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Field and crop specific manure application on a dairy farm based on historical data and machine learning

Herman Mollenhorst, Michel H.A. de Haan, Jouke Oenema, Claudia Kamphuis
2020 Computers and Electronics in Agriculture  
Until now, the applied quantity of manure is regulated by law at farm level, based on fixed phosphorus (P) application norms.  ...  This study's objective, therefore, was to predict P yields based on detailed records of on-farm data as recorded on an experimental farm combined with open source weather data.  ...  comments on the results.  ... 
doi:10.1016/j.compag.2020.105599 fatcat:wzbuskioiffmbjsmalm5lb7d6m

Automating and Analyzing Whole-Farm Carbon Models

Aditi Maheshwari, Curtis Dyreson, Jennifer Reeve, Vishal Sharma, Anthony Whaley
2020 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)  
HOLOS estimates GHG emissions for a particular year based on crop and animal agriculture input, while COMET-farm adds past and future farm management practices.  ...  HOLOS estimates GHG emissions for a particular year based on crop and animal agriculture input, while COMET-farm adds past and future farm management practices.  ...  We automated these applications to collect data on GHG emissions of the farms based on crop and animal inputs. Second, we collected data from running the applications.  ... 
doi:10.1109/dsaa49011.2020.00057 dblp:conf/dsaa/MaheshwariDRSW20 fatcat:ops2uvc6tbdp7b77be7wsm2u5a

Big Data Analytics Recommendation Solutions for Crop Disease using Hive and Hadoop Platform

Raghu Garg, Himanshu Aggarwal
2016 Indian Journal of Science and Technology  
A single machine cannot store and analyze this large amount of data.  ...  Objective: With the digital advancements in the field of agriculture, a large amount of data is being produced constantly as a result agriculture data has entered the world of big data.  ...  Farmeron 26 Farmeron is a first cloud based dairy farm business software that uses the SaaS cloud services. Farmeron helps farmers to manage their farming data online.  ... 
doi:10.17485/ijst/2016/v9i32/100728 fatcat:iy6op2gntvbnll3mjzirf72uy4

WHOLE FARM MANAGEMENT TO REDUCE NUTRIENT LOSSES FROM DAIRY FARMS: A SIMULATION STUDY

C. A. Rotz, J. Oenema, H. van Keulen
2006 Applied Engineering in Agriculture  
Whole farm simulation provides a tool for evaluating the impact of nutrient conservation technologies and strategies on dairy farms.  ...  Technology such as a low nitrogen emission barn floor, a covered manure storage, manure injection, and the interseeding of grass on corn land to absorb excess nitrogen were used on this farm to reduce  ...  The farm was simulated using historical daily climate data collected at the site.  ... 
doi:10.13031/2013.21992 fatcat:oik3qwe76fcqxa6mded3gk3r4a

Machine Learning Applications for Precision Agriculture: A Comprehensive Review

Abhinav Sharma, Arpit Jain, Prateek Gupta, Vinay Chowdary
2020 IEEE Access  
In this article, authors present a systematic review of ML applications in the field of agriculture.  ...  The mechanism that drives this cutting edge technology is machine learning (ML). It gives the machine ability to learn without being explicitly programmed.  ...  MACHINE LEARNING APPLICATIONS IN PRECISION AGRICULTURE In many countries, the farmers rely on the traditional ways of farming which is based on the reliability of the suggestions from the elderly and their  ... 
doi:10.1109/access.2020.3048415 fatcat:7r4bjin7ang7bo3j4brv6kdxiu

Towards Climate Smart Farming—A Reference Architecture for Integrated Farming Systems

Georgios Kakamoukas, Panagiotis Sarigiannidis, Andreas Maropoulos, Thomas Lagkas, Konstantinos Zaralis, Chrysoula Karaiskou
2021 Telecom  
Climate change is emerging as a major threat to farming, food security and the livelihoods of millions of people across the world.  ...  Integrated agricultural systems constitute a promising solution, as they can lower reliance on external inputs, enhance nutrient cycling and increase natural resource use efficiency.  ...  Acknowledgments: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number 957406 (TERMINET).  ... 
doi:10.3390/telecom2010005 fatcat:grkfcklbtvbnncqyor5626g3a4

Putting agricultural equipment and digital technologies at the cutting edge of agroecology

Véronique Bellon Maurel, Christian Huyghe
2017 Oilseeds and fats, crops and lipids  
adaptation of the operations to the needs of the plant or the animal based on a monitoringdiagnosis-recommendation cycle) and by the development of specialized machinery helping the farmer to achieve "  ...  ), precision technologies for input application, robotics, specialized machines to manage soil cover and weeds, or for agroforestry.  ...  Based on these vast quantities of data, new knowledge models can be created.  ... 
doi:10.1051/ocl/2017028 fatcat:ecn3dvz35fg4fchoad3d5vyso4

Internet of Things and Machine Learning Applications for Smart Precision Agriculture [chapter]

R. Sivakumar, B. Prabadevi, G. Velvizhi, S. Muthuraja, S. Kathiravan, M. Biswajita, A. Madhumathi
2021 Ubiquitous Computing [Working Title]  
Besides, it elucidates the problems, specific potential solutions, and future directions for the agriculture sector using Machine Learning and the Internet of things.  ...  Application of remote sensors like temperature, humidity, soil moisture, water level sensors and pH value will provide an idea to on active farming, which will show accuracy as well as practical agriculture  ...  Machine learning in crop production Crop Production and management include crop selection, soil preparation based on suitability analysis, sowing seeds, application of manure & fertiliser, water management  ... 
doi:10.5772/intechopen.97679 fatcat:2stbj72a3bf67bgs72swxtglf4

Farming options for The Netherlands explored by multi-objective modelling

H.F.M. ten Berge, M.K. van Ittersum, W.A.H. Rossing, G.W.J. van de Ven, J. Schans
2000 European Journal of Agronomy  
It thus contributes to a transparent learning and development process needed to arrive at farm concepts acceptable to both entrepreneurs and society.  ...  Three case studies are presented to illustrate the method: dairy farming on sandy soils; highly intensified flower bulb industry in sensitive areas in the western Netherlands; and integrated arable farming  ...  Fallow was also included as an 'activity', as were other 'inter-crop activities' such as the application of organic manures and the cultivation of catch crops and green manures (Habekotté, 1994; Habekotté  ... 
doi:10.1016/s1161-0301(00)00078-2 fatcat:teygeelmh5bbfilf6ycod4oaau

Adoption of Web-Based Spatial Tools by Agricultural Producers: Conversations with Seven Northeastern Ontario Farmers Using the GeoVisage Decision Support System

Daniel Jarvis, Mark Wachowiak, Dan Walters, John Kovacs
2017 Agriculture  
Interviews were conducted onsite at five participating farms (three dairy, one cash crop, and one public access fruit/vegetable) in 2014-2016, and these conversations were transcribed and returned to participants  ...  This idea represents a fundament shift from developing decision support systems based on scientific evidence to one that also emphasizes social values and constructs.  ...  You will see lot of yellow fields, where farmers were impatient and went out and spread manure and compacted the soil with their machines . . .  ... 
doi:10.3390/agriculture7080069 fatcat:wtoykscyyjfv3lkidjlnz5nadq

A Low-Complexity Machine Learning Nitrate Loss Predictive Model – Towards Proactive Farm Management in a Networked Catchment

Huma Zia, Nick R. Harris, Geoff V. Merrett, Mark Rivers
2019 IEEE Access  
Existing discharge models use multiple parameters and large historical data which are difficult to extract and this, coupled with constraints on network nodes (battery life, computing power, and sensor  ...  Trained on only a 12-month training dataset derived from the published measured data, results for the model generated using an M5 decision tree, giving an R 2 of 0.92 and a relative root-mean-square error  ...  on a farm, requires simplified predictive models based on fewer, and ideally, real-time field information acquired autonomously and shared by the neighboring farms.  ... 
doi:10.1109/access.2019.2901218 fatcat:3ndhusk5zzh5pgvr7gb7ttzefy

Modelling of Livestock Systems to Enhance Efficiency

2019 Animal Frontiers  
, and nutrient fate in crop uptake and loss after application of manure?  ...  The model will be able to simulate a number of soil type and crop combinations, so the biophysical variability inherent to a dairy farm fields and crop rotations is well represented.  ...  It is a great opportunity to be update on the latest publications and other relevant information in the animal sector. We have more than 3500 members already!  ... 
doi:10.1093/af/vfz023 pmid:32055429 pmcid:PMC7009596 fatcat:54nbp4e2b5hn5k7mkix25p4vfe

Planning committee members

2005 Proceedings. IEEE SoutheastCon, 2005.  
Zizka, A. Brunelle and D. A. Angers for their help in various parts of the project. This project was partially funded by the Canada-Québec agreement on soil conservation.  ...  ACKNOWLEDGEMENTS This research is funded by the National Sciences and Engineering Research Council of Canada and Nova Scotia Department of Agriculture and Marketing. We wish to acknowledge Dr. N.E.  ...  Develop a farm plan/map to identify the fields that can most utilize manure applications.  ... 
doi:10.1109/secon.2005.1423201 fatcat:znbqvzikxng6zapfna6hh5vfwe

Report on Environmental, Economic and Social Performance of Current AEFS, and Comparison to Conventional Baseline

Jan Landert, Catherine Pfeifer, Johannes Carolus, Fabrizio Albanito, Adrian Müller, Lukas Baumgart, Johan Blockeel, Gerald Schwarz, Rainer Weisshaidinger, Ruth Bartel-Kratochvil, Alexander Hollaus, Andrea Hrabalová (+32 others)
2019 Zenodo  
The tools applied were COMPAS, an economic performance assessment tool, Cool Farm Tool, a greenhouse gas inventory tool, and SMART, a multidimensional sustainability tool.  ...  This deliverable presents the overall approach taken to assess the farms along the agro-ecological transition, describes the tools, and presents results from their application in the case studies.  ...  Indeed, the definition of product quality and its identification are linked to specific winemaking processes based on grapes that are defined as being site-specific for historical, cultural and shared  ... 
doi:10.5281/zenodo.3625680 fatcat:mswxfg2gqncqpke4k26gllhzmy

Abstracts of Selected Papers

2004 Agricultural and Resource Economics Review  
This evidence supports the proposition that vital information is lost upon aggregation, and farm-level data are required if one wishes to test farm-level theory.  ...  Aggregating farm-level data to the county level reveals significant and disturbing differences in coefficient estimates, including sign reversals.  ...  Recent advances in machine learning are used to provide a structural ordering on contemporaneous innovations on a vector autoregression model fit to monthly data on three u.s. soy-based markets: soybeans  ... 
doi:10.1017/s1068280500005864 fatcat:sfkvfs4chbhfhnpx6ligg6hw5m
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