The objective of this research was to determine the optimal plot size and the number of replications to evaluate the fresh matter of ryegrass sown to haul. Twenty uniformity trials were conducted, each trial with 16 basic experimental units (BEU) of 0.5 m2. At 117, 118 and 119 days after sowing, the fresh matter of ryegrass in the BEUs of 5, 10 and 5 uniformity trials, respectively, were determined. The optimal plot size was determined by the maximum curvature method of the variation coefficient model. Next, the replications number was determined in scenarios formed by combinations of i treatments (i = 3, 4, ... 50) and d minimum differences between means of treatments to be detected as significant at 5% of probability by the Tukey test, expressed in experimental mean percentage (d = 10, 11, ... 20%). The optimal plot size to determine the fresh matter of ryegrass seeded at the haul is 2.19 m2, with a variation coefficient of 9.79%. To identify as significant at 5% probability, by the Tukey test, differences between treatment means of 20%, are required five, six, seven and eight replications, respectively, in ryegrass experiments with up to 5, 10, 20 and 50 treatments.
Mabea fistulifera Mart. (common name: canudo-de-pito) belongs to the Euphorbiaceae family and is a native tree species in Brazil showing a high potential to recover degraded lands. This study aimed to evaluate the distribution and spatial correlation between the dendrometric parameters of the M. fistulifera plants and the physical attributes of the soil through geostatistics. The study was carried out at the Paulista State University (UNESP), in the city of Selvíria, MS, Brazil, in a typical dystrophic Red Oxisol with a clayey texture. The following properties were analyzed: for soil, penetration resistance, gravimetric moisture, particle density, and, for plants, circumference and diameter at breast height (measured at 130 cm above the ground), tree height, and total volume of the tree. An experiment grid was introduced with 35 sample points spaced 13 m x 13 m. Two soil samples were taken at each point, at 0.00 - 0.10 m and 0.10 - 0.20 m depth. Descriptive data analysis and spatial dependence analysis were carried out through semivariogram adjustments and kriging maps. The dendrometric properties of the species M. fistulifera and the soil gravimetric moisture content showed spatial dependence. The spherical semivariogram model best explained the spatial structure of circumference at breast height, diameter at breast height, tree volume, and soil gravimetric moisture. There was an emphasis on the correlation between the total volume of the tree as a function of the diameter at breast height, showing a moderate spatial dependence. Furthermore, the tree diameter at breast height proved to be a good indicator for determining the total height of the M. fistulifera tree.
O conhecimento do relevo terrestre sempre foi de grande importância para a humanidade, e o modo de sua representação é objeto de constante e múltiplos estudos. O objetivo desse trabalho foi desenvolver uma proposta metodológica para elaboração de um Modelo Digital de Elevação, integrando dados geodésicos de alta acurácia e dados hidrológicos para monitoramento das áreas afetadas pelas recorrentes inundações do Rio Uruguai na cidade de Itaqui, Rio Grande do Sul, Brasil. Para tanto foi aplicada uma metodologia baseada na associação de dados provenientes de diferentes fontes, e que juntos retornam um produto final preciso e confiável para mapeamento de inundações urbanas. Para início do trabalho foi realizado a vinculação da série temporal da cota do Rio Uruguai à rede altimétrica nacional, por meio de nivelamento geométrico entre uma Referência de Nível (RN) e a régua linimétrica do rio. Na segunda parte do trabalho foi realizado um levantamento de pontos altimétricos, utilizando o sistema de navegação global por satélites - do inglês Global Navigation Satellite System (GNSS). Além disso, realizou-se a conversão das altitudes geométricas em ortométricas e sua correção com o uso do modelo geoidal oficial brasileiro. A terceira etapa do trabalho consistiu na geração de modelos digitais de elevação e uma análise estatística para validação e classificação dos modelos. Conseguiu-se elaborar um mapa de zoneamento de risco e simular as áreas afetadas pelas inundações históricas ocorridas nos anos de 1983 e 2017, sendo essas simulações validadas através do comparativo entre a resposta do modelo e os registros fotográficos das épocas em questão. O estudo demonstra uma ferramenta para gerenciamento das áreas suscetíveis a inundações adequadas a realidade e a possibilidade de investimentos do município, podendo aplicá-la de forma preventiva no intuito de reduzir as perdas e gastos resultantes dos eventos extremos ocorridos na cidade.
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