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

Tea (Camellia sinensis 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, deep...

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Detalles Bibliográficos
Autores principales: Batool, Dania, Shahbaz, Muhammad, Shahzad Asif, Hafiz, Shaukat, Kamran, Alam, Talha Mahboob, Hameed, Ibrahim A., Ramzan, Zeeshan, Waheed, Abdul, Aljuaid, Hanan, Luo, Suhuai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332224/
https://www.ncbi.nlm.nih.gov/pubmed/35893629
http://dx.doi.org/10.3390/plants11151925

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332224/
https://www.ncbi.nlm.nih.gov/pubmed/35893629
http://dx.doi.org/10.3390/plants11151925

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