UFYMA   27844
UNIDAD DE FITOPATOLOGIA Y MODELIZACION AGRICOLA
Unidad Ejecutora - UE
artículos
Título:
Effect of missing values on variance component estimates in multienvironment trials
Autor/es:
CROSSA, J.; BALZARINI, M.; AGUATE, F.
Revista:
CROP SCIENCE
Editorial:
CROP SCIENCE SOC AMER
Referencias:
Lugar: Baltimore; Año: 2019 vol. 59 p. 508 - 517
ISSN:
0011-183X
Resumen:
Multienvironment trials (METs) are conducted to evaluate cultivars across locations and years with often incomplete data structure due to annual cultivar replacements. The imbalance could cause biased variance component (VC) estimates depending on data dimension, proportion of missing values, and the cultivar dropout mechanism. The objective of this study was to quantify the bias of VC estimates obtained from imbalanced datasets. We performed simulations of METs with different data dimensions (number of cultivars, locations, and years) using VC parameters taken from real wheat (Triticum aestivum L.) METs. The missing values were generated by annually dropping and replacing cultivars. The genotypic variance estimates obtained from analyses of 2 yr of METs, and >40% missing values, were overestimated in all simulated scenarios. The percentage of bias was highly influenced by the number of years considered for analysis. Variance component estimates from simulations with more years of METs were less biased: 8-yr analyses produced