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Quantifying Soil Compaction in Persimmon Orchards Using ISUM (Improved Stock Unearthing Method) and Core Sampling Methods

Author

Listed:
  • Ehsan Moradi

    (Department of Reclamation of Arid and Mountainous Regions, University of Tehran, Karaj 31585-3314, Iran)

  • Jesús Rodrigo-Comino

    (Soil Erosion and Degradation Research Group, Department of Geography, Valencia University, Blasco Ibàñez, 28, 46010 Valencia, Spain
    Department of Physical Geography, Trier University, 54286 Trier, Germany)

  • Enric Terol

    (Department of Cartographic Engineering, Geodesy, and Photogrammetry, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain)

  • Gaspar Mora-Navarro

    (Department of Cartographic Engineering, Geodesy, and Photogrammetry, Universitat Politècnica de València, Camino de Vera, s/n, 46022 Valencia, Spain)

  • Alexandre Marco da Silva

    (Department of Environmental Engineering, Institute of Sciences and Technology of Sorocaba–SP, São Paulo State University (UNESP), São Paulo 511, Brazil)

  • Ioannis N. Daliakopoulos

    (School of Agriculture, Hellenic Mediterranean University, 71410 Heraklion, Greece)

  • Hassan Khosravi

    (Department of Reclamation of Arid and Mountainous Regions, University of Tehran, Karaj 31585-3314, Iran)

  • Manuel Pulido Fernández

    (GeoEnvironmental Research Group, University of Extremadura, 10071 Cáceres, Spain)

  • Artemi Cerdà

    (Soil Erosion and Degradation Research Group, Department of Geography, Valencia University, Blasco Ibàñez, 28, 46010 Valencia, Spain)

Abstract

Agricultural activities induce micro-topographical changes, soil compaction and structural changes due to soil cultivation, which directly affect ecosystem services. However, little is known about how these soil structural changes occur during and after the planting of orchards, and which key factors and processes play a major role in soil compaction due to cultivation works. This study evaluates the improved stock unearthing method (ISUM) as a low-cost and precise alternative to the tedious and costly traditional core sampling method, to characterize the changes in soil compaction in a representative persimmon orchard in Eastern Spain. To achieve this goal, firstly, in the field, undisturbed soil samples using metallic core rings (in January 2016 and 2019) were collected at different soil depths between 45 paired-trees, and topographic variations were determined following the protocol established by ISUM (January 2019). Our results show that soil bulk density (Bd) increases with depth and in the inter-row area, due to the effect of tractor passes and human trampling. The bulk density values of the top surface layers (0–12 cm) showed the lowest soil accumulation, but the highest temporal and spatial variability. Soil consolidation within three years after planting as calculated using the core samples was 12 mm, whereas when calculated with ISUM, it was 14 mm. The quality of the results with ISUM was better than with the traditional core method, due to the higher amount of sampling points. The ISUM is a promising method to measure soil compaction, but it is restricted to the land where soil erosion does not take place, or where soil erosion is measured to establish a balance of soil redistribution. Another positive contribution of ISUM is that it requires 24 h of technician work to acquire the data, whereas the core method requires 272 h. Our research is the first approach to use ISUM to quantify soil compaction and will contribute to applying innovative and low-cost monitoring methods to agricultural land and conserving ecosystem services.

Suggested Citation

  • Ehsan Moradi & Jesús Rodrigo-Comino & Enric Terol & Gaspar Mora-Navarro & Alexandre Marco da Silva & Ioannis N. Daliakopoulos & Hassan Khosravi & Manuel Pulido Fernández & Artemi Cerdà, 2020. "Quantifying Soil Compaction in Persimmon Orchards Using ISUM (Improved Stock Unearthing Method) and Core Sampling Methods," Agriculture, MDPI, Open Access Journal, vol. 10(7), pages 1-18, July.
  • Handle: RePEc:gam:jagris:v:10:y:2020:i:7:p:266-:d:379946
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    References listed on IDEAS

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    1. Shahab S. Band & Saeid Janizadeh & Sunil Saha & Kaustuv Mukherjee & Saeid Khosrobeigi Bozchaloei & Artemi Cerdà & Manouchehr Shokri & Amirhosein Mosavi, 2020. "Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility Using ALOS/PALSAR Data," Land, MDPI, Open Access Journal, vol. 9(10), pages 1-23, September.
    2. Shangyi Lou & Jin He & Hongwen Li & Qingjie Wang & Caiyun Lu & Wenzheng Liu & Peng Liu & Zhenguo Zhang & Hui Li, 2021. "Current Knowledge and Future Directions for Improving Subsoiling Quality and Reducing Energy Consumption in Conservation Fields," Agriculture, MDPI, Open Access Journal, vol. 11(7), pages 1-17, June.

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