English

Mekbib Firew,Abraha Eyasu,Ftwi Mebrahtom

doi:10.5897/ajps2016.1419

Abstract

Knowledge on performance of genotypes and interrelationships among traits is very important for sugarcane breeding programmes. The objectives of this study were to assess the phenotypic relationship among 49 sugarcane genotypes and the inter-relationships among traits considered. The cluster analysis demonstrated that the 49 sugarcane genotypes studied were clustered into nine groups and were highly different for Pol in juice, cane yield (tons ha-1m-1), number of tillers (ha-1), purity% and milleable stalk population (ha-1). The relationship among sugarcane genotypes was not dependent on geographic origin, suggesting that a high proportion of total genetic variation was retained within the groups of origin and active genetic ex-change was found between different origins. The principal component analysis indicated that cane yield, milleable stalk height and milleable stalk diameter were highly correlated with sugar yield while the correlation of quality traits with sugar yield was weak. In contrary, path and multiple regression analysis revealed that cane yield, recoverable sucrose percentage (%) and Pol contribute more to the variability of sugar yield; these are very important traits for high sugar yield that should be considered in sugarcane breeding programmes. Moreover, milleable stalk height and milleable stalk population via cane yield and Brix, Pol, purity and number of internodes via recoverable sucrose percentage had high indirect effects on sugar yield suggesting these traits should also be given consideration during selection for high sugar yield. Generally, similar and adequate information was generated following the use of cluster, principal component, linear discriminant, path coefficient and multiple regression analyses indicating the use of multivariate analyses was successful and results of the study were more substantial to give concrete recommendation. Key words: Clusters, genotypes, multiple regression, path coefficient, phenotypic correlation.

Highlights

Sugarcane (Saccharum officinarum L.) is an important industrial crop and global major source of energy and is a major crop in most parts of tropical and subtropical regions (Khan et al, 2013)
As the appropriate methods that provide accurate evaluations and estimation of genetic diversity depend on genetic variation, sampling methods, the magnitude of data sets, and the statistical tools applied in the data analysis (Mohammadi and Prasanna, 2003), multivariate statistical analysis techniques like principal component analysis (PCA) and cluster analysis techniques are very important to study genetic diversity of sugarcane
Based on the adjusted means of 12 sugarcane traits presented in Table 3, results of the cluster analysis indicated that the 49 sugarcane genotypes formed 10 distinct groups or clusters where 3 of the groups contained a single genotype (Table 4)

Summary

Introduction

Sugarcane (Saccharum officinarum L.) is an important industrial crop and global major source of energy and is a major crop in most parts of tropical and subtropical regions (Khan et al, 2013). Of sugarcane necessitates a strong breeding program that generates gene pools that enables identification of sugarcane genotypes with multiple uses. To have successful genetic improvement of sugarcane genotypes for multiple purposes, efficient and diversified selection procedures have to be followed. Selection will be efficient if the procedures consider many traits simultaneously during evaluation of sugarcane genotypes. As the appropriate methods that provide accurate evaluations and estimation of genetic diversity depend on genetic variation, sampling methods, the magnitude of data sets, and the statistical tools applied in the data analysis (Mohammadi and Prasanna, 2003), multivariate statistical analysis techniques like principal component analysis (PCA) and cluster analysis techniques are very important to study genetic diversity of sugarcane

Objectives

Methods

Results