Screening Maize (Zea mays L.) Genotypes by Genetic Variability of Vegetative and Yield Traits Using Compromise Programming Technique.
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Date
2012-04
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Abstract
The 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.
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Keywords
Heritability, Genetic variability, Maize, Genotypes, multiple-objective optimization, multi-criteria, compromise solutions
Citation
Idris 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.