Comparison of graphical analyses for maize genetic experiments: Application of biplots and polar plot to line × tester design

Abstract

Graphical techniques have become important tools to show results of maize (Zea mays L.) breeding experiments in current literature. The present study compared different graphical techniques to determine the best parental lines and cross combinations for yield and kernel quality traits in maize breeding experiments. We measured single plant yield, protein content, oil content, carotenoid content, oleic acid, and linoleic acid in a 5 × 2 line × tester design. Genotype + genotype × environment (GE) biplot, principal component analysis (PCA) biplot, and polar plot were used to analyze data and compare them with conventional line × tester analysis. In the conventional analysis, parents with high means and positive general combining ability (GCA) values were A680 and HYA for single plant yield, IHP for protein content, IHO and HYA for oil content, A680 and Q2 for carotenoid content, IHP for oleic acid content, and A680 for linoleic acid content. The B73 tester exhibited positive GCA values for most investigated traits. The HYA × B73 combination was the best cross in terms of single plant yield, protein, and oil contents. Results showed that biplot methods had both advantages and disadvantages. The PCA biplots can be used alone while the GGE biplot and polar plots are both useful for combining ability, heterosis, and gene action analysis in a line × tester design. Overall, graphical analysis results were very similar to conventional analysis. Consequently, it was assumed that the graphical methods used could be useful to analyze/present data from maize breeding experiments carried out with a line × tester design.

Genetic evaluation and characterization using cluster heat map to assess NaCl tolerance in tomato germplasm at the seedling stage

“…The results are in accordance with a previous study conducted by Raza et al (2016). Related results were also discussed by Kahriman et al (2016) in which a maize (Zea mays L.) line × tester breeding design was evaluated for yield and oil and protein contents by the PCA biplot graphical approach.…”

Evaluation of Single Cross Yellow Maize Hybrids for Agronomic and Carotenoid Traits

“…These findings showed that specific parental combinations could effectively be exploited for genetic improvement of studied traits in present research. Percent contribution also showed that studied lines were more contributors of variability than testers as it was also reported by Kahriman et al (2016). PV and PCV were higher than corresponding GV and GCA respectively for all studied traits which showed the prevalence of environmental factors.…”

“…GCA effects for different agronomic and yield components were studied previously by large number of researchers and they reported both positive and negative GCA effects for different traits as observed in present study (Egesel et al, 2003;Menkir and Maziya-Dixon, 2004;Chander et al, 2008;Menkir et al, 2008;Pixley et al, 2011;Wurtzel et al, 2012;Owens et al, 2014;Kahriman et al, 2016). SCA effects were also widely different for different crosses and traits as both positive and negative effects were prevailing.…”

“…These findings were agreed with previously reported results of Saleem et al (2002), Amit and Joshi (2007). Kahriman et al (2016) found that additive gene action was controlling the total carotenoid contents whereas, current study showed the prevalence of non-additive gene action. Non-additive gene action was also previously reported for plant height, number of kernels per row, grain yield per plant (Zia and Chaudhary, 1980;Saghir, 1984), number of days taken to silking (Saghir, 1984;Naveed, 1989), number of days taken to tesseling (Naveed, 1989).…”

“…Polygon view representing the best crosses. (g) Rows per cob (RPC), (h) Field weight (FW; Kg), (i) Yield per hectare (YPH; tonss), (j) Total carotenoid contents (TCC; µg/g), (k) Provitamin A contents (PVAC; µg/g) and (l) Nonprovitamin A contents (NPVAC; µg/g), L1: 15068, L2: 15076, L3: 15071, L4: 15163, L5: 24687, L6: 14959, L7: 14970, L8: 15205, L9: 24689, L10: 15350, T1: 15055, T2: 15052, T3: 15073, T4: 15130 and T5: 14966 Menkir and Maziya-Dixon, 2004;Chander et al, 2008;Menkir et al, 2008;Pixley et al, 2011;Wurtzel et al, 2012;Owens et al, 2014;Werle et al, 2014;de Almeida Rios et al, 2014;Kahriman et al, 2016).…”