Optimizing ensembles machine learning, genetic algorithms, and multivariate modeling for enhanced prediction of maize yield and stress tolerance index

Optimizing ensembles machine learning, genetic algorithms, and multivariate modeling for enhanced prediction of maize yield and stress tolerance index

The frequent occurrence of drought, halting from unpredictable climate-induced weather patterns, presents significant challenges in breeding drought-tolerant maize to identify adaptable genotypes. The study explores the optimization of machine learning (ML) to predict both the grain yield and stress...

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Bibliographic Details
Main Authors: Muhammad Azrai, Muhammad Aqil, N. N. Andayani, Roy Efendi, Suarni, Suwardi, Muhammad Jihad, Bunyamin Zainuddin, Salim, Bahtiar, Ahmad Muliadi, Muhammad Yasin, Muhammad Fitrah Irawan Hannan, Rahman, Amiruddin Syam
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-02-01
Series:Frontiers in Sustainable Food Systems
Subjects:
drought
maize
machine learning
GA
ensemble
Online Access:https://www.frontiersin.org/articles/10.3389/fsufs.2024.1334421/full

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