United States beef and dairy industry. In this study, long-read whole genome sequencing and bioinformatic methods were utilized to analyze antimicrobial resistance genes (ARGs) in 98 isolates from beef and dairy cattle in the Texas Panhandle. Fisher exact tests and elastic net models accounting for population structure were used to infer associations between genomic ARG profiles and antimicrobial phenotypic profiles and metadata. Gene mapping was also performed to assess the role of mobile genetic elements in harboring ARGs. Antimicrobial resistance genes were found to be statistically different between the type of cattle operation and Salmonella serotypes. Beef operations were statistically significantly associated with more ARGs compared to dairy operations. Salmonella Heidelberg, followed by Salmonella Dublin isolates, were associated with the most ARGs. Additionally, specific classes of ARGs were only present within mobile genetic elements.

Greenhouse gas emissions and nutrient use efficiency assessment of 6 New York organic dairies

Improving nutrient use efficiency and reducing GHG emissions are important environmental priorities for organic-certified dairy operations. The objectives of this research were to quantify annual nutrient use and GHG emissions in 6 organic New York dairy farms. Farm-gate nutrient mass balances (NMB) were estimated with the Cornell NMB calculator. Whole-farm GHG emissions were estimated using the Cool Farm Tool (CFT) and COMET. Farm-gate NMB were low, ranging from -6.5 to 19 kg N/ha for N1 (without legume N fixation), 26 to 71 kg N/ha for N2 (including N fixation), -2.4 to 8.2 kg P/ha for P, and 1.1 to 19.8 kg K/ha for K. Additional nutrient imports, coupled with nutrient management planning, adequate legume stands, and diet balancing may help improve P balances and ensure no N deficiencies in the system. Estimates of annual GHG emissions intensity ranged from 0.98 to 2.10 kg of CO2-equivalents (CO2-eq) per kilogram of fat- and protein-corrected milk (FPCM) estimated by CFT, and from 0.69 to 2.48 kg CO2-eq/kg FPCM estimated by COMET. Enteric fermentation, feed production, and fuel and energy use represented the largest sources of GHG. For farms with liquid manure storages, manure management was also a significant source. Estimates of soil carbon (C) stock changes from CFT were in agreement with or smaller than previous studies, and estimates from COMET were in agreement or greater. Variability and uncertainty in the results for soil C stock change indicate that more research and new protocols are needed. The effects of individual management changes on GHG emissions intensity were small, ranging from -8 to +7% in CFT, and -8% to +8% in COMET. The management changes that resulted in the largest reductions in GHG emissions intensity included increasing individual cow productivity and ratio of milk to total feed, and implementation of manure treatment systems.

Glycal Forte® (calcium-stabilized glycerol), a novel feed ingredient, promotes rumen function in dairy cows

Abstract Good nutritional practices are essential to support the high milk production of modern dairy cows. This requires an active rumen microbial biomass which supplies microbial protein and short-chain fatty acids to the cow. Glycal Forte® (GF) a calcium-stabilised glycerol product, increased microbial biomass in an in vitro gas production study, by some 37%. The efficacy of GF was substantiated in a trial with high-producing dairy cows fed a TMR with or without GF for 28 d. Cows fed GF showed behaviour differences. Chewing was reduced from 710 GF vs 769 for the control (CON) min/d; P=0.01 and they spent more time in an inactive state (429 GF vs 383 CON min/d; P=0.01). There was a statistically significant improvement in feed efficiency with GF (2.19 CON vs 2.34 GF kg ECM/kg dry matter intake (DMI); P=0.03). Feed efficiency has an important bearing on costs and profitability of a dairy operation. Cows fed GF yielded an improved profit of $1.45 per cow per day over 28 d with an ROI of 2.23. Extrapolated to a 100 dairy cow herd for 28 d gave an additional profit of $4,060. Milk yields continued to show benefits for 70 d in milk (DIM) after the GF treatment was stopped, showed a numerical increase in milk yield of 3.2 kg/d. The benefits in rumen function continues after the feeding of GF had ceased. In summary, this trial with high-producing dairy cows was consistent with the in vitro trial data and showed that GF can improve rumen function manifested as less time chewing, more inactive time and most importantly, improved feed efficiency. This has both economic and environmental advantages in that dairy cow productivity can be enhanced solely by nutritional means

Assessing the impact of biosecurity practices and animal welfare in small-scale mountain dairy farming

This study estimates the association between the level of biosecurity, animal welfare, milk quality, and economic performance on 2291 mountain dairy farms which largely differs in management and structure from large dairy operations in the lowlands mainly due to climatic and topographic constraints in mountain areas. The dairy industry’s increasing emphasis on biosecurity is crucial for ensuring animal health, productivity, and disease mitigation. Therefore, in the present study the biosecurity and animal welfare status of mountain dairy farms were assessed considering the official welfare protocol for dairy cows of the Italian ClassyFarm system. Our findings reveal a suboptimal adoption of biosecurity measures, attributed to structural limitations in mountain farms and farmers’ awareness gaps. Despite these challenges, the economic significance of biosecurity adoption is evident, emphasizing potential benefits for farm viability and animal health. Conversely, the study indicates a moderate to good welfare status in assessed farms, reflecting farmers’ awareness of the importance of high welfare standards for dairy cows. Improved welfare positively correlates with milk sales and productivity, highlighting the economic advantages of prioritizing animal well-being. Challenges persist, particularly regarding animal housing deficiencies and related consumer concerns about animal welfare in dairy production. Therefore, targeted interventions and educational initiatives are crucial to empower farmers and promote best practices in biosecurity and animal welfare management. However, addressing resultant production cost increases necessitates society’s willingness to pay more for animal-based food, emphasizing the importance of aligning economic incentives with sustainable farming practices.

An observational study to investigate the association of teat skin condition with clinical mastitis risk

The importance of teat canal integrity and its adjacent tissues in the dynamics of IMI is well documented, whereas research on the relationship between teat skin condition and clinical mastitis occurrence is scarce. The objective of this ambidirectional cohort study was to investigate the association of teat skin condition with clinical mastitis occurrence in a closed cohort from a commercial dairy farm with a thrice daily milking schedule in the Northeast of the United States. We tested the hypothesis that quarters with teats with altered skin condition would have higher odds of clinical mastitis than those with normal skin. Teat skin condition from 2,670 cows was assessed during a single visit and categorized into (1) normal, (2) dry skin, (3) skin lesion, and (4) dry skin and skin lesion. Cows were monitored for 2 wk after the teat skin condition assessment and the occurrence of clinical mastitis at the quarter level was documented. A generalized linear mixed model with a logit link and a binomial distribution revealed an association between teat skin condition and the occurrence of clinical mastitis. Compared with quarters with teats with normal teat skin, the odds (95% confidence intervals) of clinical mastitis were 0.98 (0.60–1.60) for teats with dry skin, 1.88 (0.97–3.66) for teats with a skin lesion, and 4.87 (1.71–13.85) for teats with dry skin and a skin lesion. We conclude that quarters from teats with dry skin and skin lesions had higher odds of clinical mastitis. In addition, we found evidence that quarters with teats with skin lesions have higher odds of clinical mastitis than those with normal teat skin, though future studies are needed. The results from this study show that teat skin condition should be considered in mastitis control programs on dairy operations.

Technological frontier in Uruguay's beef cattle production: An analysis of technical efficiency and its main drivers

AbstractGlobally, livestock grazing is a major land occupier and is often criticized for its environmental impact. To address these concerns, enhancing livestock productivity is crucial to mitigate these impacts, boost farm competitiveness, and increase food production. The understanding of production variability is key to this endeavor. This paper assesses the technical efficiency of cow‐calf beef production units in Uruguay, excluding dairy and feedlot operations. Using data from the 2016 National Livestock Survey and Wang's frontier model, we estimate a translog stochastic production frontier, incorporating bovine livestock units, land area, and equivalent working units as key inputs. This model also controls soil productivity, improved grazing areas, productive orientation (beef‐cattle systems or beef cattle‐ovine mixed systems), beef production system (cow‐calf, full cycle, and fattening operation), access to electric power, and agroecological regions. Furthermore, it explores factors affecting technical inefficiency, such as ownership (individual, corporate without contract, and corporate with contract) and land tenure types (owner, tenant, or other types), besides the presence of third‐party owned cattle, technical assistance (including veterinarian and agronomic), and specific beef cattle technologies (such as continuous bull presence, artificial insemination, ovarian activity diagnosis, pregnancy diagnosis, use of scales for classifying females, temporary and early weaning, and cows and heifers grazing together). Findings indicate an average technical efficiency of 71.3%. Notably, factors such as agronomic and veterinary assistance, artificial insemination, weaning practices, third‐party‐owned cattle presence, pregnancy diagnosis, land tenure, and ownership type significantly impact technical efficiency. Our findings suggest that within the specific segment of cow‐calf operations in Uruguay, there is a potential to enhance beef production by 40.2% through improvements in farm management. [EconLit Citations: Q12, D24].

Ruminal methane emission and lactational performance of cows fed rapeseed cake and oats on a grass silage–based diet

The objective of this experiment was to investigate the effect of lipid from rapeseed cake and oats on ruminal CH4 emission and lactational performance of dairy cows. Twelve lactating Nordic Red cows, of which 4 were primiparous, and averaging (±SD) 48 ± 22.9 DIM, 37.8 ± 7.14 kg/d milk yield were enrolled in a switch-back design experiment with 3 periods of 4 wk each. The cows were assigned into 6 pairs based on parity, DIM, milk yield, and BW at the beginning of the experiment. The experimental treatments were (1) rapeseed cake and oats (RSC+O), and (2) rapeseed meal and barley (RSM+B) as the concentrate feeds. Cows in each pair were randomly assigned to 1 of the 2 groups, which received the treatments in 2 different sequences (i.e., group 1 received RSC+O in period 1 and 3, and RSM+B in period 2, whereas group 2 was fed RSM+B in period 1 and 3, and RSC+O in period 2). The diets consisted of a partially mixed ration with grass silage mixed with either oats or barley, according to the treatment sequence, and the rapeseed cake or meal being mixed into a pellet with either oats or barley according to the treatments, and a mineral mix. The pellet was delivered at a fixed amount (i.e., 6 kg/d for multiparous and 5 kg/d for the primiparous cows) from the milking robot. The actual forage to concentrate ratios for RSC+O and RSM+B were 51:49 and 52:48, respectively, with NDF concentrations of 41.5% and 36.0% and CP concentrations of 17.0% and 16.7% of diet DM. Dry matter intake, milk yield, and gas exchange (with a GreenFeed system attached to the milking robot) were recorded daily, and milk composition and spot fecal samples were collected during the last week of each period. Based on feed analysis, and DMI of the cows during the experiment, the total fat content of the experimental diets was 4.1% and 2.7% of DM for RSC+O and RSM+B diets, respectively. Dry matter intake was 1.6 kg/d lower, and milk yield tended to be 1.0 kg/d greater for RSC+O versus RSM+B. There were no differences in ECM yield and milk composition between the treatments, whereas milk ME efficiency was greater for cows fed RSC+O than RSM+B. Methane yield (g/kg DMI) did not differ between treatments, but CH4 production (g/d) was 9.4% and CH4 intensity as g/kg ECM was 11.7% lower for RSC+O versus RSM+B. The lower CH4 production was likely caused by the lower DMI and fiber digestibility, observed with the RSC+O diet. In addition, the greater lipid intake also contributed to lower rate of fermentation and subsequent decrease in CH4 production. Overall, feeding rapeseed cake with oats in a grass silage-based diet increased feed efficiency while decreasing CH4 emission intensity in lactating cows. This provides a practical way of mitigating ruminal CH4 emission from dairy operations while maintaining milk production with commonly used feedstuffs in Nordic conditions.

Renewable Horizons: Solar Power and Dairy Industry in India

Renewable energy is energy obtained from sources that are essentially inexhaustible such as wind power, solar power, geothermal energy, tidal power, bio-energy and hydropower. It is also known as non-conventional energy. Harnessing renewable energy offers numerous environmental benefits, including mitigating climate change, reducing air pollution, conserving natural resources, and enhancing energy security by diversifying energy sources. Solar resources are available in every country and both Solar Photovoltaic (SPV) and Concentrating Solar Power (CSP) technologies can be used to convert solar resource into electricity. SPV can use both direct and diffuse sunlight to generate power, while CSP relies on direct sunlight, restricting its deployment to areas with high Direct Normal Irradiance (DNI). Mandatory demand supported with higher subsidies for green technologies will positively attracts dairies towards use of solar energy. In many villages, power cut hinders the reception of milk from milk producers as electronic weighing system and milk testing instruments require uninterrupted power supply. solar-powered dairy operations offer resilience against power outages and fluctuating energy costs, empowering farmers with greater control over their operations. As the Indian dairy industry embraces solar power, it not only secures a greener future but also fosters economic growth and energy access in rural communities, marking a significant stride towards sustainability and self-sufficiency.

102 Estradiol and follicular growth are associated with estrous behavior monitored by an accelerometer in grazing beef cows

Abstract In beef cattle, 40% of cows that display estrus do not remain pregnant after embryo transfer (ET). Estrus is a physiological behavior influenced by the concentration of sex-steroids. The use of accelerometer devices for estrus detection is a common practice in dairy operations. It remains unclear if this same artificial intelligence software can accurately measure reproductive behavior in beef females. We hypothesized that estrous variables detected by an accelerometer are associated with ovarian, hormonal, pregnancy outcome, and fertility-related variables measured in the cow. Fifty Bos indicus-influenced, cyclic, primiparous cows were fitted with an accelerometer collar (SCR Engineers, Israel) and a breeding indicator (Estrotectâ) to detect estrus after a synchronization protocol in five subsequent experimental replicates (n = 50*5 = 250). Only cows that showed estrus (d 0) remained in the study. The following variables were used from the accelerometer software: Activity Peak, Rumination Nadir, Estrus Duration, and Heat Index, calculated by proprietary algorithms. Dominant follicle (DF) diameter and plasma concentration of estradiol were measured on d -2 (day of progesterone device removal) and on d 0. On d -1 and d 4, endometrial thickness and luminal fluid accumulation were measured by ultrasonography. On d 7, two embryos were transferred/cow. Pregnancies were diagnosed on d 45 and terminated. After 30 d, a new replicate started. Cows included in at least two replicates that remained pregnant 100%, 99-50%, or less than 50% were classified as fertile, sub fertile, and infertile, respectively. Estrus display was recorded for 166 cows (66%). Estrus detection by accelerometer and Estrotect had excellent agreement rate (kappa coefficient 0.76). Cows detected in estrus only by Estrotect had 66% less pregnancy/ET than cows in estrus by both (9/21 vs. 97/145; P = 0.01). The DF diameter on d 0 was not associated with accelerometer variables. Cows with greater and moderate Activity Peak had a greater growth rate of the DF from d -2 to d 0 than lower Activity Peak cows (interaction day*Activity Peak; P = 0.06). Estradiol on d -1 was positively associated with the Activity Peak (P < 0.0001). Cows with lower Activity Peak had a thicker endometrium on both d -1 and d 4 (P=0.02), and greater uterine luminal fluid score on d -1 (P=0.03). Fertility status was not associated with any accelerometer variables. In conclusion, the Activity Peak is associated positively with estradiol concentration and DF growth, however no association was found with pregnancy outcome and fertility. Therefore, the main advantage of accelerometers in beef ranches is the ability to detect estrus at a similar accuracy as breeding indicators, using less labor. Future enhancements in hardware and software to allow prediction of pregnancy outcomes are expected to increase reproductive efficiency in cow-calf operations.

Environmental impact of Holstein Friesian and 3-breed crossbred dairy cows using a life cycle assessment approach applied to individual animals

This study aimed to set up a Life Cycle Assessment (LCA) approach at level of individual animals to assess the effects of a 3-breed crossbreeding program on the environmental impact of cows. It involved 564 cows, 279 purebred Holstein (HO) and 285 crossbreds (CR), originated from a 3-breed crossbreeding program based on the rotational use of Viking Red, Montebèliarde and HO sires and kept in 2 dairy herds of northern Italy (224 and 340 cows/herd, respectively). The reference unit of the LCA model was the lifetime of cows, from the birth to culling or death. Data were collected at different levels: individual animal-based data referred to the whole life (birth, calving, dry, cull or death dates, and milk production); individual test-date collection of body measures and BCS, used to predict body weight and to estimate energy requirements; common farm-based data concerning herd management (diets composition, and materials used). Data were used to compute: dry matter intake, milk and milk components production, gross income (GI) and income over feed costs (IOFC) pertaining to the lifespan of cows. An individual LCA-derived approach was set up to compute global warming potential (GWP), acidification and eutrophication potential (AP and EP, respectively), and land occupation (LO), which have been associated with different functional units (cow in her whole life or per d of life; kg of milk fat plus protein, and € of GI and of IOFC produced in the herd life). Data were analyzed using a generalized linear model including the fixed effects of genetic group (CR vs HO), farm and their interaction (genetic group x farm). Compared with HO, CR cows completed more lactations (+12%), had earlier first calving (-2 weeks), yielded more fat plus protein in milk both in the lifespan (+8%) and per d of life (+4%). Concerning the environmental impact, when compared with HO herd mates, CR cows had nominal greater emissions per cow in the whole life, similar emissions per d of life and nearly 3% lower GWP, AP and EP per kg of fat plus protein yielded in lifespan. Income over feed costs per unit of emission tended to be nearly 4% greater in CR compared with HO cows. Also the use of land tended to be lower in CR compared with HO in most indicators considered. In conclusion, LCA could be adapted to represent individual animals. Moreover, managing dairy cows according to a 3-breed rotational crossbreeding scheme may be regarded as a strategy that can contribute to mitigate the emissions and to improve the environmental impact of dairy operations.

An artificial intelligence approach of feature engineering and ensemble methods depicts the rumen microbiome contribution to feed efficiency in dairy cows

Genetic selection has remarkably helped U.S. dairy farms to decrease their carbon footprint by more than doubling milk production per cow over time. Despite the environmental and economic benefits of improved feed and milk production efficiency, there is a critical need to explore phenotypical variance for feed utilization to advance the long-term sustainability of dairy farms. Feed is a major expense in dairy operations, and their enteric fermentation is a major source of greenhouse gases in agriculture. The challenges to expanding the phenotypic database, especially for feed efficiency predictions, and the lack of understanding of its drivers limit its utilization. Herein, we leveraged an artificial intelligence approach with feature engineering and ensemble methods to explore the predictive power of the rumen microbiome for feed and milk production efficiency traits, as rumen microbes play a central role in physiological responses in dairy cows. The novel ensemble method allowed to further identify key microbes linked to the efficiency measures. We used a population of 454 genotyped Holstein cows in the U.S. and Canada with individually measured feed and milk production efficiency phenotypes. The study underscored that the rumen microbiome is a major driver of residual feed intake (RFI), the most robust feed efficiency measure evaluated in the study, accounting for 36% of its variation. Further analyses showed that several alpha-diversity metrics were lower in more feed-efficient cows. For RFI, [Ruminococcus] gauvreauii group was the only genus positively associated with an improved feed efficiency status while seven other taxa were associated with inefficiency. The study also highlights that the rumen microbiome is pivotal for the unexplained variance in milk fat and protein production efficiency. Estimation of the carbon footprint of these cows shows that selection for better RFI could reduce up to 5 kg of diet consumed per cow daily, potentially reducing up to 37.5% of CH4. These findings shed light that the integration of artificial intelligence approaches, microbiology, and ruminant nutrition can be a path to further advance our understanding of the rumen microbiome on nutrient requirements and lactation performance of dairy cows to support the long-term sustainability of the dairy community.

Investigating the Possibility of Using Renewable Energies in Livestock Units in Iran (A Case Study: Fereydounshahr)

Fereydounshahr experiences growing electricity shortfalls and an overreliance on polluting diesel generators. This analysis models renewable hybrid systems to electrify a local dairy operation using HOMER Pro 3.11 software. Despite higher upfront costs, adding just 5% solar photovoltaics maintained low net present costs while increasing clean energy penetration versus diesel generators alone. Furthermore, a combined diesel-solar-wind system reduced carbon dioxide and nitrogen oxide emissions by over 1%. Although diesel generators had the shortest payback period at 48 years, the capital recovery factor for a diesel–solar combination reached 62 years. Thus, tailored hybrid renewable systems could provide an affordable, low-emissions electricity solution for the Fereydounshahr livestock facility. With suitable wind and solar resources, the right policy incentives could also unlock substantial local renewable capacity to meet rising demand and mitigate dependence on imported, climate-harming fossil fuels.

Thermotolerance capabilities, blood metabolomics, and mammary gland hemodynamics and transcriptomic profiles of slick-haired Holstein cattle during mid lactation in Puerto Rico

Holstein cattle carrying a prolactin receptor gene mutation (SLICK) exhibit short and sleek hair coats (short-haired Holstein [SLK]) enhancing thermotolerance and productivity compared with wild type-haired Holstein (WT) under tropical conditions. The objectives were to unravel the physiological and molecular mechanisms that confer an advantage to this slick genotype in Puerto Rico and determine potential correlations between metabolites and physiological variables. At 160 ± 3 DIM we compared vaginal temperatures (VT) and voluntary solar radiation exposure (VSRE) during 48 h between 9 SLK and 9 WT Holsteins, whereas a subsample of 7 SLK and 7 WT were used to assess udder skin temperature, mammary gland hemodynamics and transcriptomics, and blood plasma untargeted metabolomics at a single time point. The SLK cattle showed lower VT throughout the day and greater VSRE at 1000 h and 1100 h compared with their WT counterparts. Total mammary blood flow (MBF) was greater in SLK Holsteins compared with WT. The metabolite 9-nitrooctadecenoic acid was identified as a potential biomarker for MBF; moreover, SLK cattle had greater amounts of this metabolite in their plasma. Prostaglandin D2 synthase (PTGS) was upregulated in the slick mammary gland, while plasma prostaglandin D2 was positively correlated with milk yield and increased in SLK Holsteins compared with WT. Interestingly, the arachidonic acid metabolism pathway was enriched in the mammary gland transcriptome and perturbed in the blood metabolome in the SLK Holsteins. In conclusion, SLK Holsteins exhibited lower body temperatures, greater VSRE, enhanced blood supply to the mammary gland, and alterations in genes and metabolites involved in arachidonic acid metabolism at the mammary gland and blood plasma. The usage of the SLK Holstein cattle genetics in dairy operations could be a feasible alternative to mitigate the adverse consequences of heat stress.

Employee perception of precision technology use at the dairy farm.

The adoption of precision technologies on dairy farms has increased significantly in recent decades, leading to the challenge of providing employees with resources to maximize the efficient use of these tools. The objective of this study was to explore how dairy farm employees perceive the available precision technologies and to identify possible challenges they face when adapting to their use at the farm. An online survey consisting of four sections (employee demographics, precision technologies in use, perception of these technologies, and opportunities for adapting to technology use) was completed from September to December 2022 by 266 farm employees from three dairies operated under similar management. Most of the respondents were identified as male (72.2%), Hispanic or Latino (92.5%), aged between 21 and 30 (39.1%) or 31 and 40 yr (36.8%), with a bachelor's degree (34.6%) or completion of middle school (29.3%) and having basic or no English proficiency (74%). Overall, the respondents indicated being comfortable (95.6%) with and understanding (91.8%) the technology they use. Employees recognized precision technology as a tool that helps them to be more efficient (93.7%), identifying the technologies' benefits (92.1%). However, challenges for adapting to these technologies included personal limitations, such as not knowing the language of the technology (31%), visual impairments (24%), light sensitivity (14%), and not being able to read (7%). Environmental limitations were also recognized and included cold weather (64.3%), wind (46%), and surroundings that were too dark (31%) or too bright (21%). Significant associations between perception of the technology and age, level of education, and English proficiency were identified. Respondents indicated their desire to learn more about precision technologies implemented at work, which could eventually lead to improved efficiency at the dairy operation through innovations in the way users interact with these technologies, increasing employees' motivation. This study provides insights that could assist the dairy industry in addressing challenges and enhancing opportunities for a more efficient use of precision technologies at dairy farms.

Prevalence of e.coli O157:H7, Salmonella, and Cryptosporidium Among Arizona Dairy Workers Using Post-Work Swabbing

Highlights Microbial assessment of dairy workers in Arizona, U.S. Provides demographic and working information of an underserved group. Highlights the need for health and safety assessments and solutions in the dairy industry. Abstract. The dairy industry in Arizona, like many other agricultural industries in the United States, is dependent on the labor that migrant farm workers provide. Infections caused by zoonotic pathogens are commonly underreported or misdiagnosed, and possibly more so in migratory workers that face cultural, structural, legal, financial, and geographic barriers to health services. The objectives of this project were to: assess the demographics of Arizona dairy workers, determine the exposure potential of Arizona dairy workers to zoonotic organisms, and inform best management practices. A questionnaire including demographics, work tasks, and household characteristics was administered. Swab samples were collected from the shoulders, knees, and foreheads of employees at two dairy operations at the end of the work shift. The swabs were cultured for E.coli O157:H7 and Salmonella. Molecular DNA isolated from Salmonella and Cryptosporidium was quantified using droplet-digital Polymerase Chain Reaction (ddPCR). Twenty dairy workers were recruited, and 60 samples were collected. The majority of workers were male, preferred to speak Spanish, and identified as Latino/Hispanic (68.8%, 93.8%, and 93.8%, respectively). E. coli O157:H7 was detected in 13% of cultured knee and forehead samples. Salmonella spp. gene copies were detected on 60.0% of samples collected from forehead skin samples; 40.0% of shoulder clothing samples; and 15% of knee clothing samples, as measured via ddPCR. The positive cultural and molecular samples indicate the need for improved post-workday sanitation practices at farms. This study provides surveillance of a largely invisible population, including insights that can be used to create site-specific health and safety protocols for the dairy industry, inform risk assessment models, and foster preventive practices in the dairy industry. Keywords: Agricultural workers, Dairy workers, ddPCR, Exposure, Microbial, Zoonotic

Evolution over the last 40 years of the assisted reproductive technologies in cattle - the Brazilian perspective for embryo transfer and resynchronization programs (part II).

The productivity of the beef and dairy industries depends directly on the reproductive efficiency and genetic gain of the herd, which are directly associated with the appropriate use of Assisted Reproductive Technologies (ARTs). The objective of this review is to show from a Brazilian perspective the evolution over the last 40 years of ARTs related to ovulation resynchronization programs and embryo transfer in cattle. Despite significant improvements and high fertility obtained in timed artificial insemination (TAI) protocols (Sales et al., 2024 - Part I), the improvement of the use of in vitro-produced embryos, development of resynchronization programs, and the advance in Doppler ultrasonography (Doppler-US) for reproductive assessments of bovine females were the ARTs that presented the greatest relevance on reproductive effectiveness in cattle. In the last seven years, the embryo transfer (ET) technology using in vitro-produced (IVP) embryos took over the conventional ET of in vivo produced embryos after donor's superovulation. Also, procedures and pregnancy rates after ET of IVP embryos were improved in dairy and beef operations. The Doppler-US allows the identification of non-pregnant females at an early stage based on the evaluation of blood perfusion of the corpus luteum. Recent studies in beef and dairy cows indicate satisfactory accuracy when Doppler-US is used at 20-22 days after TAI. Consequently, super-early resynchronization programs have been developed and are being implemented in commercial programs, thereby facilitating earlier conception through the use of semen from superior bulls, providing genetic and economic improvements in herds. Likewise, the assessment of luteal function by Doppler-US allows the selection of embryo recipients with greater receptivity, and consequently may increase the effectiveness of timed ET programs.