METHODS AND RESULTS: The amplification of genomic DNA with 32 ISSR markers detected an average of 97.64% polymorphism while 35.15% and 51.08% polymorphism per population and geographical zone, respectively. Analysis of molecular variance revealed significant variation within population 75% and between population 25% whereas within region 84% and between region 16%. The Bidillali exposed greater number of locally common band i.e., NLCB (≤ 25%) = 25 and NLCB (≤ 50%) = 115 were shown by Cancaraki while the lowest was recorded as NLCB (≤ 25%) = 6 and NLCB (≤ 50%) = 72 for Roko and Maibergo, accordingly. The highest PhiPT value was noted between Roko and Katawa (0.405*) whereas Nei's genetic distance was maximum between Roko and Karu (0.124). Based on Nei's genetic distance, a radial phylogenetic tree was constructed that assembled the entire accessions into 3 major clusters for further confirmation unrooted NJ vs NNet split tree analysis based on uncorrected P distance exposed the similar result. Principal coordinate analysis showed variation as PC1 (15.04%) > PC2 (5.81%).
CONCLUSIONS: The current study leads to prompting the genetic improvement and future breeding program by maximum utilization and better conservation of existing accessions. The accessions under Cancaraki and Jatau are population documented for future breeding program due to their higher genetic divergence and homozygosity.
RESULTS: Yield per plant showed positive and highly significant (P ≤ 0.01) correlations with most of the characters studied at both the phenotypic and genotypic levels. By contrast, disease incidence and days to flowering showed a significant negative association with yield. Fruit weight and number of fruits exerted positive direct effect on yield and also had a positive and significant (P ≤ 0.01) correlation with yield per plant. However, fruit length showed a low negative direct effect with a strong and positive indirect effect through fruit weight on yield and had a positive and significant association with yield.
CONCLUSION: Longer fruits, heavy fruits and a high number of fruits are variables that are related to higher yields of chili pepper under tropical conditions and hence could be used as a reliable indicator in indirect selection for yield. © 2016 Society of Chemical Industry.
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.