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Utility of visible and near-infrared spectroscopy to predict base neutralizing capacity and lime requirement of quaternary soils

  • Detailed knowledge of a soil’s lime requirement (LR) is a prerequisite for a demand-based lime fertilization to achieve the optimum soil pH and thus sustainably increasing soil fertility and crop yields. LR can be directly determined by the base neutralizing capacity (BNC) obtained by soil-base titration. For a site-specific soil acidity management, detailed information on the within-field variation of BNC is required. However, soil-base titrations for BNC determination are too laborious to be extensively applied in routine soil testing. In contrast, visible and near-infrared spectroscopy (visNIRS) is a time and cost-effective alternative that can analyze several soil characteristics within a single spectrum. VisNIRS was tested in the laboratory on 170 air-dried and sieved soil samples of nine agricultural fields of a quaternary landscape in North-east Germany predicting the soil’s BNC and the corresponding lime requirement (LRBNC) at a target pH of 6.5. Seven spectral pre-processing methods were tested including a new technique basedDetailed knowledge of a soil’s lime requirement (LR) is a prerequisite for a demand-based lime fertilization to achieve the optimum soil pH and thus sustainably increasing soil fertility and crop yields. LR can be directly determined by the base neutralizing capacity (BNC) obtained by soil-base titration. For a site-specific soil acidity management, detailed information on the within-field variation of BNC is required. However, soil-base titrations for BNC determination are too laborious to be extensively applied in routine soil testing. In contrast, visible and near-infrared spectroscopy (visNIRS) is a time and cost-effective alternative that can analyze several soil characteristics within a single spectrum. VisNIRS was tested in the laboratory on 170 air-dried and sieved soil samples of nine agricultural fields of a quaternary landscape in North-east Germany predicting the soil’s BNC and the corresponding lime requirement (LRBNC) at a target pH of 6.5. Seven spectral pre-processing methods were tested including a new technique based on normalized differences (ND). Furthermore, six multivariate regression methods were conducted including a new method combining a forward stagewise subset selection algorithm with PLSR (FS-PLSR). The models were validated using an independent sample set. The best regression model for most target variables was FS-PLSR combined with the second Savitzky-Golay derivation as pre-processing method achieving R2s from 0.68 to 0.82. Finally, the performance of the direct prediction of LRBNC (R2 = 0.68) was compared with an indirect prediction that was calculated by the predicted BNC parameters. This resulted in slightly higher correlation coefficients for the indirect method with R2 = 0.75.show moreshow less

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Metadaten
Author:Michael Horf, Eric Bönecke, Robin Gebbers, Charlotte Kling, Eckart KramerORCiDGND, Jörg Rühlmann, Ingmar Schröter, Wolfgang Schwanghart, Sebastian Vogel
URN:urn:nbn:de:kobv:eb1-opus-4916
DOI:https://doi.org/10.1007/s11119-022-09945-9
ISSN:1385-2256
ISSN:1573-1618
Parent Title (German):Precision Agriculture
Publisher:Springer Nature
Document Type:Article
Language:English
Year of Completion:2023
Publishing Institution:Hochschule für nachhaltige Entwicklung Eberswalde
Release Date:2023/05/15
Tag:Soil acidification; pH buffer capacity; Soil-base titration; Precision agriculture; Chemometrics
Volume:24
First Page:288
Last Page:309
Institutions / Departments:Fachbereich Landschaftsnutzung und Naturschutz
open_access (DINI-Set):open_access
University Bibliography:University Bibliography
Zweitveröffentlichung
Peer-Review / Referiert
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
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