British Biotechnology Journal, ISSN: 2231-2927,Vol.: 2, Issue.: 2 (April-June)
Screening Maize (Zea mays L.) Genotypes by Genetic Variability of Vegetative and Yield Traits Using Compromise Programming Technique
Atif Elsadig Idris1* and Hassan Ibrahim Mohammed2 1Department of Agronomy, College of Agricultural Studies, Sudan University of Science and Technology, Shambat, P.O. Box 71, Khartoum North, Sudan.
2Department of Agricultural Engineering, College of Agricultural Studies, Sudan University of Science and Technology, Shambat, P.O. Box 71, Khartoum North, Sudan.
Atif Elsadig Idris1* and Hassan Ibrahim Mohammed2
1Department of Agronomy, College of Agricultural Studies, Sudan University of Science and Technology, Shambat, P.O. Box 71, Khartoum North, Sudan.
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.
Heritability; Genetic variability; Maize; Genotypes; multiple-objective optimization; multi-criteria; compromise solutions.
Full Article - PDF Page 102-114
DOI : 10.9734/BBJ/2012/1292Review History Comments