Chemometrics in spectroscopy. Part 1. Classical chemometrics

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Principles and Applications of Hyperspectral Imaging in Quality Evaluation of Agro-Food Products: A Review (2012, methodology): “The number of LVs to be extracted depends on the prediction error, typically done by cross validation, while the optimum number of latent variables used to build the calibration model depends on the sample properties and the target for both PCR and PLSR (Geladi, 2003).”
Characterization of Organosolv Lignins using Thermal and FT-IR Spectroscopic Analysis (2013, methodology): “PCA is a statistical method that visually represents the differences in a data set (Martens and Naes 1989; Geladi 2003).”
Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review (2019, methodology): “Moreover, correlating the spectral signatures with soil properties requires the use of multivariate statistical methods also known as chemometrics [36].”
Application of Near and Mid-Infrared Spectroscopy to Determine Cheese Quality and Authenticity (2008, methodology): “Chemometrics can be described as going beyond the limitations of univariate statistics using multivariate methodologies derived from mathematics, statistics, and computer science ( Geladi 2003 ).”