Genetic diversity assessment of philippine germplasm collections of yautia [xanthosoma sagittifolium (L.) schott] using morpho-agronomic traits

Abstract

Xanthosoma sagittifolium (L.) Schott or “yautia” belongs to the Araceae family. In the Philippines, the traditional varieties are categorized based on the color of the corms, leaves, and petioles. However, there is a limited production of this crop and, thus, the production data is reported with another edible aroid – “taro.” A total of 148 accessions of yautia germplasm were collected from 32 provinces in the country and are conserved ex situ at the National Plant Genetic Resources Laboratory (NPGRL), Institute of Plant Breeding (IPB), University of the Philippines Los Baños (UPLB). These were morphologically characterized to determine the genetic diversity of the germplasm accessions. The data gathered a total of 57 qualitative and 21 quantitative parameters for the whole plant per accession. The results of diversity analysis showed a total of five qualitative and 10 quantitative characters obtaining high index values, ranging from 0.67–0.96 H’. The shape of corm (0.96) had the highest H’ among the qualitative characters while the lamina length: breadth ratio (0.90) was the highest H’ among the quantitative characters observed. The results of the principal component analysis (PCA) have shown that the first five components have eigenvalues up to 1.03, which explains 85.03% of the total variation among the genotypes of Xanthosoma. The phenotypes or traits with loading values of ≥ 0.50 explained the total variation within each component. Furthermore, outliers can be seen in the scree plots, which means these accessions have the least similarities in either of the groupings formed. The germplasm collections at the NPGRL are highly diverse in terms of the morpho-agronomic characteristics established on the basis of the results of the diversity analysis using the Shannon-Weaver diversity index, multivariate analysis using SAHN (sequential, agglomerative, hierarchical, and nested) clustering, and PCA.