RESULTS: In general, the genetic diversity decreased from Costa Rica towards the north (Honduras) and south-east (Colombia). Principle coordinate analysis (PCoA) showed a single cluster indicating low divergence among palms. The phylogenetic tree and STRUCTURE analysis revealed clusters based on country of origin, indicating considerable gene flow among populations within countries. Based on the values of the genetic diversity parameters, some genetically diverse populations could be identified. Further, a total of 34 individual palms that collectively captured maximum allelic diversity with reduced redundancy were also identified. High pairwise genetic differentiation (Fst > 0.250) among populations was evident, particularly between the Colombian populations and those from Honduras, Panama and Costa Rica. Crossing selected palms from highly differentiated populations could generate off-springs that retain more genetic diversity.
CONCLUSION: The results attained are useful for selecting palms and populations for core collection. The selected materials can also be included into crossing scheme to generate offsprings that capture greater genetic diversity for selection gain in the future.
RESULTS: Our results indicate that the SHELL markers can theoretically reduce the major losses due to dura contamination of tenera planting material. However, these markers cannot distinguish illegitimate tenera, which reduces the value of having bred elite tenera for commercial planting and in the breeding programme, where fruit form is of limited utility, and incorrect identity could lead to significant problems. We propose an optimised approach using SNPs for routine quality control.
CONCLUSIONS: Both dura and tenera contamination can be identified and removed at or before the nursery stage. An optimised legitimacy assay using SNP markers coupled with a suitable sampling scheme is now ready to be deployed as a standard control for seed production and breeding in oil palm. The same approach will also be an effective solution for other perennial crops, such as coconut and date palm.
RESULTS: The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods.
CONCLUSION: Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly outperformed other methods, but required parameters optimization for GS implementation.