Linear model to predict holocellulose content from MIR spectra from Teickner and Knorr (2022)

model_holocellulose_2 is a linear model to predict holocellulose mass fractions [g/g] in samples based on mid infrared spectra. Predictions with this model can be generated with irp_holocellulose_2().

Usage

model_holocellulose_2

Format

An object of class brms::brmsfit-class().

Source

The model is described in Teickner and Knorr (2022) . The data set was derived from https://www.nature.com/articles/s41467-018-06050-2 and published by Hodgkins et al. (2018) under the CC BY 4.0 license https://creativecommons.org/licenses/by/4.0/. Hodgkins et al. (2018) originally derived the data on holocellulose content from De La Cruz, Florentino B. et al. (2016) https://www.liebertpub.com/doi/full/10.1089/ees.2014.0402.

Details

The model was trained on the data from Hodgkins et al. (2018) (available via ir::ir_sample_data()) and is described in Teickner and Knorr (2022) . See model_holocellulose_2_config() for details on how the training spectra were preprocessed prior model fitting.

The model is an improved version of irp_content_h_hodgkins_model (Teickner and Knorr 2022) . It is a Bayesian beta regression model using all binned spectral variables for prediction.

Note

Note that this is a preliminary model only which has not been fully validated for peat samples yet and which has known limitations in predicting contents for peat samples (Teickner and Knorr 2022) .

References

De La Cruz, Florentino B., Osborne J, Barlaz MA (2016). “Determination of Sources of Organic Matter in Solid Waste by Analysis of Phenolic Copper Oxide Oxidation Products of Lignin.” Journal of Environmental Engineering, 142(2), 04015076. ISSN 0733-9372, doi:10.1061/(ASCE)EE.1943-7870.0001038 .

Hodgkins SB, Richardson CJ, Dommain R, Wang H, Glaser PH, Verbeke B, Winkler BR, Cobb AR, Rich VI, Missilmani M, Flanagan N, Ho M, Hoyt AM, Harvey CF, Vining SR, Hough MA, Moore TR, Richard PJH, De La Cruz, Florentino B., Toufaily J, Hamdan R, Cooper WT, Chanton JP (2018). “Tropical peatland carbon storage linked to global latitudinal trends in peat recalcitrance.” Nature communications, 9(1), 3640. doi:10.1038/s41467-018-06050-2 .

Teickner H, Knorr K (2022). “Improving Models to Predict Holocellulose and Klason Lignin Contents for Peat Soil Organic Matter with Mid Infrared Spectra.” Soil and methods. doi:10.5194/soil-2022-27 .