2011
DOI: 10.1590/s1415-43662011001000002
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Spatial variability of soil properties and cotton yield in the Brazilian Cerrado

Abstract: This research aimed at assessing the spatial variability and relationships between factors that affect cotton (Gossypium hirsutum L.) yield. Plant and soil data were collected by a 90 ha area divided in a regular grid of 100 m. In order to detect the variation at small scale, more intense samplings were made with spacing of 33 m, resulting in 5 "clusters" and totalizing 170 samples. Data were submitted to descriptive statistical analysis, geostatistic and interpolation through ordinary kriging. Variability exp… Show more

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Cited by 14 publications
(16 citation statements)
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References 20 publications
(21 reference statements)
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“…For the soil properties (Table 2), it was observed DF in NO (OM, pH, K, Ca, Mg, SB, T and V%) and IN (P and H+Al), agreeing with the data observed by Zonta et al (2014) and Dalchiavon et al (2015). In general, the coefficients of variation were between low (OM, pH and T), moderate (Ca, H+Al, SB and V%), high (Mg) and very high (P and K), consistent with Motomiya et al (2011) and Dalchiavon et al (2015) for P and K and with Sana et al (2014) for soil pH when they analyzed the variability of soil properties and their effects on cotton productivity.…”
Section: Resultssupporting
confidence: 89%
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“…For the soil properties (Table 2), it was observed DF in NO (OM, pH, K, Ca, Mg, SB, T and V%) and IN (P and H+Al), agreeing with the data observed by Zonta et al (2014) and Dalchiavon et al (2015). In general, the coefficients of variation were between low (OM, pH and T), moderate (Ca, H+Al, SB and V%), high (Mg) and very high (P and K), consistent with Motomiya et al (2011) and Dalchiavon et al (2015) for P and K and with Sana et al (2014) for soil pH when they analyzed the variability of soil properties and their effects on cotton productivity.…”
Section: Resultssupporting
confidence: 89%
“…The geostatistical analysis (Table 5) revealed, for the plant attributes that did not result in pure nugget effect, that the decreasing order of the spatial correlation coefficients (r 2 ) was: 1) PH (0.888), 2) %F (0.851), 3) SD (0.818), 4) FM (0.596), 5) BM (0.587), 6) SM (0.521), 7) #CY (0.508) and 8) RB (0.504). The PH derived in a very high spatial correlation coefficient (r 2 ), very high spatial dependency (SDE) (87.2%) and angular coefficient (b) of the cross-validation near 1 (1.022), denoting high quality of the experimental semivariogram of spherical type, thus agreeing with the semivariographic model reported by Motomiya et al (2011), who proposed a diagnosis for the localized management of the cotton crop, and mentioned high r 2 (0.640) and high SDE (68.0%).…”
Section: Resultssupporting
confidence: 82%
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“…In a practical way, the range of a variable guarantees that all of the neighbors are so similar that they can be used to estimate values for any point (Machado et al, 2007). A lower interval than the range provides soil samples with superposition of the spatial characteristics; on the other hand, a higher interval than the range does not comprise the spatial variability, while the medium value obtained does not reflect the area studied (Motomiya et al, 2011). …”
Section: Resultsmentioning
confidence: 99%
“…A técnica de geoestatística vem sendo aplicada em várias áreas do conhecimento científico, podendo-se citar: geologia (Mouslopoulou & Hristopulos, 2011); propriedades físicas dos solos (Motomiya et al, 2011;Bohling et al, 2012;Santos et al, 2012); recursos minerais (Abichequer et al, 2012); climatologia (Fouquet et al, 2011;Ramos et al, 2011;Wanderley et al, 2012;) e hidrologia (Ávila et al, 2009;Castro et al, 2010). Nour et al (2006) utilizando a técnica geoestatística consideraram as implicações que o projeto de uma rede de monitoramento pluviométrico pode acarretar no mapeamento de precipitações e concluíram que, a partir da krigagem ordinária, a análise geoestatística forneceu bons resultados na identificação de locais para instalação de estações pluviométricas, possibilitando a redução dos erros de estimativa espaciais.…”
Section: Introductionunclassified