IngentaConnect Near infrared spectroscopy for soil bulk density assessment

Authors: Moreira, C. S.¹; Brunet, D.²; Verneyre, L.³; Sá, S. M. O.⁴; Galdos, M. V.¹; Cerri, C. C.¹; Bernoux, M.

Source: European Journal of Soil Science, Volume 60, Number 5, October 2009 , pp. 785-791(7)

Abstract:

Summary

Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic “core cylinders”. The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (−0.002 g cm⁻³) and the lowest prediction error (0.13 g cm⁻³) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

Document Type: Research article

DOI: 10.1111/j.1365-2389.2009.01170.x

Affiliations: 1: Laboratório de Biogeoquímica Ambiental, Centro de Energia Nuclear na Agricultura, Universidade de São Paulo, 13416-000 Piracicaba, Brazil 2: Institute de Recherche pour le Développement- IRD, UMR Eco&Sols INRA-IRD-SupAgro, 2 place Viala, 34060 Montpellier, France 3: DIREN Guyane, Service eaux et milieux aquatiques, risques et déchets, 97328 Cayenne, Guyane Française 4: Centro de Ciências Agrárias, Universidade Estadual do Maranhão, 65055-310 São Luís, Brazil

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