Aleksandra Nastasić

Biplot analysis of diallel crosses of NS maize inbred lines

Bocanski J., A. Nastasic, D. Stanisavljevic, Z. Sreckov, B. Mitrovic, S. Treskic and M. Vukosavljev (2011): Biplot analysis of diallel crosses of NS maize inbred lines- Genetika, Vol 43, No. 2, 277 - 284. Genetic markers, from morphological to molecular, in function with early Heterosis is a prerequisite for the successful commercial maize production. It does not appear in any cross of two inbred lines, and therefore, the determination of combining abilities of parental lines is essential. The most commonly used method for determining combining abilities is diallel analysis. Besides conventional methods for diallel analysis, a new biplot approach has been sugested. In this paper, we studied the combining ability for grain yield in a set of genotypes obtained by diallel crossing system of six inbred lines. Both, the Griffings conventional method and the biplot approach have been used for diallel analysis. Comparing the GCA values from biplot analysis and Griffings method, similar results can be observed, with the exception of NS L 1051 and NS L 1000 whose ranks are interchanged. Biplot analysis enables the SCA estimation of parent inbred, and the highest SCA has inbred B73D. Biplot analysis also allows the estimation of the best crosses. Inbred B73D shows the best results when crossed with testers Mo17Ht, NS L 1051 and N152, inbred N152 combines best with testers NS L 1001 and NS L 1000, whereas the cross of inbred NS L 1051 with tester B73D results with the highest grain yield per plant in comparison with other testers.

Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.)

Bocanski J., Z. Sreckov, A. Nastasic, M. Ivanovic, I.Djalovic and M. Vukosavljev (2010): Mode of inheritance and combining abilities for kernel row number, kernel number per row and grain yield in maize (Zea mays L.) - Genetika, Vol 42, No. 1, 169- 176. Utilization of heterosis requires the study of combining abilities of potential parents. In view of this, the objective of this paper was to study combining abilities and determine the mode of inheritance and gene effects for the main agronomic character, grain yield, and its components, kernel row number and kernel number per row. Six inbred lines Were used in the study, three of which originated in the U.S., while the other three were developed at the Institute of Field and Vegetable Crops in Novi Sad. Kernel row number was inherited by superdominance, partial dominance, complete dominance and intermediacy. The mode of inheritance of kernel number per row and grain yield was superdominance. Additive gene action had the greatest influence on the expression of kernel row number, while the other two traits were influenced the most by nonalditive gene.

Multiple marker-traits associations for maize agronomic traits

0 CHILEAN JOURNAL OF AGRICULTURAL RESEARCH 76(1) JANUARY-MARCH 2016 3 ULY-SEPTEMBER Association analysis is a relatively novel approach in quantitative traits studies that allows high resolution mapping and time efficient and direct application on breeding material. Since the markers, which are close to the quantitative trait loci stable across environments and genetic backgrounds, may be valuable for marker assisted selection, we chose microsatellite markers previously linked to traits of interest in various mapping studies. A set of 36 microsatellite markers positioned near important maize (Zea mays L.) agronomic loci was used to evaluate genetic diversity and determine population structure. To verify the associations between the markers and traits, a panel of diverse maize inbred lines was genotyped with microsatellites and phenotyped for flowering time, yield and yield components. A relatively high level of polymorphism detected in number of alleles per locus (8.2), average polymorphic information content value (0.64), and average gene diversity (0.684) lines showed the analyzed panel of maize inbred contained significant genetic diversity and was suitable for association mapping. The population structure estimated by model-based clustering method grouped maize inbred lines into three clusters. The association analysis using the general linear and mixed linear models determined significant correlations between several agronomic traits and three microsatellites on chromosomes 3, 5, and 8, namely umc1025, bnlg1237, and bnlg162 consistent across the environments, explaining from 4.7% to 18.2% of total phenotypic variations. The results suggest that the chromosome regions containing quantitative trait loci (QTLs) associated with multiple yield-related traits consistently across environments are potentially important targets for selection.