The Agricultural Academy (Bulgarian: Селскостопанска академия) is an organization with headquarters in Sofia, Bulgaria, for scientific research, for applied, service and support activities in the field of agriculture, animal husbandry, food industry.It has the right to prepare doctoral students in the relevant scientific disciplines. In the past, from 1971 to 1975, the Academy was a higher school, teaching undergraduate and postgraduate students..
The aim of the current study was to select and test the appropriate model and input parameters for remote sensing retrieval of surface soil moisture (SSM) in the case of bare Chernozems on flat and sloping terrains in northern Bulgaria under different tillage systems. Normalized synthetic aperture radar (SAR) measurements from Sentinel-1 C-band dual-pol products (Gamma-Nought in VV, ratio) were utilized in two ways to delineate SSM from environmental factors that bias determination. The accuracy of the obtained SSM prediction was evaluated against ground-based volumetric water content (VWC) measured in the 0-3.8 cm soil layer at multiple points using a TDR meter. The TDR VWC data were preliminarily calibrated against gravimetric measurements in the 0-5 cm soil layer. The obtained data for soil water retention curves in all studied variants were used to determine the range of soil moisture variation. The measured ground-based data for surface roughness generally correlate with the co-pol Gamma-Nought in VV. The data modeled with the surface soil moisture script in Sentinel Hub (SSM-SH) was calibrated using the ground-based data. Incidence angle normalization of Sentinel-1 products improved the relationship between SAR observables and SSM, when expressed as the ratio of soil moisture to total porosity (rVWC). The modeling indicated the highest importance of the optical indices, together with the temporal differences of radar descriptors sensitive to variations in soil moisture over time. Although the applied Random Forest Regression (RFR) model achieved higher accuracy during training (nRMSE of 7.27%, R2 of 0.86), the Gaussian Process Regression (GPR) model provided better generalization performance on the independent validation dataset. The results proved the advantages of the joint utilization of temporal Sentinel-1 SAR measurements with Sentinel-2 optical acquisitions to determine SSM in different bare soil conditions for achieving high accuracy.
This study investigated the vigor and molecular responses of soybean (Glycine max) seedlings belonging to cultivars from various maturity groups under simulated abiotic stress. Seeds and seedlings were subjected to varying concentrations of NaCl (150-300 mM) and PEG-6000 (20-30%), during long-term (12 days) and short-term (72 h) treatments, to evaluate the impact of salinity and drought on seedling viability and gene expression. Molecular analysis via qRT-PCR focused on the transcriptional profiles of the auxin transmembrane influx carrier LAX6, the vacuolar pyrophosphatase H+-PP-ase, and the stress protein kinase StrK2. The data indicated a dose-dependent correlation between stress intensity and developmental inhibition; increased concentrations of stress agents generally resulted in delayed germination and reduced survival rates. Certain soybean genotypes exhibited a robust transcriptional response, characterized by a several-fold increase in the expression of all studied genes following stress induction. These findings suggest that soybean abiotic stress responses may be influenced by a complex interaction between stress severity, exposure duration, genotype specificity and the maturity group.
Maize is the most important feed grain crop worldwide and plays a central role in global food, feed, and industrial production systems. It covers more than а half of the cultivated areas (55%) and nearly three-quarters (72%) of the grain production of all feed crops worldwide. It is a major raw material used for the production of a wide variety of products, mainly concentrated and compound feeds, as well as various food and industrial products such as starch, alcohol, cellulose, paper, construction and insulation materials, among others. Economic analysis of fertilizer use is increasingly recognized as a key component of sustainable agricultural decision-making. This study presents an extended partial economic assessment of grain maize production under non-irrigated conditions, based on real experimental data obtained at the Bozhurishte experimental field in 2023. The analysis was conducted for all experimental variants, as seven fertilization variants were evaluated using grain yield, taking into account the most important indicators characterizing economic efficiency in maize production. The following indicators were analyzed: grain yield (GY), grain revenue (GR), direct production costs (DPC), net income (NI), profitability rate (PR) and benefit–cost ratio (BCR). The results revealed that yield maximization does not coincide with economic optimization. Variants characterized by lower input intensity achieved higher economic efficiency, while excessive fertilization resulted in negative economic outcomes. The findings provide a solid economic basis for optimizing fertilization strategies under rainfed maize production systems. Under conditions of increasing climatic variability, particularly irregular precipitation, economic efficiency becomes a decisive factor in crop management. Rainfed maize production systems are exposed to high yield risk, which amplifies the negative economic consequences of high input intensity. The results of the present study clearly demonstrate that fertilization variants with excessive input costs are economically vulnerable under such conditions.
Plastic pollution is known to impact the biophysical characteristics of soil. However, there is currently limited knowledge regarding the sequence of events that occur at the foundational levels of terrestrial ecosystems. This encompasses changes in the abiotic properties of soil and their subsequent effects on various aspects of soil-plant interactions, including soil microbial communities and plant characteristics. This study aims to investigate the influence of four different types of plastic pellets - polylactic acid (PLA), polyamide six (PA6), polypropylene (PP), and polystyrene (PS) - on various indicators that reflect soil quality, as well as the growth and development of mangold (Beta vulgaris var. cicla). The study found that the presence of plastic pellets in soil led to significant changes in various parameters, such as the biomass of the plants, the elemental composition of tissues, and root characteristics. The biomass of the plants was reduced in the presence of plastic pellets, indicating that plastic pollution in soil can have a negative impact on plant growth and development. The elemental composition of tissues was found to be altered, which could potentially affect the nutritional quality of the crops. The study revealed changes in root characteristics, which can have implications for nutrient uptake and water absorption.
