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.
RESULTS: Using total RNA extracted from young roots as template, we performed a comparative transcriptome analysis on oil palm responding to 14d and 28d of Pi deprivation treatment and under adequate Pi supply. By using Illumina HiSeq4000 platform, RNA-Seq analysis was successfully conducted on 12 paired-end RNA-Seq libraries and generated more than 1.2 billion of clean reads in total. Transcript abundance estimated by fragments per kilobase per million fragments (FPKM) and differential expression analysis revealed 36 and 252 genes that are differentially regulated in Pi-starved roots at 14d and 28d, respectively. Genes possibly involved in regulating Pi homeostasis, nutrient uptake and transport, hormonal signaling and gene transcription were found among the differentially expressed genes.
CONCLUSIONS: Our results showed that the molecular response mechanism underlying Pi starvation in oil palm is complexed and involved multilevel regulation of various sensing and signaling components. This contribution would generate valuable genomic resources in the effort to develop oil palm planting materials that possess Pi-use efficient trait through molecular manipulation and breeding programs.
MATERIALS AND METHODS: The flexural strength and flexural modulus of three OPEFB fiber-reinforced PMMA were compared with a conventional and a commercially available reinforced PMMA. The three test groups included OPEFB fibers of 0.5 mm thickness, 2.0 mm thickness, and OPEFB cellulose.
RESULTS: All test group specimens demonstrated improved flexural strength and flexural modulus over conventional PMMA. Reinforcement with OPEFB cellulose showed the highest mean flexural strength and flexural modulus, which were statistically significant when compared to the conventional and commercially reinforced PMMA used in this study. OPEFB fiber in the form of cellulose and 0.5 mm thickness fiber significantly improved flexural strength and flexural modulus of conventional PMMA resin. Further investigation on the properties of PMMA reinforced with OPEFB cellulose is warranted.
CONCLUSIONS: Natural OPEFB fibers, especially OPEFB in cellulose form, can be considered a viable alternative to existing commercially available synthetic fiber reinforced PMMA resin.