Condutividade elétrica aparente como ferramenta de espacialização com alta resolução de atributos do solo

Abstract

The digital agriculture that drives the productive agriculture system, requires more and more new technologies to collect, store and manipulate data in high quantity and quality of agricultural fields, seeking to understand patterns and trends that are subsequently used as strategic information for decision-making in crop management. To overcome this demand, devices such as soil sensors are being developed that constitute a quick and inexpensive method to map the soil spatial variability. Among these, the apparent electrical conductivity (ECa) has been outstanding, since it presents a high correlation with soil chemical and physical attributes. However, as ECa is affected by a set of factors that act simultaneously in the soil, its interpretation becomes extremely complex, being necessary the conduction of new studies that allow understanding the behavior of the same in contrasting soil conditions. In this way, the present study was divided in two chapters which had as objectives to measure the capacity of the ECa of soil in capturing changes in the attributes of acidity and in the contents of calcium (Ca+2) and magnesium (Mg+2) in different places using plots with different texture and submitted to increasing rates (Cal), as well as to evaluate the feasibility of generation soil fertility maps through samples collected at strategic points in the field, selected from the spatial variability of the ECa maps, and to verify its potential as a specialization tool with high resolution of the chemical and physical properties of the soil. For this, the experiments were conducted in four croplands in the State of Rio Grande do Sul. The ECa registration was performed using the Veris 3100 sensor. The ECa was positively correlated with pH H20, Ca+2, Mg+2, sum of bases (SB), cation exchange capacity (CEC), and negatively with aluminum (Al+3), potential acidity (H + Al), and saturation of aluminum (m), showing itself as a promising tool in the detection of soil chemical variability, being sensitive to acidity attributes. The magnitude of the ECa values was influenced, in the first order, by the textural class of the soil, is the variability of the same dependence on the soil Ca+2 and Mg+2 contents. The use of king external drift (KED), using ECa as auxiliary information, in relation to ordinary kriging (OK) was able to better describe the spatial variability of soil chemical properties, which directly affected the distribution and amplitude of the doses of limestone to be applied, with an increase of 7.9% in the field 2 and 9.4% in the field 3. The results of the present study represent a significant advance in the soil sampling process of the soil for the prescription of maps with greater reliability, demonstrating that through the application of ECa to drive soil sampling is possible to increase the reliability in the application of agricultural correctives.