NutraCast: Genetic analysis predicts sunflower oil composition
To get a headstart on all this, researchers at Skoltech University in Russia performed genetic analysis of a Russian sunflower collection and identified genetic markers that can help predict the oil's fatty acid composition. The research was published in BMC Genomics.
The team looked at species from two major Russian sunflower gene banks as well as a collection from the seed-producer Agroplasma. Their genetic analysis covered 601 lines of cultivated sunflower to check genetic diversity against the global collection and compare the results with chemical tests of oil obtained from these lines. Bioinformatic analysis revealed genetic markers that can help control the oil's fatty acid content.
"The reason we chose the sunflower is that it is a key source of vegetable fats, and Russia is the world's leading supplier of sunflower oil. You can vary the oil's fatty acid composition—which was the focus of our research—to obtain oils with different properties suitable for roasting, dressings or industrial uses," said Skoltech PhD student and study co-author Rim Gubaev.
This is the first large-scale implementation of high-throughput lipidomic profiling to sunflower germplasm characterization. This study contributes to the genetic characterization of Russian sunflower collections, which made a substantial contribution to the development of sunflower as the oilseed crop worldwide, and provides new insights into the genetic control of oil composition that can be implemented in future studies.
To hear more about the many uses of sunflower oil and what other species the researchers are working on, listen to the NutraCast.
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NutraCast is a podcast that focuses on insights from inside the nutrition industry. It is a production by NutraIngredients-USA. Music by Kevin Macleod.
