From sugar industry to cane industry: investigations on multivariate data analysis techniques in the identification of different high biomass sugarcane varieties

Abstract

Apart from sugar production, the sugarcane plant is now viewed as a high value lowcost feedstock for renewable energy. However, in depth studies on the biomass potential of the crop are relatively new and current varieties have not been optimised to achieve the required high biomass yield for different end-uses. The objective of this study was to examine the possibility of using multivariate data analysis (MVDA) techniques in the selection of different types of high biomass canes. Sixty genotypes of different generations of crosses were evaluated for 18 inter-related traits. Principal component analysis compressed the different characters into five major principal components (PCs). The first two explained 77 % of total variation. PC1 emphasised on the cane quality traits while PC2 stressed on biomass characteristics. The biplot with the two PCs was very helpful in visualising the existing variations in the population. Cluster analysis defined six major groups in the population. Candidates from three of them were found suitable for commercial exploitation, for either sugar, fibre, or both as the main end-products. The MVDA techniques were thus found to be very effective in assessing the extent of genetic divergence between genotypes in the population and in the selection of different types of high biomass canes for multipurpose use. It was also clear that sucrose content was positively associated with cane diameter while high fibre varieties tended to be thinner and taller than the traditional commercial varieties.