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URI permanente desta comunidadehttps://thoth.dti.ufv.br/handle/123456789/3352
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Resultados da Pesquisa
Item Multivariate analysis applied to spray deposition in ground application of phytosanitary products in coffee plants(Associação Brasileira de Engenharia Agrícola, 2021) Palma, Roxanna P.; Cunha, João P. A. R. da; Guimarães, Ednaldo C.; Santana, Denise G. de; Assunção, Heli H. T. deAn adequate combination of factors involved in the technology used for phytosanitary product application contributes to an efficient spray deposition on the target. The objective of this study was to use multivariate analysis to characterize the magnitude of effects and the order of influence of three factors that interfere with the quality of phytosanitary product application in coffee plants. An entirely randomized design was adopted, with four repetitions, using a 2 × 2 × 3 factorial scheme, with two classes of droplets quality (fine and coarse), two application rates (250 and 400 L ha-1), and the use of adjuvants (with no adjuvant or with Fighter® and Aureo® adjuvants). The quality of the application was determined by jointly analyzing the spray deposition on three thirds of leaves, in their internal and external layers, the runoff to soil, coverage, droplet density, relative amplitude, and the volumetric median diameter. The results underwent analysis of variance (ANOVA) to measure the effect sizes (η2). After testing the assumptions of multivariate analysis, clustering and principal component analyses were performed. The class of droplets was found to be the most influential factor in the quality of the phytosanitary product application (spray deposition and runoff to soil). When focusing on spray deposition on leaves, the second-most influential factor was the application rate and the relation between the application rate and the adjuvants. For the other variables, the second-most influential factor was the application rate.Item Multivariate analysis and geostatistics of the fertility of a humic rhodic hapludox under coffee cultivation(Sociedade Brasileira de Ciência do Solo, 2012-03) Silva, Samuel de Assis; Lima, Julião Soares de SouzaThe spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 – 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K + , Ca 2+ , Mg 2+ , Na + , S, Al 3+ , pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characte- ristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.