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The ability to discriminate germplasm is important for plant breeding as well as for plant variety protection. To achieve this, plant breeders have been using molecular, physiological and biochemical markers in discriminating and grouping of genotypes. Breeders have been looking for effective, quick and cheaper ways of grouping germplasm. Therefore this study was carried out to assess the ability of the traits used for determining the distinctness, uniformity and stability (DUS) of new plant varieties and agro-morphological characteristics for differentiating Southern African maize inbreds. In this study, 18 maize inbred lines were assessed for their variation based on 25 agronomic and 12 DUS traits. The maize inbred lines were grouped differently based on qualitative or quantitative traits or when combined. The correlation between the qualitative and quantitative similarity matrices was low (r=0.048) and non-significant. This indicated that both qualitative and quantitative traits should be used for effective maize inbred line discrimination. Both qualitative and quantitative similarity matrices were highly significantly (p<0.001) and highly correlated to mixed data (r=0.82 and r=0.61 respectively). The grouping of the inbred lines based on Principal Component Analysis (PCA) was similar to the similarity matrix of the mixed data. The first principal component, which explained 27.8% of the total variation, was due to grain yield and productive parameters. The second component, explaining 13.2% of the total variation was due to number of tassel branches (TBNo) and tassel length (TL). The Shannon diversity index showed that the inbred lines were diverse in days to silking, ear diameter, days to maturity, shelling percentage and leaf colour. It is concluded that for effective discrimination of maize inbred lines both agro-morphological and DUS traits should be used especially when few inbreds are being considered.

african journal of agricultural research

A comparative analysis of distinctness, uniformity and stability (DUS) data in discriminating selected Southern African maize (Zea mays L.) inbred lines