Combining Ability for Grain Yield of Imidazolinone-Resistant Maize Inbred Lines Under Striga (Striga hermonthica) Infestation

Author(s):  
I.H. Rwiza ◽  
M. Mwala ◽  
A. Diallo
2007 ◽  
Vol 24 (3) ◽  
pp. 133-137 ◽  
Author(s):  
D. W. Gissa ◽  
H. Zelleke ◽  
M. T. Labuschagne ◽  
T. Hussien ◽  
H. Singh

2021 ◽  
Vol 4 (3) ◽  
pp. 286-304
Author(s):  
Lemi Mideksa Yadesa ◽  
Sentayehu Alamerew ◽  
Berhanu Tadesse

In spite of the importance of quality protein maize to alleviate protein deficiency, almost all maize varieties cultivated in Ethiopia are normal maize varieties, which are devoid of lysine and tryptophan. Perusing the combining ability of QPM inbred for grain yield and its components is vital to design appropriate breeding strategies for the development of nutritionally enhanced maize cultivars. A line x tester analysis involving 36 crosses generated by crossing 9  elite maize inbred lines with 4 testers were evaluated for different desirable agronomic traits during the 2019 main season at BNMRC and JARC. The experiment was conducted using alpha lattice design with 3 replications. The objectives were to determine the combining ability of quality protein maize inbred lines, adapted to mid altitude agroecology of Ethiopia for agronomic traits. The crosses were evaluated in alpha lattice design replicated 3 times. Analyses of variances showed significant mean squares due to crosses for almost all the traits studied. GCA mean squares due to lines and testers were significant (P<0.05 or P<0.01) for most studied traits. SCA mean squares were also significant for most attributes across locations. The comparative importance of GCA and SCA variances observed in the current study for most studied traits indicated the preponderance of additive genetic variance in governing these attributes. Only L3 was the best general combiner for grain yield. Inbred line L3, for days to anthesis and L5 for days to silking had negative and significant GCA effects. L5 and L6 displayed negative and significant GCA effects for plant and ear height. Crosses, L2xT4, L3xT4, L4xT4, L5xT2, L6xT3, L7xT2, L9xT1 and L9xT4 were good specific combiners for grain yield. In general, these genotypes help as a source of promising alleles that could be used for forthcoming breeding work in the development of quality protein maize cultivars with desirable traits.


2021 ◽  
Author(s):  
Siphiwokuhle Funani Shandu ◽  
John Derera ◽  
Kingston Mashingaidze ◽  
Edmore Gasura

Abstract An efficient hybrid breeding program defines and utilizes few heterotic groups. The objectives of this study were to determine genetic diversity and alignment of South Africa maize inbred lines collection towards tropical and temperate testers. Forty-two maize inbred lines were genotyped with 56110 single nucleotide polymorphism (SNP) DNA markers, using the Illumina MaizeSNP50 Bead chip. The 42 lines were crossed to two tropical and two temperate inbred line testers. The testcrosses were evaluated across seven environments, in South Africa, during 2014-2016. Genotypes and specific combining ability (SCA) effects of hybrids were significantly different (P<0.05) for grain yield. There was a weak correlation between molecular genetic distances and both grain yield mean and specific combining ability effects of hybrids, indicating that productivity of maize inbred lines could not be reliably determined based on molecular genetic distances. The SCA data was capable of classifying these maize inbred lines into three heterotic groups with respect to both tropical and temperate testers. Only a few lines could not be grouped on the basis of SCA data. The study also indicated high level of diversity among the maize inbred lines, which was shown by both the dendogram and molecular genetic distances. The SNP marker data classified the inbred lines into 11 clusters that could be simplified into three major groups of normal maize endosperm and two groups of quality protein maize (QPM) endosperm types. However, the SNP data indicated that maize lines were more aligned towards tropical than temperate inbred testers. This information would be useful for simplifying heterotic classification of the lines with profound implications for breeding progress.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. E. Stanley ◽  
A. Menkir ◽  
B. Ifie ◽  
A. A. Paterne ◽  
N. N. Unachukwu ◽  
...  

AbstractStriga hermonthica is a widespread, destructive parasitic plant that causes substantial yield loss to maize productivity in sub-Saharan Africa. Under severe Striga infestation, yield losses can range from 60 to 100% resulting in abandonment of farmers’ lands. Diverse methods have been proposed for Striga management; however, host plant resistance is considered the most effective and affordable to small-scale famers. Thus, conducting a genome-wide association study to identify quantitative trait nucleotides controlling S. hermonthica resistance and mining of relevant candidate genes will expedite the improvement of Striga resistance breeding through marker-assisted breeding. For this study, 150 diverse maize inbred lines were evaluated under Striga infested and non-infested conditions for two years and genotyped using the genotyping-by-sequencing platform. Heritability estimates of Striga damage ratings, emerged Striga plants and grain yield, hereafter referred to as Striga resistance-related traits, were high under Striga infested condition. The mixed linear model (MLM) identified thirty SNPs associated with the three Striga resistance-related traits based on the multi-locus approaches (mrMLM, FASTmrMLM, FASTmrEMMA and pLARmEB). These SNPs explained up to 14% of the total phenotypic variation. Under non-infested condition, four SNPs were associated with grain yield, and these SNPs explained up to 17% of the total phenotypic variation. Gene annotation of significant SNPs identified candidate genes (Leucine-rich repeats, putative disease resistance protein and VQ proteins) with functions related to plant growth, development, and defense mechanisms. The marker-effect prediction was able to identify alleles responsible for predicting high yield and low Striga damage rating in the breeding panel. This study provides valuable insight for marker validation and deployment for Striga resistance breeding in maize.


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