Predicting lignin content of wood samples with FTIR spectra: Building a principal component regression model in data of Norway spruce clones
This research study explores how FTIR spectra can be used to predict lignin content in wood samples from Norway spruce clones. It presents a principal component regression model, connecting spectroscopic data with statistical analysis in a focused application of data-driven wood science.
About This Book
This study examines the prediction of lignin content in wood samples from Norway spruce clones.
It focuses on Fourier-transform infrared spectroscopy, commonly abbreviated as FTIR, as the source of spectral data.
The work develops a principal component regression model using data from the spruce samples.
It is suited to readers interested in wood science, spectroscopy, forestry research, and applied statistical modeling.
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