Dairy Production Systems Research Articles

Association Between Dairy Production System and Milk Functionality Based on Analysis of miRNAs in Exosomes from Milk.

Dairy farming practices significantly affect the nutritional and functional properties of milk. This study compares miRNAs in milk exosomes from extensive and intensive dairy systems and explores their potential implications for human consumers. Extensive systems are believed to produce milk of higher quality with better animal welfare compared to intensive systems. Milk samples from eight extensive and nine intensive dairy farms were analysed. Milk-derived extracellular vesicles were isolated through sequential ultracentrifugation and characterised through Dynamic Light Scattering and Nanosight to determine the size and the concentration of the extracellular vesicles, in addition to immunoblotting to ensure the presence of exosome-specific proteins in their membrane. miRNA levels were quantified using RT-qPCR, and metabolic pathways associated with miRNAs showing significant differences between farm groups were analysed. EVs from extensive farms had higher concentrations. Notably, bta-miR-451 levels were significantly higher in milk from extensive farms (p = 0.021). Like human miRNA hsa-miR-451, it is linked to pathways related to Parkinson's disease and cancer. Our research suggests that milk production in extensive systems not only provides socioeconomic and environmental benefits but may also have positive effects on human health. Further research is warranted to explore the bioactive potential of these miRNAs and their implications for human health.

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.

Uncovering service gaps and patterns in smallholder dairy production systems: A data mining approach

Traditional clustering algorithms have often been used to categorize farmers but tend to overlook the underlying reasons for these groupings. Typically, clusters are formed based on common metrics such as dispersal and centrality, which provide limited insights into the relationships among key attributes. This study introduces an innovative approach using pattern and association rules analysis to better understand the characteristics of dairy production clusters. Focusing on Tanzanian smallholder farmers, the research moves beyond identifying clusters to uncovering the hidden relationships within them. Through pattern analysis, the study logically examines the behavioral mechanisms that define these clusters, highlighting service gaps that, if addressed, could enhance smallholder dairy farmers' productivity. Frequent patterns with support ranging from 57 % to 93 % and confidence levels between 85 % and 100 % were identified, revealing critical challenges faced by these farmers. For instance, farmers using Artificial Insemination—typically younger or new entrants—face constraints related to farm size, land holdings, fodder production, lack of farmer groups, and insufficient formal training in dairy care. Meanwhile, seasoned farmers deal more with institutional barriers such as limited access to marketplaces, extension services, and distant water sources. The study highlights the diverse challenges faced by different farmer groups and provides strategic recommendations for improving dairy productivity. Enhancing access to formal training, improving fodder production, supporting the formation of farmer groups, and addressing institutional barriers are key actions that could help Tanzanian smallholder dairy farmers increase milk yield and overall productivity.

The stability of fatty acids in yoghurts produced from bulk milk samples intentionally selected according to dairy production systems

The stability of fatty acids in yoghurts produced from bulk milk samples intentionally selected according to dairy production systems

Development of a Gold Nanoparticle-Based Sensor for Authentication of Organic Milk Based on Differential Levels of miRNA.

Dairy production systems significantly impact environmental sustainability, animal welfare, and human health. Intensive farming maximizes output through high-input practices, raising concerns about environmental degradation, animal welfare, and health risks from antibiotic residues. Conversely, organic farming emphasizes sustainable practices, animal welfare, and minimal synthetic inputs, potentially enhancing biodiversity, soil health, and milk quality. MicroRNAs (miRNAs), non-coding RNAs regulating gene expression, are promising biomarkers due to their response to various conditions. In this study, miRNAs bta-miR-103 and bta-miR-155, which are abundant in milk from pasture-fed cows, were selected. Additionally, bta-miR-215, which is abundant in milk fat from intensive systems, was also studied, in order to differentiate dairy production systems. A novel, cost-effective gold nanoparticle (AuNP)-based sensor was developed for miRNA detection, leveraging the unique plasmonic properties of AuNPs for visual detection. The method involves functionalizing AuNPs with complementary RNA probes and detecting miRNA-induced aggregation through colorimetric changes. This rapid, results in 30 min, and sensitive, visual limit of detection of 200 nM, assay requires minimal instrumentation and can be easily interpreted, offering significant advantages for field implementation in characterizing dairy production systems. This study demonstrates the successful application of this sensor in detecting miRNAs in 350 nM miRNA spiked raw milk, highlighting its potential for in situ dairy industry applications.

An Assessment of Sustainability of Dual-Purpose, Dairy and Beef Cattle Production Systems in the Cundinamarca Department (Colombia) Using the MESMIS Framework

An Assessment of Sustainability of Dual-Purpose, Dairy and Beef Cattle Production Systems in the Cundinamarca Department (Colombia) Using the MESMIS Framework

The LTAR Integrated Common Experiment at Upper Mississippi River Basin-Platteville.

Alternative agronomic practices are needed to address the various climatic, agronomic, edaphic, and water quality related challenges faced by the dairy farmers of the Driftless Area (DA) in the Upper Mississippi River Basin (UMRB). These practices should be innovative in nature, inclusive of regional stakeholders, and sustainable to meet the future food and climate related challenges of Wisconsin agriculture. Here, we outline our Integrated (grazing and cropland) Long-Term Agroecosystem Research Common Experiment at the University of Wisconsin-Platteville Pioneer Farm (UW-P PF) in the UMRB and describe our collaboration in this USDA network. In this field-scale experiment, we are comparing the conventional dairy production system common to this region (i.e., corn-on-corn [Zea mays L.] for 4 years, followed by alfalfa [Medicago sativa L.] for 3 years, with no cover crops) with two alternative dairy production systems-(1) soil health management with no-till, cover crops, and application of a novel manure-based nutrient-rich stable product, and (2) management intensive grazing-and rotational grazing on pastures established with diverse forage-legume mix. Meteorological, edaphic, hydrologic, and agronomic data are collected and analyzed at regular frequencies. Going forward, the experiment will continue as a form of stakeholder-driven adaptive research and receive evaluation on a regular basis to determine whether any changes are required to address the "real-world" challenges faced by the farmers in the Midwest.

Investigating the genomic background of calving-related traits in Canadian Jersey cattle

Traits related to calving have a significant impact on animal welfare and farm profitability in dairy production systems. Identifying genomic regions associated with calving traits could contribute to refining dairy cattle breeding programs and management practices in the dairy industry. Therefore, the primary objectives of this study were to estimate genetic parameters and perform genome-wide association studies (GWAS) and functional enrichment analyses for stillbirth, gestation length, calf size, and calving ease traits in North American Jersey cattle. A total of 40,503 animals with phenotypic records and 5,398 animals genotyped for 45,101 single nucleotide polymorphisms (SNPs) were included in the analyses. Genetic parameters were estimated based on animal models and Bayesian methods. The effects of SNPs were estimated using the Single-step Genomic Best Linear Unbiased Prediction (ssGBLUP) method. The heritability (standard error) estimates ranged from 0.01 (0.01) for stillbirths (SB) in heifers to 0.11 (0.01) for gestation length (GL) in cows. The genetic correlations ranged from -0.58 (0.11) between calving ease (CE) and SB in heifers to 0.44 (0.14) between calving ease and calf size (CZ) in cows. CE showed the highest genetic correlation between heifers and cows, 0.8 (0.22) respectively. The candidate genes identified, including MTHFR, SERPINA5, IGFBP3, and ZRANB1, are involved in key biological processes and metabolic pathways related to the studied traits. Reducing environmental variation and identifying novel indicators of reproduction traits in the Jersey breed are needed given the low heritability estimates for most traits evaluated in this study. In conclusion, this study provides a characterization of the genetic background of calving-related traits in Jersey cattle. The estimates obtained can be used to improve or build selection indexes in Jersey cattle breeding programs in North America.

Identifying strategies to enhance the milking and operator efficiency of herringbone and rotary parlor systems in Ireland

International trends of increasing dairy herd sizes coupled with scarcity of labor has necessitated the enhancement of labor efficiency for dairy production systems. This study quantified the effects of infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors used on pasture-based farms in Ireland. Data from 592 milkings across 26 farms (16 herringbones and 10 rotaries) was used. The metrics of cows milked per hour (cows/h), cows milked per operator per hour (cows/h per operator) and liters of milk harvested per hour (L/h) described milking efficiency. The metrics of total process time per cow (TPT, s/cow), milk process time per cow (MPT, s/cow), work routine time (WRT, s/cow), cluster time (CT, s/cluster), and attachment time per cow (ATC, s/cow) described operator efficiency. Automations investigated were backing gates, cluster flush, plant wash, cluster removers (ACRs), feeders, entry gates, rapid-exit, and teat spray. Additional operator presence at milking was also investigated. Herringbone and rotary parlors were assigned to quartiles from their cows/h per operator values to examine infrastructure, automations, and management practices variations. Fourth quartile herringbones based on cows/h per operator values (Q4) averaged 93 cows/h per operator using average system sizes of 24 clusters with 5 parlor automations. Q4 rotaries averaged 164 cows/h per operator using average system sizes of 47 clusters and an average CT of 13 s/cluster. Cows/h per operator values for Q4 herringbone and rotary parlors were 82% and 54% higher, respectively, than values observed on Q1 parlors, indicating the considerable potential to improve efficiency. To determine if infrastructure, automations, or additional operators at milking significantly affected operator efficiencies, general linear mixed models were developed. For parlor infrastructure, additional clusters had greater significance on operator efficiencies (MPT) for herringbones (-1.3 s/cow) as opposed to rotaries (-0.2 s/cow). Hence, increases in system size was likely to result in improved efficiencies for herringbones but less so for rotaries. For automations, ACRs significantly reduced herringbone TPT, CT, and WRT values by 13.3 s/cow, 18.9 s/cluster, and 32.6 s/cow, respectively, whereas rapid-exit significantly lowered CT by 18.6 s/cluster. We found no significant effect on rotary TPT, MPT, CT, or WRT values from the use of automatic teat sprayers. An additional operator at milking was found to significantly reduce herringbone TPT but not MPT or CT. For rotaries, a second operator had no significant effect on TPT, MPT, CT, or WRT values. We documented strong negative correlations between operator efficiencies (TPT, MPT) and milking efficiency (cows/h) for both herringbone (-0.91, -0.84) and rotaries (-0.98, -0.89). Strong negative correlations between the herringbone automation count and TPT (-0.80), MPT (-0.72), and CT (-0.75) suggested highly automated parlors were likely to achieve greater operator efficiencies than less automated parlors. The strong negative correlation (-0.81) between rotary milking efficiency (cows/h) and CT suggested lower CT values (i.e., rotation speed) resulted in increased milking efficiency. In conclusion, our study quantified the effects of parlor infrastructure, automation, and management practices on the milking and operator efficiency of herringbone and rotary parlors.

Evaluating the Potential of Double-Muscled Angus Sires to Produce Progeny from Dairy Cows to Meet Premium Beef Brand Specifications

In response to the increasing global demand for sustainable beef production, this review of the literature was undertaken to explore the possibility of using the progeny of cows in the pasture-based New Zealand dairy production system that are mainly of the Holstein–Friesian, Jersey, and Holstein–Friesian × Jersey-cross breeds, to produce beef that meets the standards demanded by the Certified Angus Beef® (CAB) standard. CAB is a United States of America (USA) benchmark for beef quality. Traditionally, the offspring of dairy breeds have not been suitable for producing high-quality beef due to their genetic makeup and physical characteristics. However, in the USA, breeding programmes have used genetic strategies to boost muscle meat yield in terminal-sire breeds like the Lim-Flex® and NuEra Genetics® T14 cattle lines. In these lines, selection has focused on enhancing muscling and other Angus traits, including ensuring the cattle are homozygous polled and black-coloured. The overall aim has been to alter the phenotypic characteristics of the offspring of dairy cows by terminal-sire crosses, so they resemble the phenotype of purebred Angus cattle and meet the CAB standard. The approach can involve using different alleles of the myostatin gene (MSTN) carried by the terminal Angus sires to increase carcass value from the dairy cow-derived male progeny (including the MSTN c.821(del11) allele or the myostatin protein p.F94L leucine-containing allele) to increase meat yield and eating characteristics. It is concluded that a targeted selection and mating strategy could provide another source of high-quality beef production, and one that also meets societal demands for better animal welfare and increased sustainability.

CARACTERIZACIÓN DE SISTEMAS DE PRODUCCIÓN LECHERA Y SALUD DE LA UBRE EN EL NORTE DE ANTIOQUIA, COLOMBIA

<p><strong>Background: </strong>The sociodemographic characterization of milk producers allows knowing their particular conditions in terms of social, political and economic structure through indicators that describe them as social actors, interaction networks, conflict situations and events related to milk production. <strong>Objective:</strong> To characterize the diversity of dairy production systems in Northern Antioquia with a focus on the producer, the farms, access to services and their impact on the biological indicators of udder health. <strong>Methodology:</strong> A cross-sectional study was designed <span style="text-decoration: line-through;">that</span> including 216 milk producers within distributed in 9 dairy municipalities in northern Antioquia. Surveys to characterize the producer, the farm and access to services for health and milk production were carried out. As biological indicators of udder health, the annual average<span style="text-decoration: line-through;">s</span> of bulk tank somatic cell counts (BTSCC) and colony-forming units (CFU) of each farm were analyzed. Statistical analyzes were performed with SPSS version 25.0 and a p < 0.05. <strong>Results: </strong>The biological indicators of udder health in the studied farms presented poor sanitary quality according to the BTSCC for 67 % of the producers and poor hygienic quality with CFU in for 22 % of the participating farms. Briceño producers showed the lowest production in contrast to Santa Rosa de Osos milk producers, who have the highest production. In the linear regression models, 18.2 % of the BTSCC was explained by the location in relation to the municipality, the size of the production system and the type of milking. The CFU values were explained in 29.8 % by the municipality, the cooperative association or livestock association, the milk storage system, the offer of laboratory services for milk and cows, the area of the farm dedicated to grazing, the number of animals on the farm and the average daily production per cow. <strong>Implications:</strong> This study shows the importance of understanding udder health issues not only at the cow level from a biomedical approach. The understanding of udder health from the farm in the sociodemographic context shows that its location, access to services, technology, education and associativity establish opportunities to improve production and competitiveness of milk production. <strong>Conclusions:</strong> udder health can be positively or negatively affected by the location of the production system, the size of the production system, the type of milking, the association to a cooperative or livestock association, the milk storage system, the supply of laboratory services for milk and cows, the area of the farm dedicated to grazing, the number of animals on the farm and the average daily production per cow. To consider these variables is fundamental in decision-making in mastitis control and preventive care for udder health.</p>

An integral assessment of the impact of diet and manure management on whole-farm greenhouse gas and nitrogen emissions in dairy cattle production systems using process-based models

Feed management decisions are crucial in mitigating greenhouse gas (GHG) and nitrogen (N) emissions from ruminant farming systems. However, assessing the downstream impact of diet on emissions in dairy production systems is complex, due to the multifunctional relationships between a variety of distinct but interconnected sources such as animals, housing, manure storage, and soil. Therefore, there is a need for an integral assessment of the direct and indirect GHG and N emissions that considers the underlying processes of carbon (C), N and their drivers within the system. Here we show the relevance of using a cascade of process-based (PB) models, such as Dutch Tier 3 and (Manure)-DNDC (Denitrification-Decomposition) models, for capturing the downstream influence of diet on whole-farm emissions in two contrasting case study dairy farms: a confinement system in Germany and a pasture-based system in New Zealand. Considerable variation was found in emissions on a per hectare and per head basis, and across different farm components and categories of animals. Moreover, the confinement system had a farm C emission of 1.01 kg CO2-eq kg−1 fat and protein corrected milk (FPCM), and a farm N emission of 0.0300 kg N kg−1 FPCM. In contrast, the pasture-based system had a lower farm C and N emission averaging 0.82 kg CO2-eq kg−1 FPCM and 0.006 kg N kg−1 FPCM, respectively over the 4-year period. The results demonstrate how inputs and outputs could be made compatible and exchangeable across the PB models for quantifying dietary effects on whole-farm GHG and N emissions.

Multispecies pasture diet and cow breed impacts on milk composition and quality in a seasonal spring-calving dairy production system

In recent years, there has been significant emphasis on the composition of pasture-based cow feed and the potential benefits of incorporating multispecies swards to improve sustainability and biodiversity. This study compared the effects of a conventional perennial ryegrass (PRG) monoculture supported by high chemical nitrogen (N) usage with a low chemical N application multispecies sward system (MSS) on the composition and quality of milk across lactation using spring-calving Holstein-Friesian (HF) and Jersey Holstein-Friesian (JFX) cows. Bulk milk samples (n = 144) were collected from each group at morning and evening milking on a weekly basis (n = 36) throughout lactation and analyzed for gross composition and physico-chemical properties. Cow breed had a significant impact on milk profile, with milk from HF cows having significantly smaller milk fat globule (MFG) size, higher instability index values, higher yield, and lower total solids levels, compared with JFX cows. Notably, HF cows had increased milk total solids and fat levels when fed on MSS, as opposed to the PRG-fed HF cows. Feeding MSS pasture increased creaming velocity values in mid and late lactation, and resulted in similar milk gross composition to PRG. In comparison to PRG, MSS-fed groups showed significantly increased total solids yield, including higher levels of protein and fat yield. In late lactation, MSS feeding was associated with reduced MFG size. All physicochemical properties studied (MFG size, creaming velocity, instability index) showed decreasing values from early to late lactation stage. Overall, these findings demonstrate the significant effects of cow diet, breed and stage of lactation on compositional and physico-chemical characteristics of milk, with important implications for milk processing and dairy product quality.

Assessing lameness prevalence and associated risk factors in crossbred dairy cows across diverse management environments

BackgroundA thorough understanding of lameness prevalence is essential for evaluating the impact of this condition on the dairy industry and assessing the effectiveness of preventive strategies designed to minimize its occurrence. Therefore, this cross-sectional study aimed to ascertain the prevalence of lameness and identify potential risk factors associated with lameness in Holstein Friesian crossbred cows across both commercial and smallholder dairy production systems in Bengaluru Rural District of Karnataka, India.MethodsThe research encompassed six commercial dairy farms and 139 smallholder dairy farms, involving a total of 617 Holstein Friesian crossbred cattle. On-site surveys were conducted at the farms, employing a meticulously designed questionnaire. Lameness in dairy cattle was assessed subjectively using a locomotion scoring system. Both bivariate and binary logistic regression models were employed for risk assessment, while principal components analysis (PCA) was conducted to address the high dimensionality of the data and capture the underlying structure of the explanatory variables.ResultsThe overall lameness prevalence of 21.9% in commercial dairy farms and 4.6% in smallholder dairy farms. Various factors such as age, body weight, parity, body condition score (BCS), floor type, hock and knee injuries, animal hygiene, provision of hoof trimming, and the presence of hoof lesions were found to be significantly associated with lameness. Binary logistic regression analysis indicated that the odds of lameness in crossbred cows increased with higher parity, decreased BCS, presence of hard flooring, poor animal hygiene, and the existence of hoof lesions. These factors were identified as potential risk factors for lameness in dairy cows. Principal component analysis unveiled five components explaining 71.32% of the total variance in commercial farms and 61.21% in smallholder dairy farms. The extracted components demonstrated higher loadings of housing and management factors (such as hoof trimming and provision of footbath) and animal-level factors (including parity, age, and BCS) in relation to lameness in dairy cows.ConclusionsThe findings suggest that principal component analysis effectively reduces the dimensionality of risk factors. Addressing these identified risk factors for lameness is crucial for the strategic management of lameness in dairy cows. Future research in India should investigate the effectiveness of management interventions targeted at the identified risk factors in preventing lameness in dairy cattle across diverse environments.

OLE! Dairy model

The process of intensification of the dairy sector has been characterized in recent decades by the increase in milk production per hectare, the increase in livestock density, the inclusion of more concentrates in the diet, and the improvement of the genetic merit of dairy cows. The use of models has productive, environmental, and economic advantages. The objectives of the study were to describe a new model, “OLE! Dairy model”, to (a) simulate the biophysical performance of a pasture-based dairy production system; (b) evaluate the predictive capacity of the model with a set of statistical parameters, comparing its results with the biophysical performance of experimental studies of dairy farm systems, and (c) calibrate by adjusting the technical coefficient. The experimental design combines two feeding strategies with a different proportion of pasture in the diet and two animal genotypes. We make a description of the biophysical component and the calculations proposed in the “OLE! Dairy model”. Then a variety of parameters was calculated for model testing, including the Mean Squared Error, the Relative Prediction Error, the square root of the MSE, the Concordance Correlation Coefficient, and the Model Efficiency. The model presented a good predictive capacity for stocking rate and concentrate, pasture, and reserve intake. The predictive capacity of the model for individual production and area production improves after performing a rapid calibration, which allows for avoiding overestimations or underestimations that generate erroneous measurements in the planning and management of milk production systems, and can be adjusted to different conditions of production of the region.

Decreasing environmental footprints of dairy production systems through optimization of feed rations and origins

Environmental impacts of livestock production systems are a global concern, because of the large greenhouse gas (GHG) emissions and nitrogen (N) and phosphorus (P) losses associated with feed production and livestock rearing. These losses are in part related to the system of livestock production and their feed rations and feed origin. This study aims to investigate the economic and environmental impacts of optimizing feed configurations of dairy farms in Inner Mongolia (China), using data from farm surveys, life cycle assessments and linear optimization programming. The findings of our study reveal that feed optimization may lower carbon footprints by 36–44%, nitrogen footprints by 35–42%, and phosphorus footprints by 42–71%, compared to the baseline. The need for cropland decreased by 11–38% per kilogram of milk, feed costs decreased by 15–48%, and net profit increased by 39–129%. Further, we found a statistically significant negative correlation between environmental footprints and feed self-sufficiency of dairy farms. Notably, energy-rich feeds, silage maize, and grass should be grown on-farm. These findings underscore the potential of adjusting feed rations and origin to decrease environmental footprints and enhance net profits of dairy farms. However, we observed several barriers to widespread adoption of optimal feed rations and origin, which relate to land scarcity, high land rental costs, and lack of trust and cooperation with nearby arable farms. Our research provides a scientific foundation for optimizing feed rations and origins for diverse dairy systems to achieve improved environmental and economic performance.

Effect of carbohydrate source on energy-nitrogen balance and methane emissions in lactating dairy cows

The chemical characteristics of Cenchrus clandestinus grass, nutritional base in dairy production systems, demand the energy supplementation. Corn grain is the most used food for this purpose, but considering its demand and prices, the objective of this work was to evaluate its partial replacement by alternative non-fibrous carbohydrates sources on methane emissions, energy and nitrogen balance and productive performance of dairy cows. Sixteen multiparous Holstein cows were fed Cenchrus clandestinus plus one of four concentrate supplements formulated with corn (Zea mays) or a partial replacement of corn with sorghum (Sorghum vulgare), cassava (Manihot esculenta) or citrus pulp (Citrus sp.). Inclusion of sorghum, cassava or citrus pulp did not affect dry matter intake, dry matter digestibility, enteric methane emissions, energy and nitrogen balance, milk yield or composition. The results allow to conclude that these ingredients can partially replace corn in the diet of lactating dairy cows.

Silvopastoral arrangements and tree species diversity on dairy farms of Monción, Dominican Republic

Traditional livestock systems of the Northwest of the Dominican Republic require a transformation towards sustainable productive alternatives such as silvopastoral systems (SPS), which result from the combination and interaction of trees-animals-grass. Therefore, the study was carried out with the objective of studying the diversity of silvopastoral arrangements and their tree species in dairy production systems of the municipality of Monción, Santiago Rodríguez, Dominican Republic, for the promotion of these systems as a sustainable alternative to the climate change. The silvopastoral arrangements and their tree species were studied through direct inspection and application of semi-structured interviews to selected livestock producers from Monción. Dasometric variables were measured (e.g.: chest diameter or CD, total height) and descriptive statistics were applied. It was evident that the most predominant SPS was scattered trees (87 %), followed by windbreaks (23 %) and trees on boundaries (20 %). The least frequent arrangements were living fences (13 %), riparian forests (7 %) and forest patches (7 %). 26 tree species were recorded, the four being dominant: Prosopis juliflora(21 %), Pinus occidentalis(17 %), Mangifera indica(10 %) and Swietenia mahagoni(9 %). The species Acacia skleroxylaobtained the highest height with 8.62 m and M. indicastood out with the highest DBH with 54.85 cm. It is recommended that Monción ranchers expand the tree coverage of their farms with the replanting and management of species such as Gliricidia. sepium, P. julifloraand Guazuma ulmifolia, in order to enrich the forage alternatives for their livestock.

How the type of dairy production system affects the nutrient balance from an environmental and economic perspective

The knowledge of nutrient flow in dairy farms has to be explored to find optimized strategies for efficient nutrient conversion to milk. This study aims to improve the understanding of variances in nitrogen and phosphorus balance and efficiency indicators between dairy farm systems. The study analyzed 67 dairy cattle farms located in the watershed Lajeado Tacongava, Rio Grande do Sul State, Brazil. Selected dairy farms represented three production systems: confined (3 farms); semi-confined (7 farms); pasture-based (57 farms). Input–output nutrient balances were calculated at the dairy system level for nitrogen and phosphorus over a year. Inputs are feed and fertilizer and outputs are milk and meat. The main nitrogen and phosphorus input on the all farms resulted from the feed. The average N and P surplus on pasture-based farms were 352 and 49 kg ha−1 year−1, respectively. In semi-confined systems were 508 and 63 kg ha−1 year−1 and in confined systems were 786 and 70 kg ha−1 year−1. When considering the monetary value of the total N surplus, the averages were US$ 2.615, 4.950, and 12.171 for pasture-based, semi-confined and confined systems respectively. Monetary values of P surplus were US$ 346, 588, and 1119 for pasture-based, semi-confined and confined. The productive aspects that most determined the values of N and P surplus were the total number of lactating cows and the farm area. Results indicate that surplus can partially replace chemical nitrogen fertilizer, except in the confined system, and fully replace phosphorus fertilizer. Confined farms presented values to use surplus as fertilizer greater than the crop demand. For the other production systems, it happens only for phosphorus. Large variability between dairy farms of the same production system and between different production systems was observed. It reflects the inherent productive, economic, and environmental conditions of each farm and system.