2015
DOI: 10.1590/s0100-83582015000100018
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Abstract: -The aim of this study was to identify and map the weed population in a notillage area. Geostatistical techniques were used in the mapping in order to assess this information as a tool for the localized application of herbicides. The area of study is 58.08 hectares wide and was sampled in a fixed square grid (which point spaced 50 m, 232 points) using a GPS receiver. In each point the weeds species and population were analyzed in a square with a 0.25 m 2 fixed area. The species Ipomoea grandifolia, Gnaphalium … Show more

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Cited by 8 publications
(9 citation statements)
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“…The model that best described the spatial variability of horseweed plants was the exponential one. In the study conducted by Rocha et al (2015), the spherical model showed the best fit to the empirical semivariance observed for the spatial distribution of horseweed in an area under no-tillage system. The range was 128 m and the fit exhibited coefficient of determination of 0.83, and these values are higher than those found in the present study.…”
Section: Resultsmentioning
confidence: 94%
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“…The model that best described the spatial variability of horseweed plants was the exponential one. In the study conducted by Rocha et al (2015), the spherical model showed the best fit to the empirical semivariance observed for the spatial distribution of horseweed in an area under no-tillage system. The range was 128 m and the fit exhibited coefficient of determination of 0.83, and these values are higher than those found in the present study.…”
Section: Resultsmentioning
confidence: 94%
“…Weeds were sampled in each point using a template of 0.25 m 2 (0.5 x 0.5 m), as adopted in the study of Rocha et al (2015). The surveys were conducted in November, in both agricultural years, at the pre-sowing of soybean.…”
Section: Methodsmentioning
confidence: 99%
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“…Crossvalidation is an important factor to consider when selecting the best fit of a variogram model. Higher values of the crossvalidation coefficient of determination indicate a better fit of the model; the ideal is a value of 1 (Pelissari et al, 2014;Rocha et al, 2015).…”
Section: Resultsmentioning
confidence: 99%
“…There may be mentioned the Relative Nugget Effect (NE) (Trangmar, Yost, Uehara, 1985;Cambardella et al, 1994) and the Spatial Dependence Degree (SPD) (Biondi, Myers, Avery, 1994), considering, respectively, the following relations between the parameters of the semivariogram: nugget effect (C0) and sill (C0 + C1); contribution (C1) and sill (C0 + C1). These two indexes to evaluate the spatial dependence are used by many studies, for example, Barbieri et al (2013), Costa et al (2013), Kamimura et al (2013), Neves , Peluco et al (2013), Santos, H. et al (2013), , Nascimento et al (2014), Lundgren, Silva, Ferreira (2015), Rocha et al (2015).…”
Section: Introductionmentioning
confidence: 99%