Guidelines for precise lime management based on high-resolution soil pH, texture and SOM maps generated from proximal soil sensing data

dc.bibliographicCitation.firstPage493eng
dc.bibliographicCitation.lastPage523eng
dc.bibliographicCitation.volume22eng
dc.contributor.authorBönecke, Eric
dc.contributor.authorMeyer, Sven
dc.contributor.authorVogel, Sebastian
dc.contributor.authorSchröter, Ingmar
dc.contributor.authorGebbers, Robin
dc.contributor.authorKling, Charlotte
dc.contributor.authorKramer, Eckart
dc.contributor.authorLück, Katrin
dc.contributor.authorNagel, Anne
dc.contributor.authorPhilipp, Golo
dc.contributor.authorGerlach, Felix
dc.contributor.authorPalme, Stefan
dc.contributor.authorScheibe, Dirk
dc.contributor.authorZieger, Karin
dc.contributor.authorRühlmann, Jörg
dc.date.accessioned2021-07-26T11:25:24Z
dc.date.available2021-07-26T11:25:24Z
dc.date.issued2020
dc.description.abstractSoil acidification is caused by natural paedogenetic processes and anthropogenic impacts but can be counteracted by regular lime application. Although sensors and applicators for variable-rate liming (VRL) exist, there are no established strategies for using these tools or helping to implement VRL in practice. Therefore, this study aimed to provide guidelines for site-specific liming based on proximal soil sensing. First, high-resolution soil maps of the liming-relevant indicators (pH, soil texture and soil organic matter content) were generated using on-the-go sensors. The soil acidity was predicted by two ion-selective antimony electrodes (RMSEpH: 0.37); the soil texture was predicted by a combination of apparent electrical resistivity measurements and natural soil-borne gamma emissions (RMSEclay: 0.046 kg kg−1); and the soil organic matter (SOM) status was predicted by a combination of red (660 nm) and near-infrared (NIR, 970 nm) optical reflection measurements (RMSESOM: 6.4 g kg−1). Second, to address the high within-field soil variability (pH varied by 2.9 units, clay content by 0.44 kg kg−1 and SOM by 5.5 g kg−1), a well-established empirical lime recommendation algorithm that represents the best management practices for liming in Germany was adapted, and the lime requirements (LRs) were determined. The generated workflow was applied to a 25.6 ha test field in north-eastern Germany, and the variable LR was compared to the conventional uniform LR. The comparison showed that under the uniform liming approach, 63% of the field would be over-fertilized by approximately 12 t of lime, 6% would receive approximately 6 t too little lime and 31% would still be adequately limed. © 2020, The Author(s).eng
dc.description.versionpublishedVersioneng
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/6365
dc.identifier.urihttps://doi.org/10.34657/5412
dc.language.isoengeng
dc.publisherDordrecht [u.a.] : Springer Science + Business Media B.Veng
dc.relation.doihttps://doi.org/10.1007/s11119-020-09766-8
dc.relation.essn1573-1618
dc.relation.ispartofseriesPrecision Agriculture 22 (2020)eng
dc.relation.issn1385-2256
dc.rights.licenseCC BY 4.0 Unportedeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/eng
dc.subjectSite specific soil managementeng
dc.subjectSoil organic mattereng
dc.subjectSoil pHeng
dc.subjectSoil sensingeng
dc.subjectSoil textureeng
dc.subjectVariable rate soil limingeng
dc.subject.ddc630eng
dc.subject.ddc640eng
dc.titleGuidelines for precise lime management based on high-resolution soil pH, texture and SOM maps generated from proximal soil sensing dataeng
dc.typearticleeng
dc.typeTexteng
dcterms.bibliographicCitation.journalTitlePrecision Agricultureeng
tib.accessRightsopenAccesseng
wgl.contributorATBeng
wgl.subjectLandwirtschafteng
wgl.typeZeitschriftenartikeleng
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Bönecke2021_Article_GuidelinesForPreciseLimeManage.pdf
Size:
2.18 MB
Format:
Adobe Portable Document Format
Description: