Navegando por Autor "Xavier, Alexandre Candido"

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Distribuição e incerteza da acidez de um latossolo vermelho-amarelo húmico sob cultivo de café
(Sociedade Brasileira de Ciência do Solo, 2009-07) Silva, Samuel de Assis; Lima, Julião Soares de Souza; Souza, Gustavo Soares de; Xavier, Alexandre Candido
Com o desenvolvimento da agricultura, a utilização de novas alternativas na avaliação das propriedades que influenciam o rendimento das plantas tornou-se indispensável para melhor manejar o sistema agrícola. O objetivo deste trabalho foi utilizar uma ponderação por meio da modelagem fuzzy para estudar, com base em atributos químicos do solo, a propagação de incertezas da acidez de um Latossolo Vermelho-Amarelo húmico cultivado com café arábica. As amostragens de solo foram realizadas na profundidade de 0–20 cm, em uma malha totalizando 50 pontos. Os atributos avaliados foram: pH em H 2 O, acidez trocável (Al 3+ ), acidez potencial (H + Al) e saturação por Al (m). Os dados foram analisados pela estatística descritiva e pela geoestatística. Utilizou-se um sistema de classificação fuzzy e os atributos descritos para inferir sobre a acidez do solo. A lógica fuzzy, pelo algoritmo utilizado, teve um bom desempenho na caracterização e no mapeamento das incertezas da acidez do solo em questão.
Fuzzy logic in the spatial and temporal distribution in the quality of the beverage in conilon coffee
(Editora UFLA, 2019-04) Fonseca, Abel Souza da; Lima, Julião Soares de Souza; Silva, Samuel de Assis; Dardengo, Maria Christina Junger Delôgo; Xavier, Alexandre Candido
The objective in this study was to evaluate the spatial and temporal variability of the beverage quality by applying the fuzzy classification in the final global sensory analysis, for Coffea canephora Pierre ex A. Froehner, in two consecutive harvests. The studied variables were: fragrance (aroma), flavor, bitterness (sweetness), set, balance, cleaning, aftertaste, mouth feel, uniformity, salinity (acidity) and drink (global note). To the average overall scores of the drinks obtained on the cup-tasting at 80.0 points of a sampling, the mesh has applied the function of association of the fuzzy classification linear model to determine the degree of pertinence. The data were analyzed by the descriptive statistics and then by geostatistics to verify the existence and quantify the degree of spatial dependence of the variables. In the interval classified as “very good coffee” is found in the global average grade, in the two harvests. The methodology fuzzy applied in the global beverage note of the coffee conilon seminal made it possible to determine their spatial variability in the same distribution pattern in the two harvests, close ranges, and adjustments to the spherical model, which was confirmed by the spatial correlation of 61.6% among the fuzzy maps for the global score.
Spatial variability of the productivity and the nutritional condition of Coffee canephora
(Editora UFLA, 2015-10) Fonseca, Abel Souza da; Lima, Julião Soares de Souza; Silva, Samuel de Assis; Xavier, Alexandre Candido; Drumond Neto, Antonio Pereira
Utilizing precision farming techniques along with the Diagnosis and Recommendation Integrated System (DRIS) allows crop management to be improved, thereby making it possible to better control plant nutrition and to assist in reducing fertilizer expenditures. This study aimed to evaluate the spatial variability of the nutritional status of conilon coffee (Coffea canephora), using the Nutritional Balance index (NBI). 140 points were georeferenced within a coffee crop, each sampling point contained five plants. Leaf samples were analyzed in order to determine levels of N, P, K, Ca, Mg, S, Fe, B, Zn, Mn and Cu. The crop showed itself to have a nutritional imbalance, as shown by the deficiency and excess variation of some nutrients in the crop. The nutritional balance index (NBI) was not correlated with productivity (Prod), indicating that, when the crop has a high nutritional imbalance IBN is not a good tool for establishing nutritional standards for conilon coffee.