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Near‐Infrared Analysis as a Rapid Method to Simultaneously Evaluate Several Soil Properties
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1995
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Environmental MonitoringEngineeringLand DegradationRapid MethodEarth ScienceSoil CharacterizationSoil PropertyMicrometeorologySoil PropertiesThermal Infrared Remote SensingNear Infrared AnalysisSoil ClassificationGeographyNear-infrared SpectroscopyRadiometrySpectroscopyOrganic MatterReflectance CurvesRemote Sensing
Near‑infrared analysis (NIRA) was evaluated for its ability to predict key soil properties from NIR reflectance curves of arid and semiarid soils. The study recorded high‑resolution diffuse reflectance spectra for 91 Israeli soil samples, measured six properties by standard laboratory methods, and developed an empirical NIRA model with data manipulations to optimize prediction accuracy. The model performed best using 25–63 spectral points, accurately predicting most properties with only minor bias for organic matter and hygroscopic moisture, demonstrating NIRA as a promising rapid, non‑restrictive soil analysis technique that warrants further investigation.
Abstract The near infrared analysis (NIRA) approach was studied to examine its capability for predicting spectral feature soil properties from the reflectance curves in the near infrared (NIR) region (1–2.5 µm) of arid and semiarid soils. High‐resolution diffuse reflectance spectra (3113 spectral points) in the NIR region were recorded for 91 soil samples from Israel. Six soil properties (clay content, specific surface area, cation‐exchange capacity, hygroscopic moisture, carbonate content, and organic matter content) were measured by routine methods employed in soil laboratories. An empirical model to predict each property from its spectral signature was developed by adapting the NIRA technique. Several data manipulations were used to obtain optimum performance. The optimum performance of all properties was found to be between 25 and 63 spectral points. Strong support for the NIRA capability was provided by its ability to examine most of the spectral assignments. A slight bias was observed for the prediction of both organic matter and hygroscopic moisture, suggesting that more attention in the prediction of these constituents is required. It was concluded that NIRA is a promising method for rapid and nonrestrictive analysis of soil materials, and further study of the synergism between NIRA and soil materials is recommended.