Typical Dairy Farm Research Articles

Strategic Categorization of Dairy Cow Farms in Croatia using Cluster Analysis

Abstract Background The milk processing sector in the Republic of Croatia faces numerous challenges. It is a distinctly bipolar structure, with some entities resembling the largest milk producers in the EU, while many small and medium-sized dairy farms struggle to remain competitive and achieve further progress. To formulate effective policy, it is important to differentiate between these types and address their key challenges. Objectives The aim is to find the most representative solution that will help us define typical dairy farms and upgrade a SiTFarm tool (Slovenian Typical Farm Model), enabling us to assess the situation in Croatia comprehensively. Methods/Approach Cluster analysis was conducted using empirical data obtained from the Croatian Agency for Agriculture and Food. The analysis involved applying both hierarchical and non-hierarchical clustering techniques. Results Two cluster analysis scenarios are presented, differing in the variables used. In each scenario, 16 relatively homogeneous clusters of farms were obtained. Diversity was minimized within these clusters, and they effectively explain the dairy business in Croatia. Conclusions The results of this analysis thus represent an important starting point for further analysis of the dairy sector in Croatia. These findings could help policymakers identify the types of farms that would benefit most from targeted investments to enhance efficiency, economic viability, and environmental sustainability.

Performance evaluation of Uruguayan dairy farming systems

In the last 20 years, the Uruguayan dairy sector has intensified and concentrated on higher cow productivity, maintaining the herd, smaller land, and fewer farms. The research aims are to identify, describe, and evaluate the economic performance of different types of dairy farms. A sample of 284 farms from the National Dairy Farm Survey 2019 was used (representing 2,021 dairies); using k-means Cluster analysis with the variables: cow productivity, stocking rate, land productivity, concentrate, roughage, and grass intake (per hectare). We identified six farm types, three with high participation of grass in the cows’ diets (HG, 60% or more of dry matter intake), and the other three focused on supplementation (HS); with three intensification levels (1-low, 2-intermediate and 3-high productivity per ha). For the 2018/19 season three types of farms presented the best economic performance (HS-3, HG-3, and HG-2), including those with the highest stocking rate and grass intake per hectare, and more than USD 225 Economic Farm Surplus (EFS) per hectare with the lower unitary cost. Other two types exhibited intermediate economic performance (HS-2 and HG-1) with EFS close to zero and unitary cost similar to price. And one type (HS-1) displayed the worst economic performance, with negative indicators and the largest number of farms with very low productivity.

Understanding the Dairy Sector in Slovenia: A Modeling Approach for Policy Evaluation and Decision Support

This study investigates the dairy sector in Slovenia, focusing on farm heterogeneity, efficiency in resource utilization, and policy implementations. Through a modeling approach, we explore the differences among dairy farms, considering factors such as herd size, farm management, natural conditions, and production potential. Based on 32 typical dairy farms, representing the entire dairy sector, composed of 6400 dairy farms, the analysis was performed using the farm model (SiTFarm). We emphasize the importance of accurate assessments, given the variability of policy impacts across farm types. While medium-to-large, specialized farms dominate milk production, smaller farms, particularly in less favored areas, hold social and environmental importance despite facing competitive challenges. Addressing environmental sustainability could involve promoting practices that improve milk yield and include grazing, as this tends to lower greenhouse gas emissions per kilogram of milk (−5%). Dairy farms contribute about one-third of the generated revenue in Slovene agriculture, of which a good half goes to farms located in less favored areas. They manage a good quarter of permanent grassland in Slovenia, and it is certainly the sector that can achieve the highest return on these areas. In 75% of the farms, the gross margin is higher than 1756 EUR/ha and using best practices they exceed 3400 EUR/ha. The model results indicate that the average hourly rate on dairy farms during the observed period falls within the range of EUR 7.3 to 17.4 of gross margin for most farms, with the top-performing ones exceeding 24 EUR/h. However, due to the significant reliance on budgetary payments (on average, 58% of the gross margin), the implementation of the common agricultural policy strategic plan generally leads to a deterioration in the economic indicators of dairy farms. This impact is particularly pronounced on medium-sized and larger farms, increasing the effect on income due to the substantial fixed costs involved. Our findings underscore the interplay between policy interventions, farm characteristics, and sectoral outcomes, offering valuable insights for policy-makers and stakeholders.

Development of LIME-NZ: a generic tool for prompt estimation of economic impacts of disease for New Zealand livestock

ABSTRACT Aims To develop a simple and robust generic tool to measure the impacts of livestock diseases on New Zealand dairy, beef and sheep farms using enterprise gross margin models. Methods The most recent (2018–2020) livestock production benchmarking data was extracted from industry-led economic surveys. Gross margin models were built for each enterprise type, accounting for 11 dairy farm types and 16 farm types for beef and sheep. Disease parameters, including changes in mortality, reproduction performance, milk yield, price of animals and culling rate, as well as additional expenses for veterinary intervention, were applied to the infected compartment of the herd/flock using the assumed annual within-herd disease incidence. Farm-level disease impacts were estimated as the difference in annual profit between the baseline and infected farm. The baseline gross margin models were validated against the industry data. The disease impact models were validated using a recently published study on bovine viral diarrhoea (BVD). The impact assessment tool, LIME-NZ, was developed using the statistical software R and implemented in the web-based R package Shiny. The input parameters can be varied interactively to obtain a range of disease impacts for uncertain disease parameters. Results The baseline gross margin models demonstrated reasonable accuracy with a mean percentage error of <14% when compared with the industry reports. The estimated annual impacts of BVD were comparable to those reported in the BVD study, NZ$38.5–140.4 thousand and $0.9–32.6 thousand per farm per year for dairy and beef enterprises, respectively. Conclusions LIME-NZ can be used to rapidly obtain the likely economic impacts of diseases that are endemic, recently introduced or at increased risk of introduction in the New Zealand context. This will aid communication and decision-making among government agencies and the livestock industry, including veterinarians and livestock producers, about the management of diseases, until refined information becomes available to improve decision-making.

On-farm investments into dairy cow health: evidence from 15 case study countries.

Managing investments in dairy cow health at a national and global scale, requires an improved understanding of current on-farm expenses for cow health (e.g., expenditure for medicine and veterinary consultations). The aim of this study was to assess on-farm health investments for typical dairy farms in 15 case study countries, including Argentina, Australia, Bangladesh, Brazil, Canada, India, China, Colombia, Indonesia, Kenya, New Zealand, Uganda, UK, Uruguay, and USA. The study was conducted using a descriptive analysis of a secondary data set that was obtained from the International Farm Comparison Network (IFCN). The results suggest that health expenditures take up a relatively small proportion (<10%) of the annual total production costs per cow across all countries in the sample. The means of production costs (e.g., feed, machinery) can take up to 90% of the total production costs for highly intensive systems, while these costs can be as low as 9% for extensive systems. This study highlights the importance of understanding on-farm animal health investments as a contribution to improved national and global decision making about animal health in the dairy sector.

Examining the trade-offs between agri-environmental and manure policies in Dutch dairy farming

Farmers increasingly have to navigate through a complex web of agricultural and environmental regulations. In the EU, for example, the Nitrate Directive aims to control the nutrient levels in the water and agri-environmental schemes aim to protect habitats and increase biodiversity. The trade-offs between such environmental policies are not clear. Therefore, this paper studies the interaction between manure policy, especially derogation policy, and meadow bird schemes for the Netherlands. We develop a mathematical programming farm model with nine representative dairy farm types, based on location and economic size, that gain utility from both profit and agri-environmental services production. We show that the abolishment of derogation and the introduction of a low-protein feeding measure – both aimed at reducing nitrogen emissions – reduce total land contracted for meadow birds. This is because (1) without derogation makes farms switch to more maize production, hence reducing grassland, and (2) the protein measure requires extra feed production on-farm which most farms cannot accomplish and which makes contracting for the meadow bird scheme less attractive. Especially farms on peat and more intensive farms, who are more dependent on buying feed, reduce the amount of land contracted. We advocate that policy makers should become aware of how policies interact and that researchers do not study them in isolation.

Dairy Cows Grazing Plantain-Based Pastures Have Increased Urine Patches and Reduced Urine N Concentration That Potentially Decreases N Leaching from a Pastoral System.

The objective of this study was to determine the effect of grazing plantain-based pastures on urine volume, urination frequency, and urinary nitrogen (UN) concentration of dairy cows under a typical pastoral dairy practice offering approximately 25% supplemented feeds. The experiment was a completely randomised design with three pasture treatments (perennial ryegrass-white clover (RGWC); RGWC + low plantain rate (PLL); and RGWC + high plantain rate (PLH)), five replicate plots, and repeated in two sequential grazing periods. Forty-five lactating Friesian × Jersey cows were randomly assigned into three groups of 15 animals each to graze over six days in adaptation paddocks and three days in experimental plots. Urine flow sensors were used to measure urine volume and urinary frequency, while spot urine sampling was conducted to determine nitrogen (N) concentration in cow urine. The results showed that including 25% plantain in the diet (PLH) increased daily urine volume by 44% and the daily number of urinations by 28%, compared to grazing the RGWC pasture. In addition, N concentration in cow urine was decreased by 18 and 29% when the diet contained 18% and 25% plantain, respectively. In conclusion, under a typical dairy farm practice, incorporating plantain into the RGWC pasture with the proportion of 25% plantain in the diet can increase the number of urine patches and reduce the concentration of N in the urine, thereby providing the opportunity to decrease N leaching from pastoral systems.

Production pathways for profitability and valuing ecosystem services for willow coppice in intensive agricultural applications

Increasing agricultural sustainability is a key challenge facing the globe today. Energy crops, planted as riparian buffers are one way to support this, simultaneously mitigating water quality degradation and climate change. However, the economics of implementing such riparian buffer systems is under researched. Hence this work conducted a bottom-up economic analysis of willow coppice riparian buffers on a Northern Irish dairy farm, which is indicative of agricultural intensification across Europe. This work includes an economic assessment of a willow coppice riparian buffer strip, using harvested yield data from an established willow buffer site for the first time. It also considered the impact of harvesting technology on the economic performance of a willow coppice riparian buffer strip for the first time. The analysis considered three willow production pathways: 1) direct chip harvesting, 2) full-stem harvesting, and 3) a scenario with a guaranteed purchasing contract for fresh chip. Economic performance was considered using net present value over a 25-year plantation lifetime. The full-stem scenario provided the highest economic return over its lifetime with an average yearly net present value of £497 ha−1 (in £ sterling). This system was then considered for integration into a typical dairy farm, assuming 5 % land usage and including government grants for establishing riparian zones. The result was a drop in value of £28 ha−1 yr−1 compared to a dairy-only scenario; however, per litre of milk the farm employing willow coppice riparian buffer strips outperformed a typical dairy farm both environmentally and economically. Further analysis considered a novel approach that included payments for ecosystem services in the economic analysis. This analysis found that the implementation of government payments for ecosystem services (nutrient removal) increased the economic return of the willow coppice riparian buffer system by £400 ha−1 yr−1, resulting in minimal impact on the return from dairy land.

Estimation of feed costs and feed efficiency in typical dairy Farms of Bangladeshduring Coronavirus (Covid-19) emergency: implications toward feed support policy

Feed cost is the highest cost item to the total costs of dairy farming all over the world including India, Pakistan and Bangladesh. Reducing feed costs and increasing feed efficiency-are two promising ways to decrease the cost of milk production and increase the competitiveness nationally and internationally(Hemme et al. 2014). Feed price in Bangladesh dairy farm is 51%higher than global feed price which has increased further due to the sudden infection of Coronavirus (Covid-19) (IDRN, 2020).Therefore, the objective of this paper is to estimate the impact of pandemic novel Coronavirus (COVID-19) prevalence on feed costs and feed efficiency in order to find a suitable feed supporting policy to the dairy farmers. The International Farm Comparison Network (IFCN) Feed Simulation Approach and Technology Impact Policy Impact Calculations (TIPICAL) model was used for estimating feed costs and feed efficiency of the dairy farm with and without Corona situation (This model is highly relevant to this study due to the fact that this model can produce result seven with the scarcity of the data and it is highly scientific and produce the results that are simultaneously used both Academia(University and Research organization) and Industry (for business strategic decisions). The Integrated Dairy Research Network (IDRN) dairy sector and dairy farm database (January2019 to March 2020) was used where 2019 is considered as without Corona (WOC) and March 2020 is considered as with Corona(WC). Two typical farms:2cow farm (BD-2) which is representative of 42% household farm (Household Farm (HF) is defined as one the income source for livelihoods, mainly consumed at household level and sells the surplus milk. The average size of the household farm (1-3 cows/farm) as per the International Farm Comparison Network (IFCN) methodology) and fourteen cow (BD-14) which is representative of 48% family farms in Bangladesh were selected. The share of feed cost to the total costs of milk production is increased by 9.5% and 8.9% for BD-2/19-WC and BD-14/20-WC,respectively. The purchased feed costs before corona was 22.1USD/100 kg milk for BD-2/19-WOC and 32.2 USD/100 kg milk forBD-14/19-WOC which is increased to 23.8 USD/100 kg and 35.0USD/100 kg for BD-2/20-WC and BD-14/20-WC, respectively(Author’s own results). The purchased feed costs increased by7.6% and 8.7% for BD-2/20-WC and BD-14/20-WC, respectively while for the homegrown feed, it is increased even higher which is 14.1% and 9.7%, respectively. The results revealed that decreasing milk price and increasing feed price has direct impact on increasing feed costs of 8.6% and decreasing margin over compound feed costs by 4.5% due to Coronavirus. As a result, an increase in feed cost, decrease in the margin over total feed cost and the feed efficiency (total, energy, and protein efficiency)was observed due to coronavirus (Covid-19) infection. The finding of this study revealed that for short-term and medium-term, farmers might need feed incentives either in the form of reduced feed price or liberalized concentrate feed input market. The outcome of this study is expected to be beneficial for policymakers, feed suppliers and farmers in Bangladesh and similar other countries like India, Pakistan, Sri Lanka and Nepal.

Determinants of technical efficiency among dairy farms in Chitwan, Nepal

Nepalese dairy sector has been showing structural changes with adoption of latest technologies like improved breeds, feeds, cultivated fodder and additives. In the context of these changes, this research was conducted to assess the technical efficiency and its determinants among dairy farms. The study was accomplished with primary data collected through face-to-face interview using semi-structured interview schedule from a sample of 240 dairy farms selected randomly using simple random sampling technique from 8 wards of Bharatpur Metropolitan City, Chitwan. Data were analyzed using descriptive statistics, stochastic production frontier and tobit regression model. Technical efficiency was found to be the highest in mix dairy farms (3.530) followed by cow farms (2.56) and buffalo farms (2.138). Labour was the most contributing factor in all three types of dairy farms. This study had shown that average annual income per farm should be Rs. 542000, Rs. 403225 and Rs. 611400 for getting 90% technical efficiency in milk production at buffalo, cow and mix farms, respectively. Similarly, 57% buffalo farms were operating at efficiency of 30-60%, 46% cow farms were operating at efficiency of 30%, and 67.5% mix farms were operating at efficiency of 30 to 60%. Total investment in dairy farming, training and adopting dairy as primary occupation were positively and significantly affecting technical efficiency on buffalo, cow and mix type of dairy farming system. There is still large scope to increase the annual milk production in the dairy farms of Chitwan through efficient use of available resources with the existing technologies. This is concluded that dairy farming system can be promoted efficiently by increasing total investment in dairy farming through easy access to loan, training on dairy animal production and management, ensuring dairy business as profitable primary occupation, promotion of fodder and pasture production, and securing easy access to medicines and additives.

Acidified diet is not effective in preventing hypocalcemia in dairy cows on French commercial farms

The objective of this study was to assess, in the context of typical dairy farms in western France, the preventive effects of prepartum diet acidification (AcD) and mineral intake during late gestation on the incidence of subclinical hypocalcemia (SHC) and subclinical hypophosphatemia (SHP) after calving. We conducted a longitudinal study that followed a cohort of 371 Holstein cows from 26 French dairy farms; of these, 235 cows (15 farms) were supplied with anionic salts during late gestation, and 136 cows (11 farms) were not. Blood samples were collected from 1 to 22 cows per farm (average of 14.3 cows per farm) between 24 and 48 h after calving. Total calcium and inorganic phosphorus concentrations in plasma were then quantified by inductively coupled plasma - optical emission spectrometry. The effects of AcD on the incidence of SHC and SHP were assessed using mixed linear models that evaluated the cow-level factors parity, milk yield index, and individual health events/treatments, and the farm-level factors diet calcium and magnesium content, dietary phosphorus intake, vitamin D supply, diet crude protein content, and duration of AcD, with farm as a random effect. Approximately 55% of cows were diagnosed with SHC (calcium &amp;lt; 2.0 mmol/l, n = 203) and 37% with SHP (inorganic phosphorus &amp;lt; 1.3 mmol/l, n=136). The first model confirmed earlier findings that the risk of SHC is higher with increased parity (P ≤ 0.0001) and revealed a higher risk associated with high milk yield (P = 0.0005), high phosphorus intake (40–60 g/cow per day, OR = 3.5; ≥ 60 g/cow per day, OR = 7.3; P = 0.0003) and high vitamin D supply (≥ 19950 IU/cow per day, OR = 3, P = 0.007). The second model highlighted a greater risk of SHP with increasing parity (P = 0.03) and showed trends for the preventive effects of AcD (OR = 0.4, P = 0.07) and moderate amounts of phosphorus in the diet (OR = 0.4, P = 0.10). Overall, our results do not support the effectiveness of AcD in preventing SHC or SHP under field conditions examined here, probably resulting from insufficient diet acidification.

Metagenomic insights into the antibiotic resistomes of typical Chinese dairy farm environments.

Antibiotic resistance genes (ARGs) in the environment pose a threat to human and animal health. Dairy cows are important livestock in China; however, a comprehensive understanding of antibiotic resistance in their production environment has not been well clarified. In this study, we used metagenomic methods to analyze the resistomes, microbiomes, and potential ARG bacterial hosts in typical dairy farm environments (including feces, wastewater, and soil). The ARGs resistant to tetracyclines, MLS, β-lactams, aminoglycoside, and multidrug was dominant in the dairy farm ecosystem. The abundance and diversity of total ARGs in dairy feces and wastewater were significantly higher than in soil (P < 0.05). The same environmental samples from different dairy have similar resistomes and microbiomes. A high detection rate of tet(X) in wastewater and feces (100% and 71.4%, respectively), high abundance (range from 5.74 to 68.99 copies/Gb), and the finding of tet(X5) challenged the clinical application of the last antibiotics resort of tigecycline. Network analysis identified Bacteroides as the dominant genus in feces and wastewater, which harbored the greatest abundance of their respective total ARG coverage and shared ARGs. These results improved our understanding of ARG profiles and their bacterial hosts in dairy farm environments and provided a basis for further surveillance.

Relative Cost, Profitability and Efficiency among Different Types of Dairy Farms at Bharatpur, Chitwan, Nepal

Dairy sector is gradually commercializing and modernizing with the use of improved breeds, processed feeds, cultivated grass, fodders, medicines and additives in Nepal. In this context, this study was designed to evaluate the relative cost, return, resource use efficiency, return to scale and profitability of milk production in different type of dairy farms. Primary data were collected through face-to-face interview using semi-structured interview schedule from a sample of 240 dairy farms selected from simple random sampling technique in 8 wards of Bharatpur Metropolitan City, Chitwan. Data were analyzed using descriptive statistics, cost and profit analysis, linear production function and Cobb-Douglas function. It was found that pure buffalo farms were facing negative profit margin against the profit of Rs. 32565 and Rs. 106627 at cow and mix system of dairy farming, respectively. Average variable cost of per liter milk production was Rs. 93.70, Rs. 54.80 and Rs. 44.73 for buffalo, cow and mix farms, respectively with benefit-cost ratio of 0.99, 1.44 and 1.62 for respective categories of the farms. Green grass, dry fodder, labour, feed, medicines and additives were significantly contributing to milk production in buffalo and cow farms. But, only grass, fodder and labour were contributing to milk production in mix dairy farms. All categories of farms were suffering from decreasing return to scale but they were still profitable over variable cost. Labour was the most contributing factor in all three categories of farms and thus dairy farming seems potential to create productive employment. This is concluded that dairy farming system can be promoted profitably by enhancing the level of use of labour, grass, fodder, medicines and additives.

Resource use efficiency of milk production among different types of dairy farms in Kerala

The present study analysed the resource use efficiency of milk production among different types of dairy farms in Kerala. The area of study and the respondents were selected using a stratified multi-stage random sampling technique. The farmers/farm households were categorized into small farms (1-2 cows), medium (3-10 cows), and large farms (more than ten cows). The relationship between inputs and milk production has been explored through the production function approach. Resource use efficiency was essentially a comparison between the Marginal Value Product (MVP) of an input with its price that gave direction on the use of that particular input in order to maximize profit. The results showed that in small farms, the MVPs of two inputs viz. roughages and labour was significantly less than unity, signifying overutilisation of these inputs. The MVP value of concentrate was significantly higher than unity, indicating their underutilisation in the milk production process. The MVP of concentrate was positive and significantly greater than unity in medium and large farms, also indicating their underutilisation.

Economics of milk production among different types of dairy farms in Kerala

The present study was carried out to study the variation in the cost of milk production among different types of dairy farms in Kerala. A stratified multistage random sampling procedure was used to select the area of study and respondents. The farmers/farm households were categorized into small or subsistence farms (1-3 cows), medium (4-10 cows), and large farms (more than 10 cows). When calculated on a milch animal basis, the average costs of production per litre of milk (cost B) were rupees 28.09, 28.49, 25.68, and 27.69 in small, medium, large and overall farms, respectively. The average costs/litre of milk after deduction of imputed family labour (cost A) were 19.93, 22.78, 24.93, and 21.81 in small, medium, large, and overall farms, respectively. It was observed that on the milch animal basis, the average cost/litre of milk (cost B) were 32.51, 34.29, 29.08, and 32.29 in small, medium, large, and overall farms, respectively. The average cost per litre of milk after deduction of imputed family labour cost (cost A) were 22.02, 26.33, 27.08, and 24.34 in small, medium, large, and overall farms, respectively. The present study indicated that the average cost of milk production in the state of Kerala was very high, and the milk price has to be regulated accordingly so that dairy farming becomes a lucrative livelihood opportunity for poor farmers.

Odpornost kmetij s prirejo mleka z različnimi prilagoditvami proizvodnega načrta

In this study, the resilience of farm production plan through different management adjustments was analyzed. For this purpose, a farm model based on mathematical programming was applied. Through organized workshops typical farms focusing on dairy production were defined through qualitative and quantitative classification. Data were obtained from various databases and expert assessments from the agricultural sector. Analysis of resilience was carried out for three of these typical dairy farms. Using the farm model, the production plan of each farm was reconstructed in the first step and then tested for possible deviations from the baseline. Gross margin was used as the main economic indicator. The results show that the typical farms have very different levels of efficiency and potential for improvement. Furthermore, it was found that all farms can achieve significantly higher gross margin only with improved feed quality, which indirectly leads to a lower need for purchased feed and consequently to lower variable costs and higher gross margin. The level of the latter is also significantly affected by the milk yield achieved, especially on larger farms. However, on smaller farms they can improve profitability more significantly by keeping dairy cows on pasture to a greater extent, which results in a reduction in harvesting costs.

Cost and Returns of Milk Production Under Different Types of Dairy Farms in Kerala

Cost and Returns of Milk Production Under Different Types of Dairy Farms in Kerala

Measurement and Evaluation of the Efficiency and Total Productivity of Dairy Farms in Poland

The aim of the article is to measure and evaluate the economic and technical efficiency as well as the total productivity of dairy farms in Poland. The research used data from the Polish FADN. The analysis covered the years 2008–2017. The study group consisted of 730 farms. An iteration-optimization method, k-means clustering, non-parametric DEA method, and aggregated Färe–Primont indexes were used to achieve the goal. The conducted research allowed for the distinction of four types of dairy farms with different levels of economic efficiency. We prove that the costs of labor, energy, maintenance of machines and buildings, fodder, depreciation, and overheads, as well as agricultural land, affect the technical efficiency and total productivity of dairy farms. We also prove that over the analyzed years, technical efficiency decreased in all groups of dairy farms, while the Färe–Primont index of total productivity changes slightly increased. The validity of these studies and their practical significance result from the need to improve the competitiveness of dairy farms and increase their profitability. Our research fills a gap in research on measuring and evaluating the efficiency and productivity of dairy farms, and at the same time represents an original approach to the studied phenomenon. Moreover, it allows for the explanation of differences in the effectiveness of different types of dairy farms, providing useful information for the design of effective targeted policy interventions to improve the competitiveness of the Polish dairy sector. There are opportunities to improve both the technical efficiency and productivity of dairy farms in Poland. This increase will be possible thanks to the improvement of agricultural advisory services and ensuring that farmers participate in training in proper nutrition, reproduction, milk marketing and other management skills.

Improving the accuracy of nitrous oxide emission factors estimated for hotspots within dairy-grazed farms

Nitrous oxide (N2O) emissions from dairy-grazing pastures can be dominated by large emissions from small areas (‘hotspots’) frequently used by grazing dairy cattle (i.e., water troughs and gateways). N2O emissions from these hotspots are quantified by investigating whether N2O emissions and emission factors (% of applied N emitted as N2O, EF3) from potential hotspots are different from non-hotspots. To better characterise N2O emissions from hotspots and non-hotspots of farms to understand their contributions to national agricultural greenhouse gas inventory calculations, a series of measurements were conducted during winter and spring on two NZ typical dairy farms with contrasting soil drainage (poorly versus well drained). Before measurements were taken, the soils either received a cow urine application or remained untreated. The results showed that changes in water-filled pore space (WFPS) and mineral N around water troughs and gateways, due to additional stock movements and disproportionate excreta-N deposition during previous grazing events, affected both background and total N2O emissions. But there was little impact on EF3 values (calculated using IPCC guidelines) from deposited urine between hotspot and pasture areas. These results suggest the same EF3 values can be used for both to calculate emissions from urine deposited on grazed pastures. However, these results raise concerns about higher background emission in hotspots subtracted from measured emissions from urine-N deposition in calculating EF3 values and discounting the effects of disproportionate N inputs in intensive agriculture on increased background emissions (legacy effect). This IPCC inventory method does not account for the legacy effect of N loading prior to the measurements which may underestimate the emissions. Thus, an allowance for higher hotspot background emissions could be included in the Inventory to accurately estimate total emissions from agriculture.

An economic analysis of anaerobic digestate fuel pellet production: can digestate fuel pellets add value to existing operations?

Anaerobic digestion provides renewable energy through waste valorisation, but the digestate by-product is underutilised and presents a risk to water quality. Mechanical separation partitions phosphorous into the solid fraction and further processing into a fuel pellet can provide an additional source of energy and revenue. Previous economic analyses looked only at aspects of the system (e.g. operational costs solely) and the system requires further investigation to determine viability. In this paper, an economic assessment of digestate fuel pellet production at farm-scale anaerobic digestion plants was carried out. The significance of this work is to provide a comprehensive assessment of the energy, phosphorous, and economic balances involved in digestate fuel pellet production at existing anaerobic digestion plants. The aim of this paper is to determine the financial viability of digestate fuel pellet production with objectives to compare two mechanical separation technologies: screw press, and decanting centrifuge. Economies of scale hold true for digestate pellet production and the available digestate in typical UK farm-based anaerobic digestion plants (≤500 kW e ) is insufficient for profitability, with pellet production costing from £176/t (decanting centrifuge) to £215/t (screw press), compared to a typical wood pellet sale price of £185/t. Increasing digestate quantity by collaboration of plant operators can reduce the cost of pellet production to between £95/t and £121/t, improving financial viability and increasing the profit per head of cattle by 9–20% on a typical dairy farm utilising anaerobic digestion. The system has potential to aid rural development while also protecting the environment and contributing to the diversification of energy supply. • Energy balance, phosphorous flows, and cost analysed for digestate fuel pellets. • Fuel pellet production redirects phosphorous from land and runoff to waterways. • Pellet breakeven price of £95 ​t −1 to £121 ​t −1 compared to £186 ​t −1 market price. • Profits of up to £200,000 yr −1 achievable for 3 plant collaboration. • Process can improve profitability of dairy cows by 9–20%.