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Chilean Journal of Agricultural Research
Instituto de Investigaciones Agropecuarias, INIA
ISSN: 0718-5820
EISSN: 0718-5839
Vol. 76, No. 3, 2016, pp. 294-299
Bioline Code: cj16038
Full paper language: English
Document type: Research Article
Document available free of charge

Chilean Journal of Agricultural Research, Vol. 76, No. 3, 2016, pp. 294-299

 en An accurate prediction of maize crosses using diallel analysis and best linear unbiased predictor (BLUP)
Oliveira, Gustavo H.F.; Buzinaro, Rodolfo; Revolti, Lucas T.M.; Giorgenon, Carlos H.B.; Charnai, Kauê; Resende, Diego & Moro, Gustavo V.


A major obstacle in corn ( Zea mays check for this species in other resources L.) breeding programs is how to obtain strains which, when combined, ensure increased productivity in all crop characteristics. Therefore, the objective of this study was to evaluate the prediction efficiency of hybrid maize using diallel analysis and the best linear unbiased predictor (BLUP). Eight synthetic varieties were sown in a diallel scheme and the hybrid and their parents were then evaluated in three separate environments; both combining ability and predicted breeding values (BLUPs) were estimated. Correlations between the BLUP and combining abilities were also obtained. Combining ability analysis revealed that both additive and non-additive types of gene action were important in the studied traits. There was a moderate to high correlation between the mean square of the combining ability and the predicted breeding values. This shows that BLUP can be used to select the best parents for different traits, especially for ear height and ear position, which had the highest correlations. The parent VAR-01 had significant general combining ability (GCA) values, and it can be used in crosses to reduce plant height, ear height, and ear position while the parent VAR-06 can participate in crosses to increase ear height, plant height, and ear position. The result obtained for combining ability was moderately to highly consistent with BLUP results, but selection must be carefully undertaken.

GCA; mixed models; SCA; Zea mays

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