Linear model to predict Klason lignin content from MIR spectra from Teickner and Knorr (2022)
model_klason_lignin_2.Rd
model_klason_lignin_2
is a linear model to predict
Klason lignin mass fractions [g/g] in samples based on mid infrared spectra.
Predictions with this model can be generated with
irp_klason_lignin_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 Klason lignin 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_klason_lignin_2_config()
for details on how the training spectra were preprocessed prior model
fitting.
The model is an improved version of irp_content_kl_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
.