Benchmarking between item based collaborative filtering algorithm and genomic best linear unbiased prediction (GBLUP) model in terms of prediction accuracy for wheat and maize//Estudio comparativo en términos de capacidad predictiva para datos de trigo y maíz entre el algoritmo de filtrado colaborativo y el modelo genómico mejor predictor lineal insesgado (GBLUP)

Benchmarking between item based collaborative filtering algorithm and genomic best linear unbiased prediction (GBLUP) model in terms of prediction accuracy for wheat and maize//Estudio comparativo en términos de capacidad predictiva para datos de trigo y maíz entre el algoritmo de filtrado colaborativo y el modelo genómico mejor predictor lineal insesgado (GBLUP)

Aim/background: in view of the growing demand for food, new methodologies are needed to improve the genomic selection (GS) methodology to obtain more productive plant varieties and there is empirical evidence that GS it is revolutionizing plant breeding for food production around the world. Methods:...

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Main Authors: Montesinos-López, Osval A., Franco-Pérez, Emeterio, Luna-Vázquez, Francisco J., Salinas-Ruiz, Josafat, Sandoval-Carrillo, Sara, Valenzo Jiménez, Marco Alberto, Cuervas, Jaime, Santana-Mancilla, Pedro C.
Format: Online
Language:eng
Published: Universidad de Sonora 2020
Online Access:https://biotecnia.unison.mx/index.php/biotecnia/article/view/1255
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