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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampBarbosa, Emanuel Pimentel-
dc.typeArtigopt_BR
dc.titleState-space approach to evaluate effects of land levelling on the spatial relationships of soil properties of a lowland areapt_BR
dc.contributor.authorAquino, Leandro Sanzi-
dc.contributor.authorTimm, Luís Carlos-
dc.contributor.authorReichardt, Klaus-
dc.contributor.authorBarbosa, Emanuel Pimentel-
dc.contributor.authorParfitt, José Maria Barbat-
dc.contributor.authorNebel, Alvaro Luiz Carvalho-
dc.contributor.authorPenning, Letiane Helwig-
dc.subjectSolospt_BR
dc.subject.otherlanguageSoilspt_BR
dc.description.abstractLand levelling is an agricultural practice to correct soil surface irregularities turning the area more efficient for management of agronomic inputs. The technique has been adopted mainly in lowland areas used for flood irrigation of rice. As a result sub-surface soil layers may be exposed with possible impact on crop production by changing soil properties. This study aimed to evaluate the effects of land levelling on the spatial relationships of soil properties. Relations among them were quantified using a state-space approach in different scenarios constructed from data sets in a 1 ha lowland area sampled as a grid. The grid consisted of 100 sampling points (10 m × 10 m), with samples collected from the 0–0.20 m soil layer, before and after levelling, totalizing 200 samples. Soil water contents at field capacity (θFC) and permanent wilting point (θPWP) were taken as response variables due to their importance on rice water management. Sand, silt and clay contents, soil microporosity (Micro) and bulk density (BD), cation exchange capacity (CEC), organic carbon content (Corg), and the depth of the top of the B horizon in relation to soil surface (DTB) were used as co-variables through an evaluation of their spatial auto- and cross-correlation behaviors with θFC and θPWP. Eight data-array scenarios were tested. Results showed that levelling induced negative effects on soil quality since this procedure decreased θFC and θPWP, Corg, and CEC as well as increased BD. Using the state-space approach, we concluded that its performance in estimating θFC and θPWP was affected by the scenarios after levelling, the best performance being for the vertical scenarios. DTB and CEC contributed to the estimation of both soil water contents for all scenarios after levelling. The main problem associated to the levelling is the cutting of shallow soils which decreases their capacity to store water and to exchange cations in the effective arable depth which will be explored by the crop root system. As DTB is directly related to the spatial distribution of taxonomic soil profile properties, the state-space approach, which considers sampling location coordinates, may be a potential on-site-specific tool aiming at the recuperation of degraded soils through amendments since it opens the possibility for farmers to manage a crop field based on local environmental properties, with their spatial association and localized variation being a function of the distance between their measurementspt_BR
dc.relation.ispartofSoil and tillage researchpt_BR
dc.publisher.cityAmsterdampt_BR
dc.publisher.countryPaíses Baixospt_BR
dc.publisherElsevierpt_BR
dc.date.issued2015-
dc.date.monthofcirculationJan.pt_BR
dc.language.isoengpt_BR
dc.description.volume145pt_BR
dc.description.firstpage135pt_BR
dc.description.lastpage147pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0167-1987pt_BR
dc.identifier.doi10.1016/j.still.2014.09.007pt_BR
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S016719871400186Xpt_BR
dc.description.sponsorshipCONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQpt_BR
dc.description.sponsorshipCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESpt_BR
dc.description.sponsordocumentnumberSem informaçãopt_BR
dc.description.sponsordocumentnumberSem informaçãopt_BR
dc.date.available2021-02-02T14:29:08Z-
dc.date.accessioned2021-02-02T14:29:08Z-
dc.description.provenanceSubmitted by Thais de Brito Barroso (tbrito@unicamp.br) on 2021-02-02T14:29:08Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-05-24T16:47:45Z : No. of bitstreams: 1 000345183400017.pdf: 1396958 bytes, checksum: c6bf2515bda2d4c7a70ec9f3f3c54b6b (MD5)en
dc.description.provenanceMade available in DSpace on 2021-02-02T14:29:08Z (GMT). No. of bitstreams: 0 Previous issue date: 2015en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/355109-
dc.contributor.departmentDepartamento de Estatísticapt_BR
dc.contributor.unidadeInstituto de Matemática, Estatística e Computação Científicapt_BR
dc.subject.keywordTime series analysispt_BR
dc.subject.keywordSoil attributespt_BR
dc.subject.keywordSpatial variabilitypt_BR
dc.subject.keywordAutoregressive modelspt_BR
dc.subject.keywordSoil management practicespt_BR
dc.identifier.source000345183400017pt_BR
dc.creator.orcidSem informaçãopt_BR
dc.type.formArtigopt_BR
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