Metrics and methods for characterizing dairy farm intensification using farm survey data

Short-Term Effects of Heat Stress on Cow Behavior, Registered by Innovative Technologies and Blood Gas Parameters

Heat stress (HS) is one of the key factors affecting an animal's immune system and productivity, as a result of a physiological reaction combined with environmental factors. This study examined the short-term effects of heat stress on cow behavior, as recorded by innovative technologies, and its impact on blood gas parameters, using 56 of the 1070 cows clinically evaluated during the second and subsequent lactations within the first 30 days postpartum. Throughout the experiment (from 4 June 2024 until 1 July 2024), cow behavior parameters (rumination time min/d. (RT), body temperature (°C), reticulorumen pH, water consumption (L/day), cow activity (h/day)) were monitored using specialized SmaXtec boluses and employing a blood gas analyzer (Siemens Healthineers, 1200 Courtneypark Dr E Mississauga, L5T 1P2, Canada). During the study period, the temperature-humidity index (THI), based on ambient temperature and humidity, was recorded and used to calculate THI and to categorize the data into four THI classes as follows: 1-THI 60-63 (4 June 2024-12 June 2024); 2-THI 65-69 (13 June 2024-18 June 2024); 3-THI 73-75 (19 June 2024-25 June 2024); and 4-THI 73-78 (26 June 2024-1 July 2024). The results showed that heat stress significantly reduced rumination time by up to 70% in cows within the highest THI class (73 to 78) and increased body temperature by 2%. It also caused a 12.6% decrease in partial carbon dioxide pressure (pCO2) and a 32% increase in partial oxygen pressure (pO2), also decreasing plasma sodium by 1.36% and potassium by 6%, while increasing chloride by 3%. The findings underscore the critical need for continuous monitoring, early detection, and proactive management to mitigate the adverse impacts of heat stress on dairy cow health and productivity. Recommendations include the use of advanced monitoring technologies and specific blood gas parameter tracking to detect the early signs of heat stress and implement more timely interventions.

Typology and characterization of the agricultural productive units in the NE Amazonian region of Ecuador

Objective

Many studies have observed different characteristics among productive systems in the rural territories of Latin America. Therefore, understanding and characterizing them while they function plays an essential role in determining their relationship between development and environment. A study has been conducted in the Orellana province of NE Ecuador to determine their typology and then classify them according to the variables that describe their main traits or attributes using cluster analysis (CA).

Materials and Methods

A survey was structured to investigate physical, productive, environmental, as well as socioeconomic character variables, which were subsequently applied to a random sample of the 5,963 agricultural productive units (APUs) through face-to-face contact with producers during an in situ visit to their farms.

Result

The CA allowed us to identify three typologies of APUs in the Orellana Province. The first has been Type 1, which is denominated as the most conventional (40%), while Type 2 uses more efficient natural resources but represents an amount of only 9.4%. In contrast, type 3 (50.6%) depends on a significant part of local or national development programs.

Conclusion

All groups indicated some peculiarities in common, as there were marked differences in the use and distribution of land as well as production methods among them. Consequently, this pioneering study allowed us to identify different production methods. Therefore, we encourage local and national governments to establish policies for natural resource conservation in such high-diversity zones.

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.

Feasibility of mitigation measures for agricultural greenhouse gas emissions in the UK. A systematic review

The UK Government has set an ambitious target of achieving a national "net-zero" greenhouse gas economy by 2050. Agriculture is arguably placed at the heart of achieving net zero, as it plays a unique role as both a producer of GHG emissions and a sector that has the capacity via land use to capture carbon (C) when managed appropriately, thus reducing the concentration of carbon dioxide (CO2) in the atmosphere. Agriculture's importance, particularly in a UK-specific perspective, which is also applicable to many other temperate climate nations globally, is that the majority of land use nationwide is allocated to farming. Here, we present a systematic review based on peer-reviewed literature and relevant "grey" reports to address the question "how can the agricultural sector in the UK reduce, or offset, its direct agricultural emissions at the farm level?" We considered the implications of mitigation measures in terms of food security and import reliance, energy, environmental degradation, and value for money. We identified 52 relevant studies covering major foods produced and consumed in the UK. Our findings indicate that many mitigation measures can indeed contribute to net zero through GHG emissions reduction, offsetting, and bioenergy production, pending their uptake by farmers. While the environmental impacts of mitigation measures were covered well within the reviewed literature, corresponding implications regarding energy, food security, and farmer attitudes towards adoption received scant attention. We also provide an open-access, informative, and comprehensive dataset for agri-environment stakeholders and policymakers to identify the most promising mitigation measures. This research is of critical value to researchers, land managers, and policymakers as an interim guideline resource while more quantitative evidence becomes available through the ongoing lab-, field-, and farm-scale trials which will improve the reliability of agricultural sustainability modelling in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13593-023-00938-0.

In-Line Registered Milk Fat-to-Protein Ratio for the Assessment of Metabolic Status in Dairy Cows

This study endeavors to ascertain alterations in the in-line registered milk fat-to-protein ratio as a potential indicator for evaluating the metabolic status of dairy cows. Over the study period, farm visits occurred biweekly on consistent days, during which milk composition (specifically fat and protein) was measured using a BROLIS HerdLine in-line milk analyzer (Brolis Sensor Technology, Vilnius, Lithuania). Clinical examinations were performed at the same time as the farm visits. Blood was drawn into anticoagulant-free evacuated tubes to measure the activities of GGT and AST and albumin concentrations. NEFA levels were assessed using a wet chemistry analyzer. Using the MediSense and FreeStyle Optium H systems, blood samples from the ear were used to measure the levels of BHBA and glucose in plasma. Daily blood samples were collected for BHBA concentration assessment. All samples were procured during the clinical evaluations. The cows were categorized into distinct groups: subclinical ketosis (SCK; n = 62), exhibiting elevated milk F/P ratios without concurrent clinical signs of other post-calving diseases; subclinical acidosis (SCA; n = 14), characterized by low F/P ratios (<1.2), severe diarrhea, and nondigestive food remnants in feces, while being free of other post-calving ailments; and a healthy group (H; n = 20), comprising cows with no clinical indications of illness and an average milk F/P ratio of 1.2. The milk fat-to-protein ratios were notably higher in SCK cows, averaging 1.66 (±0.29; p < 0.01), compared to SCA cows (0.93 ± 0.1; p < 0.01) and healthy cows (1.22). A 36% increase in milk fat-to-protein ratio was observed in SCK cows, while SCA cows displayed a 23.77% decrease. Significant differences emerged in AST activity, with SCA cows presenting a 26.66% elevation (p < 0.05) compared to healthy cows. Moreover, SCK cows exhibited a 40.38% higher NEFA concentration (p < 0.001). A positive correlation was identified between blood BHBA and NEFA levels (r = 0.321, p < 0.01), as well as a negative association between BHBA and glucose concentrations (r = -0.330, p < 0.01). Notably, AST displayed a robust positive correlation with GGT (r = 0.623, p < 0.01). In light of these findings, this study posits that milk fat-to-protein ratio comparisons could serve as a non-invasive indicator of metabolic health in cows. The connections between milk characteristics and blood biochemical markers of lipolysis and ketogenesis suggest that these markers can be used to check the metabolic status of dairy cows on a regular basis.

A cluster analysis on the potential of livestock farming: Türkiye in a global context

This study aims to rank, and cluster countries in terms of some essential livestock indicators, and evaluate the subject with specific attention to the conditions existing in Türkiye. The study material covers 142 countries whose 2020 data were fully reported by the World Food and Agriculture Organization, the World Trade Organization, and the World Bank. It was determined that the most appropriate number of clusters would be 4 and significant differences were found between these clusters in terms of medium and high effect size for all indicators (P < 0.01). The cluster of 31 countries, according to the Ward algorithm, and the cluster of 37 countries according to the K-Means algorithm, both including Türkiye, were found to have higher averages than the other clusters in terms of related indicators (P < 0.01). The common elements in both clusters were determined: Türkiye, USA, Germany, Argentina, Brazil, Ethiopia, Morocco, France, India, the Netherlands, England, Spain, Italy, Canada, Kazakhstan, Kenya, Colombia, Pakistan, Peru, Poland, and Russia. Taking into account the geographical proximity and economic relations, Türkiye should examine the livestock models followed by these countries and evaluate the possible areas of cooperation that can be developed and competition that could be faced by these countries.

Identifying ways of producing pigs more sustainably: tradeoffs and co-benefits in land and antimicrobial use

Pork accounts for the largest proportion of meat consumed globally and demand is growing rapidly. Two important externalities of pig farming are land use and antimicrobial resistance (AMR) driven by antimicrobial use (AMU). Land use and AMU are commonly perceived to be negatively related across different production systems, so those with smaller land footprints pose greater risk to human health. However, the relationship between land use and AMU has never been systematically evaluated. We addressed this by measuring both outcomes for 74 highly diverse pig production systems. We found weak evidence of an AMU/land use tradeoff. We also found several systems characterized by low externality costs in both domains. These potentially promising systems were spread across different label and husbandry types and indeed no type was a reliable indicator of low-cost systems in both externalities. Our findings highlight the importance of using empirical evidence in decision-making, rather than relying on assumptions.

Evaluation of reticuloruminal temperature for the prediction of clinical mastitis in dairy cows challenged with Streptococcus uberis

Automated monitoring devices have become increasingly utilized in the dairy industry, especially for monitoring or predicting disease status. While multiple automated monitoring devices have been developed for the prediction of clinical mastitis (CM), limitations in performance or applicability remain. The aims of this study were to (1) detect variations in reticuloruminal temperature (RRT) relative to an experimental intramammary challenge with Streptococcus uberis and (2) evaluate alerts generated automatically based on variation in RRT to predict initial signs of CM in the challenged cows based on severity of clinical signs and the concentration of bacteria (cfu/mL) in the infected quarter separately. Clinically healthy Holstein cows without a history of CM in the 60 d before the experiment (n = 37, parity 1 to 5, ≥120 d in milk) were included if they were microbiologically negative and had a somatic cell count under 200,000 cells/mL based on screening of quarter milk samples 1 wk before challenge. Each cow received an intra-reticuloruminal automated monitoring device before the trial and was challenged with 2,000 cfu of Strep. uberis 0140J in 1 rear quarter. Based on interrupted time series analysis, intramammary challenge with Strep. uberis increased RRT by 0.54°C [95% confidence interval (CI): 0.41, 0.66] at 24 h after the challenge, which remained elevated until the end of the study. Alerts based on RRT correctly classified 78.3% (95% CI: 65.8, 87.9) of first occurrences of CM at least 24 h in advance, with a sensitivity of 70.0% (95% CI: 50.6, 85.3) and a specificity of 86.7% (95% CI: 69.3, 96.2). The accuracy of CM for a given severity score was 90.9% (95% CI: 70.8, 98.9) for mild cases, 85.2% (95% CI: 72.9, 93.4) for moderate cases, and 92.9% (95% CI: 66.1, 99.8) for severe cases. Test characteristics of the RRT alerts to predict initial signs of CM improved substantially after bacterial count in the challenged quarter reached 5.0 log₁₀ cfu/mL, reaching a sensitivity of 73.5% (95% CI: 55.6, 87.1) and a specificity of 87.5% (95% CI: 71.0, 96.5). Overall, the results of this study indicated that RRT was affected by the intramammary challenge with Strep. uberis and the RRT-generated alerts had similar accuracy as reported for other sensors and algorithms. Further research that includes natural infections with other pathogens as well as different variations in RRT to determine CM status is warranted.

Dairy farmer practices and attitudes relating to pasture-based and indoor production systems in Scotland

This study assesses the practices and views of Scottish dairy farmers relating to pasture-based and indoor systems. There are the debates about the environmental, economic and animal welfare implications of these systems. Indoor dairy farming is a contentious practice among the public. While this controversy is sometimes represented as a lack of public understanding, there is a need for more research on farmers' views to facilitate discussion in the industry. A survey was posted to 909 dairy farmers in Scotland with questions about their grazing practices and attitudes to grazing and indoor systems. 254 surveys were completed, online and in paper form. There was a 26% response rate to the paper version of the survey. The results showed that 19% of respondents housed some or all the cows all year-round. 68% agreed or strongly agreed that cows should graze for part of the year and 51% agreed or strongly agreed that welfare was better if cows grazed for part of the year. These views coexisted with the view that management was more important than the type of system for determining profitability or welfare outcomes (83% and 82% strongly agree or agree respectively). Respondents whose system involved grazing and respondents who had spent longer in farming were moderately more likely to agree that cows should have access to pasture, and slightly less likely to agree that management was more important than system for determining welfare outcomes. The results indicate that the picture is more complicated than the public rejecting indoor dairy farming and those in the industry accepting it. The results showed that a majority preference for cows to graze co-existed with the view that management was more important than system. In terms of industry and policy recommendations, the research suggests that measures should be taken to safeguard farmers' ability to graze through for instance research and advisory support on grazing; ensuring different systems are not penalised in the development of dairy sector environmental measures and recommendations; and potentially supply chains that financially rewards farmers for grazing.

How do dairy farmers communicate with the government? A case study in northwest of Spain

With the aim of assessing the farmers’ situation in terms of the use of ICT (Information and Communication Technologies) and their relationship with the e-government (electronic government), a case study consisting of 34 face-to-face surveys between February and March 2020 in dairy farms in the region of Galicia (Spain) was conducted. From the census, we chose those farms considered most representative taking into account the following criteria: the level of CAP (Common Agricultural Policy) and the production of milk (litres / cow and year). The results show that, in spite of the fact that a vast majority of the users use the web tools of the Public Administration, there are many users who find problems related to the agility and ease of use of these tools, especially when compared with private APPs which they also use daily in connection to their farms. Our research delves into those farmers who do not use the internet and the alternative methods which they employ. The telephone helpline is particularly important, as it is the favourite method of smaller farms.

Assessment of feed and economic efficiency of dairy farms based on multivariate aggregation of partial indicators measured on field

Many of the metrics used to evaluate farm performance are only partial indicators of farm operations, which are assumed to be best predictors of the whole farm efficiency. The main objective of this work was to identify aggregated multiple indexes of profitability using common partial indicators that are routinely available from individual farms to better support the short-term decision-making processes of the cattle-feeding process. Data were collected from face-to-face interviews with farmers from 90 dairy farms in Italy and used to calculate 16 partial indicators that covered almost all indicators currently used to target feeding and economic efficiency in dairy farms. These partial indicators described feed efficiency, energy utilization, feed costs, milk-to-feed price ratio, income over feed costs, income equal feed cost, money-corrected milk, and bargaining power for feed costs. Calculations of feeding costs were based on lactating cows or the whole herd, and income from milk deliveries was determined with or without considering the milk quality payment. Multivariate factor analysis was then applied to the 16 partial indicators to determine simplified and latent structures. The results indicated that 5 factors explained 70% of the variability. Each of the original partial indicator was associated with all factors in different proportions, as indicated by loading scores from the multivariate factor analysis. Based on the loading scores, we labeled these 5 factors as "economic efficiency," "energy utilization," "break-even point," "milk-to-feed price," and "bargaining power of the farm," in decreasing order of explained communality. The first 3 factors shared 83% of the total communality. Feed efficiency was similarly associated with factor 1 (53% loading) and factor 2 (66% loading). Only factor 4 was significantly affected by farm location. Milk production and herd size had significant effects on factor 1 and factor 2. Our multivariate approach eliminated the problem of multicollinearity of partial indicators, providing simple and effective descriptions of farm feeding economics. The proposed method allowed the evaluation, benchmarking, and ranking of dairy herd performance at the level of single farms and at territorial level with high opportunity to be used or replicated in other areas.

Evaluation of nitrogen excretion equations for ryegrass pasture-fed dairy cows

Accurate and precise estimates of nitrogen (N) excretion in faeces and urine of dairy cattle may provide direct tools to improve N management and thus, to mitigate environmental pollution from dairy production. Empirical equations of N excretion have been evaluated for indoor dairy cattle but there is no evaluation for cows fed high proportions of fresh forage. Therefore, the objective of the current study was to evaluate N excretion equations with a unique data set of zero-grazing experiments. Through literature searches, 89 predictive equations were identified from 13 studies. An independent data set was developed from seven zero-grazing experiments with, in total, 55 dairy Holstein-Friesian cows. Models' performance was evaluated with statistics derived from a mixed-effect model and a simple regression analysis model. Squared sample correlation coefficients were used as indicators of precision and based on either the best linear unbiased predictions (R²_BLUP) or model-predicted estimates (R²_MDP) derived from the mixed model and simple regression analysis, respectively. The slope (β₀), the intercept (β₁) and the root mean square prediction error (RMSPE_m%) were calculated with the mixed-effect model and used to assess accuracy. The root mean square prediction error (RMSPE_sr%) and the decomposition of the mean square prediction error were calculated with the simple regression analysis and were used to estimate the error due to central tendency (mean bias), regression (systematic bias), and random variation. Concordance correlation coefficient (CCC) were also calculated with the simple regression analysis model and were used to simultaneously assess accuracy and precision. Considering both analysis models, results suggested that urinary N excretion (UN; R²_MDP = 0.76, R²_BLUP = 0.89, RMSPE_m% = 17.2, CCC = 0.82), total manure N excretion (ManN; R²_MDP = 0.83, R²_BLUP = 0.90, RMSPE_m% = 11.0, CCC = 0.84) and N apparently digested (NAD; R²_MDP = 0.97, R²_BLUP = 0.97, RMSPE_m% = 5.3, CCC = 0.95) were closely related to N intake. Milk N secretion was better predicted using milk yield as a single independent variable (MilkN; R²_MDP = 0.77, R²_BLUP = 0.97, RMSPE_m% = 6.0, CCC = 0.74). Additionally, DM intake was a good predictor of UN and ManN and dietary CP concentration of UN and ManN. Consequently, results suggest that several evaluated empirical equations can be used to make accurate and precise predictions concerning N excretion from dairy cows being fed on fresh forage.

Factors Affecting e-Government Adoption by Dairy Farmers: A Case Study in the North-West of Spain

With the objective of assessing the farmers’ situation regarding the use of the ICT and their relations with the electronic government, a case study consisting in the realization of 34 face-to-face surveys was conducted between February and March 2020 in dairy farms in the region of Galicia (Spain). The sample was selected according to one of the most important online journals in the farming sector at a national level. From the census, we chose those farms considered most representative taking into account the main criteria: the level of PAC (Common Agrarian Politics) subsidies and milk production (litres/cow and year). The results show that the majority of the farmers used the internet, but on many an occasion, they were discontented in relation to the poor connection quality in their farms. In regard to the use of the electronic government for procedures related to their farms, many of them were able to perform them through the government website; however, there were procedures which the users defined as “complex” and which had to be outsourced to authorised entities. The results also show that the farmers do want to employ the e-government, mainly because of the time and cost saving; however, the current web pages do not meet the users’ expectations. Finally, this situation, applied to a region placed among the 10 most productive regions of milk, is comparable to what happens in other regions.

ICT in Rural Areas from the Perspective of Dairy Farming: A Systematic Review

This study presents a systematic review of 169 papers concerning the ICT (Information and Communication Technologies) related to rural areas, specifically to dairy farms. The objective was to delve into the relationship between dairy farmers and the administrative authorities via e-government, comparing this area to another eight concerning the farmer’s needs and expectations in relation to the ICT in different fields of their business. We observed that areas such as connectivity and digital inclusion are the most covered areas not only at the study level but also at the government level since countries all over the world are trying to develop politics to put an end to the so-called “digital divide,” which affects rural areas more intensely. This is increasing due to the growing technological innovations. The areas of the market, production, financial development, management and counseling, Smart Farming, and Internet of Things have been approached, associated with the ICT in dairy farms, showing in the latter two an increasing number of papers in the last few years. The area of public administration in relation to dairy farms has also been covered, being remarkable the low number of pieces of research concerning the interaction by the farmers, more specifically by dairy farmers, with the public administration, which is surprising due to the new global need and especially in the European Union (EU) of interacting with it telematically by all legal entities. The results show that there are still barriers to the implementation of the electronic government (e-government) since the websites do not meet the user’s expectations. Therefore, this study lays the ground for future research on this area. As a graphical abstract of the contributions of this paper, we present a graphic summary, where the different contributions by areas and expressed in percentage values are shown.

Identifying key pathways in manure and sewage management of dairy farming based on a quantitative typology: A case study in China

With the greatly increased demand for animal products, the global dairy sector has experienced rapid expansion and intensification. The correspondingly increasing manure and sewage produced has been the major contributor to environmental burden and human health, especially in developing countries like China. Both worldwide environmental concerns and growing awareness of the circular economy have focused the governments' attention on environmental policies related to sustainable manure and sewage management (MSM). However, inherently dynamic decision-making processes of individual farms result in a great diversity of MSM practices, which leads to enormous difficulties and complexity in further sustainability and policy evaluation. Hence, it is essential to explore the key MSM pathways to represent diversity at a scientific and statistic view. While it is rarely practiced, particularly in China's dairy farming. We used China as a case study to develop the key MSM pathways using data from the nationwide survey of 306 scale dairy farms via a quantitative typology methodology. The results by optimal clustering solution revealed four key pathways based on the individual practices which are associated with the collection, storage, and processing and utilization stages. Furthermore, general characteristics were compared to identify potential determinant factors. It revealed that the major indicators such as resource endowments, milk productivity and quality, and revenues and expenditure showed a consistently increasing trend among pathways. The results indicated resource availability and intensive degree, to a certain extent, affected the farmers' selection. The possibilities of performing sustainability and policy evaluation at a higher scale were also demonstrated. Overall, the identified key pathways can help to know regional waste utilization and economic potential to evolve their MSM strategies. They are especially critical for developing countries to obtain typical MSM profiles and formulate targeted policies more effectively, aiming to promote dairy sustainable development and achieve the circular economy globally.

Impact of Feeding Pattern on the Structure and the Economic Performance of Dairy Cow Sector

In dairy farms, the feeding cost, which includes the expenses for purchased feed but also the expenses for feed production, constitutes a very large part of production cost (more than 60%), which indicates the economic importance of the feeding strategy. This study discerns three different feeding strategies: landless farms only purchasing feed from markets (“Purchasing”), farms for which home-grown feeds stand for more than 10% of feeding costs (“Producing”) and farms with less than 10% home-grown feeds (“Multi-purpose”). Based on technical and economic data from 47 dairy cow farms in Greece, alternative scenarios of development of the dairy sector are determined taking into account the dependence on on-farm feed production. Through a parametric programming model, the study provides insights regarding the optimal structure of the system under different scenarios (changing availability of variable capital, changes in milk prices). The results indicate that “Purchasing” farms are the preferred option when variable capital is abundant and milk prices are satisfactory, while “Producing” are the ones surviving with milk prices significantly lower than the actual ones in Greece and European Union. “Multi-purpose” farms perform worse than the other two and are sidelined in both scenarios, as they do not seem to be able to specialize in the dairy enterprise or in crop production and thus to minimize costs.

Assessment of Performance and Some Welfare Indicators of Cows in Vietnamese Smallholder Dairy Farms

Smallholder dairy farms (SDFs) are distributed widely across lowland and highland regions in Vietnam, but data on the productivity and welfare status of these cows remains limited. This cross-sectional study was conducted to describe and compare the productivity and welfare status of SDF cows across contrasting regions. It was conducted in autumn 2017 on 32 SDFs randomly selected from four typical but contrasting dairy regions (eight SDFs per region); a south lowland, a south highland, a north lowland, and a north highland region. Each farm was visited over a 24-h period (an afternoon followed by a morning milking and adjacent husbandry activities) to collect data of individual lactating cows (n = 345) and dry cows (n = 123), which included: milk yield and concentrations, body weight (BW), body condition score (BCS, 5-point scale, 5 = very fat), inseminations per conception, and level of heat stress experienced (panting score, 4.5-point scale, 0 = no stress). The high level of heat stress (96% of lactating cows were moderate to highly heat-stressed in the afternoon), low energy corrected milk yield (15.7 kg/cow/d), low percentage of lactating cows (37.3% herd), low BW (498 and 521 kg in lactating and dry cows, respectively), and low BCS of lactating cows (2.8) were the most important productivity and welfare concerns determined and these were most serious in the south lowland. By contrast, cows in the north lowland, a relatively hot but new dairying region, performed similarly to those in the south highland; a region historically considered to be one of the most suitable for dairy cows in Vietnam due to its cool environment. This indicates the potential to mitigate heat stress through new husbandry strategies. Cows in the north highland had the highest BW (535 and 569 kg in lactating and dry cows, respectively) and the highest energy corrected milk yield (19.2 kg/cow/d). Cows in all regions were heat-stressed during the daytime, although less so in the highlands compared to the lowlands. Opportunities for research into improving the productivity and welfare of Vietnamese SDF cows are discussed.

Maintaining production while reducing local and global environmental emissions in dairy farming

While milk is a major agricultural commodity, dairy farming also supports a large share of global beef production. In Life Cycle Assessment (LCA) studies of dairy farming systems, dairy-beef production is often ignored or 'allocated off', which may give a distorted view of production efficiencies. This study combines LCA with Data Envelopment Analysis (DEA) to develop an indicator of eco-efficiency for each of 738 UK dairy farms (3624 data points in 15 years) that aggregates multiple burdens and expresses them per unit of milk and dairy-beef produced. Within the DEA framework, the importance (weight) of dairy-beef relative to milk is iteratively increased to quantify the environmental losses from heavily focussing on milk-production, via e.g. higher yields per cow, with consequent lower burdens per unit of milk, yet with lower dairy-beef production levels, where burdens for beef production are externalized. Then, the relationship between DEA eco-efficiency and a series of indicators of dairy farming intensity at animal- and farm-levels was studied with Generalized Additive Models (GAM). For all sets of DEA weights (proportion of deviance explained ranged between 68% and 82%) indicate that milk yield per cow and forage area, and larger dairy herds all have a positive effect on eco-efficiency, while concentrate fed per unit of milk and the forage area both have a negative effect (p < 0.05 for all modelled relationships). These findings suggest that more intensive and consolidated dairy farms can positively impact on eco-efficiency. However, as the DEA weight for dairy-beef relative to milk increases, the relationship between environmental efficiency and farming specialization (expressed as L milk per kg dairy-beef produced) reverses from positive to negative. In conclusion, dairy-beef production is pivotal in determining the wider environmental efficiency of dairy (and ruminant food) systems, and its under-representation in efficiency studies has generated a misleading approach to meeting emission targets.

Diversification not specialization reduces global and local environmental burdens from livestock production

Milk and beef production generates environmental burdens globally and locally. Across many regions a typical dairy intensification pathway is for dairy farms to specialize on milk production and reduce the co-production of beef (i.e. 'dairy-beef'). Dairy-beef thus reduces and beef needs to be produced elsewhere if beef production is to be maintained. Life Cycle Assessment (LCA) studies quantifying the environmental implications of dairy and beef production have largely focused on the farm level and not captured system connections. Further LCA work has generally represented the 'average' farm of a region, consequently ignoring the range in farm management observed in practice and few studies consider a range of LCA environmental footprints other than carbon footprints. For the first time, we present comprehensive LCA results for multiple environmental burdens based on a large panel dataset for commercial dairy and suckler-beef farms. We present a 15-year LCA assessment of a total of 738 dairy (3624 data points in 15 years) and 1887 suckler-beef (10,340 data points in 15 years) UK farms for five major LCA footprints. We also explore the footprint implications of compensating for reduced dairy-beef through producing this 'displaced' beef on suckler-beef farms. We found a substantial variation in farm footprints not captured in 'average farm' studies. Dairy-beef was much more efficient than beef produced on suckler-beef farms in terms of footprints per unit of beef output. Reducing dairy-beef and replacing it on a suckler-beef farm generally significantly increased environmental burdens. A reduction in carbon footprint was also associated with a reduction in other burdens suggesting no trade-off between local and global emissions. Increasing dairy farm diversification via higher dairy-beef output per unit of milk reduced burdens by up to 11-56%, on average, depending on burden and sensitivity run. We conclude that overspecialization of dairy farms in milk production increases the combined burdens from beef and milk, and that more intensive beef systems that make more efficient use of forage land play a crucial role in mitigating these burdens.

Economic elasticities of input substitution using data envelopment analysis

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA.

Intensification and Upgrading Dynamics in Emerging Dairy Clusters in the East African Highlands

Based on farmer and value chain actor interviews, this comparative study of five emerging dairy clusters elaborates on the upgrading of farming systems, value chains, and context shapes transformations from semi-subsistent to market-oriented dairy farming. The main results show unequal cluster upgrading along two intensification dimensions: dairy feeding system and cash cropping. Intensive dairy is competing with other high-value cash crop options that resource-endowed farmers specialize in, given conducive support service arrangements and context conditions. A large number of drivers and co-dependencies between technical, value chain, and institutional upgrading build up to system jumps. Transformation may take decades when market and context conditions remain sub-optimal. Clusters can be expected to move further along initial intensification pathways, unless actors consciously redirect course. The main theoretical implications for debate about cluster upgrading are that co-dependencies between farming system, market, and context factors determine upgrading outcomes; the implications for the debate about intensification pathways are that they need to consider differences in farmer resource endowments, path dependency, concurrency, and upgrading investments. Sustainability issues for consideration include enabling a larger proportion of resource-poor farmers to participate in markets; enabling private input and service provision models; attention for food safety; and climate smartness.

Evaluating lifetime nitrogen use efficiency of dairy cattle: A modelling approach

The increased nitrogen (N) use efficiency in cattle farming is proposed as a key action to improve N management and reduce the environmental impact of cattle farming systems. Most attention has been given to lactating cow nutrition, excluding the elements of fertility, disease, and the non-lactating animals within the herd. Therefore, the aim of the current study was to develop a herd-level simulation model incorporating these elements to assess dairy farm N use efficiency. We developed a cattle N use efficiency (CNE) model with six primary compartments: (i) heifer growth, (ii) heifer removal, (iii) pregnancy, (iv) cow removal, (v) disease and fertility, and (vi) milk production. The CNE model calculates N loss or gain for each compartment, and then calculates the lifetime N loss or gain taking into account the replacement rate (rep) and/or the corresponding number of lactations in a herd (Lact = 1/rep). Finally, three N use efficiencies were estimated: (i) ReplNE: replacement cattle N use efficiency, (ii) LactNE: lifetime N use efficiency for lactation, and (iii) LNE: lifetime N use efficiency. The sensitivity of the model to variation in farm- and animal-related input values was evaluated using Monte Carlo simulation. Values for a model dairy farm were used based on published data reflecting typical dairy farming practices in the United Kingdom. To assist reporting net values of main N outputs, a dairy herd of 100 lactating cows was modelled. Productive N outputs (1000s of kg) over the course of an animal’s lifetime, partitioned into milk and meat, were dominated by milk production (89% of total N output). We estimated a mean ReplNE of 23.7%, affected most by the last stage of heifer growth. The Monte Carlo sensitivity analysis suggested that variation in time to first calving (T_1stCal) might cause larger changes on ReplNE than variation in feed. The sensitivity analysis revealed a strong positive correlation between dietary oriented milk N use efficiency (MNE) and LactNE and LNE (r = 0.99 and 0.97 for LactNE and LNE, respectively). However, our study highlighted two other model variables that affected LNE. Variation in calving interval (CI; r = −0.15) and T_1stCal (r = −0.15) may cause measurable reductions of overall LNE. The first is an indicator of lactating cattle fertility, and the second an indicator of replacement cattle growth and fertility efficiency. In conclusion, with the current study we provided a dairy cattle herd model that is sensitive in elements of diet, fertility and health. Lifetime N use efficiency of dairy cattle is dominated by MNE, but we detected specific non-diet related variables that affect ReplNE, LactNE and LNE.