Abstract
Acacia mangium Willdenow and Acacia auriculiformis A. Cunningham ex Bentham and their hybrid have become important planting species in Malaysia. Due to their high demand and consumption, development of high quality planting materials is desired. Conventional breeding of Acacia Miller is slow but the utilization of marker-assisted selection breeding can expedite the breeding process. Markers associated with quantitative trait loci (QTLs) required pedigreed populations whereas association mapping can be used directly on diverse germplasm. This study was conducted to screen provenances of A. mangium and A. auriculiformis of different geographical origins for their performance under the Malaysian environment. A. mangium exhibited superior traits compared to A. auriculiformis. More trait variation was observed within and between provenances of A. auriculiformis. Provenances from Queensland (QLD) were superior to those from Papua New Guinea (PNG) and Northern Territory. The best performing provenance with all three superior traits was from Claude River QTL of A. mangium and the worst was Bensbach Western Province, PNG belonging to A. auriculiformis. For individual traits like DBH, Morehead, PNG was superior. For plant height, Morehead, PNG was the superior provenance for A. mangium and Morehead River, QLD was from A. auriculiformis. For stem straightness the A. auriculiformis provenance Jardines Garden, QTL was superior to West of Morehead (PNG) for A. mangium. Multivariate analysis grouped provenances together based on similar traits and genetic similarity. These provenances can be used for seed families which can be treated as a homogeneous population for association mapping or for the development of segregating hybrid populations for Acacia breeding. For the purpose of utilization, provenances of A. mangium can be used for sawn timber. For fuelwood and charcoal industries, A. auriculiformis provenances should be preferred by selecting multi-stemmed trees. The most variable provenances with superior phenotypic traits can be integrated with the genotypic data e.g. single nucleotide polymorphism markers for association mapping to identify quantitative trait loci for marker-assisted breeding.
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