2016
DOI: 10.33865/wjb.001.01.0006
|View full text |Cite
|
Sign up to set email alerts
|

Introgression of Striga Resistance Into Popular Sudanese Sorghum Varieties Using Marker Assisted Selection

Abstract: Witchweed (Strigas spp.) is one of the most important cereals production constraints globally and is projected to worsen with anticipated climate change. It is especially a devastating parasitic weed in Sub-Saharan Africa and parts of Asia. Integrated management strategies that depend mainly on host plant resistance provide the most effective control mechanism for Striga. We used molecular marker-assisted backcrossing to introgress Striga resistance from a resistant genotype, N13, into agronomically important … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
10
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
6
1

Relationship

0
7

Authors

Journals

citations
Cited by 12 publications
(10 citation statements)
references
References 22 publications
0
10
0
Order By: Relevance
“…As with most crops of value, there are concerns associated with sorghum production, including losses due to abiotic and biotic stress pressure, as well as the desire to enhance composition and increase yield, indicating that a variety of targets exist for trait improvement. Improvement efforts have utilized breeding, coupled with approaches such as QTL identification and mapping, molecular marker identification and genome wide association studies, with the goal of improving germplasm 2 of 18 while also gaining an understanding of the genetic loci/genes/allelic variation contributing to the various traits [10][11][12][13][14][15][16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…As with most crops of value, there are concerns associated with sorghum production, including losses due to abiotic and biotic stress pressure, as well as the desire to enhance composition and increase yield, indicating that a variety of targets exist for trait improvement. Improvement efforts have utilized breeding, coupled with approaches such as QTL identification and mapping, molecular marker identification and genome wide association studies, with the goal of improving germplasm 2 of 18 while also gaining an understanding of the genetic loci/genes/allelic variation contributing to the various traits [10][11][12][13][14][15][16][17][18].…”
Section: Introductionmentioning
confidence: 99%
“…for Striga resistance in sorghum and rice (Atera et al, 2015;Yasir & Abdalla, 2013;Yohannes et al, 2015;Ali et al, 2016). Using genomic association wide (GWA), 24 SNPS markers associated with grain yield, Striga damage at 8 and 10 weeks after planting (WAP), ears per plant and ear aspect under Striga infestation were detected in early maturing maize inbred (Adewale et al, 2020).…”
Section: Marker-assisted Breeding For Striga Resistancementioning
confidence: 99%
“…Using the linkage mapping method, two putative QTLs have been discovered that govern incompatible response to Striga parasitism in maize amongst F2 segregated populations (Amusan, 2010). Whereas some QTLs have been discovered for Striga resistance in sorghum and rice (Atera et al., 2015; Yasir & Abdalla, 2013; Yohannes et al, 2015; Ali et al., 2016). Using genomic association wide (GWA), 24 SNPS markers associated with grain yield, Striga damage at 8 and 10 weeks after planting (WAP), ears per plant and ear aspect under Striga infestation were detected in early maturing maize inbred (Adewale et al., 2020).…”
Section: Breeding Approaches Used For Striga Resistance In Maizementioning
confidence: 99%
“…These are (i) MAS and MAB, (ii)Multiple resistance, (iii) Quantitative resistance (QR), (iv) Durable resistance, (v) Gene pyramiding and (vii) Gene stacking. MAS insects resistance in rice (Shabanimofred et al, 2015;Venkanna et al, 2018;Jaiswal et al, 2018) Striga resistance in sorghum (Yasir and Abdalla, 2013, Yohannes et al, 2015Ali et al, 2016), multiple insects resistance in maize (Badji et al, 2018) multiple resistances to herbicides (Gressel, 2000;Neve et al, 2009) Quantitative resistance (QR)…”
Section: Variants Of Plant Resistance To Pestsmentioning
confidence: 99%