The impact of twice daily 3-nitroxypropanol supplementation on enteric methane emissions in grazing dairy cows

Although 3-NOP has been proven to reduce enteric methane (CH4) by ∼30% in indoor systems of dairying when the additive is mixed throughout a total mixed ration (TMR), there has been very limited research to date in grazing systems in which the most convenient method of additive supplementation is at milking twice daily. To investigate the effect of twice daily 3-NOP supplementation on enteric CH4 emissions, a 12-week study was undertaken in which treatment cows (n = 26) were supplemented with 3-NOP (80 mg per kg dry matter intake; DMI) twice daily at morning and evening milking, while control cows (n = 26) received no additive supplementation. Enteric CH4, hydrogen (H2) and carbon dioxide (CO2) were measured using GreenFeed units, while milk production, body weight (BW), body condition score (BCS) and DMI were monitored to determine the effect of 3-NOP supplementation on productivity. There was no significant effect of 3-NOP supplementation on any of the aforementioned parameters with the exception of CH4 and H2 production, respectively. Cows supplemented with 3-NOP produced ∼36% more H2 (P < 0.001) across a 24-h period, with reductions in CH4 production of 28.5% recorded in the 3 h after additive consumption (P < 0.001), however, levels of CH4 production returned to that of the control group thereafter. When CH4 production was considered across the entire 24-h period, the cows offered 3-NOP produced ∼5% less CH4 than the control (P < 0.050). Future research should focus on methods to increase the efficacy of the additive throughout the day which would include the deployment of a slow-release form or an out of parlor feeding system that allows animals consume the product at additional time points.

Cattle production strategies to deliver protein with less land and lower environmental impact

Global land resources are over-exploited and natural habitats are declining, often driven by expanding livestock production. In Ireland, pastureland for grazing cattle and sheep account for circa 60% of terrestrial land use. The agriculture, forestry and other land use sector (AFOLU) is responsible for 44% of national greenhouse gas (GHG) emissions. A new Grassland Animal response Model (GLAM) was developed to relate livestock-cohort grass and feed requirements to farm-grassland system areas, enhancing environmental assessment of prospective AFOLU configurations. Although land conversion targets are often well-defined, they tend to lack a clear definition of where land sparing can occur. Through analyses of 10 scenarios of milk and beef production and management strategies, we found that displacing beef cows with dairy cows can increase national protein output while sparing up to 0.75 million ha (18%) of grassland (albeit with a minor increase in overseas land requirement for additional concentrate feed). Reducing slaughter age, increasing exports of male dairy calves and increasing grassland use efficiency on beef farms each achieved between 0.19 and 0.32 million ha of land sparing. Sexed semen to achieve more favourable male-female birth ratios had a minor impact. GHG emissions, ammonia emissions and nutrient leaching were only reduced substantially when overall cattle numbers declined, confirming the need for cattle reductions to achieve environmental objectives. Nonetheless, application of GLAM shows potential for improved grass and cattle management to spare good quality land suitable for productive forestry and wetland restoration. This change is urgently needed to generate scalable carbon dioxide removals from the land sector in Ireland, and globally.

Quantitative risk ranking of mycotoxins in milk under climate change scenarios

Mycotoxins are toxic fungal metabolites that may occur in crops. Mycotoxins may carry-over into bovine milk if bovines ingest mycotoxin-contaminated feed. Due to climate change, there may be a potential increase in the prevalence and concentration of mycotoxins in crops. However, the toxicity to humans and the carry-over rate of mycotoxins from feed to milk from bovines varies considerably. This research aimed to rank emerging and existing mycotoxins under different climate change scenarios based on their occurrence in milk and their toxicity to humans. The quantitative risk ranking took a probabilistic approach, using Monte-Carlo simulation to take account of input uncertainties and variabilities. Mycotoxins were ranked based on their hazard quotient, calculated using estimated daily intake and tolerable daily intake values. Four climate change scenarios were assessed, including an Irish baseline model in addition to best-case, worst-case, and most likely scenarios, corresponding to equivalent Intergovernmental Panel on Climate Change (IPCC) scenarios. This research prioritised aflatoxin B1, zearalenone, and T-2 and HT-2 toxin as potential human health hazards for adults and children compared to other mycotoxins under all scenarios. Relatively lower risks were found to be associated with mycophenolic acid, enniatins, and deoxynivalenol. Overall, the carry-over rate of mycotoxins, the milk consumption, and the concentration of mycotoxins in silage, maize, and wheat were found to be the most sensitive parameters (positively correlated) of this probabilistic model. Though climate change may impact mycotoxin prevalence and concentration in crops, the carry-over rate notably affects the final concentration of mycotoxin in milk to a greater extent. The results obtained in this study facilitate the identification of risk reduction measures to limit mycotoxin contamination of dairy products, considering potential climate change influences.

Graduate Student Literature Review: System, plant, and animal factors controlling dietary pasture inclusion and their impact on ration formulation for dairy cows

Diet formulation in a pasture-based dairy system is a challenge as the quality and quantity of available pasture, which generally constitutes the base diet, is constantly changing. The objective of this paper is to cover a more in-depth review of the nutritional characteristics of pasture-based diets, identifying potential system, plant, and animal factors that condition pasture dietary inclusion in dairy cows. In practice, there is a wide diversity of pasture-based systems with predominant to minimal use of pasture requiring a more specific classification that potentially considers the amount and time of access to pasture, access to housing, length of grazing season, seasonality of calving, and level and method of supplementation. There are important differences in the nutritional quality between pasture species and even cultivars. However, under management practices that promote maintenance of pasture in a vegetative state as well as controlling the availability of pasture, it is possible to achieve high dry matter intakes (∼2.9%-3.4% of live weight) of pasture with moderate to high diet energy density, protein supply, and digestibility. The amount of pasture to include in the diet will depend on several factors, such as the type of production system, the cost of supplementary feeds, and the farmer's objectives, but inclusions of ∼40% to 50% of the diet seem to potentially reduce costs while apparently not limiting voluntary feed intake. Considering that there seems to be a continuum of intermediate management systems, a better understanding of the factors inherent to the feed ingredients used, as well as the use of nutrients by cows, and potential interactions between animal × system should be addressed in greater depth. This requires a meta-analysis approach, but given the diversity of the pasture-based system in practice, the existing information is highly fragmented. A clear definition of "subsystems" is necessary to direct the future research and development of mechanistic models.

Carbon footprint based on lifetime productivity for future cows selected for resilience to climate-related disturbances

Droughts, which can affect feed production, are projected to become more common under future climate conditions. In light of this, breeding cattle resilient to changes in feeding regimens is increasingly becoming an important topic. Body reserves can play a crucial role when feed resources are limited. We simulated populations of dairy cows selected with 2 different breeding goals: one reflecting the current breeding goal and the other placing weight on minimum level of body reserves in early lactation and change in body reserves during lactation. We considered this latter as a breeding goal for resilience. We used the 2 dynamic simulation programs ADAM and AQAL to predict performance of the cows after selection. In AQAL, we modeled moderate and severe drought by decreasing feed quality and quantity offered to cows during one year. We compared cows selected with the 2 breeding goals under 3 environments: without disturbances related to climate and with moderate and severe drought. In the environments without disturbances and the moderate drought, the cows selected with the current breeding goal had higher lifetime lactation efficiency (energy invested in milk/energy acquired from feed) and lower carbon footprint per kilogram of protein in milk and meat than cows selected for resilience. However, with severe drought, cows selected for resilience had higher lifetime lactation efficiency and lower carbon footprint per kilogram of protein in milk and meat than those selected with the current breeding goal. This suggests that cows selected for high productive performance do not perform well under very limiting conditions, leading to increased climate impact. The importance of inclusion of body reserves as a resilience trait in dairy cattle breeding depends on the future environment in which the cows will be used.

Impact of varying levels of pasture allowance on the nutritional quality and functionality of milk throughout lactation

The objective of this study was to examine the impact of increasing proportions of grazed pasture in the diet on the composition, quality, and functionality of bovine milk across a full lactation. Fifty-four spring-calving cows were randomly assigned to 1 of 3 groups (n = 18), blocked on the basis of mean calving date (February 15, 2020 ± 0.8 d), pre-experimental daily milk yield (24.70 ± 3.70 kg), milk solids yield (2.30 ± 0.27 kg), lactation number (3.10 ± 0.13), and economic breeding index (182 ± 19). Raw milk samples were obtained weekly from each group between March and November 2020. Group 1 (GRS) consumed perennial ryegrass and was supplemented with 5% concentrates (dry matter basis); group 2 was maintained indoors and consumed a total mixed ration (TMR) diet consisting of maize silage, grass silage, and concentrates; and group 3 consumed a partial mixed ration diet (PMR), rotating between perennial ryegrass during the day and indoor TMR feeding at night. Raw milk samples consisted of a pooled morning and evening milking and were analyzed for gross composition, free amino acids, fatty acid composition, heat coagulation time, color, fat globule size, and pH. The TMR milks had a significantly higher total solids, lactose, protein, and whey protein as a proportion of protein content compared with both GRS and PMR milks. The GRS milks demonstrated a significantly lower somatic cell count (SCC), but a significantly higher pH and b*-value than both TMR and PMR milks. The PMR milks exhibited significantly lower total solids and fat content, but also demonstrated significantly higher SCC and total free amino acid content compared with GRS and TMR. Partial least squares discriminant analysis of fatty acid profiles displayed a distinct separation between GRS and TMR samples, while PMR displayed an overlap between both GRS and TMR groupings. Variable importance in projection analysis identified conjugated linoleic acid cis-9,trans-11, C18:2n-6 cis, C18:3n-3, C11:0, and C18:2n-6 trans as the largest contributors to the variation between the diets. Milk fats derived from GRS diets exhibited the highest proportion of unsaturated fats and higher unsaturation, health-promoting, and desaturase indices. The lowest proportions of saturated fats and the lowest atherogenic index were also exhibited by GRS-derived milk fats. This work highlights the positive influence of grass-fed milk for human consumption through its more nutritionally beneficial fatty acid profile, despite the highest milk solid percentages derived from TMR feeding systems. Furthermore, this study demonstrates the proportional response of previously highlighted biomarkers of pasture feeding to the proportion of pasture in the cow's diet.

Evaluating the effects of grass management technologies on the physical, environmental, and financial performance of Irish pasture-based dairy farms

Grass management technologies (grass measuring devices and grassland management decision support tools) have been identified as important tools to improve the performance of pasture-based dairy farms. They have the potential to significantly improve the efficiency and sustainability of dairy systems by increasing milk production through enhanced pasture growth and utilization, which would reduce the need for supplementary feeds, along with increased output, therefore increasing farm profitability and environmental sustainability. Despite the several potential benefits of grass management technologies, there is a lack of empirical research around the effects of these technologies on the performance of pasture-based dairy systems. The current study aimed to fill this knowledge gap by using a 2018 nationally representative survey of Irish dairy farms and a propensity score matching approach to determine the effects of adopting grass management technologies on the physical, environmental, and financial performance of Irish pasture-based dairy farms. The findings showed that dairy farms utilizing grass management technologies had, on average, higher farm physical, environmental, and financial performance (in terms of grazed pasture use, total pasture use, length of the grazing season, milk yield, milk solids, greenhouse gas emissions per kilogram of fat- and protein-corrected milk, gross output, and gross margin) compared with dairy farms not utilizing these technologies. However, when controlling for selection bias, we can only attribute a positive causal effect of grass management technology adoption on the use of grazed pasture per cow, grazing season length, milk yield per cow, and milk solids per cow. This might be due to dairy farmers not yet using the technologies to their full potential, 2018 being an unusual year in terms of weather (and therefore not being able to capture the full range of farm performance benefits), or because grass management technologies need to be adopted in association with other technologies and practices to achieve their expected performance outcomes. Future research should include updated farm-level data to capture the weather and learning effects and so be able to determine the impact of grass management technologies on a wider range of performance indicators.

Measurement of grass uptake of the urease inhibitor NBPT and of the nitrification inhibitor dicyandiamide co-applied with granular urea

Grass uptake and phytoaccumulation factors of N-(n-butyl) thiophosphoric triamide (NBPT) and dicyandiamide (DCD) were quantified. Following the application of urea fertilizer treated with the inhibitors in Irish grassland, grass samples were collected at 5, 10, 15, 20, and 30 day time intervals following five application cycles. Uptake of NBPT by grass was below the limit of quantitation of the analytical method (0.010 mg NBPT kg-1). Dicyandiamide concentrations in grass ranged from 0.004 to 28 mg kg-1 with the highest concentrations measured on days 5 and 10. A reducing trend in concentration was found after day 15. The DCD phytoaccumulation factor was ranged from 0.004% to 1.1% showing that DCD can be taken up by grass at low levels when co-applied with granular urea. In contrast, NBPT was not detected indicating that grass uptake is unlikely when co-applied with granular urea fertilizer. The contrasting results are likely due to very different longevity of DCD and NBPT along with the much lower rate of NBPT, which is used compared with DCD.

Assessment of the current performance of grazing infrastructure across Irish dairy farms

The increased average Irish dairy herd size in a post-quota environment has put heightened pressure on grazing infrastructure. In a rotational grazing system, grazing infrastructure consists of the paddock system, which delineates the grazing areas into appropriately sized grazing parcels, and the roadway network, which connects these paddocks to the milking parlor. Where herd size has increased without corresponding adaptations to the infrastructure, farm management and roadway network performance has been affected. The links between suboptimal grazing infrastructure and roadway network efficiency are poorly understood and not widely documented. The aims of this study were to (1) analyze the effect of herd expansion and paddock size on pasture allocations per paddock, (2) identify the factors that affect the total distance walked per year, and (3) create a metric to compare the efficiency of roadway networks across farms of varying grazing platforms. A sample population of 135 Irish dairy farms with a median herd size of 150 cows was used for this analysis. Herds were split into the following 5 categories: <100 cows, 100 to 149 cows, 150 to 199 cows, 200 to 249 cows, and ≥250 cows. Herds with ≥250 cows had a greater number of paddocks per farm and rotated around the grazing paddocks more frequently, with 46% of paddocks only suitable for 12 h allocations relative to herd size, compared with just 10% to 27% of paddocks for herds with <100 cows to herds with 200-249 cows. When predicting the total distance walked per year on each study farm, the mean distance from a paddock to the milking parlor was the strongest indicator (R² = 0.8247). Other metrics, such as herd size, have failed to account for the location of the milking parlor relative to the grazing platform. The creation of the relative mean distance from a paddock to milking parlor (RMDMP) metric allowed the calculation of a farm's roadway network efficiency for moving the herd between paddocks and the milking parlor. The analyzed farms increased their efficiency in terms of RMDMP (0.34-40.74%) as they increased herd size post quota. However, the position of new additional paddocks relative to the milking parlor substantially affected their RMDMP.

Modeling the economic impacts of mobility scores in dairy cows under Irish spring pasture-based management

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues compared the ideal scenario.

Dairy farmer practices and attitudes relating to grass-based, high-feed-input, and indoor production systems in Ireland

Grazing has become a less common dairy farming practice in most European countries. Ireland is an exception with its predominantly grass-based system. After the removal of European milk quotas, farmers were encouraged to expand within a grass-based paradigm rather than pursuing yield increases through feeding more concentrate. This research assessed Irish dairy farmer attitudes toward grass-based, higher-feed-input, and indoor paradigms. A paradigm of agriculture is a shared understanding about how agriculture should be carried out. Grass-based, higher-feed-input, and indoor paradigms propose different solutions to economic, environmental, and animal-welfare challenges facing dairy farming. An online survey was distributed to Irish dairy farmers in August 2018, which received 396 responses. There was support among respondents for the grass-based paradigm of maximizing milk from forage and minimizing concentrate use, with 73% of respondents strongly agreeing or agreeing this was the best option for Irish dairy farmers. The results suggest there were not significant ideological disagreements among respondents about the economic, environmental, and animal-welfare merits of different paradigms. Rather, the results showed respondents supported grass-based or higher-feed-input paradigms for different reasons as follows: profitability and lifestyle for the former, and the ability to expand production without access to additional land and less dependence on weather for the latter. These findings could be of interest in countries where grazing is less widely practiced, but where there is a desire to increase the uptake of grazing practices. Messaging about the profitability and simplicity of the grass-based system clearly resonated with respondents, and could be replicated in other countries. There is a desire within the Irish government, industry, and advisory bodies to keep dairy expansion within a grass-based paradigm. The results suggested individuals may diverge from this paradigm not because they disagree with messaging about its benefits, but rather if difficulties with land access or managing weather variability lead them to expand through feeding more concentrate. To maintain production within the grass-based paradigm, more opportunities could be created for farmers who are restricted from further expansion, such as alternative supply chains or payments for environmental services.

Application of machine-learning methods to milk mid-infrared spectra for discrimination of cow milk from pasture or total mixed ration diets

The prevalence of "grass-fed" labeled food products on the market has increased in recent years, often commanding a premium price. To date, the majority of methods used for the authentication of grass-fed source products are driven by auditing and inspection of farm records. As such, the ability to verify grass-fed source claims to ensure consumer confidence will be important in the future. Mid-infrared (MIR) spectroscopy is widely used in the dairy industry as a rapid method for the routine monitoring of individual herd milk composition and quality. Further harnessing the data from individual spectra offers a promising and readily implementable strategy to authenticate the milk source at both farm and processor levels. Herein, a comprehensive comparison of the robustness, specificity, and accuracy of 11 machine-learning statistical analysis methods were tested for the discrimination of grass-fed versus non-grass-fed milks based on the MIR spectra of 4,320 milk samples collected from cows on pasture or indoor total mixed ration-based feeding systems over a 3-yr period. Linear discriminant analysis and partial least squares discriminant analysis (PLS-DA) were demonstrated to offer the greatest level of accuracy for the prediction of cow diet from MIR spectra. Parsimonious strategies for the selection of the most discriminating wavelengths within the spectra are also highlighted.

Incorporation of the grazing utilization subindex and new updates to the Pasture Profit Index

Grazing efficiency has been shown to differ between perennial ryegrass varieties. Such differences affect the utilization of grass within grazing systems, influencing the profitability of grass-based ruminant production systems. The Pasture Profit Index (PPI) is an economic merit grass variety selection tool developed to identify varieties with the greatest economic potential for grass-based dairy production systems. A new grass utilization subindex was developed and incorporated into the PPI to identify varieties with superior grazing efficiency. The subindex rewards varieties with superior grazing efficiency, measured as Residual grazed height, as these varieties allow increased amounts of herbage dry matter to be used by grazing animals. The economic values of all other traits within the PPI were reviewed and updated to ensure that the index was reflective of the current economic scenarios with appropriate assumptions included in the models, thus ensuring that varieties excelling in the agronomic traits with the greatest effect on profitability were recognized. The difference between the highest and lowest performing varieties for the grass utilization trait ranged from €23 to -€24. A range of €211 to €43 was recorded between the highest and lowest ranked varieties within the updated PPI. Spearman's rank correlation between the updated and original PPI lists was 0.96. The introduction of the utilization subindex will allow farmers to make informed variety selection decisions when reseeding pasture, particularly on their grazing platforms and it will allow a demand-based communication process between the farmer and the grass merchant or breeder, ultimately affecting trait selection for future breeding strategies.

Evaluation of Molly model predictions of ruminal fermentation, nutrient digestion, and performance by dairy cows consuming ryegrass-based diets

Several studies have been conducted to improve grazing management and supplementation in pasture-based systems. However, it is necessary to develop tools that integrate the available information linking the representation of biological processes with animal performance for use in decision making. The objective of this study was to evaluate the precision and accuracy of the Molly cow model predictions of ruminal fermentation, nutrient digestion, and animal performance by cows consuming pasture-based diets to identify model strengths and weaknesses, and to derive new digestive parameters when relevant. Model modifications for adipose tissue, protein synthesis in lean body mass and viscera representation were included. Data used for model evaluations were collected from 25 publications containing 115 treatment means sourced from studies conducted with lactating dairy cattle. The inclusion criteria were that diets contained ≥45% perennial ryegrass (Lolium perenne L.), and that dry matter intake, dietary ingredient composition, and nutrient digestion observations were reported. Animal performance and N excretion variables were also included if they were reported. Model performance was assessed before and after model reparameterization of selected digestive parameters, global sensitivity analysis was conducted after reparameterization, and a 5-fold cross evaluation was performed. Although rumen fermentation predictions were not significantly improved, rumen volatile fatty acids absorption rates were recalculated, which improved the concordance correlation coefficient (CCC) for rumen propionate and ammonia concentration predictions but decreased CCC for acetate predictions. Similar degradation rates of crude protein were observed for grass and total mixed ration diets, but rumen-undegradable protein predictions seemed to be affected by the solubility of the protein source as was the intestinal digestibility coefficient. Ruminal fiber degradation was greater after reparameterization, driven primarily by hemicellulose degradation. Predictions of ruminal and fecal outflow of neutral detergent fiber and acid detergent fiber, as well as total fecal output predictions, improved significantly after reparameterization. Blood urea N and urinary N excretion predictions resulted in similar accuracy using both sets of model parameters, whereas fecal N excretion predictions were significantly improved after reparameterization. Body weight and body condition score predictions were greatly improved after model modifications and reparameterization. Before reparameterization, yield predictions for daily milk, milk fat, milk protein, and milk lactose were greatly overestimated (mean bias of 61.0, 58.7, 73.7, and 64.6% of mean squared error, respectively). Although this problem was partially addressed by model modifications and reparameterization (mean bias of 3.2, 1.1, 1.7, and 0.4% of mean squared error, respectively), CCC values were still small. The ability of the model to predict grass digestion and animal performance in dairy cows consuming pasture-based diets was improved, demonstrating the applicability of this model to these productive systems. However, the failure to predict grass digestion based on standard model inputs without reparameterization indicates there are still fundamental challenges in characterizing feeds for this model.

Greenhouse gas emissions and nitrogen efficiency of dairy cows of divergent economic breeding index under seasonal pasture-based management

Greenhouse gas (GHG) emissions and nitrogen (N) efficiencies were modeled for 2 genetic groups (GG) of Holstein-Friesian cows across 3 contrasting feeding treatments (FT). The 2 GG were (1) high economic breeding index (EBI) animals representative of the top 5% of cows nationally (elite) and (2) EBI representative of the national average (NA). The FT represented (1) generous feeding of pasture, (2) a slight restriction in pasture allowance, and (3) a high-concentrate feeding system with adequate pasture allowance. Greenhouse gas and N balance models were parameterized using outputs generated from the Moorepark Dairy Systems model, a stochastic budgetary simulation model, having integrated biological data pertaining to the 6 scenarios (2 GG × 3 FT) obtained from a 4-yr experiment conducted between 2013 and 2016. On a per hectare basis, total system GHG emissions were similar for both elite and NA across the 3 FT. Per unit of product, however, the elite group had 10% and 11% lower GHG emissions per kilogram of fat- and protein-corrected milk and per kilogram of milk solids (MSO; fat + protein kg), respectively, compared with the NA across the 3 FT. The FT incorporating high concentrate supplementation had greater absolute GHG emissions per hectare as well as GHG per kilogram of fat- and protein-corrected milk and MSO. The elite group had a slightly superior N use efficiency (N output/N input) and lower N surplus (N input - N output) compared with the NA group. The high concentrate FT had an inferior N use efficiency and a higher N surplus. The results of the current study demonstrate that breeding for increased EBI will lead to a general improvement in GHG emissions per unit of product as well as improved N efficiency. The results also illustrate that reducing concentrate supplementation will reduce GHG emissions, GHG emissions intensity, while improving N efficiency in the context of pasture-based dairy production.

Invited review: A 2020 perspective on pasture-based dairy systems and products

Grazing pasture is the basis for dairy production systems in regions with temperate climates, such as in Ireland, New Zealand, parts of Australia, the United States, and Europe. Milk and dairy products from cows on pasture-based farms predominantly consuming fresh grazed grass (typically classified as "grass-fed" milk) have been previously shown to possess a different nutrient profile, with potential nutritional benefits, compared with conventional milk derived from total mixed ration. Moreover, pasture-based production systems are considered more environmentally and animal welfare friendly by consumers. As such, there is significant potential for market capitalization on grass-fed dairy products. As competition in this space increases, the regulations of what constitutes as grass-fed vary between different regions of the world. With this in mind, there is a need for clear and independently accredited grass-fed standards, defining the grass-fed criteria for labeling of products as such, subsequently increasing the clarity and confidence for the consumer. This review outlines the numerous effects of pasture production systems on dairy product composition, nutritional profile, and sustainability, and highlights potential future methods for authentication.

The Impact of Seasonality in Pasture-Based Production Systems on Milk Composition and Functionality

Seasonal calving, pasture-based dairy systems are widely practiced in countries with a temperate climate and plentiful rainfall such as Ireland and New Zealand. This approach maximizes milk production from pasture and, consequently, is a low-cost, low-input dairy production system. On the other hand, the majority of global milk supply is derived from high input indoor total mixed ration systems where seasonal calving is not practiced due to the dependence on ensiled silages, grains and concentrated feeds, which are available year-round. Synchronous changes in the macro and micronutrients in milk are much more noticeable as lactation progresses through early, mid and late stages in seasonal systems compared to non-seasonal systems-which can have implications on the processability and functionality of milk.

Dry Matter Intake and In Vivo Digestibility of Grass-Only and Grass-White Clover in Individually Housed Sheep in Spring, Summer and Autumn

Simple Summary

Feed intake and the digestibility of that feed are key drivers of animal production from grazed forage. This study compared the digestibility and voluntary dry matter (DM) intake of grass-only and grass-white clover (grass-clover) forage in individually housed sheep. The study was a Latin square design, repeated in spring, summer and autumn in 2017. Grass-clover and grass-only forage was harvested daily and offered ad libitum to 6 individually housed wether sheep per treatment. Digestibility of the forage DM, organic matter (OM), neutral detergent fibre (NDF) and acid detergent fibre (ADF) was determined using the total faecal collection method. Dry matter intake was similar on both forage types. White clover inclusion increased forage crude protein concentration in autumn and reduced NDF concentration in the offered forage, resulting in increased nitrogen intake in autumn and reduced NDF intake in all seasons. Grass-clover swards had a significantly greater OM and DM digestibility compared to grass-only swards. This could potentially result in increased animal production from grass-clover swards compared to grass-only swards.

Abstract

Intake and digestibility are key drivers of animal production from grazed forage. The objective of this study was to compare the in vivo digestibility and voluntary dry matter (DM) intake of grass-only and grass-white clover (grass-clover) forage in individually housed sheep. This study was a Latin square design, repeated on three occasions in 2017: Spring (27 March–29 April), summer (19 June–22 July) and autumn (4 September–29 September). Grass-clover and grass-only swards were harvested daily and offered ad libitum to 6 individually housed wether sheep per treatment per period. Digestibility of DM, organic matter (OM), neutral detergent fibre (NDF) and acid detergent fibre (ADF) were determined using the total faecal collection method. Dry matter intake was not significantly different between treatments. White clover inclusion increased forage crude protein concentration in autumn (p < 0.001) and reduced NDF concentration in the offered forage (p < 0.001), increasing nitrogen intake per sheep in autumn (p < 0.001) and decreasing NDF intake per sheep in autumn (p < 0.001). Grass-clover swards had a significantly greater OM and DM digestibility compared to grass-only swards (p < 0.05). This could potentially result in increased animal production from grass-clover swards compared to grass-only swards.

Economic assessment of Holstein-Friesian dairy cows of divergent Economic Breeding Index evaluated under seasonal calving pasture-based management

The objective of this study was to investigate the economic performance of 2 genetic groups (GG) of Holstein-Friesian dairy cows of divergent Economic Breeding Index (EBI), evaluated within 3 contrasting spring-calving pasture-based feeding treatments (FT). The study was a simulated economic appraisal, using the Moorepark Dairy Systems Model, a stochastic budgetary simulation model integrating biological data obtained from a 4-yr experiment conducted from 2013 to 2016. The 2 divergent GG were (1) high EBI representative of the top 5% nationally (elite) and (2) EBI representative of the national average (NA). The 3 FT were reflective of slight restriction to generous feeding. The elite GG had the lowest replacement rate, and therefore had lower replacement costs and an older and more productive parity structure. The elite GG consistently had higher sales of milk (on average +3% or +18,370 kg of milk) and milk solids (milk fat plus protein yield; +8.7% or +4,520 kg) compared with the NA GG across the 3 FT scenarios. Milk income was consequently greater for elite versus NA (on average +9.5% or +€21,489) cows. Livestock sales were greater (on average +13.2% or +€4,715) for NA compared with elite cows. Baseline net farm profit and net profit/ha at a base milk price of 29.5 cents per liter (3.3% protein and 3.6% fat) were on average €31,156, and €772 greater for elite compared with NA cows across the 3 FT. Greater profitability achieved with elite cows in each of the FT investigated demonstrated the adaptability of high-EBI cows across different levels of feeding intensities in seasonal pasture-based feeding systems. Sensitivity analysis of varying milk price and concentrate cost did not result in a reranking of GG for farm profit. This study clearly demonstrates the power of a suitably constructed genetic-selection index together with a well-considered breeding program to deliver genetics capable of favorable change to farm physical performance and profit over a relatively short duration.

Replacing Barley and Soybean Meal With By-products, in a Pasture Based Diet, Alters Daily Methane Output and the Rumen Microbial Community in vitro Using the Rumen Simulation Technique (RUSITEC)

Plant based by-products (BP) produced from food and bioethanol industries are human inedible, but can be recycled into the global food chain by ruminant livestock. However, limited data is available on the methanogenesis potential associated with supplementing a solely BP formulated concentrate to a pastoral based diet. Therefore the objective of this in vitro study was to investigate the effects of BP inclusion rate (in a formulated concentrate) to a pasture based diet on dietary digestibility, rumen fermentation patterns, methane production and the prokaryotic microbial community composition. Diets consisted of perennial ryegrass and one of two supplementary concentrates, formulated to be isonitrogenous (16% CP) and isoenergetic (12.0 MJ/ME/kg), containing either 35% BP, barley and soybean meal (BP35) or 95% BP (BP95) offered on a 50:50 basis, however, starch, NDF and fat content varied. The BPs, included in equal proportions on a DM basis, were soyhulls, palm kernel expeller and maize dried distillers grains. The BP35 diet had greater (P < 0.05) digestibility of the chemical constituents DM, OM, CP, NDF, ADF. Greater total VFA production was seen in the BP35 diet (P < 0.05). Daily methane production (mmol/day; +22.7%) and methane output per unit of total organic matter digested (MPOMD; +20.8%) were greatest in the BP35 diet (P < 0.01). Dietary treatment influenced microbial composition (PERMANOVA; P = 0.023) with a greater relative abundance of Firmicutes (adj P < 0.01) observed in the BP35. The Firmicutes:Bacteroidetes ratio was significantly reduced in the BP95 diet (P < 0.01). The relative proportions of Proteobacteria (adj P < 0.01), Succinivibrionaceae (adj P < 0.03) and Succinivibrio (adj P = 0.053) increased in the BP95 diet. The abundance of Proteobacteria was found to be negatively associated with daily methane production (r_s, −0.71; P < 0.01) and MPOMD (r_s, −0.65; P < 0.01). Within Proteobacteria, the relationship of methane production was maintained with the mean abundance of Succinivibrio (r_s, −0.69; P < 0.01). The abundance of the Firmicutes phyla was found to be positively correlated with both daily methane production (r_s, 0.79; P < 0.001) and MPOMD (r_s, 0.75; P < 0.01). Based on in vitro rumen simulation data, supplementation of an exclusively BP formulated concentrate was shown to reduce daily methane output by promoting a favorable alteration to the rumen prokaryotic community.

Sward type alters the relative abundance of members of the rumen microbial ecosystem in dairy cows

The performance of ruminant livestock has been shown to benefit from the enhanced nutritive value and herbage yield associated with clover incorporation in the grazing sward. However, little research to date has been conducted investigating the effects of mixed swards containing white clover on the composition of the rumen microbiome. In this study, the rumen microbial composition of late lactation dairy cows grazing perennial ryegrass only (PRG; n = 20) or perennial ryegrass and white clover (WCPRG; n = 19) swards, was characterised using 16S rRNA amplicon sequencing. PERMANOVA analysis indicated diet significantly altered the composition of the rumen microbiome (P = 0.024). Subtle shifts in the relative abundance of 14 bacterial genera were apparent between diets, including an increased relative abundance of Lachnospira (0.04 vs. 0.23%) and Pseudobutyrivibrio (1.38 vs. 0.81%) in the WCPRG and PRG groups, respectively. The composition of the archaeal community was altered between dietary groups, with a minor increase in the relative abundance of Methanosphaera in the WCPRG observed. Results from this study highlight the potential for sward type to influence the composition of the rumen microbial community.

Increasing Grazing in Dairy Cow Milk Production Systems in Europe

In temperate regions of Europe where grass grows for most of the year, grazed pasture is the lowest cost feed for milk production. Grazed pasture can make a contribution to dairy cow feeding systems in other parts of Europe, but is less important. While there are many challenges to maintaining or increasing the proportion of grazed grass in dairy cow diets, there are also opportunities to increase its contribution. Grass use and quality can be challenging for several reasons, including the cow and sward interaction, and factors influencing dry matter intake. Adapting grazing management strategies can provide opportunities for incorporating grazing and perhaps increase grazing in dairy cow milk production systems. Pasture management tools and techniques offer the opportunity to increase herbage use at grazing. While there are many benefits of grazing including economic, environmental, animal welfare and social, there are also the challenges to maintaining grazed pasture in dairy cow diets. The objective of this paper is to present an overview of the challenges and opportunities for grazing in dairy milk production systems.

The "Grass-Fed" Milk Story: Understanding the Impact of Pasture Feeding on the Composition and Quality of Bovine Milk

Milk is a highly nutritious food that contains an array of macro and micro components, scientifically proven to be beneficial to human health. While the composition of milk is influenced by a variety of factors, such as genetics, health, lactation stage etc., the animal's diet remains a key mechanism by which its nutrition and processing characteristics can be altered. Pasture feeding has been demonstrated to have a positive impact on the nutrient profile of milk, increasing the content of some beneficial nutrients such as Omega-3 polyunsaturated fatty acids, vaccenic acid, and conjugated linoleic acid (CLA), while reducing the levels of Omega-6 fatty acids and palmitic acid. These resultant alterations to the nutritional profile of "Grass-Fed" milk resonate with consumers that desire healthy, "natural", and sustainable dairy products. This review provides a comprehensive comparison of the impact that pasture and non-pasture feeding systems have on bovine milk composition from a nutritional and functional (processability) perspective, highlighting factors that will be of interest to dairy farmers, processors, and consumers.

Associating cow characteristics with mobility scores in pasture-based dairy cows

The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.

Influence of Supplemental Feed Choice for Pasture-Based Cows on the Fatty Acid and Volatile Profile of Milk

The purpose of this study was to examine the impact of a variety of supplemental feeds on the composition and quality of milk in a pasture-based dairy system. Four pasture-supplemented feeding systems were compared: Group 1 supplementation with 16% crude protein parlour concentrate (CONC); Group 2 supplementation with palm kernel expeller plus parlour concentrate (PKE); Group 3 supplemented with soya hulls plus parlour concentrate (SOYA); Group 4 was supplemented with molassed beet pulp plus parlour concentrate (BEET). Supplemental feeding system was demonstrated to have a significant effect on the size of native casein micelles and the gelation properties of milks. While CONC feeding produced significantly higher casein micelle size, gel strength (Young’s Modulus) was significantly negatively correlated with casein micelle size. Supplemental feeding system had a significant effect on a number of fatty acids (FA) and indices derived therefrom, including total saturated and unsaturated fatty acids, de novo produced FA, omega 3, and omega 6 FA. The volatile profile of milks was also affected by supplemental feed choice, whereby multivariate analysis demonstrated that the CONC diet was distinctly different to that of the PALM, SOYA, and BEET milks. Multivariate analysis demonstrated that it is possible to distinguish milks from different pasture-supplemented feeding systems by their FA profile.