Qlucore helps reduce plants' dependancy on fungicides
Scientists at the Institution of Plant Protection Biology within the Swedish University of Agricultural Sciences have been researching how to reduce the dependence on chemical fungicides in farming, assisted by Qlucore Omics Explorer.
The scientists used Qlucore Omics Explorer to aid their research which focused on understanding plant defence mechanisms and so produce plants that are more resistant to disease, which will lessen pesticide use, and ultimately benefit the environment.
The research is focused on how plants defend themselves against oomycetes and fungi. Oomycetes, also known as ‘water moulds’, are a group of several hundred organisms that include some of the most devastating plant pathogens. The team of 16 at the Institution of Plant Protection Biology have been studying biochemical components of plant defense and the interactions with pathogens and trying to identify resistance factors that can be used in future breeding for disease resistance crops, and in developing methods for induced resistance by applying non-toxic inducing agents in order to reduce the dependence on chemical fungicides.
In the past, one of the major problems facing the scientists was how to handle the increasingly vast amounts of data that was being produced from their research.
'Seeing structures in the data and finding meaningful biology in them has been a problem,' commented Dr Erik Alexandersson, Assistant professor at SLU Alnarp, Institution of Plant Protection Biology.
‘We have used Qlucore both for gene expression and quantitative proteomics data,' continued Dr Erik Alexandersson. ‘Some of the sampling is done in the field in order to obtain molecular data in a realistic setting as it would be out in the farm avoiding laboratory artifacts. We see clear differences in the mechanisms at play in these two settings. Qlucore has turned out to be very powerful in handling noisy data and quickly assessing underlying structures not relevant to the research question. We were recently able to “save” a noisy dataset by taking the set-up time into account and use the function “eliminate factor” in Qlucore.’
By the active use of Visualisation techniques important structures and patterns can be identified quickly, with the user getting instant feedback. Qlucore Omics Explorer allows 3D modelling and the ability to change parameters quickly and easily which can make the whole process of analysis more efficient.