Plot level sugarcane yield estimation by machine learning on multispectral images: A case study of Bundaberg, Australia

Early crop yield prediction provides critical information for Precision Agriculture (PA) procedures, policymaking, and food security. The availability of Remote Sensing (RS) datasets and Machine Learning (ML) approaches improved the prediction of sugarcane crop yield on the local and global scales,...

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Detalhes bibliográficos

Principais autores:	Sharareh Akbarian, Mostafa Rahimi Jamnani, Chengyuan Xu, Weijin Wang, Samsung Lim
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2024-12-01
coleção:	Information Processing in Agriculture
Assuntos:	Sugarcane yield prediction Random forest regression (RFR) Support vector machine (SVM) Nonlinear autoregressive exogenous artificial neural network (NARX ANN)
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S2214317323000574
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