Skip to content
Research Article Open access CC BY 3.0

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

Atif Elsadig Idris, Hassan Ibrahim Mohammed

Biotechnology Journal International · pp. 102–114 · Published 17 Jun 2012

10.9734/BBJ/2012/1292

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.

Heritability Genetic variability Maize Genotypes multiple-objective optimization multi-criteria compromise solutions

References (15)

  1. 1 Biometrical methods in quantitative genetic analysis
  2. 2 A concept of compromise solutions and the method of the displaced ideal [DOI]
  3. 3 Genetic diversity in major farm crops on the farm and in reserve [DOI]
  4. 4 Genotypic variation between maize (Zea mays L.) single cross hybrids in response to drought stress [DOI]
  5. 5 Combining ability for maize grain yield and other agronomic characters in a typical southern guinea savanna ecology of Nigeria [DOI]
  6. 6 RELATIVE PERFORMANCE OF SELFED AND OUTCROSSED PROGENY IN IMPATIENS CAPENSIS [DOI]
  7. 7 PREFERENCE RANKING OF ALTERNATIVE IRRIGATION TECHNOLOGIES VIA A MULTICRITERION DECISION-MAKING PROCEDURE [DOI]
  8. 8 Reproductive and stay-green trait responses of maize hybrids, improved open-pollinated varieties and farmers' local varieties to terminal drought stress
  9. 9 Estimation of Quantitative Genetic Parameters for Nitrogen Use Efficiency in Maize under Two Nitrogen Rates [DOI]
  10. 10 Genotypic and phenotypic relationship between physiological and grain yield related traits in four maize (Zea mays L.) crosses of subtropical climate [DOI]
  11. 11 Genetic variability for vegetative and yield traits in maize (Zea mays L.) genotypes
  12. 12 Maturity Studies in Hybrid and Open Pollinated Cultivars of Maize [DOI]
  13. 13 Performance of Sorghum (Sorghum vulgare) and Maize (Zea mays) as Forages in Irrigated Saline Soils of the Sudan [DOI]
  14. 14 Intérêt de la valeur propre des descendances S1 associée à la valeur en croisement avec un testeur pour la sélection du maïs fourrage [DOI]
  15. 15 Genetic variation, heritability and genetic advance of quantitative characters in maize

Cited by 7

Screening of suitable genotype for Bangladesh conditions based on genetic variability and path analysis in F2 white maize populations

Md. Mahmudul Hasan, Jamilur Rahman, Fahmida Sultana · Crop Science · 2021

Showing 1 of 7 known citations — external sources report more than can currently be individually listed.

Related research

Article metrics

Real usage data collected on this platform.

65

Page views

0

PDF downloads

31

Outbound clicks

7

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.