Calibration of Near-Infrared Spectra for Phosphorus Fractions in Grassland Soils on the Tibetan Plateau

Abstract

Soil phosphorus (P) is essential for plant growth and influences biological processes. Determining the amounts of available P to plants has been challenging, and many different approaches exist. The traditional Hedley sequential extraction method and its subsequent modification are applied to determine different soil P forms, which is critical for understanding its dynamics and availability. However, quantifying organic and inorganic P (Po & Pi) in different extracts is labor-intensive and rarely used with large sample numbers. As an alternative, near-infrared spectroscopy (NIRS) has been employed to determine different P fractions at reasonable costs in a short time. This study aimed to test whether the analysis of P fractions with NIRS is an appropriate method to disentangle the effects of P limitation on high-altitude grassland ecosystems, particularly with fertilizer amendments. We explored NIRS in soils from the grassland soil samples on the northern Tibetan Plateau. First, we extracted the P fractions of 191 samples from the Haibei Alpine Meadow Ecosystem Research Station at four depth increments (0–10 cm, 10–20 cm, 20–40 cm, and 40–70 cm), including nutrient additions of nitrogen (N) and P. We compared the results of the Hedley extraction with the laboratory-based NIRS model. The fractionation data were correlated with the corresponding NIRS soil spectra; the coefficient of determination (R2) of the NIRS calibrations to predict P in P fractions ranged between 0.12 and 0.90; the ratio of (standard error of) prediction to the standard deviation (RPD) ranged between 1.07 and 3.21; the ratio of performance to inter-quartile distance (RPIQ) ranged from 0.3 to 4.3; and the model prediction quality was higher for Po than Pi fractions, and decreased with fertilizer amendment. However, the external-validation results were not precise enough for the labile P fractions (RPD < 1.4) due to the limited number of samples. The results indicate that using NIRS to predict the more stable P pools, combined with Hedley fractionation focusing on the labile P pool, can be a promising approach for soils in alpine grasslands on the Tibetan Plateau.