In many agricultural crops, the number of parents used in cross breeding make it difficult to obtain all possible hybrids in diallels. Therefore, using maize as a model plant and based on traits with high and low heritabilities, the aim of the present study was to quantify the correlation estimates of the general combining ability (GCA) and specific combining ability (SCA) between a complete diallel and a circulant diallel, with and without the inclusion of parents. For the high heritability trait, the GCA estimates can be obtained with low s values, whereas for the SCA estimates, s values close to half the number of parents should be used. For the low heritability trait, information from parents must be used to obtain the SCA estimates. For the GCA estimates, considering the stabilization of r above 0.70 for s=7, s values greater than half the number of parents must be used in the circulant models.
In the last decades, a new trend to use more refined analytical procedures, such as artificial neural networks (ANN), has emerged to be most accurate, efficient, and extensively applied for mining and data prediction in different contexts, including plant breeding. Thus, this study was developed to establish a new classification proposal for targeting genotypes in breeding programs to approach classical models, such as a complete diallel and modern prediction techniques. The study was based on the standard deviation values of an interpopulation diallel and it also verified the possibility of training a neural network with the standardized genetic parameters for a discrete scale. We used 12 intercrossed maize populations in a complete diallel scheme (66 hybrids), evaluated during the 2005/2006 crop season in three different environments in southern Brazil. The implemented MLP architecture and other associated parameters allowed the development of a generalist model of genotype classification. The MLP neural network model was efficient in predicting parental and interpopulation hybrid classifications from average genetic components from a complete diallel, regardless of the evaluation environment.
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