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

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...

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Bibliographic Details
Main Authors: Dania Batool, Muhammad Shahbaz, Hafiz Shahzad Asif, Kamran Shaukat, Talha Mahboob Alam, Ibrahim A. Hameed, Zeeshan Ramzan, Abdul Waheed, Hanan Aljuaid, Suhuai Luo
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Plants
Subjects:
crop simulation models
machine learning
AquaCrop
tea yield
crop yield prediction
Online Access:https://www.mdpi.com/2223-7747/11/15/1925

Internet

https://www.mdpi.com/2223-7747/11/15/1925

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