164 resultados para soil attributes
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The precision agriculture technologies such as the spatial variability of soil attributes have been widely studied mostly with sugarcane. Among these technologies have been recently highlighted the use of the vegetation index derived from remote sensing products, such as powerful tools indicating the development of vegetation. This study aimed to analyze the spatial variability of clay content, pH and phosphorus in an Oxisol in an area with sugarcane production, and correlate with the Normalized Difference Vegetation Index (NDVI). The georeferenced grid was created for the soil properties (clay, phosphorus and pH) and generated the maps of spatial variability. For these same sites were calculated the NDVI, in addition to mapping of this ratio, the evaluation of the spatial correlation between this and other studied properties. The clay and phosphorus content showed positive spatial correlation with the NDVI, while no spatial correlation was observed between NDVI and pH. The satellite images from the sensor ETM + Landsat were used to correlate to NDVI to observe the spatial variability of the studied attributes.
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Rustic forages as the signal-grass are predominant in areas of Cerrado in extensive livestock systems that favor soil degradation. However, with time, not even these forages can have a good development in those areas. The objective of this study was to analyze the variability of plant and soil attributes; to define the linear and spatial correlations between signal-grass yield and the chemical attributes of the studied soil, and to evaluate, among the chemical attributes of the soil, which one that best explain the variability in this forage yield. The experiment was conducted in an area that had been under pasture for more than 30 years, belonging to UNESP - Ilha Solteira Campus, located in Selvíria - MS. A geostatistical grid was installed in an oxisol, for soil and plant data collection, with 121 sampling stations, consisted of eleven transections with 160 m width in the direction of the Cartesian axes. The dry mass yield of signal-grass was low, presenting high variation. The attributes MSr, N, PB, MO1, MO2, pHa1, pHa2, pHk1 and pHk2 did not vary at random. They presented data variability from low to high and followed clearly defined spatial patterns, ranging between 17.7-162.9 m. There was significant linear correlation at 1% between MSr and N leaf, and between MSr and PB. The cross semivariograms MSr=f(N) and MSr=f(PB) confirmed that the dry matter can be estimated from data of nitrogen leaf and crude protein content of this forage.
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Ciência do Solo) - FCAV
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Agronomia (Produção Vegetal) - FCAV
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA