Efficient breeding and selection of superior genotypes requires a comprehensive understanding of the genetics of traits. This study was aimed at establishing the general combining ability (GCA), specific combining ability (SCA), and heritability of sweetpotato weevil (Cylas spp.) resistance, storage root yield, and dry matter content in a sweetpotato multi-parental breeding population. A population of 1,896 F1 clones obtained from an 8 × 8 North Carolina II design cross was evaluated with its parents in the field at two sweetpotato weevil hotspots in Uganda, using an augmented row-column design. Clone roots were further evaluated in three rounds of a no-choice feeding laboratory bioassay. Significant GCA effects for parents and SCA effects for families were observed for most traits and all variance components were highly significant (p ≤ 0.001). Narrow-sense heritability estimates for weevil severity, storage root yield, and dry matter content were 0.35, 0.36, and 0.45, respectively. Parental genotypes with superior GCA for weevil resistance included “Mugande,” NASPOT 5, “Dimbuka-bukulula,” and “Wagabolige.” On the other hand, families that displayed the highest levels of resistance to weevils included “Wagabolige” × NASPOT 10 O, NASPOT 5 × “Dimbuka-bukulula,” “Mugande” × “Dimbuka-bukulula,” and NASPOT 11 × NASPOT 7. The moderate levels of narrow-sense heritability observed for the traits, coupled with the significant GCA and SCA effects, suggest that there is potential for their improvement through conventional breeding via hybridization and progeny selection and advancement. Although selection for weevil resistance may, to some extent, be challenging for breeders, efforts could be boosted through applying genomics-assisted breeding. Superior parents and families identified through this study could be deployed in further research involving the genetic improvement of these traits.
Sweetpotato weevils (SPWs) can cause up to 100% yield losses in sweetpotato (Ipomoea batatas). Nevertheless, there has been limited success in breeding for SPW resistance globally. This is attributed partly to difficulty in screening for resistance because resistance to the SPW is complex and is mediated by several resistance indicators. Measuring all these resistance indicators is costly and time consuming. To enhance efficiency in selection for SPW resistance, there is need to profile and identify key resistance indicators. Potentially, this will better enable breeders to timely and precisely select for SPW resistance. The objective of this study was to identify the most efficient morphological resistance indicators against SPW. Thirty sweetpotato genotypes that varied in resistance to SPW comprising local collections, released varieties, and breeding lines were evaluated at three locations for two seasons in Uganda using an alpha lattice design. Data were collected on storage root yield, SPW root and stem damage, and weevil resistance indicators such as vine vigor (VV), ground cover (GC), vine weight (VW), storage root neck length (NL), latex content, cortex thickness (CT), and dry matter content (DM). Genotype means for all measured traits varied significantly except for CT. Negative relationships were observed between SPW root damage and GC, VW, CT, VV, NL, and DM. However, path coefficient analysis showed storage root NL (direct effect of −0.43, p < 0.001
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.