📢 Pre-conference workshop:
Open-source chemometrics for real-world NIR handheld spectroscopy

A hands-on course at CAC 2026 (International Conference on Chemometrics in Analytical Chemistry):
https://congressos.urv.cat/cac-2026/preliminary-courses

📅 29 June – 3 July 2026
📍 Tarragona, Spain (sunny and Mediterranean)

Fee: only 75 EUR, so reserve your seat asap

If you work with NIR, chemometrics, or deploy models in practice, this may be relevant.

#Chemometrics #NIRSpectroscopy #OpenScience #AnalyticalChemistry #soil

🚨 #publication alert!

Just a few days into the new year and we already have a published #paper first-authored by our PhD candidate Sarah. 🎉

It is the first study on the volatile emissions of Synchytrium endobioticum (potato wart disease) on potatoes. We identified seven possible marker compounds using TD-GC-MS and #chemometrics.

S. endobioticum is a highly potent fungus classified as a quarantine pathogen in the EU, since it can affect #potato fields for more than 40 years.

Our research offers new insights into the volatilome and may enable future screening methods for potato diseases.

Read more ➡️ https://link.springer.com/article/10.1007/s41348-025-01216-9

#voc #planthealth #gcms #analyticalchemistry #potatowartdisease

It took a while, but I'm finally back to writing my blog 😎

The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

Read more at https://nirpyresearch.com/information-entropy-spectra/

#MachineLearning #NIR #Physics

I used chembl-downloader to create some nice charts on how the number of compounds, assays, activities, and other entities in ChEMBL have grown over time

📖 https://cthoyt.com/2025/08/26/chembl-history.html

#chembl #chemistry #chemometrics #chemoinformatics #cheminformatics #rdkit #cdk #proteochemometrics

Our first step towards a semi-automated approach for finding relevant VOC profiles of plant pests and pathogens has recently been published in Scientific Reports. 🥼🦠🔬

It's the first publication of our PhD-student Sarah! 🎉🥳
She developed a multivariate evaluation method of GC-MS data and found a few more possible VOC markers for ALB infestation in maple trees compared to a manual evaluation.

Read more: https://rdcu.be/exF4r

#science #publication #research #volatiles #PlantProtection #ALB #AsianLonghornedBeetle #QuarantinePests #chemometrics

📚 New post from me | Genetic Algorithm for Wavelength Selection Using NumPy

TL;DR A simplified implementation of a genetic algorithm (GA) for wavelength selection, using only @numpy and @sklearn

📝 Key Points:

🔸 The basics, including population, fitness function, crossovers, and mutations.

🔸 A step-by-step implementation of the GA for wavelength selection, with clear Python code examples.

🔸An example using NIR spectroscopy data to demonstrate the algorithm's application in selecting optimal wavelengths for predicting soil properties.
Improved regression results when comparing the performance before and after optimization.

This post may be valuable for spectroscopists, chemometricians, and data scientists looking to optimise feature selection in #spectroscopy datasets using evolutionary algorithms.

🌐 Full post available here
https://nirpyresearch.com/genetic-algorithm-wavelength-selection-numpy/

#chemometrics #python #numpy #MachineLearning

New publication: a novel quantitative method to validate accurate scale-up of chemical reactions in real time.

Discover the full methodology at https://oa.eu/E4xb6X

#datascience #chemometrics #cmc #pharma

☕ Here's a bit of technical content from me - today a deep dive on #baseline correction methods.

📈 Baseline correction is a preprocessing technique to remove background signal and isolate peaks in hashtag#spectroscopy data.

📝 In my recent post I discuss two methods:
1. Wavelet transform (WT) - Decomposes signal into components at different frequencies. Lowest frequency component represents baseline and can be removed.
2. Asymmetric least squares (ALS) - Fits a smooth baseline function, penalising positive deviations more than negative ones.

TL;DR: WT method is intuitive but can distort peaks. ALS produces better results.

🔎 Both methods are applied on a #Raman spectrum and an X-ray fluorescence (#XRF) spectrum. ALS gives a cleaner baseline correction and it's effective for removing broad, slowly varying background while preserving sharper spectral features.

#chemometrics #Python #MachineLearning #wavelets #regression

https://nirpyresearch.com/two-methods-baseline-correction-spectral-data/