Does intensification improve the economic efficiency of dairy farms?

How increased heifer growth rate and reduced dairy cow replacement rate can improve farm economy and reduce greenhouse gas emissions - a win to win situation?

Rearing of replacement heifers makes up a significant part of the total costs in dairy farming. Nevertheless, the average age at first calving for dairy heifers still stays well above 2 years in many countries. This study examined the economic and environmental impacts of increased heifer growth rates and reduced replacement rates on Norwegian dairy farms. The current average growth rate in Norway (baseline scenario) was compared to an accelerated growth rate scenario. Within each of the two growth rate scenarios, we compared three different cow replacement rates. A farm account survey dataset containing physical and economic data on 311 Norwegian farms was clustered into three farm groups: small, medium, and large. To model economic consequences, we used the whole-farm linear programming model ScotFarm. A life cycle analysis model was used to model the environmental impacts of the baseline scenario and an accelerated growth rate scenario on the three farm groups. Accelerated heifer growth rate had a positive effect (14-28%) on farm annual gross margin depending on farm size. While accelerated growth rate resulted in only minor reductions in total emissions at farm level compared to the baseline scenario, reduced replacement rate lowered total farm level emissions by up to 8%, and emissions per unit of output by up to 6%. We conclude that an accelerated heifer growth rate scenario could potentially increase farm gross margin by some 14-28% compared with a baseline growth rate scenario. Reducing the replacement rate would be more efficient to reduce farm-level greenhouse gas emissions.

Characteristics of Buffalo Farming Systems in Turkey Based on a Multivariate Aggregation of Indicators: A Survey Study

This study aimed to determine the heterogeneity that exists in water buffalo husbandry systems in Marmara Region, Turkey. A questionnaire containing a total of 60 indicators was submitted to 52 farmers. A Principal Component Analysis was performed to reduce original variables into a simplified and latent structure, which was characterized by six orthogonal components: milk productivity, economic efficiency, roughage management, dual-purpose farming, concentrate supply, and fodder production. An ANOVA model was applied to the six components to investigate the effects of the province, investment levels, grazing type, milk production, and profitability. Differences in milk productivity, roughage management, concentrate supply, and fodder management were significant according to the province and grazing type, which indicated a difference in intensification levels among the cities. Economic efficiency and dual-purpose farming differed significantly for milk production levels as well as milk productivity, and economic efficiency differed for profitability levels. We found a tendency regarding the impact of roughage management on profitability. The results conclude that profitability was associated with improving the milking traits of buffaloes and roughage management of the farms.

Economic Implications of a Protein Transition: Evidence From Walloon Beef and Dairy Farms

In Europe, cattle production is confronted with major challenges across all dimensions of sustainability, urging the need to promote environmentally friendly but also economically viable livestock systems. In addition, animal protein consumption greatly exceeds the dietary guidelines in most European countries. The protein transition, defined as the rebalancing between animal and alternative proteins in diets, is presented as a solution to mitigate the harmful effects of cattle production on the environment, but also as an opportunity to induce healthier diets. Yet, the implications of such a transition on current livestock farmers are still unclear. In this article, we investigate different factors associated with a protein transition (e.g., reduction of herd size, increased concentrate autonomy and increased share of pastures) and assess their implications for the economic performance of dairy and beef farmers in Wallonia, Belgium. In the dairy sector, we find that a reduction in herd size, a higher share of pastures and an increased concentrate autonomy are correlated with lower operating costs, resulting in higher margins. Therefore, a switch to more extensive grazing systems that rely on on-farm fodder production can entail economic benefits for farmers. In the beef sector, on the other hand, farm characteristics are uncorrelated with most economic indicators, but highly associated with subsidies. This suggests that changes in this sector will rather be induced by policy choices than by economic parameters.

Trade-offs between economic, environmental and social sustainability on farms using a latent class frontier efficiency model: Evidence for Spanish crop farms

This article studies trade-offs of farms in terms of economic sustainability (proxied here by technical efficiency), environmental sustainability (proxied here by farmers’ commitment towards the environment) and social sustainability (proxied here by farmers’ contribution to on farm well-being and communities’ well-being). We use the latent class stochastic frontier model and create classes based on three separating variables, representing farms’ environmental sustainability and social sustainability. The application to a sample of Spanish crop farms shows that more environmentally sustainable farms are likely to have lower levels of technical efficiency. However, improvements in social concerns, both towards own farm and the larger community, may lead to improved technical efficiency levels. In general, our study provides evidence of trade-offs for farms between economic sustainability and environmental sustainability, but also between environmental sustainability and social sustainability.

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.

Measuring technology and performance differentials among the Norwegian dairy farms

Purpose

The study measures the technology gap and performance of the Norwegian dairy farms accounting for farm heterogeneity.

Design/methodology/approach

The analysis was based on a meta-frontier and unbalanced farm-level panel data for 1991–2014 from 417 Norwegian farms specialized in dairy production in five regions of Norway.

Findings

The result of the analysis provides empirical evidence of regional differences in technical efficiencies, technological gap ratios (TGRs) and input use. Consequently, the paper provides some insights into policies to increase the efficiency of dairy production in the country across all regions.

Research limitations/implications

The author used a meta-frontier approach for modeling regional differences based on a single-output production function specification. This approach has commonly been used in the economics literature since Battese et al. (2004). To get more informative and useful results, it would be necessary to repeat the analysis within terms of multiple input-output frameworks using, for instance, the input distance function approach. Moreover, the author estimated the meta-frontier using the non-parametric approach, thus it is also a need for further analysis if the values are different by estimating using a parametric approach.

Practical implications

One implication for farmers (and their advisers) is that dairy farms in all regions used available technology in the area sub-optimally. Thus, those lagging the best-performing farms need to look at the way the best-performing farmers are operating. Policymakers might reduce the gap is through training, including sharing information about relevant technologies from one area to another, provided that the technologies being shared fit the working environment of the lagging area. Moreover, some of the dairy technologies they use may not fit other regions, suggesting that agricultural policies that aim to encourage efficient dairy production, such as innovation of improved technology (like breeding, bull selection and improved feed varieties) through research and development, need to account the environmental differences between regions.

Social implications

For both taxpayers and consumers, one implication is that the contributions they pay that go to subsidize dairy farmers appear to bring some benefits in terms of more efficient milk production that, in turn, increases the supply of some foods so possibly making food prices more affordable.

Originality/value

The paper contributes to the literature in several ways. In contrast to Battese et al. (2004), the author accounts for farm-level performance differences by applying the model devised by Greene (2005), thus may serve as a model for future studies at more local levels or of other industries. Moreover, the author is fortunate to able to use a large level farm-level panel data from 1991 to 2014.

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.

The Role of Technical Efficiency Achieving Sustainable Development: A Dynamic Analysis of Norwegian Dairy Farms

Growing environmental concerns have prompted governments to make sustainable choices in agricultural resource use. Evaluating the sustainability of agricultural systems is a key issue for the implementation of policies and practices aimed at revealing sustainability. This study aimed to evaluate the performance of Norwegian dairy farms, accounting for marginal effects of environmental (exogenous) variables. We adopted the dynamic parametric approach within the input distance function framework to estimate the performance of Norwegian dairy farms, focusing on the technical efficiency and determinates. For comparison, we also estimated the static parametric model, which was used by previous studies. We used unbalanced farm-level panel data for the period 2000–2018. The result shows a mean technical efficiency score of 0.92 for the dynamic model and 0.87 for the static models. The empirical result shows that the previous studies that focused on the static model reported a biased result on the performance of dairy farms. The dynamic efficiency score suggests that Norwegian dairy farms can reduce the input requirement of producing the average output by 8% if the operation becomes technically efficient. The environmental variables have a different effect on the performance of the farmers; thus, policymakers need to place special focus on these variables for the sustainable development of the dairy sector.

A Metafrontier Analysis on the Performance of Grain-Producing Regions in Norway

Previous application of the stochastic frontier model and subsequent measurement of the performance of the crop sector can be criticized for the estimated production function relying on the assumption that the underlying technology is the same for different agricultural systems. This paper contributes to estimating regional efficiency and the technological gap in Norwegian grain farms using the stochastic metafrontier approach. For this study, we classified the country into regions with district level of development and, hence, production technologies. The dataset used is farm-level balanced panel data for 19 years (1996–2014) with 1463 observations from 196 family farms specialized in grain production. The study used the true random effect model and stochastic metafrontier analysis to estimate region level technical efficiency (TE) and technology gap ratio (TGR) in the two main grain-producing regions of Norway. The result of the analysis shows that farmers differ in performance and technology use. Consequently, the paper gives some regionally and farming system-based policy insights to increase grain production in the country to achieve self-sufficiency and small-scale farming in all regions.

Environmental Impacts of Milking Cows in Latvia

Increasing pressures surrounding efficiency and sustainability are key global drivers in dairy farm management strategies. However, for numerous resource-based, social, and economic reasons sustainable intensification strategies are herd-size dependent. In this study, we investigated the environmental impacts of Latvia’s dairy farms with different management practices. The herd size-dependent management groups varied from extensively managed small herds with 1–9 cows, extending to stepwise more intensively managed herds with 10–50, 51–100, 100–200, and over 200 milking cows. The aim is to compare the environmental impacts of different size-based production strategies on Latvia’s dairy farms. The results show that the gross greenhouse gas emissions differ by 29%: from 1.09 kg CO2 equivalents (CO2e) per kg of raw milk for the farms with 51–100 cows, down to 0.84 kg CO2e/kg milk for farms with more than 200 cows. However, the land use differs even more—the largest farms use 2.25 times less land per kg of milk than the smallest farms. Global warming potential, marine eutrophication, terrestrial acidification, and ecotoxicity were highest for the mid-sized farms. If current domestic, farm-based protein feeds were to be substituted with imported soy feed (one of the most popular high-protein feeds) the environmental impacts of Latvian dairy production would significantly increase, e.g., land use would increase by 18% and the global warming potential by 43%. Environmental policy approaches for steering the farms should consider the overall effects of operation size on environmental quality, in order to support the best practices for each farm type and steer systematic change in the country. The limitations of this study are linked to national data availability (e.g., national data on feed production, heifer breeding, differences among farms regards soil type, manure management, the proximity to marine or aquatic habitats) and methodological shortcomings (e.g., excluding emissions of carbon sequestration, the use of proxy allocation, and excluding social and biodiversity impacts in life-cycle assessment). Further research is needed to improve the data quality, the allocation method, and provide farm-size-specific information on outputs, heifer breeding, manure storage, and handling.

Herd-level associations between somatic cell counts and economic performance indicators in Brazilian dairy herds

The aims of the present study were to provide a portrait of the techno-economic status of dairy herds in Minas Gerais, Brazil, particularly with respect to bulk-tank somatic cell count (BTSCC) data, and to examine the herd-level associations of BTSCC with various economic performance indicators (EPI). Data from 543 herds, 1,052 herd-year records in total, spread over 3 years (2015-2017), from the South and Southwest mesoregions of Minas Gerais State were provided by the Brazilian Support Agency to Micro and Small Companies Division Minas Gerais (SEBRAE). Herds had an average of 82 lactating cows per herd, milk yield of 17 L/cow per day, and availability of financial information via routine monthly economic surveys. The EPI data (revenue, gross margin, GM; net margin, NM; profit; break-even point; and operational profitability) of each herd was measured monthly by SEBRAE personnel, and herd-year averages of all variables were computed. Bulk-tank data (SCC, total bacterial count, content of crude protein and fat) taken by producers or dairy processors were recorded by SEBRAE personal; and corresponding herd-year averages were calculated and included in the SEBRAE database. There were 209 selected herds, which passed all edit checks, and which had data for all 3 years. The EPI (all expressed on a per-cow basis, $/cow per year) were analyzed, including the effects of region, year, log (ln) BTSCC, production level, and herd size, together with the random effect of herd nested within region. A high proportion of herds (94.6%) presented data records (herd-years) with an average BTSCC > 200 × 10³ cells/mL: 37.8% of herd-year records had BTSCC between >200 and ≤400, 14.5% with BTSCC between >400 and ≤500, 25% with BTSCC between >500 and ≤750, and 17.3% with BTSCC >750. For each unit increase in ln BTSCC, revenue declined by $228.5/cow per year, GM by $155.6/cow per year, and profit by $138.6/cow per year. Herds with cows of lower production (<14 kg/d) presented lower GM ($286.8/cow per year) compared with herds containing cows producing ≥14 kg/d (≥14 and <19 kg/d = $446.5, and ≥19 kg/d = $601.9). The small-scale milk producers (<39 lactating cows) presented lower revenue ($1,914.9/cow per year) and GM ($274.5/cow per year) and consequently a negative profit (-$224.1/cow per year) compared with other herd size categories (≥39 lactating cows). The reduction in milk yield was 641 L/cow per lactation for each unit increase in ln BTSCC; this represented 9.4% of the milk yield per lactation, assuming an average milk production of 6,843.3 L/cow per lactation of cows from herds that had BTSCC ≤ 200 × 10³ cells/mL. Consequently, we found a negative association of BTSCC with profit; profit declining from $227.0 to -53.1/cow per year when the BTSCC increased from 100 to 750 × 10³ cell/mL. In short, the lower the BTSCC, the greater the revenue, GM and NM, profit, and operational profitability of the herds. The reduction of milk yield was the main factor associated with higher BTSCC.

The Mode of Grass Supply to Dairy Cows Impacts on Fatty Acid and Antioxidant Profile of Milk

The optimization of milk production includes a rational use of forages, respect for the environment and offers the best quality to consumers. Milk production based on grass and forages produces healthier milk and it is widely spread throughout the Atlantic arc to maximize milk yield per hectare. However, the mode of offering the grass can have a major influence on milk composition. The aim of this study was to evaluate the effect of grass supply mode (grazing, zero-grazing or ensiling) on dairy cows’ performance, with particular reference to fatty acids and fat-soluble antioxidants concentration. A three by three Latin square experiment was performed with 18 dairy cows. Experimental treatments consisted of exclusive feeding with grass silage and zero-grazing, both offered ad libitum indoors, or grazing for 24 h. The results showed that grazing cows had a higher dry matter intake and greater milk yield than cows feeding on grass silage and zero-grazing, as well as higher concentrations of protein, lactose, nonfat-solids and urea in milk than housed cows. Milk fat from grazing cows had a higher proportion of unsaturated fatty acids than from cows feeding on grass silage and zero-grazing, with significant differences in the proportion of vaccenic and rumenic acids. The 18:1 trans-11 to 18:1 trans-10 ratio is proposed as biomarker to identify the milk produced from the management system of grazing cattle. Milk from grazing cows had a greater proportion of lutein than cows eating grass silage, with the zero-grazing system having intermediate values. In conclusion, the mode of grass supply affects fatty acid and antioxidant profiles of milk.

In a Search for Equity: Do Direct Payments under the Common Agricultural Policy Induce Convergence in the European Union?

The European Union (EU) is an integrated alliance of equally treated Member States sharing mutual values, legal principles and markets. Close cooperation, deep integration and convergence are the major priorities for the EU. Anyway, these principles are not always reflected in the EU-wide policies which are implemented through financial support mechanisms. The direct payments financial support mechanism under the Common Agricultural Policy, the main instrument for promoting convergence in development of Member States’ agricultural sectors and rural sustainability, faces critique for failing to meet its objectives. One of the major deficiencies of the direct payments scheme is that it allocates more resources to already developed agricultural sectors of the older Member States and less resources to developing ones thus increasing the divergence among the Member States. The aim of this paper is to suggest new mechanisms for direct payment funds redistribution across the EU Member States which are based on the methodological principles that would more precisely correspond to the aims of convergence, transparency and fair redistribution. The results show that, regardless of the method chosen (to support more or less effective agricultural sectors of EU Member States), the proposed methodology lowers differences in direct payment rates among the EU Member States by two-fold. This ensures correspondence to the goal of convergence within the EU.

Not one Brexit: How local context and social processes influence policy analysis

This paper develops an empirical agent-based model to assess the impacts of Brexit on Scottish cattle farms. We first identify several trends and processes among Scottish cattle farms that were ongoing before Brexit: the lack of succession, the rise of leisure farming, the trend to diversify and industrialise, and, finally, the phenomenon of the "disappearing middle", characterised by the decline of medium-sized farms and the polarization of farm sizes. We then study the potential impact of Brexit amid the local context and those ongoing social processes. We find that the impact of Brexit is indeed subject to pre-Brexit conditions. For example, whether industrialization is present locally can significantly alter the impact of Brexit. The impact of Brexit also varies by location: we find a clear divide between constituencies in the north (highland and islands), the middle (the central belt) and the south. Finally, we argue that policy analysis of Brexit should consider the heterogeneous social context and the complex social processes under which Brexit occurs. Rather than fitting the world into simple system models and ignoring the evidence when it does not fit, we need to develop policy analysis frameworks that can incorporate real world complexities, so that we can assess the impacts of major events and policy changes in a more meaningful way.

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

Evaluation of agricultural intensification requires comprehensive analysis of trends in farm performance across physical and socio-economic aspects, which may diverge across farm types. Typical reporting of economic indicators at sectorial or the “average farm” level does not represent farm diversity and provides limited insight into the sustainability of specific intensification pathways. Using farm business data from a total of 7281 farm survey observations of English and Welsh dairy farms over a 14-year period we calculate a time series of 16 key performance indicators (KPIs) pertinent to farm structure, environmental and socio-economic aspects of sustainability. We then apply principle component analysis and model-based clustering analysis to identify statistically the number of distinct dairy farm typologies for each year of study, and link these clusters through time using multidimensional scaling. Between 2001 and 2014, dairy farms have largely consolidated and specialized into two distinct clusters: more extensive farms relying predominantly on grass, with lower milk yields but higher labour intensity, and more intensive farms producing more milk per cow with more concentrate and more maize, but lower labour intensity. There is some indication that these clusters are converging as the extensive cluster is intensifying slightly faster than the intensive cluster, in terms of milk yield per cow and use of concentrate feed. In 2014, annual milk yields were 6,835 and 7,500 l/cow for extensive and intensive farm types, respectively, whilst annual concentrate feed use was 1.3 and 1.5 tonnes per cow. For several KPIs such as milk yield the mean trend across all farms differed substantially from the extensive and intensive typologies mean. The indicators and analysis methodology developed allows identification of distinct farm types and industry trends using readily available survey data. The identified groups allow the accurate evaluation of the consequences of the reduction in dairy farm numbers and intensification at national and international scales.

Probiotic properties of native Lactobacillus spp. strains for dairy calves

The use of native microorganisms with probiotic capacity is an alternative tool for the treatment and prevention of several diseases that affect animals, such as neonatal calf diarrhoea. The selection of probiotic strains within a collection is based on different in vitro and in vivo assays, which predict their potential. The aim of this study was to characterise a group of native Lactobacillus spp. strains isolated from faeces of healthy calves using an in vitro approach and to assess their ability to colonise the gastrointestinal tract (GIT) of calves. Native Lactobacillus spp. strains were evaluated on their capacity to survive low pH conditions and bile salts presence, biofilm formation and adhesion to both mucus and Caco-2 cells. Based on the in vitro characterisation, four strains (Lactobacillus johnsonii TP1.1, Lactobacillus reuteri TP1.3B, L. johnsonii TP1.6 and Lactobacillus amylovorus TP8.7) were selected to evaluate their capacity to colonise and persist in the GIT of calves. The assessment of enteric persistence involved an in vivo assay with oral administration of probiotics and quantification in faeces of the administered bacterial species with real-time quantitative PCR (qPCR). The study was conducted using 15 calves (1-month-old) which were divided into five groups of three animals, four of which were treated with four different selected strains and one was the control group. Strains TP1.3B and TP1.6 managed to persist in treated animals until ten days after the end of the administration period, indicating that they could be promising candidates for the design of probiotics for calves.

ÍNDICES DE DESEMPENHO ZOOTÉCNICO E ECONÔMICO DE SISTEMAS DE PRODUÇÃO DE LEITE COM DIFERENTES TIPOS DE MÃO DE OBRA

Objetivou-se com este estudo estimar índices de desempenho zootécnico e econômico de referência, analisar a influência dos tipos de mão de obra sobre a rentabilidade da atividade e identificar os componentes que exerceram maiores representatividades sobre o custo total e operacional efetivo. Foram analisados 38 índices de tamanho, zootécnico e econômico de 61 sistemas de produção de leite, localizados em Minas Gerais e Rio de Janeiro, agrupados em função do tipo de mão de obra. Os dados foram coletados durante o período de janeiro de 2002 a dezembro de 2011. Os resultados foram comparados pelo teste de ANOVA (distribuição normal), complementado pelo teste LSD, e pelo teste de Kruskal-Wallis (distribuição não normal), também complementado pelo teste LSD. Índices de medição de desempenho de referências devem ser considerados, levando-se em conta os fatores que sejam comuns aos sistemas de produção. O tipo de mão de obra não parece determinar a eficiência econômica do sistema de produção. Os itens componentes do custo total e operacional efetivo que exerceram maiores representatividades foram, em ordem decrescente, alimentação e mão de obra, para os grupos mão de obra contratada e mista, e alimentação e despesas diversas, para o grupo mão de obra familiar.

Cluster analysis of Dairy Herd Improvement data to discover trends in performance characteristics in large Upper Midwest dairy herds

Principal component analysis (PCA) is a variable reduction method used on over-parameterized data sets with a vast number of variables and a limited number of observations, such as Dairy Herd Improvement (DHI) data, to select subsets of variables that describe the largest amount of variance. Cluster analysis (CA) segregates objects, in this case dairy herds, into groups based upon similarity in multiple characteristics simultaneously. This project aimed to apply PCA to discover the subset of most meaningful DHI variables and to discover groupings of dairy herds with similar performance characteristics. Year 2011 DHI data was obtained for 557 Upper Midwest herds with test-day mean ≥200 cows (assumed mostly freestall housed), that remained on test for the entire year. The PCA reduced an initial list of 22 variables to 16. The average distance method of CA grouped farms based on best goodness of fit determined by the minimum cophenetic distance. Six groupings provided the optimal fitting number of clusters. Descriptive statistics for the 16 variables were computed per group. On observations of means, groups 1, 2, and 6 demonstrated the best performances in most variables, including energy-corrected milk, linear somatic cell score (log of somatic cell count), dry period intramammary infection cure rate, new intramammary infection risk, risk of subclinical intramammary infection at first test, age at first calving, days in milk, and Transition Cow Index. Groups 3, 4, and 5 demonstrated the worst mean performances in most the PCA-selected variables, including DIM, age at first calving, risk of subclinical intramammary infection at first test, and dry period intramammary infection cure rate. Groups 4 and 5 also had the worst mean herd performances in energy-corrected milk, Transition Cow Index, linear somatic cell score, and new intramammary infection risk. Further investigation will be conducted to reveal patterns of management associated with herd categorization. The PCA and CA should be used when describing the multivariate performance of dairy herds and whenever working with over-parameterized data sets, such as DHI databases.

How can farming intensification affect the environmental impact of milk production?

The intensification process of the livestock sector has been characterized in recent decades by increasing output of product per hectare, increasing stocking rate, including more concentrated feed in the diet, and improving the genetic merit of the breeds. In dairy farming, the effects of intensification on the environmental impact of milk production are not completely clarified. The aim of the current study was to assess the environmental impacts of dairy production by a life cycle approach and to identify relations between farming intensity and environmental performances expressed on milk and land units. A group of 28 dairy farms located in northern Italy was involved in the study; data collected during personal interviews of farmers were analyzed to estimate emissions (global warming potential, acidification, and eutrophication potentials) and nonrenewable source consumption (energy and land use). The environmental impacts of milk production obtained from the life cycle assessment were similar to those of other recent studies and showed high variability among the farms. From a cluster analysis, 3 groups of farms were identified, characterized by different levels of production intensity. Clusters of farms showed similar environmental performances on product basis, despite important differences in terms of intensification level, management, and structural characteristics. Our study pointed out that, from a product perspective, the most environmentally friendly way to produce milk is not clearly identifiable. However, the principal component analysis showed that some characteristics related to farming intensification, such as milk production per cow, dairy efficiency, and stocking density, were negatively related to the impacts per kilogram of product, suggesting a role of these factors in the mitigation strategy of environmental burden of milk production on a global scale. Considering the environmental burden on a local perspective, the impacts per hectare were positively associated with the intensification level.

Emergy evaluation of contrasting dairy systems at multiple levels

Emergy accounting (EmA) was applied to a range of dairy systems, from low-input smallholder systems in South Mali (SM), to intermediate-input systems in two regions of France, Poitou-Charentes (PC) and Bretagne (BR), to high-input systems on Reunion Island (RI). These systems were studied at three different levels: whole-farm (dairy system and cropping system), dairy-system (dairy herd and forage land), and herd (animals only). Dairy farms in SM used the lowest total emergy at all levels and was the highest user of renewable resources. Despite the low quality of resources consumed (crop residues and natural pasture), efficiency of their use was similar to that of industrialised inputs by intensive systems in RI, PC and BR. In addition, among the systems studied, SM dairy farms lay closest to environmental sustainability, contradicting the usual image of high environmental impact of cattle production in developing countries. EmA also revealed characteristics of the three intensive systems. Systems from RI and PC had lower resource transformation efficiency and higher environmental impacts than those from BR, due mainly to feeding strategies that differed due to differing socio-climatic constraints. Application of EmA at multiple levels revealed the importance of a multi-level analysis. While the whole-farm level assesses the overall contribution of the system to its environment, the dairy-system level is suitable for comparison of multi-product systems. In contrast, the herd level focuses on herd management and bypasses debates about definition of system boundaries by excluding land management. Combining all levels highlights the contribution of livestock to the global agricultural system and identifies inefficiencies and influences of system components on the environment.

Welfare-positive management and nutrition for the dairy herd: a European perspective

As European dairy farms become larger and diverge between grass-based and fully housed systems, interest in the welfare of the dairy cow and related environmental issues by consumers and legislators is increasing. These pressures mean that good nutrition and management, which underpin much dairy cow welfare, is critical. Despite considerable research into the management and nutrition of the dairy cow from calf to adulthood there is much on-farm variability in its application. While the incidences of many endemic diseases are reduced most are still significant, for example lameness. In addition, trade and climate change are bringing a more diverse range of pathogens, parasites and pests into Northern Europe. Housing aspects are limited in application by economics and in most cases still do not match grazing for welfare in temperate climates. Genomic technologies offer increased opportunities to breed for 'robustness' but like 'precision animal management systems' have still to be fully exploited.

Pluri-energy analysis of livestock systems--a comparison of dairy systems in different territories

This paper introduces a generic assessment method called pluri-energy analysis. It aims to assess the types of energy used in agricultural systems and their conversion efficiencies. Four types of energy are considered: fossil energy, gross energy contained in the biomass, energy from human and animal labor and solar energy. The method was applied to compare smallholder low-input dairy-production systems, which are common in developing countries, to the high-input systems encountered in OECD countries. The pluri-energy method is useful for analyzing the functioning of agricultural systems by highlighting their modes of energy management. Since most dairy systems in South Mali (SM) are low-input systems, they are primarily based on solar and labor energy types and do not require substantial fossil-energy inputs to produce milk. Farms in Poitou-Charentes (PC) and Bretagne (BR) show intermediate values of fossil-energy use for milk production, similar to that found in the literature for typical European systems. However, fossil-energy use for milk production is higher on PC than BR farms because of a higher proportion of maize silage in the forage area; grazing pastures are more common on BR farms. Farms on Reunion Island (RI) require a relatively large amount of fossil energy to produce milk, mainly because the island context limits the amount of arable land. Consequently, milk production is based on large imports of concentrated feed with a high fossil-energy cost. The method also enables assessment of fossil-energy-use efficiency in order to increase the performance of biological processes in agricultural systems. Comparing the low-input systems represented by SM to the high-input systems represented by RI, PC and BR, an increase in solar-energy conversion, and thus land productivity, was observed due to intensification via increased fossil-energy use. Conversely, though fossil-energy use at the herd level increased milk productivity, its effect on gross-energy conversion by the herd was less evident. Partitioning the total on-farm gross energy produced among animal co-products (milk, meat and manure) highlights the major functions of SM herds, which are managed to produce organic crop fertilizers.

Benchmarking environmental and operational parameters through eco-efficiency criteria for dairy farms

Life Cycle Assessment (LCA) is often used for the environmental evaluation of agri-food systems due to its holistic perspective. In particular, the assessment of milk production at farm level requires the evaluation of multiple dairy farms to guarantee the representativeness of the study when a regional perspective is adopted. This article shows the joint implementation of LCA and Data Envelopment Analysis (DEA) in order to avoid the formulation of an average farm, therefore preventing standard deviations associated with the use of average inventory data while attaining the characterization and benchmarking of the operational and environmental performance of dairy farms. Within this framework, 72 farms located in Galicia (NW Spain) were subject to an LCA+DEA study which led to identify those farms with an efficient operation. Furthermore, target input consumption levels were benchmarked for each inefficient farm, and the corresponding target environmental impacts were calculated so that eco-efficiency criteria were verified. Thus, average reductions of up to 38% were found for input consumption levels, leading to impact reductions above 20% for every environmental impact category. Finally, the economic savings arising from efficient farming practices were also estimated. Economic savings of up to 0.13€ per liter of raw milk were calculated, which means extra profits of up to 40% of the final raw milk price.