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izvor podataka: crosbi !

Factors affecting the accuracy of genomic predictions in testcrosses of maize biparental population (CROSBI ID 280024)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Galić, Vlatko ; Mazur, Maja ; Brkić, Andrija ; Volenik, Mirna ; Jambrović, Antun ; Zdunić, Zvonimir ; Šimić, Domagoj Factors affecting the accuracy of genomic predictions in testcrosses of maize biparental population // Poljoprivreda (Osijek), 26 (2020), 1; 10-16. doi: 10.18047/poljo.26.1.2

Podaci o odgovornosti

Galić, Vlatko ; Mazur, Maja ; Brkić, Andrija ; Volenik, Mirna ; Jambrović, Antun ; Zdunić, Zvonimir ; Šimić, Domagoj

engleski

Factors affecting the accuracy of genomic predictions in testcrosses of maize biparental population

Genomic prediction accuracy (rMP) is affected by many factors, such as the trait heritability, training population size and structure, and the number of markers. This study’s objective was to investigate the factors associated with rMP for the ear height and the plant height in two planting densities in testcrosses of maize (Zea mays L.) IBM population. Genetic correlations between the training and validation populations were calculated. The high heritability estimates and correlations between the traits were observed. The non-zero estimates of rMP for all trait-density combinations implied an efficiency of genomic selection. The lower than expected values of genetic correlations were observed between the training and validation populations. However, a strong correlation was observed between a genetic correlation of training and the validation population and rMP in all three sizes of training populations assessed (20-40%, 40-60%, and 60-80%), suggesting that the size of the training population can be kept low by an appropriate selection while maintaining a high rMP. Further studies of relationships between the training and validation populations with larger effective population sizes are suggested, as reducing the size of training population while maintaining a high rMP can facilitate a more effective allocation of resources in a maize breeding program.

genomic selection ; genomic prediction accuracy ; training population size ; planting density ; plant architecture

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Podaci o izdanju

26 (1)

2020.

10-16

objavljeno

1330-7142

1848-8080

10.18047/poljo.26.1.2

Povezanost rada

Interdisciplinarne biotehničke znanosti, Poljoprivreda (agronomija)

Poveznice