The assessment of genetic diversity among improved crop germplasm can facilitate the expansion of the genetic base for crop improvement in breeding program. However, little effort has been made to assess the level of genetic relatedness among released varieties and elite soybean [Glycine max (L.) Merr.] genotypes. The objective of this study was to determine the degree of genetic diversity that exists among released and elite soybean genotypes in Uganda. In this study, 21 polymorphic simple sequence repeat (SSR) molecular markers were used to determine the degree of genetic diversity and varietal identification among 34 soybean genotypes. A total of 59 alleles with an average of 2.85 alleles per locus were detected. The polymorphic information content (PIC) values ranged from 0.208 on BE806308 to 0.741 on Satt411, with an average of 0.5870. The expected heterozygosity varied from 0.208 on BE806308 to 0.725 on Satt411, with an average of 0.548 per marker. The dendrogram constructed based on Jaccard's genetic similarities among 34 soybean genotypes identified three major clusters, with six of the released varieties belonging to cluster I. The majority of elite genotypes including three recently released cultivars; Maksoy 4N, Maksoy 5N and Maksoy 6N were grouped in cluster II and III. The results showed moderate genetic variation among the soybean genotypes, which could accelerate genetic vulnerability. Therefore, there is need to widen the genetic base of the working germplasm through the use of techniques such as pre-breeding and novel biotechnology techniques such as mutation breeding and CRISPR to create genetic variation necessary to cope with the dynamics of biotic and abiotic stresses that affect soybean production in Uganda.
The cassava breeding program in Uganda has released many improved cultivars resistant/tolerant to cassava brown streak disease (CBSD) and cassava mosaic disease (CMD). However, many farmers have continued to use cultivars that are susceptible to these major viral diseases but with diverse attributes. There is a need to understand farmers’ cassava cultivar attribute preferences and CBSD, CMD prevalence on the preferred cultivars. A total of 150 cassava farmer fields (74 in Bukedea district and 76 in Kumi district) located in eastern Uganda were evaluated for farmers’ cultivars and attribute preferences, as well as prevalence of CBSD and CMD on the farmer selected cultivars. The eastern region was of interest in the study, due to it-being the major cassava producing area in the country. In addition, 30 cassava plants of different genotypes were chosen randomly along transects of each field and assessed for CBSD/CMD incidence and severity on preferred cultivars. Results showed that more than 64% of the farmers in eastern Uganda preferred NASE 03 due to its sweet taste and high yields, followed by NASE 14 (21%) because of its high yields. There was a significant (P≤0.001) correlation between cassava cultivars preferred and CBSD severity (r = -0.56), CBSD incidence (r = -0.53), CMD severity (r = -0.51) and CMD incidence (r = -0.39). In corroboration, the most preferred cultivar, NASE 03 was found most susceptible to CBSD and CMD in both Bukedea and Kumi districts with CBSD incidence of 62.2% and 52.7% and CMD incidence of 56.9% and 34.3% respectively. The results showed that CBSD and CMD are prevalent on farmer preferred cassava cultivars, and that farmer cultivar preference depends not only on disease resistance but also other attributes.
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.