Spatial distribution of Yellow Sigatoka Leaf Spot correlated with soil fertility and plant nutrition

This study analyzed the spatial distribution of Yellow Sigatoka Leaf Spot relative to soil fertility and plant nutritional status using geostatistics. The experimental area comprised 1.2 ha, where 27 points were georeferenced and spaced on a regular grid 18 × 18 m. The severity of Yellow Sigatoka, soil fertility and plant nutritional status were evaluated at each point. The spherical model was adjusted for all variables using restricted maximum likelihood. Kriging maps showed the highest infection rate of Sigatoka occurred in high areas of the field which had the highest concentration of sand, while the lowest disease was found in lower areas with lower silt, organic matter, total exchangeable bases, effective cation exchange capacity, base saturation, Ca and Mg in soil, and foliar sulfur (S). These results may help farmers manage Yellow Sigatoka disease more effectively, with balanced fertilization and reduced fungicide application. This practice minimizes the environmental impact and cost of production while contributing to production sustainability.

Determinação da densidade amostral ótima para a geração de mapas temáticos na cafeicultura de precisão

Among the crops commercially exploited in Brazil, the coffee has a great economic importance, especially in the states of Minas Gerais and Espirito Santo. In the search for higher yield and lower environmental impact, farmers and researchers seek to develop new technologies that result in greater efficiency in various production processes of the coffee. For this, the adoption of precision agriculture in the management of operations in coffee crops, called precision coffee, has shown results that justify its use, by identifying the spatial variability of several variables, allowing its localized management and in the proper intensity. Unlike conventional management that is based on the average of observations in an area, precision agriculture uses a more detailed sampling, based on a sampling grid, which allows to represent in greater detail the reality of farming. Many previous studies have identified the spatial variability of the production of coffee system variables, but without worrying about the quality of information obtained due to the sampling grid used as precision and accuracy. Given the above, the objective of this study was to evaluate the quality of four different sampling grids for different variables and three times, in order to identify the most appropriate grid for use in precision coffee. Also aimed to compare the results between the precision coffee and conventional, according to reference values.