ABSTRACT
This study evaluated an interspecific hybrid (Saccharum spp. × S. spontaneum) population with the aim of developing germplasm for use in both sugar and bioenergy (biomass) production. Specific objectives were to determine the genetic variability and heritability among the interspecific hybrid progenies for traits of economic importance and to use the Best Linear Unbiased Predictions (BLUPs) to determine their genotypic values. The 46 interspecific hybrids used in this study originated from crossing commercial sugarcane cultivars (UT5, F152, and KK07–559) as female and S. spontaneum clones (THS98–41, THS98–91, THS98–95, THS98–94, and THS97–51) as male parents. There were significant residual variances, attributed to the small plot size, but the juice quality traits were measured with relatively higher precision than other traits. Selection recommendations varied for different traits, suggesting selection pressure could be moderate to high for juice quality traits and moderate for yield-related traits. No hybrid genotypes were found to outperform cultivar parents for traits such as commercial cane sugar and low fiber, necessitating further germplasm enhancement for improvement of varieties destined for sugar production. On the contrary, transgressive segregation was observed for cane yield and other traits influencing biomass yield. The production potential of these hybrids could be tested in larger plots across multiple locations.
Acknowledgments
Grateful acknowledgment is made to the Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program (PHD/0164/2561). Assistance was also received from the Northeast Thailand Cane and Sugar Research Center (NECS), Khon Kaen University, and the Department of Agriculture (DOA) for providing financial support. We are grateful to the anonymous reviewers for providing suggestions that helped to improve the quality of the manuscript and to Mr Zachary Taylor (Louisiana State University Agricultural Centre, Sugar Research Station) for help with analyzing the data using the R Studio statistical software package.
Disclosure statement
No potential conflict of interest was reported by the author(s).