Weather-based maize yield forecast in Saudi Arabia using statistical analysis and machine learning-Reference-Cited by-同舟云学术

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Weather-based maize yield forecast in Saudi Arabia using statistical analysis and machine learning

Published:2022-07-28 Issue:6 Volume:70 Page:2901-2916
ISSN:1895-7455
Container-title:Acta Geophysica
language:en
Short-container-title:Acta Geophys.

Author:

Jayagopal Prabhu,Muthukumaran Venkatesan,Koti Manjula Sanjay,Kumar Sampath Satheesh,Rajendran Sukumar,Mathivanan Sandeep Kumar

Publisher

Springer Science and Business Media LLC

Subject

Geophysics

Link

https://link.springer.com/content/pdf/10.1007/s11600-022-00854-z.pdf

Reference34 articles.

1. Adisa OM, Botai JO, Adeola AM, Hassen A, Botai CM, Darkey D, Tesfamariam E (2019) Application of artificial neural network for predicting maize production in South Africa. Sustainability 11(4):1145

2. Almazroui M, Nazrul Islam M, Athar H, Jones PD, Rahman MA (2012) Recent climate change in the Arabian Peninsula: annual rainfall and temperature analysis of Saudi Arabia for 1978–2009. Int J Climatol 32(6):953–966

3. Andorf C, Beavis WD, Hufford M, Smith S, Suza WP, Wang K, Lübberstedt T et al (2019) Technological advances in maize breeding: past, present and future. Theor Appl Genet 132(3):817–849

4. Archontoulis SV, Castellano MJ, Licht MA, Nichols V, Baum M, Huber I, Lamkey KR et al (2020) Predicting crop yields and soil-plant nitrogen dynamics in the US Corn Belt. Crop Sci 60(2):721–738

5. Balkovič J, van der Velde M, Schmid E, Skalský R, Khabarov N, Obersteiner M, Xiong W et al (2013) Pan-European crop modelling with EPIC: implementation, up-scaling and regional crop yield validation. Agric Syst 120:61–75

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1. Impact of crop management practices on maize yield: Insights from farming in tropical regions and predictive modeling using machine learning;Journal of Agriculture and Food Research;2024-12

2. A Software Framework for Predicting the Maize Yield Using Modified Multi-Layer Perceptron;Sustainability;2023-02-07

3. Guest editorial: Trends, perspectives and prospects of sensor technologies in hydrological sciences;Acta Geophysica;2022-11-07

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