Correlation analysis for maize grain yield, other agronomic parameters and Striga affected traits under Striga infested/free environment

Halidu, Jamilu; Abubakar, L.; Izge, U. A.; Ado, S. G.; Yakubu, H.; Haliru, Bello Sani

doi:10.5897/jpbcs2013.0410

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Grain yield displayed significant and positive genetic phenotypic correlations with ears per plant and plant height, but negative with days to 50% anthesis, days to 50% silking, anthesis silking interval, and Striga damage ratings. Positive correlations observed mean that grain yield increases with ears per plant and plant height; which indicates that more leaves photosynthesis and heavier grain yield (Halidu et al,2015). These traits are probably genetically dependent and can be included in the base index for selecting for improved grain yield in maize under Striga infestation and was in agreement with Badu-Apraku et al (2007) for ear aspect as secondary trait.…”

Section: Discussionsupporting

confidence: 83%

Agronomic Performance Of S1 Maize Lines Derived From A Bi-Parental Cross Under Infested And Striga Free Environments

Yacoubou

Wallis

Salami

et al. 2021

ESJ

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Striga hermonthica, causes up to 100% yield loss in maize production in sub-Saharan Africa. Developing Striga resistant maize cultivars could be a major component of integrated Striga management strategies. This study aims at assessing the agronomic performance of S1 breeding lines in improving maize for Striga resistance. Two hundred S1 lines have been evaluated under artificial infestation Striga and Striga-free conditions in Benin for two years during 2018 and 2019 growing seasons using alpha-lattice design (51 x 4) with two replicates. Twelve agro-morphological and Striga adaptive traits have been assessed. The tested lines have displayed high genetic variability for most agronomic and Striga adaptive traits. The S1 lines exhibited high grain yield than their parents with averages of 2,552.72±593 kg ha-1 and 2,965.67±635.86 kg ha-1 under Striga artificial infestation and Striga-free conditions, respectively. Grain yield has displayed high positive and significant genetic and phenotypic correlations with ears per plant and high negative correlations with days to 50% silking, ears aspect, and Striga damage rating at 8 and 10 weeks after planting (WAP). Useful traits like ears per plant, days to 50% silking, ears aspect, number of emerged Striga plants and Striga rating at 10 WAP could assist for indirect selection under Striga conditions. Based on the selection index, a total of 15 S1 lines have been identified as top ranking and can be used as sources of resistance or tolerance genes to Striga and further improvement in maize breeding in future.

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Section: Discussionsupporting

confidence: 83%

Agronomic Performance Of S1 Maize Lines Derived From A Bi-Parental Cross Under Infested And Striga Free Environments

Yacoubou

Wallis

Salami

et al. 2021

ESJ

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“…This might be due to good plant vigor with a plant height of 285 cm of this hybrid. Increased plant height provides more green areas for increased photosynthetic activities and assimilates needed for grain filling (Haseeb-ur-Rehman et al 2010) resulting in a highly significant positive genotypic correlation of plant height with grain yield (Halidu et al 2015). Similarly, the overall yield of the hybrid RL-150/RL-111 having the highest plant height of 253 cm yielded 7177 kg ha -1 across the mid-hill region during summer 2017/18.…”

Section: Grain Yieldmentioning

confidence: 99%

On-farm evaluation of hybrid maize (Zea mays L.) in different ecology of Nepal

Koirala¹,

Adhikari²,

Tripathi³

2020

Azarian J Agric

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Agro-Morphological Characterization of Kenyan Slender Leaf (Crotalaria brevidensandC. ochroleuca) Accessions

Mwakha

Gichimu

Neondo

et al. 2020

International Journal of Agronomy

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Slender leaf (Crotalaria spp) is among the indigenous and underutilized vegetables in Kenya whose production is limited to the Western and Coastal regions of the country. For a long time, this crop has been neglected in terms of research and genetic improvement. There is therefore scanty information on its morphological diversity and agronomic performance, hence the need for this study. Field experiments were carried out for two seasons in October to December 2018 and March to May 2019. The experiments were laid out in Randomized Complete Block Design with 29 accessions and replicated three times. Both qualitative and quantitative data were recorded from the accessions based on the Crotalaria descriptors. Quantitative data were subjected to analysis of variance using XLSTAT Version 2019, and accession means were separated using Student’s Newman Keuls test at 95% level of confidence. Both qualitative and quantitative data were subjected to multivariate cluster analysis, and a dendrogram was constructed using the unweighted pair-group method with arithmetic average. The principal component analysis was conducted to obtain information on the importance of the characters. Significant variation in agro-morphological traits was found within and between the two species. Cluster analysis grouped the accessions into seven major classes with a between-classes diversity of 75.13% and a within-classes diversity of 24.87%. This study sets the basis for genetic improvement of slender leaf in Kenya since the observed diversity can be exploited in selection for intraspecific and interspecific hybridization.

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Correlation analysis for maize grain yield, other agronomic parameters and Striga affected traits under Striga infested/free environment

Cited by 5 publications

References 4 publications

Agronomic Performance Of S1 Maize Lines Derived From A Bi-Parental Cross Under Infested And Striga Free Environments

Agronomic Performance Of S1 Maize Lines Derived From A Bi-Parental Cross Under Infested And Striga Free Environments

On-farm evaluation of hybrid maize (Zea mays L.) in different ecology of Nepal

Agro-Morphological Characterization of Kenyan Slender Leaf (Crotalaria brevidensandC. ochroleuca) Accessions

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