In drought-prone regions without irrigation systems, effective agrotechnologies such as subsoiling are crucial for enhancing soil infiltration and water retention. However, the effects of subsoiling can vary depending on crop type and environmental conditions. Despite previous research, there is limited understanding of the contrasting responses of C3 (sunflower) and C4 (maize) crops to subsoiling under drought stress. This study addresses this knowledge gap by assessing the effectiveness of subsoiling as a drought mitigation practice on Haplic Chernozem in Northern Bulgaria, integrating ground-based and remote sensing data. Soil physical parameters, leaf area index (LAI), canopy temperature, crop water stress index (CWSI), soil moisture, and yield were evaluated under both conventional tillage and subsoiling for the two crops. A variety of optical and radar descriptive remote sensing products derived from Sentinel-1 and Sentinel-2 satellite data were calculated for different crop types. Consequently, the use of machine learning, utilizing all the processed remote sensing products, enabled the reasonable prediction of LAI, achieving a coefficient of determination (R²) after a cross-validation greater than 0.42 and demonstrating good agreement with in situ observations. Results revealed differing responses: subsoiling had a positive effect on sunflower, improving LAI, water status, and slightly increasing yield, while it had no positive effect on maize. These findings highlight the importance of crop-specific responses in evaluating subsoiling practices and demonstrate the added value of integrating unmanned aerial systems (UAS) and satellite-based remote sensing data into agricultural drought monitoring.

Soil structure has an important role in storing and transporting substances, providing natural habitats for soil microorganisms, and allowing chemical reactions in the soil. A complex investigation on factors affecting soil structure characteristics under herbaceous (H), deciduous (D), mixed (M), and coniferous (SP—Scots Pine and NS—Norway Spruce) vegetation was conducted at three experimental stations—Gabra, Govedartsi, and Igralishte, located correspondingly in the Lozenska, Rila, and Maleshevska Mountains in South-West Bulgaria. The data set obtained includes soil structure indicators and physical, physicochemical, chemical, mineralogical, and microbiological parameters of the A and AC horizons of 11 soil profiles. Under different vegetation conditions, soil structure indicators respond differently depending on climatic conditions and basic soil properties. Regarding the plant available water capacity (PAWC), air capacity (AC), and water-stable aggregates (WSAs), the surface soil layers have an optimal structure in Gabra (H, D), Govedartsi (H, SP, NS), and Igralishte (H). The values for the relative field capacity (RFC < 0.6) showed that the studied soils were water-limited. The WSAs correlated with SOC in Gabra, while in Govedartsi and Igralishte, the WSAs correlated with the β-glucosidase known to hydrolyze organic carbon compounds in soil. The information obtained is important for soil quality monitoring under climatic and anthropogenic changes.

Biological products, including entomopathogenic fungi, are widely applied in agriculture to control pests and enhance crop productivity and quality. While their biological effects are well-documented, few studies focus specifically on their influence on soil physical quality indicators. This study addresses that gap by evaluating the effects of selected biological products, applied to common bean (Phaseolus vulgaris L.), exclusively on the physical properties of soil. The field trials were conducted over two years on two soil types: Fluvisol (Negovan, Sofia Region) and Luvic Chernozem (Ruse Region). Seven treatment variants were tested, including a control, individual and combined applications of the bioproducts Naturalis (N) and SoftGuard (SG), and three active strains (B339, B538, B730) of Beauveria bassiana. Results showed that different treatments had varying effects depending on soil type. On Fluvisol, B338 had the most beneficial effect, while B730 and B339 were most effective on Luvic Chernozem. Bioproducts reduced soil compaction but had no significant effect on plant-available water capacity (PAWC). This study contributes important insights into how biopreparations influence only the physical condition of soils, with implications for sustainable soil management in legume cultivation.