Yield performance estimation of corn hybrids using machine learning algorithms
Estimation of yield performance for crop products is a topic of interest in agriculture. In breeding programs, we cannot test all possible hybrids created by crossing two parents (inbred and tester) since it would be too time consuming and costly. In this paper, we exploit different machine learning...
Main Authors: | Farnaz Babaie Sarijaloo, Michele Porta, Bijan Taslimi, Panos M. Pardalos |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2021-01-01
|
Series: | Artificial Intelligence in Agriculture |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2589721721000179 |
Similar Items
-
Forecasting Corn Yield With Machine Learning Ensembles
by: Mohsen Shahhosseini, et al.
Published: (2020-07-01) -
Density on Seed Yield and Yield Components of Corn Hybrids
by: M Mousavi Nik
Published: (2011-06-01) -
Leafy reduced-stature maize (Zea mays L.) for mid- to short-season environments : yield, development, and physiological aspects of inbred lines and hybrids
by: Modarres Sanavy, S. A. M. (Seyed Ali Mohammad)
Published: (1995) -
Hybrid Selection and Agronomic Management to Lessen the Continuous Corn Yield Penalty
by: Alison M. Vogel, et al.
Published: (2018-10-01) -
Methodology for prediction of corn yield using remote sensing satellite data in Central Mexico
by: Jesús Soria Ruiz, et al.
Published: (2012-02-01)