Saleh,H.SalehLi-Hammed,M. A.Li-HammedKushairi,A.KushairiRajanaidu,N.RajanaiduHassan,M.S.HassanChe Wan Zanariah Che Wan NgahSukaimi,Z.Sukaimi2024-05-302024-05-302018H, S., M. A., L.-H., A., K., N., R., Hassan, M. S., Che Wan Ngah, C. W. Z., & Sukaimi, J. (2018). Evaluation of Oil Palm Germplasm from Senegal and Gambia Using Chemometric Techniques. Malaysian Journal of Science Health & Technology, 1. https://doi.org/10.33102/mjosht.v1i1.92601-000310.33102/mjosht.v1i1.9https://mjosht.usim.edu.my/index.php/mjosht/article/view/9https://oarep.usim.edu.my/handle/123456789/15510Estimation of genetic diversity and determination of the relationships between collections are useful strategies for ensuring efficient germplasm collection and utilization. Oil palm germplasm materials collected from Senegal and Gambia maintained at the Malaysian Palm Oil Board (MPOB) Kluang Station were characterized for genetic diversity. A total of 44 agronomic traits of these oil palm materials wassubjected to simple statistics to evaluate the genetic variability; and to chemometric techniques (Principal Component Analysisand Cluster analysis) to identify the characters contributing to the overall variation and classify the materials based on similarity. The results of the variability profile showed that the Senegal and Gambia oil palm germplasm exhibited low to high variability for thevarious traits. Nine principal components with eigenvalue >1 accounted for 88 % of the total variation with Principal Component 1 capturing majority of the variation. Most of the traits especially oil yield and yield component traits, contributed to the divergence between and within the germplasm, indicating that wide variation exists in the germplasm materials studied. Ward's cluster analysis based on the PCA results grouped the 42 oil palm accessions into six clusters with cluster-VI having the highest number of members. Furthermore, there was no association between genetic diversity and geographical origin. The means of the agronomic traits of each cluster showed that cluster-III had the highest mean value of yield traits. Also, the cluster groups havinghigh mean values for desired traits could be selected for the traits per se. These accessions could be used to produce high yielding oil palm materials.en-USOil PalmGenetic DiversityChemometricsPrincipal Component AnalysisCluster AnalysisArticle162611