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Spectral assessment of soil properties in semi-arid tropical regions of southern Karnataka Plateau

Lalitha, M and Dharumarajan, S and Gomez, C and Hegde, R and Koyal, A and Khandal, S and Shashikumar, BN and Parvathy, S (2022) Spectral assessment of soil properties in semi-arid tropical regions of southern Karnataka Plateau. In: Archives of Agronomy and Soil Science .

Full text not available from this repository.
Official URL: https://doi.org/10.1080/03650340.2022.2134565

Abstract

The present study assessed the visible and short wave infrared (VNIR-SWIR) laboratory spectroscopy coupled random forest regression (RF) technique for predicting soil properties in the southern Karnataka Plateau, India. The spectral data acquired for about 228 profile samples were used to predict key soil properties. The RF model fits well for the spectral prediction of clay (R2 = 0.65), sand (R2 = 0.60), cation exchange capacity (R2 = 0.74), field capacity (R2 = 0.65) and permanent wilting point (R2 = 0.72). Wherein soil organic carbon was poorly predicted with an R2 of 0.22 and RPD of 1.2 due to its lower content and narrow range (0.8 to 20 g kg−1). The spectral assessment by PCA showed that the first (50%) and third (34%) components had high spectral variation and significantly correlated with soil properties such as pH, CEC, clay, FC, and PWP related to wavelengths indicating clay minerals and iron oxides. However, the second component had less spectral variation (13%) that is related to wavelengths indicating various organic components and correlated well with SOC. Thus, the VNIR-SWIR spectroscopy could be a suitable supplementary method for rapidly predicting soil properties related to clay minerals and iron oxides. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Item Type: Journal Article
Publication: Archives of Agronomy and Soil Science
Publisher: Taylor and Francis Ltd.
Additional Information: The copyright for this article belongs to Taylor and Francis Ltd.
Keywords: laboratory VNIR-SWIR spectroscopy; random forest regression; semiarid tropical; soil properties; Soil survey
Department/Centre: Division of Interdisciplinary Sciences > Interdisciplinary Centre for Water Research
Others
Date Deposited: 22 Jan 2023 06:16
Last Modified: 22 Jan 2023 06:16
URI: https://eprints.iisc.ac.in/id/eprint/79221

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