Relevant bibliographies by topics / Precision farming

Contents

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

Academic literature on the topic 'Precision farming'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Precision farming"

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Bhatia, Kartikeya, and Devendra Duda. "Precision Farming." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 403–6. http://dx.doi.org/10.31142/ijtsrd22793.

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Kartikeya, Bhatia, and Duda Devendra. "Precision Farming." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 403–6. https://doi.org/10.31142/ijtsrd22793.

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precision mean "the quality of being clear or exact". Farmer tries hard to get the result but we need the smart way and result oriented. The history of India's development has been inexorably linked to that of its farmers, and the nation's growth with that of its agronomics. Agronomics provides highest contribution to nation income. Agronomics needed top most priority because the Government and the nation would both fail to succeed if agronomics could not be successful. Today we are living in 21st century where automation is playing significant role in human life. Automation
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Yasam, Mr Srinath, and Dr S. Anu H. Nair. "ecision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Precision Farming and Predictive Analytics in Agriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture Context Agriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture ContextAgriculture." International Journal of Engineering and Advanced Technology 9, no. 1s5 (2019): 74–80. http://dx.doi.org/10.35940/ijeat.a1023.1291s519.

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The scope of sensor networks and the Internet of Things spanning rapidly to diversified domains but not limited to sports, health, and business trading. In recent past, the sensors and MEMS integrated Internet of Things are playing crucial role in diversified farming strategies like dairy farming, animal farming, and agriculture farming. The usage of sensors and IoT technologies in farming are coined in contemporary literature as smart farming or precision farming. At its early stage of smart farming, the practices applying in agriculture farming are limited to collect the data related to the
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Norton, T., and D. Berckmans. "Developing precision livestock farming tools for precision dairy farming." Animal Frontiers 7, no. 1 (2017): 18–23. http://dx.doi.org/10.2527/af.2017.0104.

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Hamrita, Takoi K., Jeffrey S. Durrence, and George Vellidis. "Precision farming practices." IEEE Industry Applications Magazine 15, no. 2 (2009): 34–42. http://dx.doi.org/10.1109/mias.2009.931816.

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Tutkun, Muhittin. "PRECISION DAIRY FARMING." Journal of Agricultural, Food and Environmental Sciences 77, no. 1 (2023): 12–19. http://dx.doi.org/10.55302/jafes23771012t.

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Schmidt, Robin. "Precision Farming wächst." agrarzeitung 80, no. 19 (2025): 10. https://doi.org/10.51202/1869-9707-2025-19-010.

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Gnip, P., and K. Charvát. "Management of zones in precision farming." Agricultural Economics (Zemědělská ekonomika) 49, No. 9 (2012): 416–18. http://dx.doi.org/10.17221/5425-agricecon.

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Precision farming is a very fast developing form of the Farm Management System, especially in crop production, in whole world and in our country as well. There, it is adopted since the second half of the 90s of the 20th century. The system of data collection, analysis, presentation and application of information in precision farming is reaching over the possibilities of their use by common farmers or agricultural companies. Service companies in this case play a very important role as an executor of exacting analysis, data collection and their presentation. Management zones present simplificati
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Győrffy, Béla. "From Organic to Precision Farming (Contemporary Publication)." Acta Agraria Debreceniensis, no. 9 (December 10, 2002): 81–86. http://dx.doi.org/10.34101/actaagrar/9/3565.

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The paper presents a short review of the different types of farming systems:Biofarming, Organic farming, Alternatíve farming, Biodynamic farming, Low input sustainable agriculture (LISA)Mid-tech farming, Sustainable agriculture, Soil conservation farming, No till farming, Environmentally sound, Environmentally friendly, Diversity farmingCrop production system, Integrated pest management (IPM), Integrated farming, High-tech farmingSite specific production (SSP), Site specific technology (SST), Spatial variable technology, Satellite farming.Precision farmingIt concludes that the various systems
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Mandal, Manas, Bappa Paramanik, Anamay Sarkar, and Debasis Mahata. "PRECISION FARMING IN FLORICULTURE." International Journal of Research -GRANTHAALAYAH 9, no. 1 (2021): 75–77. http://dx.doi.org/10.29121/granthaalayah.v9.i1.2021.2871.

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Precision farming is a science base modern technology which provided management concept based on observation and response to intra-field variations. New technologies such as Global Positioning Systems (GPS), sensors, satellites or aerial images and Geographical Information Systems (GIS) are utilized to assess and analyse variations in agricultural and horticultural production. In this technology have two primary goals that are (i) optimum return (ii) preserving resource. Wireless Sensor Networks has crucial role to management of water resources, to assess the optimum point of harvesting, to es
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Dissertations / Theses on the topic "Precision farming"

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Rusch, Peter C. "Precision farming in South Africa." Diss., Pretoria : [s.n.], 2001. http://upetd.up.ac.za/thesis/available/etd-01072004-153302.

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Blackmore, Simon. "The role of yield maps in precision farming." Thesis, Cranfield University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269521.

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Shelley, Anthony N. "INCORPORATING MACHINE VISION IN PRECISION DAIRY FARMING TECHNOLOGIES." UKnowledge, 2016. http://uknowledge.uky.edu/ece_etds/86.

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The inclusion of precision dairy farming technologies in dairy operations is an area of increasing research and industry direction. Machine vision based systems are suitable for the dairy environment as they do not inhibit workflow, are capable of continuous operation, and can be fully automated. The research of this dissertation developed and tested 3 machine vision based precision dairy farming technologies tailored to the latest generation of RGB+D cameras. The first system focused on testing various imaging approaches for the potential use of machine vision for automated dairy cow feed int
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Waine, T. "Non-Invasive soil property measurement for precision farming." Thesis, Cranfield University, 1999. http://dspace.lib.cranfield.ac.uk/handle/1826/11322.

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This work investigates the application of new sensors to enable agronomists and farm managers to make decisions for variable treatment strategies at key crop growth stages. This is needed to improve the efficiency of crop production in the context of precision farming. Two non-invasive sensors were selected for investigation. These were: 1) The MGD-1 ion mobility gas detector made by Environics OY, Finland. 2) The EM38 electromagnetic induction (EMI) sensor made by Geonics Inc., Canada. The gas detector was used to determine residual nitrogen and to measure carbon dioxide gas as a surrogate in
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Waine, Toby William. "Non-invasive soil property measurement for precision farming." Thesis, Cranfield University, 1999. http://dspace.lib.cranfield.ac.uk/handle/1826/11322.

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This work investigates the application of new sensors to enable agronomists and farm managers to make decisions for variable treatment strategies at key crop growth stages. This is needed to improve the efficiency of crop production in the context of precision farming. Two non-invasive sensors were selected for investigation. These were: 1) The MGD-1 ion mobility gas detector made by Environics OY, Finland. 2) The EM38 electromagnetic induction (EMI) sensor made by Geonics Inc., Canada. The gas detector was used to determine residual nitrogen and to measure carbon dioxide gas as a surrogate in
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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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Yang, Chun-Chieh. "Development of a weed management system for precision farming." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0033/NQ64697.pdf.

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Yang, Chun-Chieh 1967. "Development of a weed management system for precision farming." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36735.

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The primary objective of this research project is to develop a system for precision spraying of herbicides in a corn field. Ultimately, such a system would permit real-time image collection, processing, weed identification, mapping of weed density and sprayer control using a tractor-mounted digital camera and on-board computer. The initial hypotheses underlying this project were (1) that it is possible to train an artificial neural network (ANN) to distinguish weeds from a crop species (corn in this study); (2) that it is possible to differentiate between weed species; and (3) that precision s
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Schneider, Martin [Verfasser]. "Ökonomische Potenziale von Precision Farming unter Risikoaspekten / Martin Schneider." Aachen : Shaker, 2011. http://d-nb.info/106904833X/34.

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Cillis, Donato. "Introducing innovative precision farming techniques in agriculture to decrease carbon emissions." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3425242.

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Nowadays, agricultural systems are asked to satisfy the increasing global demand for food and fiber for a growing population. The intensification of the current systems in term of inputs and outputs lead to raising the concerns about the impact on the environment. Considering the background found in literature and its highlighted gap, the hypothesis of this thesis are (1) to survey within-farm soil and yield variability in order to delineate the homogeneous zones and productive potential; (2) study the synergy between conservation agriculture and precision agriculture allowing the optimization
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Books on the topic "Precision farming"

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Emmert, Bonnie. Precision farming. National Agricultural Library, 1994.

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Emmert, Bonnie. Precision farming. National Agricultural Library, 1994.

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Emmert, Bonnie. Precision farming. National Agricultural Library, 1994.

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Cox, S., ed. Precision Livestock Farming. Wageningen Academic Publishers, 2003. http://dx.doi.org/10.3920/978-90-8686-515-4.

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Cox, S., ed. Precision Livestock Farming '05. Wageningen Academic Publishers, 2005. http://dx.doi.org/10.3920/978-90-8686-548-2.

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Cox, S., ed. Precision livestock farming '07. Wageningen Academic Publishers, 2007. http://dx.doi.org/10.3920/978-90-8686-604-5.

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Lokhorst, C., and P. W. G. Groot Koerkamp, eds. Precision livestock farming '09. Wageningen Academic Publishers, 2009. http://dx.doi.org/10.3920/978-90-8686-663-2.

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Halachmi, Ilan, ed. Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5.

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Banhazi, T., V. Halas, and F. Maroto-Molina, eds. Practical Precision Livestock Farming. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3.

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Addicott, James E. The Precision Farming Revolution. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-9686-1.

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Book chapters on the topic "Precision farming"

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Singh, Rajesh, Anita Gehlot, Mahesh Kumar Prajapat, and Bhupendra Singh. "Precision Farming." In Artificial Intelligence in Agriculture. CRC Press, 2021. http://dx.doi.org/10.1201/9781003245759-14.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Precision Water Management." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_8.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Precision Pest Management." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_9.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Introduction to Precision Agriculture." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_1.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Components of Precision Agriculture." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_2.

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Ozguven, Mehmet Metin. "Precision Livestock Farming." In The Digital Age in Agriculture. CRC Press, 2023. http://dx.doi.org/10.1201/b23229-2.

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Addicott, James E. "Farming futures." In The Precision Farming Revolution. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9686-1_6.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Recent Advances in Precision Agriculture." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_10.

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Ahmad, Latief, and Syed Sheraz Mahdi. "Precision Soil Sampling and Tillage." In Satellite Farming. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03448-1_4.

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Griffin, Terry W., Jordan M. Shockley, and Tyler B. Mark. "Economics of Precision Farming." In Precision Agriculture Basics. American Society of Agronomy and Soil Science Society of America, 2018. http://dx.doi.org/10.2134/precisionagbasics.2016.0098.

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Conference papers on the topic "Precision farming"

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Sharma, Prashant, Pratyaksh Kumar, Praveen Kumar Singh, and Arun Kumar Rana. "“Precision Agriculture Farming” Enhancing Farming Efficiency through Technology Integration." In 2024 1st International Conference on Advances in Computing, Communication and Networking (ICAC2N). IEEE, 2024. https://doi.org/10.1109/icac2n63387.2024.10895952.

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Libkovska, Una, Krista Rozenberga, and Baiba Rivza. "OPPORTUNITIES FOR INTRODUCING INNOVATIVE PRECISION FARMING METHODS IN ORGANIC FARMING IN LATVIA." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/5.1/s21.73.

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Modern agriculture, or precision agriculture, is a method that enables better, more efficient and smarter farming, ensuring sustainable development. Precision agriculture can combine data obtained from GPS systems with data from aerial photographs to precisely determine soil needs based on this data. Combining this with precise weather forecasts and location determination systems provides a powerful tool for more efficient agriculture. New technologies have already created a niche in agriculture. By combining detailed knowledge of the fields with automated systems, farm management becomes incr
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S, Bhaskar, Bharath Kumar K. R, Akkiraju Manaswini, and Gandluri Kiran Kumar. "Precision Farming Empowered by Embedded IOT." In 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2024. http://dx.doi.org/10.1109/ickecs61492.2024.10616829.

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Saradha, K. R., Balaji N, Dhineshkumar K. M, and Jaisankar K. "3D Rover Mapping for Precision Farming." In 2025 International Conference on Computing and Communication Technologies (ICCCT). IEEE, 2025. https://doi.org/10.1109/iccct63501.2025.11019988.

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Hiray, Srushti Kishor, Saiprasad Bharat More, Shantanu Gorakhanath Dhokale, Om Rushikesh Siddha, and Nitin L. Shelake. "Smart Irrigation System for Precision Farming." In 2025 7th International Conference on Intelligent Sustainable Systems (ICISS). IEEE, 2025. https://doi.org/10.1109/iciss63372.2025.11076297.

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Selvanathan, N., Keerthana A, Kunali M, and Sahana V. "Precision Agriculture: Advanced Solutions for Modern Farming." In 2024 International Conference on Sustainable Communication Networks and Application (ICSCNA). IEEE, 2024. https://doi.org/10.1109/icscna63714.2024.10863958.

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Shrene Shifna, N. Fathima, and K. Baalaji. "Precision Farming: Advanced Methods for Weed Identification." In 2024 3rd Edition of IEEE Delhi Section Flagship Conference (DELCON). IEEE, 2024. https://doi.org/10.1109/delcon64804.2024.10866880.

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Gopalakrishnan, S., M. J. Abinash, M. Sornalakshmi, S. Sunatha, N. Ramalakshmi, and M. John Bosco. "Cultivating Success using CNN-Powered Precision Farming." In 2024 8th International Conference on Electronics, Communication and Aerospace Technology (ICECA). IEEE, 2024. https://doi.org/10.1109/iceca63461.2024.10801039.

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Saraswathi, P., S. Anandhika, M. Hannah Nissi, M. Prabha, A. Poornima Srinithi, and B. Dhiyanesh. "Precision Farming: A Temperature and Humidity Monitoring Approach." In 2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN). IEEE, 2024. http://dx.doi.org/10.1109/icipcn63822.2024.00121.

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Sarjerao, Jagtap Sharad, G. Sudhagar, and Rahul Namdeo Jadhav. "Sustainable Smart Irrigation in Precision Farming using IoT." In 2025 International Conference on Emerging Smart Computing and Informatics (ESCI). IEEE, 2025. https://doi.org/10.1109/esci63694.2025.10987956.

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Reports on the topic "Precision farming"

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Staenz, K., J. C. Deguise, J. M. Chen, H. McNairn, T. Szeredi, and M. McGovern. The Use of Hyperspectral Data for Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1998. http://dx.doi.org/10.4095/219363.

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McNairn, H., J. C. Deguise, J. Secker, and J. Shang. Development of Remote Sensing Image Products for Use in Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219750.

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Pacheco, A., A. Bannari, J. C. Deguise, H. McNairn, and K. Staenz. Application of Hyperspectral Remote Sensing for LAI Estimation in Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219855.

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McNairn, H., J. C. Deguise, and A. Pacheco. Remote sensing derived products for precision farming: report on results from Clinton '99. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219916.

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McNairn, H., R. J. Brown, M. McGovern, T. Huffman, and J. Ellis. Integration of Multi-Polarized SAR Data and High Spatial Optical Imagery For Precision Farming. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2000. http://dx.doi.org/10.4095/219685.

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Research Institute (IFPRI), International Food Policy. Protected agriculture, precision agriculture, and vertical farming: Brief reviews of issues in the literature focusing on the developing region in Asia. International Food Policy Research Institute, 2019. http://dx.doi.org/10.2499/p15738coll2.133152.

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Tubb, Catherine, and Tony Seba. Rethinking Food and Agriculture 2020-2030: The Second Domestication of Plants and Animals, the Disruption of the Cow, and the Collapse of Industrial Livestock Farming. RethinkX, 2019. http://dx.doi.org/10.61322/ijip9096.

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By 2030, the number of cows in the U.S. will have fallen by 50% and the cattle farming industry will be all but bankrupt. All other livestock industries will suffer a similar fate, while the knock-on effects for crop farmers and businesses throughout the value chain will be severe. Rethinking Food and Agriculture shows how the modern food disruption, made possible by rapid advances in precision biology and an entirely new model of production we call Food-as-Software, will have profound implications not just for the industrial agriculture industry, but for the wider economy, society, and the en
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Latorre, Lucía, Valentín Muro, Leticia Riquelme, César Bustamante, and Gloria Lugo. Report on Low-Risk Technological Solutions in Emerging Technologies in Agriculture. Inter-American Development Bank, 2025. https://doi.org/10.18235/0013488.

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It provides a comprehensive overview of how these innovations are being employed to enhance efficiency and sustainability in agricultural practices, covering topics such as regenerative agriculture, precision agriculture, and agricultural technologies (AgTech). The report concludes with an analysis of the challenges and opportunities faced by farmers during the process of technology adoption. The document is structured around the different stages of the agricultural cycle: soil preparation, sowing operations, crop protection and management, smart harvesting, and digital harvest management. For
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Głąb, Tomasz, Jarosław Knaga, Tomasz Zaleski, Paweł Dziwisz, Jan Gluza, and Dariusz Glanas. Determination of soil particle size distribution using computer analysis of microscopic images. Publishing House of the University of Agriculture in Krakow, 2025. https://doi.org/10.15576/repourk/2025.1.3.

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The project aims to develop a prototype device for determining the texture of soils and mineral deposits. The innovation of the designed solution consists in a significant reduction in the time of composition analysis with the possibility of any division into granulometric groups and the complete automation of the measurement from the moment the sample is introduced into the apparatus until the result is obtained. As part of the project, industrial research and experimental development are planned to be divided into the following stages: 1. Development of the measuring system. 2. Development o
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Upadhyaya, Shrini K., Abraham Shaviv, Abraham Katzir, Itzhak Shmulevich, and David S. Slaughter. Development of A Real-Time, In-Situ Nitrate Sensor. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7586537.bard.

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Although nitrate fertilizers are critical for enhancing crop production, excess application of nitrate fertilizer can result in ground water contamination leading to the so called "nitrate problem". Health and environmental problems related to this "nitrate problem" have led to serious concerns in many parts of the world including the United States and Israel. These concerns have resulted in legislation limiting the amount of nitrate N in drinking water to 10mg/g. Development of a fast, reliable, nitrate sensor for in-situ application can be extremely useful in dynamic monitoring of environmen
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