Modelling of the effect of dry periods on yielding of spring barley
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Aggarwal, P. K., 1995. "Uncertainties in crop, soil and weather inputs used in growth models: Implications for simulated outputs and their applications," Agricultural Systems, Elsevier, vol. 48(3), pages 361-384.
- Kaul, Monisha & Hill, Robert L. & Walthall, Charles, 2005. "Artificial neural networks for corn and soybean yield prediction," Agricultural Systems, Elsevier, vol. 85(1), pages 1-18, July.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Mulka, Rafał & Szulczewski, Wiesław & Szlachta, Józef & Mulka, Mariusz, 2016. "Estimation of methane production for batch technology – A new approach," Renewable Energy, Elsevier, vol. 90(C), pages 440-449.
- Żyromski, Andrzej & Szulczewski, Wiesław & Biniak-Pieróg, Małgorzata & Jakubowski, Wojciech, 2016. "The estimation of basket willow (Salix viminalis) yield – New approach. Part I: Background and statistical description," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1118-1126.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Vlontzos, G. & Pardalos, P.M., 2017. "Assess and prognosticate green house gas emissions from agricultural production of EU countries, by implementing, DEA Window analysis and artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 155-162.
- Mooney, Sian & Antle, John M. & Capalbo, Susan Marie & Paustian, Keith H., 2003. "Incorporating Uncertainty In Integrated Assessment Modeling," 2003 Annual meeting, July 27-30, Montreal, Canada 22225, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Ji, Li-Qun, 2015. "An assessment of agricultural residue resources for liquid biofuel production in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 561-575.
- Confalonieri, Roberto & Acutis, Marco & Bellocchi, Gianni & Donatelli, Marcello, 2009. "Multi-metric evaluation of the models WARM, CropSyst, and WOFOST for rice," Ecological Modelling, Elsevier, vol. 220(11), pages 1395-1410.
- Wang, Zhiqiang & Ye, Li & Jiang, Jingyi & Fan, Yida & Zhang, Xiaoran, 2022. "Review of application of EPIC crop growth model," Ecological Modelling, Elsevier, vol. 467(C).
- Hao Hu & Yun Ren & Hongkui Zhou & Weidong Lou & Pengfei Hao & Baogang Lin & Guangzhi Zhang & Qing Gu & Shuijin Hua, 2024. "Oilseed Rape Yield Prediction from UAVs Using Vegetation Index and Machine Learning: A Case Study in East China," Agriculture, MDPI, vol. 14(8), pages 1-15, August.
- Hartkamp, A. D. & White, J. W. & Hoogenboom, G., 2003. "Comparison of three weather generators for crop modeling: a case study for subtropical environments," Agricultural Systems, Elsevier, vol. 76(2), pages 539-560, May.
- Bandaru, Varaprasad, 2022. "Climate data induced uncertainties in simulated carbon fluxes under corn and soybean systems," Agricultural Systems, Elsevier, vol. 196(C).
- Srinivasagan N. Subhashree & C. Igathinathane & Adnan Akyuz & Md. Borhan & John Hendrickson & David Archer & Mark Liebig & David Toledo & Kevin Sedivec & Scott Kronberg & Jonathan Halvorson, 2023. "Tools for Predicting Forage Growth in Rangelands and Economic Analyses—A Systematic Review," Agriculture, MDPI, vol. 13(2), pages 1-30, February.
- Jiménez, Daniel & Cock, James & Jarvis, Andy & Garcia, James & Satizábal, Héctor F. & Damme, Patrick Van & Pérez-Uribe, Andrés & Barreto-Sanz, Miguel A., 2011. "Interpretation of commercial production information: A case study of lulo (Solanum quitoense), an under-researched Andean fruit," Agricultural Systems, Elsevier, vol. 104(3), pages 258-270, March.
- Wu, Renye & Lawes, Roger & Oliver, Yvette & Fletcher, Andrew & Chen, Chao, 2019. "How well do we need to estimate plant-available water capacity to simulate water-limited yield potential?," Agricultural Water Management, Elsevier, vol. 212(C), pages 441-447.
- Xu, Chang & Katchova, Ani L., 2019.
"Predicting Soybean Yield with NDVI Using a Flexible Fourier Transform Model,"
Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 51(3), pages 402-416, August.
- Xu, Chang & Katchova, Ani, 2018. "Predicting Soybean Yield with NDVI using a Flexible Fourier Transform Model," 2018 Annual Meeting, February 2-6, 2018, Jacksonville, Florida 266693, Southern Agricultural Economics Association.
- Patryk Hara & Magdalena Piekutowska & Gniewko Niedbała, 2021. "Selection of Independent Variables for Crop Yield Prediction Using Artificial Neural Network Models with Remote Sensing Data," Land, MDPI, vol. 10(6), pages 1-21, June.
- García-Alonso, Carlos R. & Torres-Jiménez, Mercedes & Hervás-Martínez, César, 2010. "Income prediction in the agrarian sector using product unit neural networks," European Journal of Operational Research, Elsevier, vol. 204(2), pages 355-365, July.
- Pourmohammadali, Behrooz & Hosseinifard, Seyed Javad & Hassan Salehi, Mohammad & Shirani, Hossein & Esfandiarpour Boroujeni, Isa, 2019. "Effects of soil properties, water quality and management practices on pistachio yield in Rafsanjan region, southeast of Iran," Agricultural Water Management, Elsevier, vol. 213(C), pages 894-902.
- Rivington, M. & Matthews, K.B. & Bellocchi, G. & Buchan, K., 2006. "Evaluating uncertainty introduced to process-based simulation model estimates by alternative sources of meteorological data," Agricultural Systems, Elsevier, vol. 88(2-3), pages 451-471, June.
- Daniel Wallach & Linda O. Mearns & Alex C. Ruane & Reimund P. Rötter & Senthold Asseng, 2016. "Lessons from climate modeling on the design and use of ensembles for crop modeling," Climatic Change, Springer, vol. 139(3), pages 551-564, December.
- Kelvin López-Aguilar & Adalberto Benavides-Mendoza & Susana González-Morales & Antonio Juárez-Maldonado & Pamela Chiñas-Sánchez & Alvaro Morelos-Moreno, 2020. "Artificial Neural Network Modeling of Greenhouse Tomato Yield and Aerial Dry Matter," Agriculture, MDPI, vol. 10(4), pages 1-14, April.
- Jules F. Cacho & Jeremy Feinstein & Colleen R. Zumpf & Yuki Hamada & Daniel J. Lee & Nictor L. Namoi & DoKyoung Lee & Nicholas N. Boersma & Emily A. Heaton & John J. Quinn & Cristina Negri, 2023. "Predicting Biomass Yields of Advanced Switchgrass Cultivars for Bioenergy and Ecosystem Services Using Machine Learning," Energies, MDPI, vol. 16(10), pages 1-16, May.
- Bazrafshan, Ommolbanin & Ehteram, Mohammad & Moshizi, Zahra Gerkaninezhad & Jamshidi, Sajad, 2022. "Evaluation and uncertainty assessment of wheat yield prediction by multilayer perceptron model with bayesian and copula bayesian approaches," Agricultural Water Management, Elsevier, vol. 273(C).
More about this item
Keywords
Dry periods Vegetation period Weather-yield model;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:97:y:2010:i:5:p:587-595. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.