Selenium uptake and its content in soybean grains are affected by Se application methods. This study evaluated the impact of Se foliar application combined with a multi-nutrient fertilizer (MNF) on soybean, establishing a Se threshold to better understand the relationship between Se content in grains and yield of two genotypes (58I60 Lança and M5917). Two trials were conducted in a 4 × 2 factorial design: four Se rates (0, 10, 40, 80 g Se ha⁻¹) and two methods of foliar Se application (Se combined or not with MNF). Foliar fertilizers were applied twice, at phenological stages of beginning of pod development and grain filling. Grain yield increased with the application of MNF, yet Se rates increased Se contents linearly up to 80 g Se ha⁻¹, regardless of the use of MNF. Lança and M5917 genotypes had grain Se critical thresholds of 1.0 and 3.0 mg kg⁻¹, respectively. The application of Se favored higher contents of K, P, and S in grains of genotype Lança and higher contents of Mn and Fe in grains of genotype M5917. Our findings highlight the importance of addressing different Se fertilization strategies as well as genotypic variations when assessing the effects of Se on soybean yield and grain quality.

The interest in new techniques to support digital soil mapping (DSM) is increasing. Numerous studies pointed out that the measure of magnetic susceptibility (MS) can be extremely useful in the identification of properties related with factors and processes of soil formation, applied to soil mapping. This study addressed the effectiveness of magnetic soil susceptibility to identify and facilitate the distinction of different pedogenic environments of a representative hillslope in the highland Planalto Médio in the state of Rio Grande do Sul (RS), Brazil. In a 350-ha area in the municipality of Santo Augusto, RS, a representative transect was selected, trenches opened for soil characterization and 29 grid points marked at regular distances of 50 m, where soil samples were collected (layers 0.00-0.05, 0.05-0.15, 0.15-0.30, and 0.30-0.60 m) to analyze soil properties. Data from the transect samples were subjected to descriptive statistics. Limits of the pedogenetic environments along the slope were identified by the Split Moving Window (SMW) Boundary Analysis. The combined use of soil magnetic susceptibility and the SMW technique was effective in identifying different pedogenetic environments in the study area

Spatial soil data applications require sound geospatial data including coordinates and a coordinate reference system. However, when it comes to legacy soil data we frequently find them to be missing or incorrect. This paper assesses the quality of the geospatial data of legacy soil observations in Brazil, and evaluates geospatial data sources (survey reports, maps, spatial data infrastructures, web mapping services) and expert knowledge as a means to fix inconsistencies. The analyses included several consistency checks performed on 6,195 observations from the Brazilian Soil Information System. The positional accuracy of geospatial data sources was estimated so as to obtain an indication of the quality for fixing inconsistencies. The coordinates of 20 soil observations, estimated using the web mapping service, were validated with the true coordinates measured in the field. Overall, inconsistencies of different types and magnitudes were found in half of the observations, causing mild to severe misplacements. The involuntary substitution of symbols and numeric characters with similar appearance when recording geospatial data was the most common typing mistake. Among the geospatial data sources, the web mapping service was the most useful, due to operational advantages and lower positional error (~6 m). However, the quality of the description of the observation location controls the accuracy of estimated coordinates. Thus, the error of coordinates estimated using the web mapping service ranged between 30 and 1000 m. This is equivalent to coordinates measured from arc-seconds to arc-minutes, respectively. Under this scenario, the feedback from soil survey experts is crucial to improving the quality of geospatial data.