Establishment of a core collection of Cynodon based on morphological data

C.Q. Huang, T. Long, C.J. Bai, W.Q. Wang, J. Tang, G.D. Liu

Abstract


In a field plot study conducted in Danzhou, Hainan province, China, a total of 537 wild Cynodon accessions from 22 countries and classified into 11 groups according to taxonomy and origin, were characterized in terms of 11 phenotypic traits in order to construct a core collection. For this, the optimal strategy was developed by screening within the following method levels: (i) 7 sampling proportions (5, 10, 15, 20, 25, 30 and 35%); (ii) 3 sampling methods (preferential sampling, deviation sampling and random sampling); (iii) 5 clustering methods [single linkage, completed linkage, median linkage, unweighted pair-group average (UPGMA) and Ward’s method]; (iv) 3 genetic distances (Euclidean distance, Mahalanobis distance and principal component distance); and (v) 3 sampling proportions within groups (simple, logarithmic and square root proportions). Mean difference percentage, variance difference percentage, coincidence rate of range and variation coefficient changing rate were the criteria adopted for evaluating how well the core collection represented the original collection. The correlation between the original and core collections was determined for comparison. The core collections were validated with the sample distribution diagram of the main components. Results showed that the optimal sampling method for constructing a Cynodon core collection was preferential sampling, the optimal sampling proportion being 20%. The optimal sampling proportion within groups was the square root proportion, the optimal genetic distance was Mahalanobis distance and the optimal clustering method was UPGMA. The proposed core collection of Cynodon is composed of 108 accessions; it was constructed following the optimal sampling strategy identified and retained the original collection´s phenotypic diversity, phenotypic trait correlations and phenotypic group structure. Thus, this collection could be considered a representative sample of the entire resource.


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DOI: https://doi.org/10.17138/tgft(8)203-213

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