Variabilidade espacial e temporal da salinidade do solo e da produtividade de cana-de-açúcar em área de sequeiro

Abstract

Precision agriculture enables specific management of agricultural practices, with greater input application efficiency, lower production costs and reduction of environmental impacts. Soil salinity mapping makes it easier to manage and correct salt-affected areas. Therefore, the aim of this study was to characterize the spatiotemporal variability of soil salinity and sugarcane yield under rainfed conditions. The experiment was carried out in an area under sugarcane cultivation, located at the Usina Santa Teresa in Goiana, Zona da Mata-Norte of Pernambuco State, Brazil. The plot in study has 6.5 ha, under the following coordinates: 07° 33’ 39’’ S e 35° 00’ 10’’ W, and average altitude of 8.5 m. Soil sampling and crop yield measurements were performed on a 90-point regular grid in the experimental site. Disturbed soil was sampled from layers between the depths of 0-0.20 m and 0.20-0.40 m, in order to analyze the attributes: saturation extract electrical conductivity, hydrogenionic potential, soluble calcium, magnesium, sodium, potassium, bicarbonate, chloride and sulfate, as well as soil texture. Soil moisture content was determined using a TDR probe and soil apparent conductivity it was used an EM38 device. Sugarcane yield was calculated. Data were subjected to descriptive analyses and tested for normality using the Kolmogorov-Smirnov test. Spatial dependence analysis was performed using geostatistics. ECse, Na+, Ca2+, Mg2+, SAR and Cl- were used as attributed in order to demarcate homogeneous zones for site-specific management purposes. Spatial variability maps of ECse, Na+, SAR, Cl- and SO4 2- showed similarities when compared to the topography and sugarcane yield maps, and were inversely proportional to the pH maps. Rainfall index has influenced spatial and temporal variability of soluble salts and crop yield. Electrical conductivity measured by electromagnetic induction has demonstrated to be a important tool for the prediction of soil attributes. Spatial distribution maps and linear correlation of the apparent electrical conductivity and ECse and soil moisture content showed the same spatial pattern as the topography map.