Variabilidades espacial e temporal da condutividade elétrica aparente do solo

Abstract

The spatial and temporal variabilities of apparent electrical conductivity (AEC) and other soil attributes can be analyzed by digital platforms for precision agriculture and the results can contribute to decision-making regarding agricultural management. Understanding these variations allows the adoption of more efficient and sustainable management practices, adapted to the specific characteristics of each area, which result in better crop productivity and environmental impacts decreasing. The important issue that arises is whether AEC measurement should be done regularly or just once. Thus, this reaserch aimed at monitoring the AEC variability, collected in 2013, 2016, 2022 (two measurements) and 2023, in two cropping areas, correlate collected data of AEC with chemical and physical attributes of the soil in both studied cropping areas, as well as calculate spatial variability and temporal variability among the AEC measurements. The research was carried out in two experimental areas with different managements, in Céu Azul-PR municipality. Data from LAMAP database concerning CEa from 2013 and 2016 and the results of chemical and physical soil analyses of the studied areas were used. Two AEC data collections were carried out in 2022 and one collection in 2023, using EM-38 MK2 conductivimeter in horizontal dipolar and drag mode. The data was inserted iat the AgDataBox web platform where cleaning, interpolation, thematic maps and spatial correlation matrix procedures were carried out. The thematic maps allowed to observe that spatial variability has a steady standard and that, mostly, the highest values were recorded in A1 area in the Northern region, while the highest ones were recorded for A2 in Eastern region. Spatial variability was greater in A2 than in A1. Both areas showed significant cross-correlation with most other variables (chemical and physical attributes of the soil). Thus, it was concluded that the AEC measurement can be performed once, when it is asked to be used as a co-variable in the interpolation of other variables, since the AEC standard remained stable in both areas. The best performance of normalization methods in both areas was the average method with the lowest average spatial variability and by the amplitude method, with the lowest average temporal variability. The standard deviation method in both areas provided the greatest spatial and temporal variabilities, thus providing the least satisfactory results among the normalization methods.