Integrating Remote Sensing and Ground Data to Assess the Effects of Subsoiling on Drought Stress in Maize and Sunflower Grown on Haplic Chernozem

Milena Kercheva (), Dessislava Ganeva, Zlatomir Dimitrov, Atanas Z. Atanasov, Gergana Kuncheva, Viktor Kolchakov, Plamena Nikolova, Stelian Dimitrov, Martin Nenov, Lachezar Filchev, Petar Nikolov, Galin Ginchev, Maria Ivanova, Iliana Ivanova, Katerina Doneva, Tsvetina Paparkova, Milena Mitova and Martin Banov
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Milena Kercheva: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Dessislava Ganeva: Department Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Zlatomir Dimitrov: Department Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Atanas Z. Atanasov: Department of Agricultural Machinery, Agrarian and Industrial Faculty, University of Ruse “Angel Kan-Chev”, 7017 Ruse, Bulgaria
Gergana Kuncheva: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Viktor Kolchakov: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Plamena Nikolova: Department of Agricultural Machinery, Agrarian and Industrial Faculty, University of Ruse “Angel Kan-Chev”, 7017 Ruse, Bulgaria
Stelian Dimitrov: Department of Geospatial Systems and Technologies, Faculty of Geology and Geography, Sofia University St. Kliment Ohridski, 15 Tsar Osvoboditel Blvd., 1504 Sofia, Bulgaria
Martin Nenov: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Lachezar Filchev: Department Remote Sensing and GIS, Space Research and Technology Institute, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Petar Nikolov: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Galin Ginchev: Institute of Agriculture and Seed Science “Obraztsov Chiflik”, Agricultural Academy, 7007 Ruse, Bulgaria
Maria Ivanova: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Iliana Ivanova: Institute of Agriculture and Seed Science “Obraztsov Chiflik”, Agricultural Academy, 7007 Ruse, Bulgaria
Katerina Doneva: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Tsvetina Paparkova: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Milena Mitova: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria
Martin Banov: Institute of Soil Science, Agrotechnologies and Plant Protection “Nikola Poushkarov”, Agricultural Academy, 1331 Sofia, Bulgaria

Agriculture, 2025, vol. 15, issue 15, 1-24

Abstract: 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 (R 2 ) 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.

Keywords: subsoiling; maize; sunflower; crop water stress; soil moisture; canopy temperature; UAS; satellite; LAI; Haplic Chernozem (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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