Developing machine learning models for wheat yield prediction using ground-based data, satellite-based actual evapotranspiration and vegetation indices-Reference-Cited by-同舟云学术

Developing machine learning models for wheat yield prediction using ground-based data, satellite-based actual evapotranspiration and vegetation indices

Published:2023-05 Issue: Volume:146 Page:126820
ISSN:1161-0301
Container-title:European Journal of Agronomy
language:en
Short-container-title:European Journal of Agronomy

Author:

Naghdyzadegan Jahromi Mojtaba,Zand-Parsa Shahrokh,Razzaghi Fatemeh^ORCID,Jamshidi Sajad^ORCID,Didari Shohreh,Doosthosseini Ali,Pourghasemi Hamid Reza

Publisher

Elsevier BV

Subject

Plant Science,Soil Science,Agronomy and Crop Science

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4. Ang, Y., Shafri, H.Z.M., Lee, Y.P., Bakar, S.A., Abidin, H., Junaidi, M.U.U.M., Hashim, S.J., Che’Ya, N.N., Hassan, M.R., San Lim, H. and Abdullah, R., 2022. Oil Palm Yield Prediction Across Blocks Using Multi-Source Data and Machine Learning.

5. Estimation of geographical variations in virtual water content and crop yield under climate change: comparison of three data mining approaches;Arefinia;Environ. Dev. Sustain.,2022

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