Relevant bibliographies by topics / Dairy farming systems

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dairy farming systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Dairy farming systems"

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Roche, John. "Foreword to ‘Resilient Dairy Farming Systems’." Animal Production Science 55, no. 7 (2015): iii. http://dx.doi.org/10.1071/anv55n7_fo.

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Funes-Monzote, F. R., Marta Monzote, E. A. Lantinga, and H. van Keulen. "Conversion of specialised dairy farming systems into sustainable mixed farming systems in Cuba." Environment, Development and Sustainability 11, no. 4 (March 13, 2008): 765–83. http://dx.doi.org/10.1007/s10668-008-9142-7.

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Silva, Emiliana, Armando Brito Mendes, and Henrique José Duarte Rosa. "Dairy Farming Systems’ Adaptation to Climate Change." Agricultural Sciences 07, no. 03 (2016): 137–45. http://dx.doi.org/10.4236/as.2016.73013.

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Rossing, W., P. H. Hogewerf, A. H. Ipema, C. C. Ketelaar-De Lauwere, and C. J. A. M. De Koning. "Robotic milking in dairy farming." Netherlands Journal of Agricultural Science 45, no. 1 (July 1, 1997): 15–31. http://dx.doi.org/10.18174/njas.v45i1.523.

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The role of engineering research in the development of robotic milking systems and the integration of robotic milking in dairy farms are reviewed. The milking stall, robot arm, teat sensing system, milking equipment and udder cleaning devices of commercial automatic milking systems (AMS) available in the Netherlands at the end of 1996 are described. The importance of the attractiveness of the milking stall, lay-out of the barn and the introduction of a cow routing with special gates in the barn is highlighted. Increasing the milking frequency from 2 to 3 times/day results in a higher yield of approximately 1000 kg milk/lactation. It is concluded that automatic milking will decrease the physical and mental load on the farmer, but it should be considered that the farmer is working with complicated equipment.
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Velthof, G. L., and O. Oenema. "Nitrous oxide emission from dairy farming systems in the Netherlands." Netherlands Journal of Agricultural Science 45, no. 3 (October 1, 1997): 347–60. http://dx.doi.org/10.18174/njas.v45i3.510.

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A large part of the nitrogen (N) input in dairy farming systems in the Netherlands is lost from the system via N leaching and volatilization of gaseous N compounds, including the greenhouse gas nitrous oxide (N2O). The aim of the present study was to quantify N2O emission from dairy farming systems in the Netherlands, using a whole-farm approach. A total of 14 N2O sources was identified and emission factors were derived for each of these using the literature. Figures are presented for the amounts of N2O produced/kg herbage N produced (ranging from 4 to 89 g N2O-N kg-1 herbage N), depending on soil type and grassland management. Using Monte Carlo simulations, variations in mean total N2O emissions from the different sources were calculated for 3 model dairy farming systems differing in nutrient management. These different farming systems were chosen to assess the effect of improved nutrient management on total N2O emission. The total direct annual N2O emissions ranged from 15.4 +or-9.4 kg N2O-N/ha for the average dairy farming system in the 1980s to 5.3 +or-2.6 kg N2O-N/ha for a prototype of an economically feasible farming system with acceptable nutrient emissions. Leaching-derived, grazing-derived and fertilizer-derived N2O emissions were the major N2O sources on dairy farming systems. The total direct N2O emissions accounted for 3.2 to 4.6% of the N surplus on the dairy farming systems, suggesting that only a small amount of N was lost as N2O. Total N2O emissions from dairy farming systems in the Netherlands were 13.7+or-5.1 Gg N/year, which is about 35% of the estimated total N2O emission in the Netherlands. It is concluded that improvement of nutrient management of dairy farming systems will significantly decrease the N2O emissions from these systems, and thus the total N2O emission in the Netherlands.
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Aarts, H. F. M., E. E. Biewing, and H. van Keulen. "Dairy farming systems based on efficient nutrient management." Netherlands Journal of Agricultural Science 40, no. 3 (September 1, 1992): 285–99. http://dx.doi.org/10.18174/njas.v40i3.16514.

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In Dutch dairy farming, dramatic nutrient losses occur, causing serious environmental problems, and representing an economic and energy waste. So farming systems have to be developed based on efficient nutrient management. A dairy farm is characterized as a system with soils and crops, forage, cattle, and manure as main components. Simple models of nutrient flows in and between components of the farming system were used to design a prototype system for a new experimental farm on sandy soil, which has to meet strict environmental demands. Experimental results of this farm will be used to improve the models and the models will be used again to optimize the prototype system. Initial results of modelling suggest that nutrient losses can be reduced considerably by more accurate management, and introduction of relatively cheap and simple measures. However, more radical and expensive modifications of the farming system are necessary to meet further standards of the Dutch government for max. allowable emissions. (Abstract retrieved from CAB Abstracts by CABI’s permission)
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Zuliani, Anna, Isabella Lora, Marta Brščić, Andrea Rossi, Edi Piasentier, Flaviana Gottardo, Barbara Contiero, and Stefano Bovolenta. "Do Dairy Farming Systems Differ in Antimicrobial Use?" Animals 10, no. 1 (December 25, 2019): 47. http://dx.doi.org/10.3390/ani10010047.

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The quantitative assessment of antimicrobial use (AMU) in food-producing animals contributes to the provision of essential information for developing relevant and effective policies to reduce use and to control antimicrobial resistance. Information on AMU is available mainly for intensive dairy farming systems and specialized high-yielding breeds. The aim of this study is to investigate AMU in different dairy farming systems by comparing the treatment incidence in mountain farms with specialized high-yield dairy breeds or with dual-purpose breeds raised for milk production to the treatment incidence in lowland farms with specialized high-yield dairy breeds or with dual-purpose breeds raised for milk production. Significant differences were found only between the overall treatment incidence, as well as the treatment incidence of highest-priority critically important antimicrobials for human medicine, in lowland farms with high-yielding breeds and mountain farms with dual-purpose breeds. Mountain farms have a generally lower milk production and smaller herd size than lowland farms, provide cows with access to pasture, and limit concentrates in the diet. These management practices and the use of local/dual-purpose breeds could reduce the risk of production diseases and the consequent need for AMU.
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Romaniuk, Wacław, Kamila Mazur, Kinga Borek, Andrzej Borusiewicz, Witold Jan Wardal, Sylwester Tabor, and Maciej Kuboń. "Biomass Energy Technologies from Innovative Dairy Farming Systems." Processes 9, no. 2 (February 12, 2021): 335. http://dx.doi.org/10.3390/pr9020335.

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Modern and innovative dairy cattle breeding technologies are highly dependent on the level of mechanization. This article presents modern solutions for dairy cattle breeding, in particular, for livestock buildings, in which longitudinal development is possible in accordance with the farm’s needs as well as with obtaining additional energy from biogas and post-ferment for granulated organic fertilizer. In the analysed technology for milk production, methane fermentation, biogas yield, and the possibility of fertilizer production in the form of granules are considered. The presented modular cattle breeding technology includes sustainable production, which is economic; environmentally friendly, with preconditions in the facility including animal welfare; and socially acceptable, resulting from a high level of mechanization, which ensures both comfortable working conditions and high milk quality. The presented production line is an integral part of the milk production process with the possibility of organic fertilizer being used in the production of healthy food.
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O’ Mahony, Niall, Sean Campbell, Anderson Carvalho, Lenka Krpalkova, Daniel Riordan, and Joseph Walsh. "3D Vision for Precision Dairy Farming." IFAC-PapersOnLine 52, no. 30 (2019): 312–17. http://dx.doi.org/10.1016/j.ifacol.2019.12.555.

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Coquil, Xavier, Pascal Béguin, and Benoît Dedieu. "Transition to self-sufficient mixed crop–dairy farming systems." Renewable Agriculture and Food Systems 29, no. 3 (December 16, 2013): 195–205. http://dx.doi.org/10.1017/s1742170513000458.

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AbstractWhile plains favorable to agriculture are still dominated by specialized and intensive agriculture, self-sufficient mixed crop-dairy farming systems increasingly attract policy makers' and scientists' attention. Owing to their limited use of purchased inputs, they can contribute to reducing the environmental impact of agriculture. Furthermore, self-sufficient farming tends to be linked with a search for autonomy in decision-making, i.e., farmers developing their own technical reference framework. Such farming systems can thus also contribute to alternative development pathways of rural territories. In this paper, we analyze how ten intensive mixed crop–dairy farms have progressively evolved toward more self-sufficient and autonomous systems. Through formalizing farmers' transitionin action, we identified 34 tools that the farmers implemented making them reflect on their farming system, shift socio-professional networks, reorganize work routines, and steer the evolution of their production practices. For example, they created temporary pastures in crop rotation, introduced rotational pastures, observed their herds to adjust their feed and keep the animals in good health, and they limited expenditures to manage their cash flow. Which tools were used and when they were used depends on what is meaningful to them at various stages of the transition. Our analysis of transitionsin actionhas three original features: it is centered on the transition as perceived by the actors who experience and manage it; it proposes a long-term conceptualization of the dynamics of farming systems, based on the farmer's initiative and creativity; and it highlights tools implemented by farmers during the transition to self-sufficiency and autonomy.
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Dissertations / Theses on the topic "Dairy farming systems"

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Soteriades, Andreas Diomedes. "Trade-offs in sustainable dairy farming systems." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/18753.

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A key challenge facing dairy farming is to meet the increasing demand for dairy products from a growing and more affluent global population in a period of unprecedented socio-economic and environmental change. In order to address this challenge, policies are currently placing emphasis on ‘sustainable intensification’ (SI), i.e. producing ‘more’ outputs and services with ‘less’ resources and environmental impacts. Determining whether or not SI can deliver greater yet sustainable dairy production requires understanding of the relationships between sustainability pillars (environmental; economic; and social) and farm aspects (e.g. on-farm management; and animal productivity) under particular farming systems and circumstances (e.g. regional bio-physical conditions). Trade-offs between pillars and aspects is inevitable within a farming system. Many widely-used assessment methods that aim to measure, scale and weight these pillars and aspects are unable to fully capture trade-offs between them. The objectives of this thesis are: 1) to identify key trade-offs in dairy farming systems to inform greater yet sustainable food production; and 2) to introduce models and methodologies aiming at a more holistic measurement and better understanding of dairy farm sustainability. This thesis assesses the sustainability of French and UK dairy farming systems via a farm efficiency benchmarking modelling framework coupled with statistical analyses. It explores the relationships between pillars, aspects and technical, economic and environmental performance; and identifies important drivers/differentials in dairy farm efficiency. Importantly, it also suggests ways in which farm inputs and outputs can be adjusted so that improvements in environmental, technical and economic performance become feasible. Efficiency benchmarking was performed with the multiple-input – multiple-output productive efficiency method Data Envelopment Analysis (DEA). DEA calculates single aggregated efficiency indices per farm by accounting for several farm inputs and outputs which the DEA model endogenously scales and weights. In this work, the notion of farm inputs and outputs was extended to also include ‘undesirable’ outputs (greenhouse gas emissions) and environmental impacts (e.g. eutrophication, acidification etc.) of dairy farming. The DEA models employed belong to the family of ‘additive’ models, which have several advantages over ‘traditional’ DEA models. These include their ability (i) to simultaneously increase outputs and reduce inputs, undesirable outputs and environmental impacts; (ii) to identify specific sources of inefficiency. These ‘sources’ represent a farm’s shortfalls in output production and its excesses in input use and/or in undesirable outputs and environmental impacts, relatively to the other farms; (iii) to position undesirable outputs in the output set rather than consider them as inputs or ‘inverse’ outputs; and (iv) to rank farms by efficiency performance. Importantly, this thesis also proposes a new additive model with a ranking property and high discriminatory power. In a second stage, DEA was coupled with partial least squares structural equation modelling (SEM) so as to develop and relate latent variables for environmental performance, animal productivity and on-farm management practices. The results suggested that the efficacy of SI may be compromised by several on-farm trade-offs between pillars, aspects and farm inputs and outputs. Moreover, trade-offs depended on particular farming systems and circumstances. Increasing animal productivity did not always improve farm environmental performance at whole farm-level. Intensifying production at animal and farm-levels, coupled with high reliance on external inputs, reduced farm environmental performance in the French case, i.e. a significant negative relationship was found between intensification and environmental performance (SEM path coefficients ranged between -0.31 and -0.57, p < 0.05). Conversely, in the UK case, systems representing animal-level intensification (via genetic selection) for increased milk fat plus protein production performed better, on average, than controls of UK average genetic merit for milk fat plus protein production in terms of technical efficiency (DEA scores between 0.91– 0.92 versus 0.78–0.79) and environmental efficiency (scores between 0.92–0.93 versus 0.80), regardless of whether on a low-forage or high-forage diet. The levels of inefficiency in (undesirable) outputs, inputs and environmental impacts varied among farming systems and depended on the regional and managerial characteristics of each system. For instance, in France, West farms had higher eutrophication inefficiencies than East farms (average normalized eutrophication inefficiencies were, respectively 0.141 and 0.107), perhaps because of their more intensive production practices. However, West farms were more DEA-efficient than East farms as the former benefited from bio-physical conditions more favourable to dairy farming (mean DEA score ranks were 97 for West and 83 for East). Such findings can guide policy incentives for SI in different regions or dairy systems. The proposed modelling framework significantly contributes to current knowledge and the search for the best pathways to SI, improves widely-used modelling approaches, and challenges earlier findings based on less holistic exercises.
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Boda, Gayatri. "Benchmarking dairy information using interactive visualization for dairy farm decision making." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=97910.

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The main goal of this research was to explore the use of benchmarking in the dairy industry. This includes descriptions of the various sectors in North America where benchmarking has been used successfully on a continuous basis or in research. Benchmarking methods that are currently used in the Quebec dairy industry are examined. An improvement to such methods is proposed through the use of visualization, coupled with interactivity, and with a focus on adaptability and usage. The advantages of such an interactive tool are discussed in light of on-farm decision-making, and a further use of visual slider applications is described to help with parameters of known economic importance.
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Akil, Juma Malik. "Small-scale dairy farming in Zanzibar : studies on systems and feeding of dairy cows." Thesis, University of Reading, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.433452.

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Ndambi, Oghaiki Asaah [Verfasser]. "Perspectives for dairy farming systems in Africa / Oghaiki Asaah Ndambi." Kiel : Universitätsbibliothek Kiel, 2009. http://d-nb.info/1019810998/34.

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Eastwood, Callum Ross. "Innovatoive precision dairry systems : a case study of farmer learning and technology co-development /." Connect to thesis, 2008. http://repository.unimelb.edu.au/10187/3530.

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Lampkin, Nicolas. "The economic implications of conversion from conventional to organic farming systems." Thesis, Aberystwyth University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339273.

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Bayemi, Pougue Henri Dieudonne. "Improving the management of dairy production systems in Cameroon." Thesis, Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-05252009-225140.

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Swai, Emmanuel Senyael. "Epidemiological studies of tickborne diseases in small scale dairy farming systems in Tanzania." Thesis, University of Reading, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.394023.

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Manzana, Nonzwakazi Patience. "Optimal feeding systems for small scale dairy herds in the North-West Province of South Africa." Diss., Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-04112008-154155/.

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Alqaisi, Othman [Verfasser]. "Nutritional, ecological, and economic evaluation of dairy farming systems and feeding strategies in semi-arid environments / Othman Alqaisi." Kiel : Universitätsbibliothek Kiel, 2013. http://d-nb.info/1036406253/34.

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Books on the topic "Dairy farming systems"

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Baltenweck, I. Dairy farming in Uganda: Production efficiency and soil nutrients under different farming systems. Nairobi, Kenya: International Livestock Research Institute, 2007.

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Baltenweck, I. Dairy farming in Uganda: Production efficiency and soil nutrients under different farming systems. Nairobi, Kenya: International Livestock Research Institute, 2007.

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Baltenweck, I. Dairy farming in Uganda: Production efficiency and soil nutrients under different farming systems. Nairobi, Kenya: International Livestock Research Institute, 2007.

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Preston, T. R. The development of milk production systems in the Tropics. Wageningen, Netherlands: Technical Centre for Agricultural and Rural Co-operation, 1989.

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Workshop on Integrated Small Holder Dairy Farming Systems in Peri-Urban Areas with Emphasis on Forages, and Fodder Tree Utilization (1999 Embu, Kenya). Proceedings of the Workshop on Integrated Small Holder Dairy Farming Systems in Peri-Urban Areas with Emphasis on Forages, and Fodder Tree Utilization: Embu, Kenya : 13-17 June, 1999. Edited by Karanja G. M, Sabiiti E. N, Uganda, Kenya Agricultural Research Institute, and Food and Agriculture Organization of the United Nations. [Kampala?: s.n., 2000.

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Issa, Mohamoud Mohamed. Evaluation of the milk production system of Benadir area : a report. Mogadishu: GTZ, 1986.

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Moran, John. Tropical Dairy Farming. CSIRO Publishing, 2005. http://dx.doi.org/10.1071/9780643093133.

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Tropical Dairy Farming is a manual designed for use by dairy production advisors working in tropical areas, especially in South-East Asia. It aims to increase the productivity of small holder dairy farmers in the humid tropics by improving the feeding management of their livestock. It shows how to provide dairy cows with cost-effective feeds that match small holder farming systems and discusses the major obstacles to improving feeding management in the humid tropics. The author shows the benefits and drawbacks of various feed components and the calculation of balanced diets based mainly on forages combined with some supplementary feeding. Diseases and problems associated with unbalanced diets are also covered, as well as important information on growing and conserving quality forages as silage. The book draws on examples from a variety of countries including Indonesia, Malaysia, Thailand, Vietnam, China, East Timor and the Philippines.
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Moran, John, and Philip Chamberlain. Blueprints for Tropical Dairy Farming. CSIRO Publishing, 2017. http://dx.doi.org/10.1071/9781486306473.

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Blueprints for Tropical Dairy Farming provides insight into the logistics, infrastructure and management required for the development of small and large dairy farms in tropical developing countries. Farmers will learn how to improve the welfare, milk quality and productivity of their dairy herds. This book complements author John Moran’s five previous books on the principles of tropical dairy farming. The manual covers a wide range of topics related to ensuring the sustainability of dairy production systems in tropical developing countries, such as South and East Asia, Africa and Central America. It also provides guidelines for the best management practices of large-scale, more intensive dairy systems. While smallholder farms are the major suppliers of milk in the tropics, many larger farms are becoming established throughout the tropics to satisfy the increasing demands for fresh milk. Blueprints for Tropical Dairy Farming will be a valuable resource for farmers and stockpeople who want to improve the productive performance of their dairy herds, farm advisers who can assist farmers to achieve this aim, educators who develop training programs for farmers or who train dairy advisers in the basics of dairy production technology, and other stakeholders in tropical dairy production, such as local agribusiness, policy makers and research scientists. National and international agencies will learn new insights into the required long-term logistics for regional dairy development, while potential investors will acquire knowledge into intensive tropical dairy farming.
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Betts, Carolyn Paula. An economic evaluation of alternative forage feeding systems for western Washington dairy herds. 1985.

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Hansen, Brandon Dean. An economic model for analyzing alternative dairy waste handling systems. 1993.

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Book chapters on the topic "Dairy farming systems"

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Steeneveld, W., and H. Hogeveen. "3.1. Use of sensor systems on Dutch dairy farms." In Precision livestock farming applications, 77–86. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_3.1.

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Steeneveld, W., and H. Hogeveen. "3.1. Use of sensor systems on Dutch dairy farms." In Precision livestock farming applications, 77–86. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_8.

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Brock, Caroline, and Bradford Barham. "Amish Dedication to Farming and Adoption of Organic Dairy Systems." In The International Library of Environmental, Agricultural and Food Ethics, 233–55. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9190-8_12.

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Coquil, Xavier, Jean-Louis Fiorelli, André Blouet, and Catherine Mignolet. "Experiencing Organic Mixed Crop Dairy Systems: A Step-by-Step Design Centred on a Long-term Experiment." In Organic Farming, Prototype for Sustainable Agricultures, 201–17. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7927-3_11.

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Orekhov, T. K., and O. V. Gradov. "Digital Spectrozonal and Multispectral Lens-Less Devices with Spectrophotometric Temperature Calibration GUIs for Dairy Farming and Qualimetry of Diary Products." In Informatics and Cybernetics in Intelligent Systems, 300–324. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77448-6_29.

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Salau, J., J. H. Haas, W. Junge, M. Leisen, and G. Thaller. "2.3. Development of a multi-Kinect-system for gait analysis and measuring body characteristics in dairy cows." In Precision livestock farming applications, 55–64. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_2.3.

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Salau, J., J. H. Haas, W. Junge, M. Leisen, and G. Thaller. "2.3. Development of a multi-Kinect-system for gait analysis and measuring body characteristics in dairy cows." In Precision livestock farming applications, 55–64. The Netherlands: Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_5.

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Ambriz-Vilchis, Virgilio, Julieta G. Estrada-Flores, Martha Hernández-Ortega, María A. Rojas-Garduño, Ernesto Sánchez-Vera, Angélica Espinoza-Ortega, and Octavio A. Castelán-Ortega. "Development of Feeding Strategies for Cows in Small Scale Dairy Farming Systems in the Highlands of Central Mexico by a Simulation Model and On-Farm Experiments. Phase I: Development of a Novel Framework." In Crop Modeling and Decision Support, 241–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01132-0_25.

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Ambriz-Vilchis, Virgilio, Julieta G. Estrada-Flores, Martha Hernández-Ortega, María de los Angeles Rojas-Garduño, and Octavio A. Castelán-Ortega. "Development of Feeding Strategies for Cows in Small Scale Dairy Farming Systems in the Highlands of Central Mexico by a Simulation Model and On-Farm Experiments. Phase II: On-farm Experiments and Validation of a Simulation Model." In Crop Modeling and Decision Support, 249–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01132-0_26.

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Kenny, Eoin M., Elodie Ruelle, Anne Geoghegan, Laurence Shalloo, Micheál O’Leary, Michael O’Donovan, and Mark T. Keane. "Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI)." In Case-Based Reasoning Research and Development, 172–87. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-29249-2_12.

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Conference papers on the topic "Dairy farming systems"

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Höhendinger, Martin, Natascha Schlereth, Maximilian Treiber, Manfred Höld, Jörn Stumpenhausen, and Heinz Bernhardt. "Potential of cyber-physical systems in German dairy farming." In 2019 Boston, Massachusetts July 7- July 10, 2019. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2019. http://dx.doi.org/10.13031/aim.201900221.

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Kenny, Eoin M., Elodie Ruelle, Anne Geoghegan, Laurence Shalloo, Micheál O'Leary, Michael O'Donovan, Mohammed Temraz, and Mark T. Keane. "Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract)." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/657.

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Smart agriculture (SmartAg) has emerged as a rich domain for AI-driven decision support systems (DSS); however, it is often challenged by user-adoption issues. This paper reports a case-based reasoning (CBR) system, PBI-CBR, that predicts grass growth for dairy farmers, that combines predictive accuracy and explanations to improve user adoption. PBI-CBR’s key novelty is its use of Bayesian methods for case-base maintenance in a regression domain. Experiments report the tradeoff between predictive accuracy and explanatory capability for different variants of PBI-CBR, and how updating Bayesian priors each year improves performance.
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Bovo, Marco, Stefano Benni, Alberto Barbaresi, Enrica Santolini, Miki Agrusti, Daniele Torreggiani, and Patrizia Tassinari. "A Smart Monitoring System for a Future Smarter Dairy Farming." In 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). IEEE, 2020. http://dx.doi.org/10.1109/metroagrifor50201.2020.9277547.

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Briukhanov, Alexander, Eduard Vasilev, Natalia Kozlova, and Ekaterina Shalavina. "Background for introduction of BAT system in intensive dairy farming in Russia." In 17th International Scientific Conference Engineering for Rural Development. Latvia University of Agriculture, 2018. http://dx.doi.org/10.22616/erdev2018.17.n302.

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Oberschätzl-Kopp, Rosemarie, Josef Bühler, Anja Gräff, Sascha Wörz, and Heinz Bernhardt. "<i>Studies on electrical energy consumption of an automatic feeding system in dairy cattle farming</i>." In 2018 Detroit, Michigan July 29 - August 1, 2018. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/aim.201800560.

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Reports on the topic "Dairy farming systems"

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de Vries, Marion. Vulnerability and adaptation strategies of dairy farming systems to extreme climate events in southwest Uganda : results of CSA-PRA workshops. Wageningen: Wageningen Livestock Research, 2019. http://dx.doi.org/10.18174/468558.

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