Screening Maize (Zea mays L.) Genotypes by Genetic Variability of Vegetative and Yield Traits Using Compromise Programming Technique.

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dc.contributor.authorIdris, Atif Elsadig
dc.contributor.authorMohammed, Hassan Ibrahim
dc.date.accessioned2015-08-24T08:23:43Z
dc.date.available2015-08-24T08:23:43Z
dc.date.issued2012-04
dc.description.abstractThe present study was made to develop a suitable procedure for selecting the most sustainable maize genotype to grow by considering genetic variability for vegetative, yield and yield components under irrigated farming. The experiment was conducted at the experimental farm, College of Agricultural studies, Sudan University of Science and Technology, Shambat, during summer seasons of 2007/08 and 2008/09, respectively. Significant variability was observed for plant height, stem diameter, number of rows per cob and ear length during the first season 2007/08 and for days to 50% flowering and 100-seed weight during the second season 2008/09. Frantic genotype scored maximum seed weight (81.0g) while Baladi had least seed weight (57.48g). Frantic genotype had maximum grain yield (0.577 ton/ha), while minimum grain yield ton/ha was recorded in Baladi (0.473 ton/ha). Data recorded for heritability showed that days to 50% flowering had maximum heritability (79.1%) while the minimum heritability (4.46%) was recorded for 100 seed weight. The present study revealed considerable amount of diversity among the tested populations which could be manipulated for further improvement in maize breeding in Sudan. However, significant differences of grain yield were observed among varieties. Due to the observed variability multi objective compromise programming technique is employed to screen these Maize (Zea mays L.) genotypes according to their vegetative and yield traits for purpose of selecting the best one that suit irrigated farming conditions of Shambat area. The study ranked the different Maize (Zea mays L.) genotypes and recommends the best alternative. Ranking of alternatives was explored in reference to selection criteria weights preferred by an agronomist, animal production specialist and nutrition scientist in comparison to equal weights.en_US
dc.identifier.citationIdris Atif Elsadig, Mohammed Hassan Ibrahim. Screening Maize (Zea mays L.) Genotypes by Genetic Variability of Vegetative and Yield Traits Using Compromise Programming Technique. British Biotechnology Journal. 2012 Apr; 2(2): 102-114.en_US
dc.identifier.urihttps://imsear.searo.who.int/handle/123456789/162369
dc.language.isoenen_US
dc.source.urihttps://sciencedomain.org/abstract/515en_US
dc.subjectHeritabilityen_US
dc.subjectGenetic variabilityen_US
dc.subjectMaizeen_US
dc.subjectGenotypesen_US
dc.subjectmultiple-objective optimizationen_US
dc.subjectmulti-criteriaen_US
dc.subjectcompromise solutionsen_US
dc.titleScreening Maize (Zea mays L.) Genotypes by Genetic Variability of Vegetative and Yield Traits Using Compromise Programming Technique.en_US
dc.typeArticleen_US
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