Relevant bibliographies by topics / Crop modeling

Contents

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

Academic literature on the topic 'Crop modeling'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Crop modeling"

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Sirotenko, Oleg D. "Crop Modeling." Agronomy Journal 93, no. 3 (2001): 650–53. http://dx.doi.org/10.2134/agronj2001.933650ax.

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Sirotenko, Oleg D. "Crop Modeling." Agronomy Journal 93, no. 3 (2001): 650—a. http://dx.doi.org/10.2134/agronj2001.933650-ax.

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Poluektov, Ratmir A., and Alexandre G. Topaj. "Crop Modeling." Agronomy Journal 93, no. 3 (2001): 653–59. http://dx.doi.org/10.2134/agronj2001.933653x.

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Craufurd, Peter Q., Vincent Vadez, S. V. Krishna Jagadish, P. V. Vara Prasad, and M. Zaman-Allah. "Crop science experiments designed to inform crop modeling." Agricultural and Forest Meteorology 170 (March 2013): 8–18. http://dx.doi.org/10.1016/j.agrformet.2011.09.003.

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HAGIWARA, Kensuke, Naota HANASAKI, and Shinjiro KANAE. "MODELING WORLD BIOENERGY CROP POTENTIAL." Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) 67, no. 4 (2011): I_265—I_270. http://dx.doi.org/10.2208/jscejhe.67.i_265.

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Anderson, Ray, and Andrew French. "Crop Evapotranspiration." Agronomy 9, no. 10 (2019): 614. http://dx.doi.org/10.3390/agronomy9100614.

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Evapotranspiration (ET) is one of the largest components of the water cycle, and accurately measuring and modeling ET is critical for improving and optimizing agricultural water management. However, parameterizing ET in croplands can be challenging due to the wide variety of irrigation strategies and techniques, crop varieties, and management approaches that employ traditional tabular ET and make crop coefficient approaches obsolete. This special issue of Agronomy highlights nine approaches to improve the measurement and modeling of ET across a range of spatial and temporal resolutions and dif
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Phuoc, Le Huu, Irfan Suliansyah, Feri Arlius, Irawati Chaniago, Nguyen Thi Thanh Xuan, and Pham Van Quang. "Literature Review Crop Modeling and Introduction a Simple Crop Model." Journal of Applied Agricultural Science and Technology 7, no. 3 (2023): 197–216. http://dx.doi.org/10.55043/jaast.v7i3.123.

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Modeling science has been applied by many advanced countries in many fields, such as geology, meteorology, climate change, crop productivity, environment, erosion, and landslide. The crop model simulates the processes of agriculture. The writing of this article is descriptive qualitative using the Systematic Literature Review (SLR) method. So far, each model has its advantages and disadvantages but generally is based on the physiology of the growth and development of crops in relationship with soil, climate, solar radiation energy, and limiting factors to plant growth. There have been many mod
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Boote, K. J., and N. B. Pickering. "Modeling Photosynthesis of Row Crop Canopies." HortScience 29, no. 12 (1994): 1423–34. http://dx.doi.org/10.21273/hortsci.29.12.1423.

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Scholze, Marko, Alberte Bondeau, Frank Ewert, Chris Kucharik, Jörg Priess, and Pascalle Smith. "Advances in large-scale crop modeling." Eos, Transactions American Geophysical Union 86, no. 26 (2005): 245. http://dx.doi.org/10.1029/2005eo260002.

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Sinclair, Thomas R., and No'am G. Seligman. "Crop Modeling: From Infancy to Maturity." Agronomy Journal 88, no. 5 (1996): 698–704. http://dx.doi.org/10.2134/agronj1996.00021962008800050004x.

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Dissertations / Theses on the topic "Crop modeling"

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Perkins, Seth A. "Crop model review and sweet sorghum crop model parameter development." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/14037.

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Master of Science<br>Department of Biological and Agricultural Engineering<br>Kyle Douglas-Mankin<br>Opportunities for alternative biofuel feedstocks are widespread for a number of reasons: increased environmental and economic concerns over corn production and processing, limitations in the use of corn-based ethanol to 57 billion L (15 billion gal) by the Energy Independence and Security Act (US Congress, 2007), and target requirements of 136 billion L (36 billion gal) of renewable fuel production by 2022. The objective of this study was to select the most promising among currently available
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Bracho, Belkys Yasmin. "Application of statistical techniques to modeling crop growth." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0010109.

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Chowdhury, Nazea H. Khan. "Crop Acreage Response Modeling in North Dakota and Greater Midwest." Diss., North Dakota State University, 2017. https://hdl.handle.net/10365/26711.

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Our research consists of two papers. First paper focus on the trend of North Dakota (ND) crop acreage changes and include economic factors (expected prices of crops, input price, crop yield, revenue of crops) and climate factors (precipitation, minimum and maximum temperature, growing degree days, and palmer drought severity index). We are using Geographic Information System (GIS) database for cropland areas throughout ND for the years 1998 through 2013. But we are using five crops for our analysis. We use Seemingly Unrelated Tobit Left Censored Regression and Monte Carlo Simulation techniques
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Gornott, Christoph. "Improving crop modeling approaches for supporting farmers to cope with weather risks." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19266.

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Sich ändernde Klima- und Wetterbedingungen in Verbindung mit einer begrenzt ausdehnbaren Ackerfläche werden den Druck auf Nahrungsmittelproduktionssysteme weiter erhöhen. Um dieser Herausforderung gerecht zu werden, ist eine Erhöhung und Stabilisierung der Ernteerträge unverzichtbar. Dies erfordert aber ein tieferes Verständnis der Einflussfaktoren, die auf die Ertragsvariabilität wirken. Diese Dissertation leistet einen Forschungsbeitrag zu Ertragsmodellen in Deutschland, Tansania und auf globaler Ebene. Dazu analysiere und kombiniere ich statistische und prozessbasierte Ertragsmodelle in fün
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Martin, Benjamin A. "TWO ESSAYS ON WHOLE FARM MODELING AND CROP MARKETING IN WESTERN KENTUCKY." UKnowledge, 2018. https://uknowledge.uky.edu/agecon_etds/65.

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This thesis is composed of two essays that investigate whole farm planning and crop marketing in western Kentucky. In the first essay, contracting decisions between food corn producers and a mill are analyzed to observe factors affecting the bushel amount farmers contract. Unbalanced panel data containing seven years’ worth of pricing and contract information are used with a fixed-effects model to generate parameter estimates and quantify their effect on bushels contracted. It was found that contract attributes, market condition, and relationship-specific assets had a significant effect on pro
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Napier, Christopher Cameron. "Crop Yield using Novel Parametric L-system plant modelling." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2024. https://ro.ecu.edu.au/theses/2907.

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This research considers a system for the recognition of real plant parts through image analysis based upon synthetic plant modelling. It aims to use data pipelines and synthetic datasets to define recognizable features that assist in the efficient analysis of real plants and plant images. This research asks about the efficacy of L-systems in accurately simulating wheat crop characteristics. It specifically focusses on readable, understandable, accurate, and complex L-system algorithms. The research examines wheat crops in terms of phenotypes and examines the accuracy of a dataset in support of
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CAMPOS, TARANGO ISIDRO AUDBERTO. "SPATIAL MODELING OF RED SPIDER MITE Oligonychus punica (ACARI: TETRANYCIDAE) IN AVOCADO CROP." Tesis de Licenciatura, UNIVERSIDAD AUTONOMA DEL ESTADO DE MÉXICO, 2021. http://hdl.handle.net/20.500.11799/111285.

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Este artículo fue utilizado para la titulación de Licenciatura. Se Estudio y estableció la distribución espacial del ácaro araña roja en el cultivo de aguacate. Se logró establecer que la distribución es agregada y que la superficie infestada por la plaga no alcanza el 100%. Se lograron realizar mapas de densidad y distribución del ácaro los cuales servirán para dirigir las medidas de control sobre áreas específicas de infestación, con los consecuentes ahorros económicos y el menor impacto ambiente de la región. Con los resultados obtenidos es posible elaborar un Programa de Manejo Integrado
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Abreu, Daniel Carneiro de. "Whole-farm modeling approach to evaluate different crop rotations in organic dairy systems." Universidade Federal de Viçosa, 2014. http://www.locus.ufv.br/handle/123456789/6596.

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Submitted by Marco Antônio de Ramos Chagas (mchagas@ufv.br) on 2015-11-09T15:34:52Z No. of bitstreams: 1 texto completo.pdf: 492609 bytes, checksum: 66747ed601f7421b79e4e7f037a223b9 (MD5)<br>Made available in DSpace on 2015-11-09T15:34:52Z (GMT). No. of bitstreams: 1 texto completo.pdf: 492609 bytes, checksum: 66747ed601f7421b79e4e7f037a223b9 (MD5) Previous issue date: 2014-09-25<br>Fundação de Amparo à Pesquisa do Estado de Minas Gerais<br>O mercado de trigo (Triticum aestivum L.) orgânico para produção de pão cresceu em grande magnitude na região da Nova Inglaterra, nos Estados Unidos.
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Wagner, Nicole Catherine. "Wheat yield prediction modeling for localized optimization of fertilizer and herbicide application." Diss., Montana State University, 2004. http://etd.lib.montana.edu/etd/2004/wagner/WagnerN0805.pdf.

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Caiado, Marco Aurelio. "Modeling Fate and Transport of Nitrogen and Phosphorus in Crop Fields Under Tropical Conditions." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28848.

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Modeling is a very important tool for developing nonpoint source (NPS) pollution control plans. Current NPS models were developed for temperate conditions and, thus, do not appropriately represent tropical conditions. The objective of this research was to develop or adapt a nonpoint source pollution model to simulate transformations and losses of nitrogen (N) and phosphorus (P) in leachate and runoff from crop fields under humid tropical conditions. An extensive literature synthesis identified appropriate relationships for representing hydrologic and NPS processes in the tropics, as well as
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Books on the topic "Crop modeling"

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Cao, Weixing, Jeffrey W. White, and Enli Wang, eds. Crop Modeling and Decision Support. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01132-0.

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Cao, Weixing. Crop Modeling and Decision Support. Springer-Verlag Berlin Heidelberg, 2009.

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Soltani, Afshin. Modeling physiology of crop development, growth and yield. CABI, 2012.

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Boote, K. J., and R. S. Loomis, eds. Modeling Crop Photosynthesis-from Biochemistry to Canopy. Crop Science Society of America and American Society of Agronomy, 1991. http://dx.doi.org/10.2135/cssaspecpub19.

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Rodríguez, Francisco, Manuel Berenguel, José Luis Guzmán, and Armando Ramírez-Arias. Modeling and Control of Greenhouse Crop Growth. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-11134-6.

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Wei, Wei, and C. Neal Stewart Jr., eds. Gene flow: monitoring, modeling and mitigation. CABI, 2021. http://dx.doi.org/10.1079/9781789247480.0000.

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Abstract Over two decades later, gene flow research as it pertains to genetically engineered crops is still going strong, even in the face of the absence of ecological disasters in the nearly 30 years of widescale biotech crop commercialization. Nonetheless, ecological timeframes are within the study scope of the sort of research performed to date covered in this book. These studies have greatly informed regulations that govern biotech crops. The chapters in this book capture various aspects of scientific disciplines that span from organismal studies, to population and community ecology, to mo
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Soltani, A., and T. R. Sinclair, eds. Modeling physiology of crop development, growth and yield. CABI, 2012. http://dx.doi.org/10.1079/9781845939700.0000.

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G, Moore Donald, and Geological Survey (U.S.), eds. Predictive spatial modeling of narcotic crop growth patterns. U.S. Dept. of the Interior, U.S. Geological Survey, 1986.

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G, Moore Donald, and Geological Survey (U.S.), eds. Predictive spatial modeling of narcotic crop growth patterns. U.S. Dept. of the Interior, U.S. Geological Survey, 1986.

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Crouse, Chadd. Evaluation of the use of spatial modeling to improve county yield estimation. U.S. Dept. of Agriculture, National Agricultural Statistics Service, Research Division, 2000.

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Book chapters on the topic "Crop modeling"

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Tariq, Muhammad, Mukhtar Ahmed, Pakeeza Iqbal, Zartash Fatima, and Shakeel Ahmad. "Crop Phenotyping." In Systems Modeling. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4728-7_2.

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Forrester, Richard J. "Crop Rotation Modeling." In Encyclopedia of Optimization. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-54621-2_835-1.

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Bhatia, Avnish Kumar. "Crop Growth Simulation Modeling." In Simulation Foundations, Methods and Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05657-9_15.

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White, J. W. "Modeling and crop improvement." In Understanding Options for Agricultural Production. Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-017-3624-4_9.

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Kheir, Ahmed Mohammed Saad, Zheli Ding, Marwa Gamal Mohamed Ali, Til Feike, Aly Ismail Nagib Abdelaal, and Abdelrazek Elnashar. "Wheat Crop Modelling for Higher Production." In Systems Modeling. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4728-7_6.

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Panda, S. S. "Geospatial Modeling Applications for Biofuel Sustainability Assessment." In Biofuel Crop Sustainability. John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118635797.ch14.

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Wei, Wei, Jun-Ming Wang, Xiang-Cheng Mi, Yan-Da Li, and Yan-Ming Zhu. "Modeling gene flow from genetically modified plants." In Gene flow: monitoring, modeling and mitigation. CABI, 2021. http://dx.doi.org/10.1079/9781789247480.0007.

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Abstract Gene flow from genetically modified (GM) plants is concerning because of its ecological risks. In modeling studies, these risks may be reduced by altering crop management while taking environmental conditions into account. Gene flow modeling should consider many field aspects, both biological and physical. For example, empirical statistical models deduced from experimental data simulate gene flow well only under limited conditions (similar to experimental conditions). Mechanistic models, however, offer a potentially greater predictive ability. Gene flow models from GM crops to non-GM
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John S. Cundiff and Kyle R. Mankin. "Chapter 6: Crop Growth Modeling." In Dynamics of Biological Systems. American Society of Agricultural and Biological Engineers, 2003. http://dx.doi.org/10.13031/2013.34921.

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Butt, Abdullah Ahmed, and Zahra Ahmed. "Crop Modeling Under Climate Change." In Climate Smart Agriculture for Future Food Security. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-4499-5_5.

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Lu, Bao-Rong. "Assessing environmental impact of pollen-mediated transgene flow." In Gene flow: monitoring, modeling and mitigation. CABI, 2021. http://dx.doi.org/10.1079/9781789247480.0001.

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Abstract Potential environmental impact caused by pollen-mediated transgene flow from commercially cultivated genetically engineered (GE) crops to their non-GE crop counterparts and to their wild and weedy relatives has aroused tremendous biosafety concerns worldwide. This chapter provides information on the concept and classification of gene flow, the framework of the environmental biosafety assessment caused by pollen-mediated gene flow, and relevant case studies about transgene flow and its environmental impact. In general, gene flow refers to the movement of genes or genetic materials from
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Conference papers on the topic "Crop modeling"

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Khadse, Shrikant, Prateek Verma, and Athrava Milmile. "A Review of Machine Learning Techniques for Predictive Crop Yield Modeling." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968404.

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Mandge, Omprakash, and Suhasini Vijaykumar. "Intelligent Crop Yield Modeling Using Attention Networks and Dynamic Ensemble Learning." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10968285.

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Vincent, Olufunke Rebecca, Peter Oluwaseun David, Daniel Dauda Wisdom, Gboyega Festus Akinboro, Paul Adebambo, and Cecelia Ajowoh Adenusi. "Leveraging Soil Nutrient Patterns for Improved Crop Yield Through Random Forest Modeling." In 2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON). IEEE, 2024. https://doi.org/10.1109/nigercon62786.2024.10927153.

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Mahapatra, Rishit, and Deepak Sethi. "Predictive Modeling for Crop Recommendation Using Machine Learning Techniques for Agricultural Optimization." In 2024 International Conference on Computing, Sciences and Communications (ICCSC). IEEE, 2024. https://doi.org/10.1109/iccsc62048.2024.10830449.

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Singla, Aditya, Ankit Chaudhary, and Krishnan Rajkumar. "AI-based Geo-Spatial Data Modeling of Agriculture for Crop Yield Estimation." In 2024 International Conference on Advanced Technologies for Communications (ATC). IEEE, 2024. https://doi.org/10.1109/atc63255.2024.10908302.

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Poleshchenko, Dmitrij, Vladislav Petrov, and Ilia Mikhailov. "Modernization of the Automated Control Approach for Crop Development Indicators Using UAV Photography." In 2024 6th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2024. https://doi.org/10.1109/summa64428.2024.10803843.

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Wang, Jingwen, Jose Luis Pancorbo, Miguel Quemada, Shanxin Guo, Longlong Zhao, and Jinsong Chen. "Monitoring and Representing Field Management Practices with Satellite Remote Sensing in Crop Modeling." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10641707.

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Golub, E., Zaid Ali Hussein Al-Sudani, and Haidar Abdulwahhab H. Shamsuldin. "USING DRONES AND AI FOR SOIL SAMPLING AND ANALYSIS: ENHANCING CROP ROTATION EFFICIENCY IN AGRICULTURAL FIELDS." In CHALLENGING ISSUES IN SYSTEMS MODELING AND PROCESSES. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2025. https://doi.org/10.58168/cismp2024_300-302.

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The article discusses an approach to agricultural field management using drones to collect soil samples and then analyze the data using AI. The system, based on soil analysis, will allow predicting suitable crops for planting in specific years. Examples of the application of this technology are given and its advantages for increasing crop yields and sustainability of agricultural production are dis-cussed.
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Wang, Yunmei, Yuhan Yu, Junxi Chen, Changyue Wu, Weiwei Jiang, and Xin Gao. "Analysis of Crop Planting Strategies." In CMSDA 2024: 2024 4th International Conference on Computational Modeling, Simulation and Data Analysis. ACM, 2024. https://doi.org/10.1145/3727993.3728095.

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Popovych, V. F. "Features of scenario modeling of crop development." In CURRENT STATE, PROBLEMS AND PROSPECTS OF THE DEVELOPMENT OF AGRARIAN SCIENCE. Federal State Budget Scientific Institution “Research Institute of Agriculture of Crimea”, 2019. http://dx.doi.org/10.33952/09.09.2019.166.

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Reports on the topic "Crop modeling"

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Kumar, Anjani, Jaweriah Hazrana, Digvijay S. Negi, Pratap S. Birthal, and Gaurav Tripathi. Understanding the geographic pattern of diffusion of modern crop varieties in India: A multilevel modeling approach. International Food Policy Research Institute, 2020. http://dx.doi.org/10.2499/p15738coll2.133672.

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Heitman, Joshua L., Alon Ben-Gal, Thomas J. Sauer, Nurit Agam, and John Havlin. Separating Components of Evapotranspiration to Improve Efficiency in Vineyard Water Management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7594386.bard.

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Vineyards are found on six of seven continents, producing a crop of high economic value with much historic and cultural significance. Because of the wide range of conditions under which grapes are grown, management approaches are highly varied and must be adapted to local climatic constraints. Research has been conducted in the traditionally prominent grape growing regions of Europe, Australia, and the western USA, but far less information is available to guide production under more extreme growing conditions. The overarching goal of this project was to improve understanding of vineyard water
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Lieth, J. Heiner, Michael Raviv, and David W. Burger. Effects of root zone temperature, oxygen concentration, and moisture content on actual vs. potential growth of greenhouse crops. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7586547.bard.

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Soilless crop production in protected cultivation requires optimization of many environmental and plant variables. Variables of the root zone (rhizosphere) have always been difficult to characterize but have been studied extensively. In soilless production the opportunity exists to optimize these variables in relation to crop production. The project objectives were to model the relationship between biomass production and the rhizosphere variables: temperature, dissolved oxygen concentration and water availability by characterizing potential growth and how this translates to actual growth. As p
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Dudley, Lynn M., Uri Shani, and Moshe Shenker. Modeling Plant Response to Deficit Irrigation with Saline Water: Separating the Effects of Water and Salt Stress in the Root Uptake Function. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7586468.bard.

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Standard salinity management theory, derived from blending thermodynamic and semi- empirical considerations leads to an erroneous perception regarding compensative interaction among salinity stress factors. The current approach treats matric and osmotic components of soil water potential separately and then combines their effects to compute overall response. With deficit water a severe yield decrease is expected under high salinity, yet little or no reduction is predicted for excess irrigation, irrespective of salinity level. Similarly, considerations of competition between chloride and nitrat
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Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transp
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Taheripour, Farzad, Thomas Hertel, and Jing Liu. Introducing water by river basin into the GTAP-BIO model: GTAP-BIO-W. GTAP Working Paper, 2013. http://dx.doi.org/10.21642/gtap.wp77.

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This paper introduces water into the GTAP modeling framework at a river basin level. The new model: 1) distinguishes between irrigated and rainfed agriculture using different production functions; 2) takes into account heterogeneity in land quality across agro-ecological zones; 3) traces supply of water at the river basin level within each country/region; 4) fully captures competition for land among crop, livestock and forestry industries; 5) and, most importantly, offers the potential to extend the competition for managed water among agricultural and non-agricultural activities. Individuals i
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Banerjee, Onil, Martin Cicowiez, Ana Rios, and Cicero De Lima. Climate Change Impacts on Agriculture in Latin America and the Caribbean: An Application of the Integrated Economic-Environmental Modeling (IEEM) Platform. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003794.

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In this paper, we assess the economy-wide impact of Climate Change (CC) on agriculture and food security in 20 Latin American and the Caribbean (LAC) countries. Specifically, we focus on the following three channels through which CC may affect agricultural and non-agricultural production: (i) agricultural yields; (ii) labor productivity in agriculture, and; (iii) economy-wide labor productivity. We implement the analysis using the Integrated Economic-Environmental Model (IEEM) and databases for 20 LAC available through the OPEN IEEM Platform. Our analysis identifies those countries most affect
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Seginer, Ido, Daniel H. Willits, Michael Raviv, and Mary M. Peet. Transpirational Cooling of Greenhouse Crops. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7573072.bard.

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Background Transplanting vegetable seedlings to final spacing in the greenhouse is common practice. At the time of transplanting, the transpiring leaf area is a small fraction of the ground area and its cooling effect is rather limited. A preliminary modeling study suggested that if water supply from root to canopy is not limiting, a sparse crop could maintain about the same canopy temperature as a mature crop, at the expense of a considerably higher transpiration flux per leaf (and root) area. The objectives of this project were (1) to test the predictions of the model, (2) to select suitable
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Hermelink, M. I., and J. G. Conijn. Modelling crop yields and water balances for Ethiopia with LPJmL. Stichting Wageningen Research, Wageningen Plant Research, Business Unit Agrosystems Research, 2021. http://dx.doi.org/10.18174/559929.

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Hermelink, M. I., J. G. Conijn, and R. Dankers. Modelling future crop yields and water discharge for Ethiopia with LPJmL. Wageningen Plant Research, 2022. http://dx.doi.org/10.18174/581423.

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