Abstracts
Aims: The overall study objective was to contribute to sugarcane yield improvement in Ivory Coast. Specific objective was to evaluate the genetic diversity of Reunion-Ivorian first sugarcane genotypes preselected at one-row stage for further advanced selection trials of 1st and 2nd steps to be carried out under Ferké commercial field conditions.
Study Design: It was conducted on Ferké 2 experimental station under full covering sprinkler irrigation in northern Ivory Coast. The genotypes were preselected in 1st ratoon among 985 clones planted in single rows of 3 m per clone with 1.5 m of row-spacing following families. Genotypes were not replicated except for the control variety SP70/1006. That one was replicated several times every 5 rows to ease agronomics observations of clones in comparison with the control. Quantitative as well as qualitative traits observed at the age of 10 months were subjected to a series of multivariate analyses.
Results: It came out that quantitative traits which better explained diversity of genotypes were the following in decreasing order: flowering rate, number of millable stalks/3m, stalk diameter, and stalk height. These phenotypic traits highly contributed to genotypes discrimination into 8 clusters which suggested a good genetic diversity among all 148 preselected accessions. Four best represented clusters (63.5 % of total) comprised 20-30 individuals each, whereas less represented clusters (36.5 %) involved 11-15 individuals each.
Conclusions: Quantitative traits most relevant in variety clustering were high tillering, moderate tillering, erect canopy which were associated respectively with clusters G1, G7 and G2. As for lodging characters, they were associated with 6 clusters all together, namely G2, G3, G4, G5, G6 and G8. The genetic variability as shown was a prerequisite for further advanced selection trials with limited number of accessions to be conducted under commercial field conditions.
Keywords :
Visual selection; vigor; one-row stage; phenotypic trait; multivariate analysis; clustering; agro-ecology.
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