Every year, the Catalan Nutrition Center (CCNIEC) of the Institute for Catalan Studies (IEC) in Catalonia (Spain) recognizes the best doctoral theses’ in the field of food science and nutrition. In the current edition, our very own Beatriz Quintanilla Casas has been awarded the CCNIEC-Eroski Foundation 2022 Prize for her doctoral thesis, titled “Development of innovative analytical techniques for olive oil authentication and quality assessment”.
In all honesty, this is really something that happened on our duty. The work was carried out within the Lipids and bioactive compounds research group at the department of Nutrition, Food Science and Gastronomy of University of Barcelona (Spain). But we are happy and proud regardless!
We are extremely happy and proud to announce our first official version of the PARADISe software. It transforms untargeted GC-MS data from large sample sets into peak tables in a very simple, robust and reproducible manner. And it is very easy to use. You can find it at
where you can also find information on how to use the software in the form of a tutorial and a little instruction video.
Please try it and let us know what you think. We are very happy for all the support especially from Arla and the Danish Dairy Research Foundation who has made this work possible.
History. PARADISe has been in the making for more than a decade and has been developed with generous funding from numerous companies and agencies. Here is a list of some of the most important contributors to the software:
Have you ever struggled with building complex decision trees with classification models? It can be very time consuming and you often are not sure you achieved optimal results. We have automated the process with the code AHIMBU that you can find here. You can read the paper about this in Journal of Chemometrics.
The aim of this project is to create a concept design for a novel fluorescence-based instrument for the objective assessment of wine quality. This will be done to meet the demand from winemakers for a fast, easy-to-use measurement of the chemicals important for the sensorial attributes of wine. The project will achieve this by establishing an objective rapid method for determining low concentration wine quality parameters using fluorescence spectroscopy and advanced multivariate data modeling.
The PhD is a so-called industrial PhD – a collaboration between FOSS and Åsmund Rinnan. But more importantly, the PhD student is Helene Halberg which you should contact for more information.
The Physicochemical Stability of Oat-based Drinks – with an Emphasis on Rapid Spectroscopy and LF-NMR Characterisation
The oat-based drink is a popular dairy alternative, and the product is considered healthy due to the presence of β-glucan dietary fibers. However, natural plant-based drinks without additives have less physical stability than cow’s milk. Many chemical and physical factors affect product stability. The measurements of these parameters are often laborious, lengthy, or change the food matrix, which introduces bias. Spectroscopy and low-field NMR methods have the benefit of providing rapid and in-situ measurements that give multivariate information. The use of the proper chemometrics technique is crucial for interpreting these datasets. This thesis aims to investigate the various stability profile in oat-based drinks using spectroscopic and low-field NMR methods
Data comes from a MSc thesis project and consists of 216 samples of granules in glass vials analysed by NIR. A downscaled dry granulation process was developed during the project and designed such that three quality attributes variances could be controlled:
Model API concentration (Bovine Serum Albumin, BSA)
Six levels ranging from 2% to 15% w/w
Three levels, controlled by material mass used during compaction (1 g, 1.5 g and 2 g).
Four levels, controlled by the use of desiccators with relative humidity ranging from 11% to 62%.
Triplicates were produced of each attribute combination. Each sample was measured three times using a Bruker MPA II NIR equipment with resolution 8 cm-1, 64 scans and in the spectral range 11550 cm-1 to 3950 cm-1 for each measurement. The samples were measured before and after moisturization. Download the data here.