Oil palm geneticist (Montpellier, France, 2020-present)
Oil palm geneticist (Yaoundé, Cameroun, 2015-2020)
Oil palm geneticist (Montpellier, France, 2011-2015)
Oil palm breeder/Geneticist (Pobè, Benin, 2006-2011)
My researches primarily focus on breeding methodologies in order to maximize the genetic gain. I am mostly interested in quantitative genetics, genomics and statistics applied to oil palm and rubber tree breeding.
Improving the accuracy of genomic predictions in an outcrossing species with hybrid cultivars between heterozygote parents: a case study of oil palm (Elaeis guineensis Jacq.) (Feb 15, 2022, Molecular Genetics and Genomics)
Optimizing imputation of marker data from genotyping-by-sequencing (GBS) for genomic selection in non-model species: Rubber tree (Hevea brasiliensis) as a case study (Jan 29, 2021, Genomics)
Genomic predictions improve clonal selection in oil palm (Elaeis guineensis Jacq.) hybrids (final version published Aug. 8, 2020 in Plant Science)
See list of main publications on CIRAD website or Google Scholar (and full list here)
***Reviewing activities: Industrial Crops and Products, Plos One, etc.
***PhD studies (2011 - 2014): Factors controling the efficiency of genomic selection in oil palm (Elaeis guineensis)
Agricultural production must increase at an unprecedented
rate to meet the strong growth expected in food demand. Genomic selection (GS)
could contribute to reaching this goal by allowing selection of individuals on
their sole genotype, making breeding more efficient. Breeding for yield in oil
palm, the first oil crop in the world, is currently based on hybrid production
by reciprocal recurrent selection. The integration of GS to this scheme would
have major repercussions. My thesis aimed to assess the potential of GS to
predict hybrid combining abilities in parental populations (Deli and group B).
[quantitative genetics, computer simulation, oil palm breeding, genomic selection]