A Hybrid Approach to Tea Crop Yield Prediction Using Simulation Models and Machine Learning

Tea (<i>Camellia sinensis</i> L.) is one of the most highly consumed beverages globally after water. Several countries import large quantities of tea from other countries to meet domestic needs. Therefore, accurate and timely prediction of tea yield is critical. The previous studies used statistical...

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Principais autores:	Dania Batool, Muhammad Shahbaz, Hafiz Shahzad Asif, Kamran Shaukat, Talha Mahboob Alam, Ibrahim A. Hameed, Zeeshan Ramzan, Abdul Waheed, Hanan Aljuaid, Suhuai Luo
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2022-07-01
coleção:	Plants
Assuntos:	crop simulation models machine learning AquaCrop tea yield crop yield prediction
Acesso em linha:	https://www.mdpi.com/2223-7747/11/15/1925
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