article · Agronomy
An assessment of soil quality in the agricultural ecosystem of the Mnasra region, situated in the Gharb Plain of Morocco, evaluated spatial variability using combined statistical and geospatial methods. Thirty surface soil samples were gathered across thirty designated sites. Analysis revealed notable variations in soil characteristics influenced by agricultural practices, parent material, and soil texture. Statistical evaluations using Pearson correlation and principal component analysis facilitated the derivation of a Soil Quality Index. The resulting index values spanned from 0.48 to 0.74, classifying 46.66 percent of the sampled areas as having good soil quality, whilst 53.33 percent fell into the fair category. Geostatistical techniques, including semivariogram modelling and ordinary kriging interpolation, mapped the distribution of these soil attributes across the landscape. The integrated approach provides structured data to guide land management decisions and agricultural monitoring in the region.
Sustainable agricultural management relies on understanding how soil characteristics vary across farming landscapes. By evaluating soil quality indicators and mapping their distribution, land managers can identify specific areas needing intervention. This integrated analytical and mapping approach helps decision-makers monitor soil conditions effectively and make targeted choices to support regional agricultural productivity and soil conservation efforts.
The methodology provides an applied mapping and evaluation workflow that regional agricultural authorities, land managers, and agronomic advisory services can use for land management decisions and soil monitoring. While the field assessment and geostatistical mapping have been applied and tested in the Gharb region, translating this into commercial soil-testing services or digital farm management tools would require further standardisation and software development for broader operational use.
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Accurate assessment of soil quality is crucial for sustainable agriculture and soil conservation. Thus, this study aimed to assess soil quality in the agricultural ecosystem of the Mnasra region within the Gharb Plain of Morocco, employing a comprehensive approach integrating multivariate analysis and geostatistical techniques. Thirty soil samples were collected from the surface layers across thirty selected sites. The results showed significant variations in soil properties across the study area, influenced by factors such as soil texture, parent material, and agricultural practices. Pearson correlation and principal component analysis (PCA) were employed to analyze the relationships among soil properties and compute the Soil Quality Index (SQI). The SQI revealed values ranging from 0.48 to 0.74, with 46.66% of sampled soils classified as “Good” and 53.33% as “Fair”. Geostatistical analysis, particularly ordinary kriging (OK) interpolation and semivariogram modeling, highlighted the spatial variability of soil properties, aiding in mapping soil quality across the landscape. The integrated approach demonstrates the importance of combining field assessments, statistical analyses, and geospatial techniques for comprehensive soil quality evaluation and informed land management decisions. These findings offer valuable insights for decision-makers in monitoring and managing agricultural land to promote sustainable development in the Gharb region of Morocco.
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DOI: 10.3390/agronomy14061112
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