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.

The key objectives of contemporary agriculture are restoring biodiversity, preserving ecosystem health, reducing the effects of climate change, and producing safe and healthy foods. Maintaining high soil fertility while reducing greenhouse gas emissions requires a precise assessment of how fertilization and crop rotation affect carbon and nutrient cycles in agroecosystems. Fertilization affects soil conditions, which alters the environment for soil microbial development and influences the number and composition of soil microbial communities, leading to changes in nutrient and carbon cycling. There is a lack of long-term experimental data on the impact of fertilizer treatments on soil CO₂ emissions, soil microbial communities, and their interactions. The novelty of this study is that it identified the fertilization effects on soil carbon sequestration, soil properties, and microbial communities in the context of a long-term fertilizer experiment in Luvic Chernozem. The fertilization treatments that were continuously pplied for 64 years under a four-crop (wheat, barley, corn, and bean) rotation were nitrogen (N), phosphorus (P), potassium (K), NP, NK, PK, NPK, and control. The chemical and microbiological soil properties and soil CO₂ emissions were monitored. The highest organic carbon content was observed under the NPK (1.42%) and NP (1.43%) treatments. N fertilizer application most significantly affected soil properties, including pH, electrical conductivity, and soil organic carbon content, altering the environment for soil microbial development and influencing the number and composition of soil microbial communities. On average, the field-measured soil C-CO₂ emissions were the most intensive under NP (2.76 kg ha⁻¹ h⁻¹), NPK (2.83 kg ha⁻¹ h⁻¹), and PK (2.51 kg ha⁻¹ day⁻¹) treatments.

A key objective of contemporary agriculture is to restore biodiversity, preserve ecosystem health, reduce the effects of climate change, and produce safe and healthy foods. Maintaining high soil fertility while reducing greenhouse gas emissions requires a precise assessment of how fertilization and crop rotation affect the carbon and nitrogen cycles in agroecosystems. In the context of a long-term fertilizer experiment on Luvic Chernozem, a monitoring of chemical and microbiological soil properties and CO2 emission was carried out. The fertilization treatments that have been continuously applied for 64 years under four-crop (wheat, barley, corn, and beans) rotation are N, P, K, NP, NK, PK, NPK, and 0. The highest organic carbon content was observed in the treatments NPK (1.42%) and NP (1.43%), and the lowest in the control (1.05%). The constant application of nitrogen as single fertilizer led to lower SOC values (1.22%). On average, CO2 emissions were the most intensive in NP (66.34 kg ha-1 day-1), NPK (67.82 kg ha-1 day-1) and PK (60.16 kg ha-1 day-1) treatments. The nitrogen fertilizer application most significantly alters soil properties including pH, EC, and SOC, which alters the environment for soil microbial development and influences the number and composition of soil microbial communities.

Modeling crop development under different agrotechnologies is important not only for assessing the factors that affect their yields but also because of the role of vegetation in regulation of the hydrology regime. For this reason, interest in the plant module in the semi-distributed hydrological model SWAT is increasing. The model has to be supplied with a lot of information for running and testing, which can be achieved with ground-based, statistical and satellite data. The aim of the study is to determine the accuracy of the SWAT model to predict crop development by using ground-based and satellite data for LAI in the case of a 5-year field experiment. Two staple crops in rotation were monitored—winter wheat and maize—under different erosion control technologies (up-and-down conventional tillage, conventional contour tillage, and minimum contour tillage with inclusion of cover crop before maize) on sloping terrain on moderately eroded Epicalcic Chernozem in the region of Ruse, north Bulgaria. The remote sensing data from the Copernicus Sentinel-2 mission were used for estimation of LAI of both crops and verified against ground-based data in two ways—via a custom LAI script available through the Sentinel Hub cloud platform and as input to a machine learning quantile regression forests (QRF) model. The calibrated satellite-derived LAI, ground-based soil moisture and yields data were used to calibrate several SWAT model parameters (EPCO, ESCO, CN2, LAImax, HU, HI) and assess the model performance regarding these variables. Although a good temporal fit of the SWAT-modeled LAI data with the satellite data was achieved, the accuracy of predicted LAI is moderately high only in the last two years of the rotation (R² = 60.4%). The accuracy of calibrated yields (R² = 55.5%) is acceptable in four of the years. On average for the period, the applied erosion control agrotechnologies did not cause significantly different yields, but they are 14% higher compared to the up-and-down conventional tillage. The most sensitive SWAT parameters accounting for this effect are EPCO and ESCO.

Изследването, целящо установяване ефекта на различни варианти минерално торене върху съдържанието на фотосинтетични пигменти и устойчивостта на екологичен стрес при царевица, хибрид Рс 464, обхваща 16-та ротация (от 2018 до 2022 г.) на стационарен торов опит (СТО), разположен в Опитното поле на ИЗС „Образцов чифлик”, Русе. Проследено е въздействието на внасяните минерални торове върху устойчивостта на царевицата на екологичен стрес и динамиката в съдържанието на фотосинтетични пигменти по време на вегетацията на културата. По-ниска устойчивост на високи температури е установена при вариантите с включено азотно торене – измерената електроповодимост на листни мембрани на вариантите с комбинирано азотно-фосфорно (N15P12) и азотно-калиево (N15K7) торене е съотвено 65.46 µS cm-1 и 61.08 µS cm-1 при 58.52 µS cm-1 за контролния, ненаторяван, вариант. Устойчивост на атмосферното засушаване е установена при вариантите с комбинирано фосфорно-калиево (P12K7) – 52.62 µS cm-1 и със самостоятелното калиево торене (К7) – 54.18 µS cm-1. В листата на царевицата от варианта със самостоятелно азотно (N15) торене е установено най-високо съдържание на хлорофили (Ca+b 0,176 mg g-1), а най-ниското (Ca+b 0,094 mg g-1) – при самостоятелното калиево (K7) торене. Различните варианти на торене на царевицата не предизвикват съществени изменения в процентното съдържание на каротиноиди.