Simulation of Long-Term Carbon and Nitrogen Dynamics in Grassland-Based Dairy Farming Systems to Evaluate Mitigation Strategies for Nutrient Losses

Many measures have been proposed to mitigate gaseous emissions and other nutrient losses from agroecosystems, which can have large detrimental effects for the quality of soils, water and air, and contribute to eutrophication and global warming. Due to complexities in farm management, biological interactions and emission measurements, most experiments focus on analysis of short-term effects of isolated mitigation practices. Here we present a model that allows simulating long-term effects at the whole-farm level of combined measures related to grassland management, animal housing and manure handling after excretion, during storage and after field application. The model describes the dynamics of pools of organic carbon and nitrogen (N), and of inorganic N, as affected by farm management in grassland-based dairy systems. We assessed the long-term effects of delayed grass mowing, housing type (cubicle and sloping floor barns, resulting in production of slurry and solid cattle manure, respectively), manure additives, contrasting manure storage methods and irrigation after application of covered manure. Simulations demonstrated that individually applied practices often result in compensatory loss pathways. For instance, methods to reduce ammonia emissions during storage like roofing or covering of manure led to larger losses through ammonia volatilization, nitrate leaching or denitrification after application, unless extra measures like irrigation were used. A strategy of combined management practices of delayed mowing and fertilization with solid cattle manure that is treated with zeolite, stored under an impermeable sheet and irrigated after application was effective to increase soil carbon stocks, increase feed self-sufficiency and reduce losses by ammonia volatilization and soil N losses. Although long-term datasets (>25 years) of farm nutrient dynamics and loss flows are not available to validate the model, the model is firmly based on knowledge of processes and measured effects of individual practices, and allows the integrated exploration of effective emission mitigation strategies.     

京郊典型集约化"农田-畜牧"生产系统氮素流动特征

城郊畜牧业的集约化发展在满足人们日益增长的肉蛋奶等动物性产品需求的同时,也带来了巨大的环境压力。本文利用养分流动和模型分析的方法,分析北京市郊区某村三种不同类型"农田-畜牧"生产系统(大型集约化种猪场、种养结合小规模生态养殖园和集约化单一种植区)的氮素流动特征。结果表明:饲料是集约化种猪场和生态养殖园氮素输入的主要来源,饲料投入氮量分别为12469.0和9268.5 kg.hm-.2a-1);集约化种猪场农牧体系间生产脱节,致使农田氮素输入主要依赖于化肥投入,化肥氮输入量(435.0 kg.hm-.2a-1)占农田氮素输入量的82.7%。相反,生态养殖园农牧体系结合紧密,猪粪尿氮还田比例达28.6%,这使得园区化肥氮输入量仅为135.0 kg.hm-.2a-1,因此畜禽粪尿的合理循环利用可作为减少化肥投入的有效途径;集约化种猪场、生态养殖园和单一种植区农牧生产系统氮素利用效率分别为18.8%、20.6%和17.3%,均处于较低水平;集约化种猪场猪粪尿在猪舍和储藏处理过程的氮素损失率为15.8%和25.4%,分别低于小规模生态养殖园相应损失率约8.7和4.8个百分点;生态养殖园粪肥氮还田量高,导致农田氮素盈余量高达1962.8 kg.hm-.2a-1,未能实现生态型养殖的理想效果,优化氮素管理、确定合理的消纳畜禽粪尿的农田面积和调整畜禽养殖密度是解决该问题的关键。     

Impacts of biogas production on nitrogen flows on Dutch dairy system: Multiple level assessment of nitrogen indicators within the biogas production chain

Biogas production on dairy farms is promoted as a climate change measure since it captures methane, a greenhouse gas emitted by manure, and produces renewable energy. Digestate is a by‐product of biogas production and is often used for nutrient recycling in a similar way as traditional manure. Despite having similar functions, manure and digestate have different behaviors related to nitrogen recycling and nitrogen emissions which are significant agricultural and environmental concerns of manure. This paper provides an insight into the impact of biogas production on nitrogen emissions and nitrogen recycling issues of the current dairy farming practice. Using the Substance Flow Analysis (SFA) approach, we analyzed the changes on three levels: manure handling, dairy farm, and the whole chain. Four biogas production options on a Dutch dairy farm related to types and sources of feedstocks were considered. We quantified biogas output, nitrogen fertilizer replacement percentage (%) and consequential nitrogen emissions (kgN/year; kgN/m³ biogas produced) of these productions in comparison with the baseline of current dairy farming without biogas. We conclude that biogas production options with additional feedstocks will cause profound changes in the nitrogen recycling on dairy farms and the nitrogen emissions at the chain level. Besides, the results show that determining the optimal biogas production option can be challenging as the evaluation is highly dependent on the used nitrogen indicator and the included level of analysis. Our findings show how SFA and a multilevel perspective can give a broader understanding of environmental trade‐offs.     

Understanding the reproductive performance of a dairy cattle herd by using both analytical and systemic approaches: a case study based on a system experiment

Reproductive performance has recently been a growing concern in cattle dairy systems, but few research methodologies are available to address it as a complex problem in a livestock farming system. The aim of this paper is to propose a methodology that combines both systemic and analytical approaches in order to better understand and improve reproductive performance in a cattle dairy system. The first phase of our methodology consists in a systemic approach to build the terms of the problem. It results in formalising a set of potential risk factors relevant for the particular system under consideration. The second phase is based on an analytical approach that involves both analysing the shapes of the individual lactation curves and carrying out logistic regression procedures to study the links between reproductive performance and the previously identified potential risk factors. It makes it possible to formulate hypotheses about the biotechnical phenomena underpinning reproductive performance. The last phase is another systemic approach that aims at suggesting new practices to improve the situation. It pays particular attention to the consistency of those suggestions with the farmer's general objectives. This methodology was applied to a French system experiment based on an organic low-input grazing system. It finally suggested to slightly modify the dates of the breeding period so as to improve reproductive performance. The formulated hypotheses leading to this suggestion involved both the breed (Holstein or Montbéliarde cows), the parity, the year and the calving date with regard to the turnout date as the identified risk factors of impaired performance. Possible use of such a methodology in any commercial farm encountering a biotechnical problem is discussed.     

Invited review: Big Data in precision dairy farming

Insight into current scientific applications of Big Data in the precision dairy farming area may help us to understand the inflated expectations around Big Data. The objective of this invited review paper is to give that scientific background and determine whether Big Data has overcome the peak of inflated expectations. A conceptual model was created, and a literature search in Scopus resulted in 1442 scientific peer reviewed papers. After thorough screening on relevance and classification by the authors, 142 papers remained for further analysis. The area of precision dairy farming (with classes in the primary chain (dairy farm, feed, breed, health, food, retail, consumer) and levels for object of interest (animal, farm, network)), the Big Data-V area (with categories on Volume, Velocity, Variety and other V’s) and the data analytics area (with categories in analysis methods (supervised learning, unsupervised learning, semi-supervised classification, reinforcement learning) and data characteristics (time-series, streaming, sequence, graph, spatial, multimedia)) were analysed. The animal sublevel, with 83% of the papers, exceeds the farm sublevel and network sublevel. Within the animal sublevel, topics within the dairy farm level prevailed with 58% over the health level (33%). Within the Big Data category, the Volume category was most favoured with 59% of the papers, followed by 37% of papers that included the Variety category. None of the papers included the Velocity category. Supervised learning, representing 87% of the papers, exceeds unsupervised learning (12%). Within supervised learning, 64% of the papers dealt with classification issues and exceeds the regression methods (36%). Time-series were used in 61% of the papers and were mostly dealing with animal-based farm data. Multimedia data appeared in a greater number of recent papers. Based on these results, it can be concluded that Big Data is a relevant topic of research within the precision dairy farming area, but that the full potential of Big Data in this precision dairy farming area is not utilised yet. However, the present authors expect the full potential of Big Data, within the precision dairy farming area, will be reached when multiple Big Data characteristics (Volume, Variety and other V’s) and sources (animal, groups, farms and chain parts) are used simultaneously, adding value to operational and strategic decision.     

The sociocultural sustainability of livestock farming: an inquiry into social perceptions of dairy farming

Over the past 50 years, the scale and intensity of livestock farming have increased significantly. At the same time, Western societies have become more urbanised and fewer people have close relatives involved in farming. As a result, most citizens have little knowledge or direct experience of what farming entails. In addition, more people are expressing concerns over issues such as farm animal welfare. This has led to increasing public demand for more sustainable ways of livestock farming. To date, little research has been carried out on the social pillar of sustainable livestock farming. The aim of this study is to provide insights into the sociocultural sustainability of livestock farming systems. This study reviews the key findings of earlier published interdisciplinary research about the social perceptions of dairy farming in the Netherlands and Norway (Boogaard et al., 2006, 2008, 2010a and 2010b) and synthesises the implications for sociocultural sustainability of livestock farming. This study argues that the (sociocultural) sustainable development of livestock farming is not an objective concept, but that it is socially and culturally constructed by people in specific contexts. It explains the social pillar of the economics/ecological/social model sustainability in terms of the fields of tensions that exist between modernity, traditions and naturality - 'the MTN knot' - each of which has positive and negative faces. All three angles of vision can be seen in people's attitudes to dairy farming, but the weight given to each differs between individuals and cultures. Hence, sociocultural sustainability is context dependent and needs to be evaluated according to its local meaning. Moreover, sociocultural sustainability is about people's perceptions of livestock farming. Lay people might perceive livestock farming differently and ascribe different meanings to it than experts do, but their 'reality' is just as real. Finally, this study calls for an ongoing collaboration between social and animal scientists in order to develop livestock farming systems that are more socioculturally sustainable.     

Role of input self-sufficiency in the economic and environmental sustainability of specialised dairy farms

Increasing input self-sufficiency is often viewed as a target to improve sustainability of dairy farms. However, few studies have specifically analysed input self-sufficiency, by including several technical inputs and without only focussing on animal feeding, in order to explore its impact on farm sustainability. To address this gap, our work has three objectives as follows: (1) identifying the structural characteristics required by specialised dairy farms located in the grassland area to be self-sufficient; (2) analysing the relationships between input self-sufficiency, environmental and economic sustainability; and (3) studying how the farms react to a decrease in milk price according to their self-sufficiency degree. Based on farm accounting databases, we categorised 335 Walloon specialised conventional dairy farms into four classes according to their level of input self-sufficiency. To this end, we used as proxy the indicator of economic autonomy – that is, the ratio between costs of inputs related to animal production, crop production and energy use and the total gross product. Classes were then compared using multiple comparison tests and canonical discriminant analysis. A total of 30 organic farms – among which 63% had a high level of economic autonomy – were considered separately and compared with the most autonomous class. We showed that a high degree of economic autonomy is associated, in conventional farms, with a high proportion of permanent grassland in the agricultural area. The most autonomous farms used less input – especially animal feeding – for a same output level, and therefore combined good environmental and economic performances. Our results also underlined that, in a situation of decrease in milk price, the least autonomous farms had more latitude to decrease their input-related costs without decreasing milk production. Their incomes per work unit were, therefore, less impacted by falling prices, but remained lower than those of more autonomous farms. In such a situation, organic farms kept stable incomes, because of a slighter decrease in organic milk price. Our results pave the way to study the role of increasing input self-sufficiency in the transition of dairy farming systems towards sustainability. Further research is required to study a wide range of systems and agro-ecological contexts, as well as to consider the evolution of farm sustainability in the long term.     

Development of agri-environmental indicators to assess dairy farm sustainability in Quebec,Eastern Canada

Agri-environmental indicators are commonly used to assess agricultural sustainability. In North America, few are designed to be easily used by dairy farmers. As farmers assume more responsibility for managing natural resources, they play an increasingly important role in assessing sustainable agriculture. This paper describes the development of an indicator-based self-assessment tool for use at the farm level to evaluate dairy farm sustainability from an environmental standpoint. The agri-environmental indicator set was selected by using two participatory processes: the Delphi method and a focus group. The framework for developing the assessment tool consisted of six steps: (1) Defining the concept of environmental sustainability at the farm level; (2) setting up goals and principles for the assessment; (3) identifying potential indicators and selecting candidate indicators; (4) defining reference values, aggregating indicators into components, and establishing relative weights for indicators; (5) testing the candidate indicators on dairy farms, and (6) selecting the final indicator set. Six criteria were used to evaluate either the practicality or usefulness of indicators. Thirteen indicators were chosen, one of which was divided into four sub-indicators. These indicators were aggregated into four components: soil quality, cropping practices, fertilization management, and farmland management. Expert participation was the first validation of the indicator set. A compromise between feasibility, practicality, and relevance of measurement was found among indicators. When applied to 40 farms over two contrasting regions, the indicator set identified scores that differed according to production context. The tool is user-friendly and well-adapted to dairy farming systems.     

Improving nutrient efficiency as a strategy to reduce nutrient surpluses on dairy farms

Dutch nutrient policy aims at reducing leaching of agricultural nutrients by internalizing the negative externalities associated with inefficient nutrient use. This is done by taxation of nitrogen and phosphate surpluses that exceed a hectare-based threshold of maximum-allowed surpluses. One management strategy farmers may use to reduce the nutrient surpluses on their farms is to improve the nutrient efficiency of the agricultural production process. This study employs Data Envelopment Analysis (DEA) to calculate nitrogen and phosphate efficiencies and an overall nutrient efficiency measure for a 3-year panel of 114 Dutch dairy farms. Subsequent analyses show the impact of both farm intensity and nutrient efficiency on the nitrogen and phosphate surpluses. It appears that farm intensity has a positive effect on efficiency, but efficiency and intensity exert opposite influences on nutrient surpluses. This is especially the case for nitrogen. The magnitude of a possible reduction of nitrogen surpluses through a strategy of efficiency improvement is therefore limited by the intensity of the farming system, unless the technology with which nutrients are used by the farming system can be further improved or input/output ratios will be altered.     

Consequential Life Cycle Assessment of Pasture‐based Milk Production: A Case Study in the Waikato Region,New Zealand

Farm intensification options in pasture‐based dairy systems are generally associated with increased stocking rates coupled with the increased use of off‐farm inputs to support the additional feed demand of animals. However, as well as increasing milk production per hectare, intensification can also exacerbate adverse impacts on the environment. The objective of the present study was to investigate environmental trade‐offs associated with potential intensification methods for pasture‐based dairy farming systems in the Waikato region, New Zealand. The intensification scenarios selected were (1) increased pasture utilization efficiency (PUE scenario), (2) increased use of nitrogen (N) fertilizer to boost on‐farm pasture production (N fertilizer scenario), and (3) increased use of brought‐in feed as maize silage (MS) (MS scenario). Twelve impact categories were assessed. The PUE scenario was the environmentally preferred intensification method, and the preferred choice between the N fertilizer and MS scenarios depended upon trade‐offs between different environmental impacts. Sensitivity analysis was carried out to test the effects of choice associated with: (1) the approaches used to account for indirect land‐use change (ILUC) and (2) the competing product systems (conventional beef systems) used to handle the co‐product dairy meat for the climate change (CC) indicator. Results showed that the magnitude of the CC indicator results was influenced by the ILUC accounting approaches and the choice associated with a global marginal beef mix, but the relative CC indicator results for the three intensification scenarios remained unchanged.     

Integrated treatment of farm effluents in New Zealand’s dairy operations

Maintaining growth through intensification in the New Zealand dairy industry is a challenge for various reasons, in particular sustainably managing the large volumes of effluent. Dairy farm effluents have traditionally been treated using two-pond systems that are effective in the removal of carbon and suspended solids, however limited in their ability to remove nutrients. In the past these nutrient-rich two-pond treated effluents were disposed of in surface waters. Current environmental concerns associated with the direct discharge of these effluents to surface waters has prompted in developing technologies to either minimise the nutrient content of the effluent or apply effluents to land. Here, we discuss various approaches and methods of treatment that enable producers to sustainably manage farm effluents, including advanced pond treatment systems, stripping techniques to reduce nutrient concentration, land application strategies involving nutrient budgeting models to minimise environmental degradation and enhance fodder quality. We also discuss alternative uses of farm effluents to produce energy and animal feed.     

Review: Milking robot utilization,a successful precision livestock farming evolution

Automatic milking systems (AMS), one of the earliest precision livestock farming developments, have revolutionized dairy farming around the world. While robots control the milking process, there have also been numerous changes to how the whole farm system is managed. Milking is no longer performed in defined sessions; rather, the cow can now choose when to be milked in AMS, allowing milking to be distributed throughout a 24 h period. Despite this ability, there has been little attention given to milking robot utilization across 24 h. In order to formulate relevant research questions and improve farm AMS management there is a need to determine the current knowledge gaps regarding the distribution of robot utilization. Feed, animal and management factors and their interplay on levels of milking robot utilization across 24 h for both indoor and pasture-based systems are here reviewed. The impact of the timing, type and quantity of feed offered and their interaction with the distance of feed from the parlour; herd social dynamics, climate and various other management factors on robot utilization through 24 h are provided. This novel review draws together both the opportunities and challenges that exist for farm management to use these factors to improved system efficiency and those that exist for further research.     

Diffusion of precision livestock farming technologies in dairy cattle farms

The rising global demand for animal products and the growing public concerns about the environment and animal welfare require dairy farms to improve their efficiency and apply more sustainable farming systems. Precision Livestock Farming (PLF) could represent a valuable support in addressing these challenges. In recent years, dairy farms have been modernising and introducing new sensors and automatic systems for managing the herd. However, the diffusion of new technologies in Italian dairy farms is still limited and farmers are reluctant to invest in precision systems. The aim of the study was to investigate the presence of PLF tools in Italian dairy farms, the motivations, benefits and limits of technological investments from the farmers’ point of view and the factors affecting the diffusion of technology. From November 2020 to June 2021, an online questionnaire was distributed and 52 responses were obtained. About 79% of the farms were located in Lombardy. The more represented milking system was the conventional milking parlour (73%), followed by automatic milking (19%). The average age of respondents was quite low: 35% of them was less than 40 years old and more than 50% was between 40 and 60. Statistical analyses were performed to evaluate the effects of different factors on the presence of technology at farm. The age of the farmer, the milk production level and the presence of an automatic milking system influenced the technological level of the farm. Precision systems that provide information on animal activity for the management of reproduction and on milk yield and flow are the most popular and are considered among the most useful. Management of reproduction and milk production are the areas where farmers appear to show interest for future investments as well. Younger farmers appear to have implemented more PLF systems than older ones, and they show a propensity to invest in latest generation precision tools. Farmers seem to have a growing interest in PLF, but some limits have been identified: the investment costs, followed by the lack of time to check information from sensor systems and the difficulty in data interpretation. As PLF technologies can play an important role in the development of sustainable, animal-friendly and efficient livestock production, further improvements and efforts are necessary to increase the propensity to PLF of dairy farmers. Results can be useful in the Italian context but also in other countries where dairy farming is rapidly intensifying but PLF is encountering resistance.     

The Application of Biotechnical and Epidemiologic Tools for Pig Health

Health maximization is a farm essential because of its implications for animal well-being and for production. Health care in all livestock species is a dynamic, technologically-limited, and resource-constrained enterprise. As in any health endeavor, challenges abound. Fundamentally, the cornerstones of animal health are good husbandry and good housing. Effective health systems, however, incorporate other management aspects, including biotechnology and epidemiology. The degree to which each affects the incidence and severity of pig disease is not fully appreciated. Shortfalls in management, resource allocation, available tools, and/or understanding are not uncommon. This article reviews the dynamics of pig health emphasizing how technology and management marginally affect the course of disease. Further, management techniques that incorporate technology in disease control, elimination, and eradication are reviewed. Antimicrobials are a key biotechnical tool for maximizing pig health.     

Mixed crop-livestock systems: an economic and environmental-friendly way of farming?

Intensification and specialisation of agriculture in developed countries enabled productivity to be improved but had detrimental impacts on the environment and threatened the economic viability of a huge number of farms. The combination of livestock and crops, which was very common in the past, is assumed to be a viable alternative to specialised livestock or cropping systems. Mixed crop-livestock systems can improve nutrient cycling while reducing chemical inputs and generate economies of scope at farm level. Most assumptions underlying these views are based on theoretical and experimental evidence. Very few assessments of their environmental and economic advantages have nevertheless been undertaken in real-world farming conditions. In this paper, we present a comparative assessment of the environmental and economic performances of mixed crop-livestock farms v. specialised farms among the farm population of the French ‘Coteaux de Gascogne’. In this hilly region, half of the farms currently use a mixed crop-livestock system including beef cattle and cash crops, the remaining farms being specialised in either crops or cattle. Data were collected through an exhaustive survey of farms located in our study area. The economic performances of farming systems were assessed on 48 farms on the basis of (i) overall gross margin, (ii) production costs and (iii) analysis of the sensitivity of gross margins to fluctuations in the price of inputs and outputs. The environmental dimension was analysed through (i) characterisation of farmers’ crop management practices, (ii) analysis of farm land use diversity and (iii) nitrogen farm-gate balance. Local mixed crop-livestock farms did not have significantly higher overall gross margins than specialised farms but were less sensitive than dairy and crop farms to fluctuations in the price of inputs and outputs considered. Mixed crop-livestock farms had lower costs than crop farms, while beef farms had the lowest costs as they are grass-based systems. Concerning crop management practices, our results revealed an intensification gradient from low to high input farming systems. Beyond some general trends, a wide range of management practices and levels of intensification were observed among farms with a similar production system. Mixed crop-livestock farms were very heterogeneous with respect to the use of inputs. Nevertheless, our study revealed a lower potential for nitrogen pollution in mixed crop-livestock and beef production systems than in dairy and crop farming systems. Even if a wide variability exists within system, mixed crop-livestock systems appear to be a way for an environmental and economical sustainable agriculture.     

The application of biotechnical and epidemiologic tools for pig health

Health maximization is a farm essential because of its implications for animal well-being and for production. Health care in all livestock species is a dynamic, technologically-limited, and resource-constrained enterprise. As in any health endeavor, challenges abound. Fundamentally, the cornerstones of animal health are good husbandry and good housing. Effective health systems, however, incorporate other management aspects, including biotechnology and epidemiology. The degree to which each affects the incidence and severity of pig disease is not fully appreciated. Shortfalls in management, resource allocation, available tools, and/or understanding are not uncommon. This article reviews the dynamics of pig health emphasizing how technology and management marginally affect the course of disease. Further, management techniques that incorporate technology in disease control, elimination, and eradication are reviewed. Antimicrobials are a key biotechnical tool for maximizing pig health.     

Measures to improve dairy cow foot health: consequences for farmer income and dairy cow welfare

Dairy farming in western countries with cubicle housing is an efficient way of dairy farming. Though, a disadvantage is the high prevalence and incidence of foot disorders (clinical and subclinical), which cause high economic losses and also seriously impair the welfare of dairy cattle. To point out the importance of reducing the amount and severity of foot disorders, advice to farmers should include information about the scale of the problem and the consequences in terms of economics and animal welfare. To provide support in making decisions on implementing intervention measures, insight into costs and benefits of different measures should be available. The objective of this study, therefore, is to provide more insight into the costs and benefits, for farmer and cow, of different intervention measures to improve dairy cow foot health. Intervention measures were modeled when they were applicable on a dairy farm with cubicle housing and when sufficient information was available in literature. Net costs were calculated as the difference between the costs of the measure and the economic benefits resulting from the measure. Welfare benefits were calculated as well. Cost-effective measures are: improving lying surface (mattress and bedding, €7 and €1/cow per year, respectively), reducing stocking density (break even) and performing additional foot trimming (€1/cow per year). Simultaneously, these measures have a relative high welfare benefit. Labor costs play an important role in the cost-effectiveness of labor-intensive measures. More insight into cost-effectiveness and welfare benefits of intervention measures can help to prioritize when choosing between intervention measures.     

The economics of fibre and meat on Norwegian dairy goats

Seasonal variations in the volume of milk in Norwegian goat dairy farming complicate the production of brand goat cheeses. In the specialised goat dairy farming system most kids are culled shortly after birth without utilising the meat. In this paper the farm economics of an alternative system with altered period of kidding (currently from January to March) combined with the production of meat and cashmere fibre, is examined. May kidding combined with raising the kids for 8 or 20 months yielded the most promising economical return. Raising the kids for 1 year is also profitable when kidding takes place in February while December kidding seems to perform best with the present system of culling the kids right after birth. Cashmere fibre production seems to be profitable on Norwegian dairy goat farms and fibre and meat could become an option in countries seeking to improve incomes on dairy goat farms. Compared to the present system the changes would also be favourable from an animal welfare point of view.