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.
Here is (most of) the chemometrics group meeting up to discuss how we can best create synergy between our many projects on a cold November day in 2022
On November 11, 2022, Margherita Tonolini very successfully defended her PhD thesis entitled “Process Analytical Technology in whey processing: on-line selective protein quantification”.
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.
Tiffany Patra defended her thesis entitled:
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
- Particle size
- Three levels, controlled by material mass used during compaction (1 g, 1.5 g and 2 g).
- Moisture content
- Four levels, controlled by the use of desiccators with relative humidity ranging from 11% to 62%.
Menstrual effluent has the potential to act as a versatile biospecimen allowing for longitudinal studies providing chemical snapshots of multiple hours, with a non-invasive sampling method that can be done from home. Half of the menstrual effluent is blood, apart from this it consists of vaginal fluids, epithelia, enzymes and tissue from multiple origin of the abdomen. Sampling menstrual effluent from 20 women for 3 cycle days during 3 menstrual cycles and a venous blood sample at each period, we will characterize the metabolome using H-NMR. An explorative and comprehensive data analysis is examining both natural variance, lifestyle parameters, day-to-day and period-to-period differences and correlations with venous blood metabolome.
Giacomo Baccolo has defended his PhD thesis called “Chemometrics approaches for the automatic analysis of metabolomics GC-MS data”. The work was a joint venture between our chemometric group and Davide Ballabio from Milano. You can download the thesis here.
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Welcome to our new website!
Take a look around and see if you can use some of our datasets or other resurses.
Also try take a look at our Youtube Channel, lots of pretty awesome stuff there as well!