Use of multivariate analysis and machine learning methods to characterize traits contributing to wheat yield diversity

Use of multivariate analysis and machine learning methods to characterize traits contributing to wheat yield diversity

Aim of study: Regarding the third largest staple food crop in the world, determining the factors affecting wheat yield is of great importance. This study aimed to determine useful subsets of agronomic traits and evaluate the order of importance of traits in grain yield. Area of study: Fars provi...

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Bibliographic Details
Main Authors:	Ali BEHPOURI, Sara FAROKHZADEH, Zahra ZINATI, Zobeir KHOSRAVI
Format:	Article
Language:	English
Published:	Consejo Superior de Investigaciones Científicas (CSIC) 2023-02-01
Series:	Spanish Journal of Agricultural Research
Subjects:	Triticum aestivum multivariate statistical analysis partial least squares regression support vector regression
Online Access:	https://revistas.inia.es/index.php/sjar/article/view/19835

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