Omics Platform Technologies for Discovery and Understanding the Systems Biology of Oil Palm

Abstract

Palm oil is the leading vegetable oil in terms of volume in the world market. Indonesia and Malaysia are the top producers and exporters of the commodity. The global production of palm oil reached 73.5 million tonnes in the period 2018/2019, up from approximately 70.5 million tonnes in 2017/2018. Oil palm is the most productive crop in the world being 10 times more productive than soyabean which produces only about 0.45 t oil per hectare. Nonetheless, the industry is continuously under pressure to improve productivity and sustainability. This will require concerted innovations across the entire palm oil supply chain and fully committed research efforts including upstream technologies to expedite crop improvement. At the Malaysian Palm Oil Board (MPOB), research efforts at development of tools for improving oil palm traits by genetic modification have been augmented more recently with omics-based approaches and all of these innovations are synchronised towards improved product quality. Omics is a multidisciplinary field encompassing genomics, epigenomics, transcriptomics, proteomics and metabolomics. Each of these fields provides an opportunity to understand and view oil palm biology from a global perspective, enabling accelerated discoveries for improved productivity and the development of new and improved varieties. An integrative omics approach promises great value in both phenotyping and diagnostic analyses. With the current technological capabilities, metabolomics is also being exploited for identifying unique chemical fingerprints to detect product contamination and adulteration in oil palm. This effort is actively being conducted in order to position the oil palm industry to meet and optimise the delivery of the highest quality oil with minimum environmental and social concerns. In this review, an overview is given on the current knowledge and progress made in oil palm research, focusing on the application of omics strategies and their integration with high-throughput technologies for oil palm crop improvement, development of geographical traceability system and ensuring that palm oil is free from residual oil contamination.

Predicting Heritability of Oil Palm Breeding Using Phenotypic Traits and Machine Learning

“…Bunch production [47], Bunch index [25,29,45,46]. Bunch Quality Traits Pulp-to-fruit ratio (PF, in %), fruit-to-bunch ratio (FB, in %), oil extraction rate (OER, in %), and oil-to-pulp ratio (OP, in %) [30].…”

“…The fruit traits, including Oil-to-Dry Mesocarp (O/DM), Mesocarp-to-Fruit (M/F), Shell-to-Fruit (S/F), and Kernel-to-Fruit (K/F) [12,48]. Oil-bearing mesocarp [18], Shell-to-Fruit (S/F%) [47], Shell Thickness [39], Fruit traits such as high mesocarp to fruit, reasonable stalk length, good fruit set, and low parthenocarpy [25], fruit form, fruit quality, and fruit ripeness [49].…”