Relationship between genetic diversity and cold-tolerance of maize inbred lines

• Published in: Genetika (Beograd) Vol. 49; no. 2; pp. 635 - 646
• Main Authors: Milivojevic, Marija, Nikolic, Ana, Markovic, Ksenija, Filipovic, Milomir, Vancetovic, Jelena, Petrovic, Tanja, Srdic, Jelena
• Format: Journal Article
• Language: English
• Published: 2017
• ISSN: 0534-0012; 1820-6069
• DOI: 10.2298/GENSR1702635M

Early maize sowing enables longer growing season with enhanced possibility of
achieving higher and more stable yields, and better chances of avoiding
summer droughts. For early sowing, cold-tolerant maize genotypes should be
used. Breeding maize, tolerant to low temperatures, requires knowledge of
genetic diversity and heterotic patterns of breeding material. The objective
of this study was to determine genetic diversity of 15 ZP maize inbred lines
applying the method of protein markers (UTLIEF method), and to establish
correspondence between thus obtained classification with the results of cold
test (CT) and field emergence (FE). During two production seasons (2011 and
2014), 15 maize inbred lines were self-pollinated. Pedigree data showed that
material belongs to different maturity and heterotic groups. Cold tolerance
was assessed in laboratory (2015) by cold test (7.5 ?C, 10 days), and field
trials on two locations during two successive years (2015, 2016). ZP maize
inbred lines showed very good response to stressful conditions of CT and FE.
Inbred lines with Lancaster background were more sensitive to low
temperatures than inbred lines with BSSS and Iowa Dent background. Based on
UTLIEF method two inbred lines with Lancaster background (ZPL 5 and ZPL 7)
were grouped by cluster analysis together with Iowa Dent inbred lines, that
also expressed better cold tolerance, and thus exceptional consent was
achieved with the results of CT and FE. Classification of maize inbred lines
based on UTLIEF method, followed by cluster analysis and PCA, showed good
agreement with pedigree data, which points out that this method could be
successfully applied for genetic classification of breeding material of a
wide genetic background.
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