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| Bottega,Eduardo L.; Pegoraro,Camilo; Guerra,Naiara; Oliveira Neto,Antonio M. de; Queiroz,Daniel M. de. |
| ABSTRACT Brazil is one of the largest grain producers in the world, due to its extensive arable land and favorable climate for the cultivation of any species. The production could be higher, but problems such as competition between crops and weeds reduces crop yields. This study aimed to analyze the spatial distribution of weeds, especially milkweed (Sonchus oleraceus), horse weed (Conyza spp.) and ‘maria-mole’ (Senecio brasiliensis) in an area under no-tillage system for two harvests. The work was carried out during the 2013/14 and 2014/15 crop years in an area of 22.5 ha, where soybean is grown in the summer and oat in the winter. The weeds were mapped using a sampling grid of 85 points. The number of plants present in 0.25 m2 was recorded at each... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Precision agriculture; Spatial variability; Sonchus oleraceus; Conyza spp.; Senecio brasiliensis. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662016001201107 |
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| Bottega,Eduardo L.; Queiroz,Daniel M. de; Pinto,Francisco A. C.; Oliveira Neto,Antonio M. de; Vilar,Cesar C.; Souza,Cristiano M. A. de. |
| The objective of this study was to evaluate the influence of different sampling grids density in the lime requirements in an Oxisol. The experiment was conducted at a rural property located in Sidrolândia city, Mato Grosso do Sul state, in the Brazilian ‘Cerrado’. In the soil attributes mapping, regular sampling grid was used consisting of 99 points, spread over an area of 90 ha. Other two grids (51 and 27 points) were derived by deleting lines or lines and points from the original one. Based on the results of soil analysis, the lime requirement at each sample point was calculated. Using geostatistical techniques the spatial variability of lime requirement was studied and grid configuration for each sample was tested. By kriging, maps were made. By... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Precision agriculture; Geostatistics; Spatial variability; Soil acidity correction. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662014001100008 |
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