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Principal variations in the chemical composition of peat: Predictive peat scales based on multivariate strategies
Author(s) -
Hämäläinen Markku,
Albano Christer
Publication year - 1992
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1180060105
Subject(s) - principal component analysis , peat , multivariate statistics , partial least squares regression , chemometrics , chemistry , compositional data , chemical composition , biological system , lignin , multivariate analysis , mathematics , soil science , statistics , environmental science , chromatography , ecology , organic chemistry , biology
Abstract The principal properties, here called the ρ‐scales, of peat have been calculated on the basis of chemical analysis. The scales were derived from quantitative contents of carbohydrates, Klason lignin, amino acids, amino sugars and conventional chemical peat measurements. The variation in the chemical parameters was compressed using principal component analysis (PCA). Partial least squares (PLS) regression was used for prediction of botanical, microbial, physical and dewatering data. A rapid estimation of the scales has been made from near‐infrared (NIR) spectroscopy and offers, indirectly, rapidly obtainable, chemically interpretable, biological information. A reduced scale based on carbohydrate data was also tested. The ρ‐scales offer an interface between different areas of peat research. Strategies are outlined for the selection of a subset of chemical measurements among the variables used for characterization. A multivariate strategy based on these ideas is discussed.