Name: Akinwale Richard
Qualifications: B. Agric., M. Sc., Ph.D
Status: Associate Professor (Reader)
Specialization: Plant breeding and Biometrics
Highlights of my research focus
- Germplasm collection and characterization of orphan crops of tropical origin.
- Genetic analysis of the performance of tropical maize inbreds under major production stresses and non-stress conditions
- Identification of adaptive traits for Striga hermonthica resistance, drought and low N tolerance, among early and extra-early maturing maize groups and computation of a new base index for selecting for Striga tolerant maize genotypes in these maturity groups.
- Identification of distinct heterotic groups among tropical early and extra-early maize germplasm under stress and non-stress environments for the purpose of hybrid development and population improvement.
- Determination of mode of inheritance and heterotic response of tropical maize for drought at seedling, vegetative, flowering and grain filling periods, soil low-nitrogen, Helminthosporiutm urcicum, and Striga hermonthica parasitism. In addition, I am involved in studying the genetics of seed quality traits as well as Fe and Zn contents of maize
- Identification of proven inbred testers for the purpose of test cross-development and line x-tester studies.
- Characterization and classification testing sites for early and extra-early maize across all agroecological zones in West and Central Africa into mega-environments and determining core testing sites for easy
management of evaluation trials of maize genotypes without sacrificing precision.
- Testing the usefulness and efficiency of molecular markers (Simple sequence repeat, (SSR) and Single Nucleotide Polymorphism (SNPs) in assessing genetic diversity and identifying QTLs and genomic regions
controlling tolerance/resistance to stresses among tropical maize.
Some of my professional accomplishments
- I have authored and co-authored over 50 scientific articles published in reputable local and international journals.
- I have supervised and co-supervised 15 Master and Doctor of Philosophy Students in the field of Plant Breeding and Genetics
- I am highly proficient in field plot technique, conduct and management of breeding trials at local, national,
regional and international levels, analysis and management of data generated from such trials using statistical
software such as Microsoft Excel, SAS, GENSTAT, FieldBook, Breeding Management System and GGEBiplot.
Direction for future research
- My future projection is to explore the use of machine learning algorithms and artificial intelligence for better phenotyping (phenomics) of crop responses under stress conditions and for predicting crop hybrid performance
- Use of molecular techniques in enhancing tolerance of crops to production stresses and nutritional quality.