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Evaluating Intra-Field Spatial Variability for Nutrient Management Zone Delineation through Geospatial Techniques and Multivariate Analysis

Author

Listed:
  • Haytham Mohamed Salem

    (Department of Soil and Water Systems, Twin Falls Research and Extension Center, University of Idaho, P.O. Box 1827, Twin Falls, ID 83303, USA)

  • Linda R. Schott

    (Department of Soil and Water Systems, Twin Falls Research and Extension Center, University of Idaho, P.O. Box 1827, Twin Falls, ID 83303, USA)

  • Julia Piaskowski

    (Statistical Programs, University of Idaho, 875 Perimeter Drive MS 2337, Moscow, ID 83844, USA)

  • Asmita Chapagain

    (Department of Soil and Water Systems, Twin Falls Research and Extension Center, University of Idaho, P.O. Box 1827, Twin Falls, ID 83303, USA)

  • Jenifer L. Yost

    (USDA-ARS, Grassland Soil and Water Research Laboratory, 808 East Blackland Road, Temple, TX 76502, USA)

  • Erin Brooks

    (Department of Soil and Water Systems, University of Idaho, 875 Perimeter Drive MS 2060, Moscow, ID 83844, USA)

  • Kendall Kahl

    (Department of Soil and Water Systems, University of Idaho, 875 Perimeter Drive MS 2060, Moscow, ID 83844, USA)

  • Jodi Johnson-Maynard

    (Department of Crop and Soil Sciences, University of Georgia, Athens, GA 30602, USA)

Abstract

This research study underscores the importance of effectively managing soil nutrients in a site-specific manner to enhance crop productivity while considering the spatial variability of the soil. The objective is to identify subfields with similar soil characteristics, referred to as management zones (MZs), to promote sustainable land utilization. This study was conducted in two central pivot fields located in Southern Idaho, USA, where barley and sugar beets were grown. Soil samples were collected from each field in a grid pattern and analyzed for various chemical properties. These properties included soil pH, organic matter, cation exchange capacity, excess lime, electrical conductivity, total inorganic nitrogen, phosphorus, potassium, calcium, magnesium, zinc, iron, manganese, copper, and boron. Descriptive statistics and normality assessments were performed, and the coefficient of variation was calculated to assess the heterogeneity of soil properties, revealing significant variability. To determine the spatial variability of soil properties, ordinary kriging was used revealing diverse spatial patterns for each location and soil variable examined with moderate to strong spatial dependence. To develop the MZs, a combination of principal component analysis and fuzzy k-means clustering was utilized, and specific parameters that represented the overall variability of soil properties in each field were identified. Based on the identified parameters, two clusters were created in each field. The first management zone (MZ1) exhibited lower values of soil pH, excess lime content, and electrical conductivity compared to the MZ2. Consequently, higher crop productivity was observed in MZ1 in both fields. The biomass yields of barley and sugar beets in MZ1 surpassed those in MZ2. This study highlights the effectiveness of the methodology employed to delineate MZs, which can be instrumental in precise soil nutrient management and maximizing crop productivity.

Suggested Citation

  • Haytham Mohamed Salem & Linda R. Schott & Julia Piaskowski & Asmita Chapagain & Jenifer L. Yost & Erin Brooks & Kendall Kahl & Jodi Johnson-Maynard, 2024. "Evaluating Intra-Field Spatial Variability for Nutrient Management Zone Delineation through Geospatial Techniques and Multivariate Analysis," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:645-:d:1317285
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    References listed on IDEAS

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    1. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
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