Partial Least Squares (PLS) Regression in Food Analysis
Understanding PLS regression — the workhorse of quantitative chemometric analysis in food science.
Chemometrics
Chemometric methods and their applications in food science — from spectroscopy data analysis to quality control and safety testing.
📚 Knowledge Base
View all →NIR Spectroscopy for Food Quality Assessment
How near-infrared spectroscopy combined with chemometrics enables rapid, non-destructive food quality testing.
Introduction to Principal Component Analysis (PCA)
Learn the fundamentals of PCA and how it reduces dimensionality in spectroscopy data for food analysis.
🎓 Tutorials
View all →PCA for Food Classification with Python
A hands-on tutorial on using PCA to classify food samples based on spectral data using Python and scikit-learn.
📄 Documentation
View all →Spectral Preprocessing Methods Reference
Spectral Preprocessing Methods A reference guide to common preprocessing techniques used in chemometric analysis of spectral data. Standard Normal Variate (SNV) Centers and scales each…
📜 White Papers
View all →NIR Spectroscopy for Olive Oil Authentication: A Case Study
This paper presents a chemometric approach using NIR spectroscopy and PLS-DA to detect adulteration in extra virgin olive oil, achieving 97% classification accuracy across 500+…
▶️ Video Training
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Introduction to Chemometrics in the Food Industry
A 1-minute overview of chemometric methods and how they are transforming food quality analysis.
🔧 Tools
View all →The Unscrambler X
Industry-leading multivariate data analysis and chemometrics software by CAMO Analytics (Aspen Technology).