Abstract. The analysis of soil phosphorus (P) in fractions of different plant availability is a common approach to characterize the P status of forest soils. However, quantification of organic and inorganic P fractions in different extracts is labor intensive and therefore rarely applied for large sample numbers. Therefore, we examined whether different P fractions can be predicted using near-infrared spectroscopy (NIRS). We used the Hedley sequential extraction method (modified by Tiessen and Moir, 2008) with increasingly strong extractants to determine P in fractions of different plant availability and measured near-infrared (NIR) spectra for soil samples from sites of the German forest soil inventory and from a nature reserve in southeastern China. The R2 of NIRS calibrations to predict P in individual Hedley fractions ranged between 0.08 and 0.85. When these fractions were combined into labile, moderately labile and stable P pools, R2 of calibration models was between 0.38 and 0.88 (all significant). Model prediction quality was higher for organic than for inorganic P fractions and increased with the homogeneity of soil properties in soil sample sets. Useable models were obtained for samples originating from one soil type in subtropical China, whereas prediction models for sample sets from a range of soil types in Germany were only moderately useable or not useable. Our results indicate that prediction of Hedley P fractions with NIRS can be a promising approach to replace conventional analysis, if models are developed for sets of soil samples with similar physical and chemical properties, e.g., from the same soil type or study site.
Abstract. The fractionation of soil P into fractions of different plant availability is a common approach to characterize the P status of forest soils. However, quantification of organic and inorganic P fractions in different extracts is labour-intensive and therefore rarely applied for large sample numbers. Therefore, we examined whether different P fractions can be predicted using near-infrared spectroscopy (NIRS). We used the Hedley method with increasingly strong extractants to determine P in fractions of different plant availability and measured NIR spectra for soil samples from sites of the German forest soil inventory and from a nature reserve in south-eastern China. The R2 of NIRS calibrations to predict P in individual Hedley fractions ranged between 0.08 and 0.85. When these were pooled into labile, moderately labile and stable fractions, R2 of calibration models was between 0.38 and 0.88. Model prediction quality was higher for organic than for inorganic P fractions and increased with the homogeneity of soil sample sets. Useful models were obtained for samples originating from one soil type in subtropical China, whereas prediction models for sample sets from a range of soil types in Germany were only moderately useful or not useful. Our results indicate that prediction of Hedley P fractions with NIRS is a promising approach to replace conventional analysis, if models are developed for sets of soil samples with similar physical and chemical properties.
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