Integrated phenology and climate in rice yields prediction using machine learning methods
Rice (Oryza sativa L.) is a staple cereal crop and its demand is substantially increasing with the growth of the global population. Precisely predicting rice yields are of vital importance to ensure the food security in countries like China, where rice accounts for one-fifth of the total agricultura...
Saved in:
Main Authors: | Yahui Guo, Yongshuo Fu, Fanghua Hao, Xuan Zhang, Wenxiang Wu, Xiuliang Jin, Christopher Robin Bryant, J. Senthilnath |
---|---|
Format: | article |
Language: | EN |
Published: |
Elsevier
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/681319c8e6d3410cbf182d64fffda8c6 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Targeted yield precision model assessment for rice-rice crop sequences in Farmers' Fields in Humid, Sub-tropical Northeastern India
by: Das,K.N, et al.
Published: (2016) -
Impact of Nursery Seeding Density, Nitrogen, and Seedling Age on Yield and Yield Attributes of Fine Rice
by: Sarwar,Naeem, et al.
Published: (2011) -
Relationships between grain yield and agronomic traits of rice in southern China
by: Zhao,Hua, et al.
Published: (2020) -
GGE biplot analysis of multi-environment yield trials of rice produced in a temperate climate
by: Donoso-Ñanculao,Gabriel, et al.
Published: (2016) -
Effects of submergence stress at the vegetative growth stage on hybrid rice growth and grain yield in China
by: Chen,Yutiao, et al.
Published: (2021)