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Assessment of soil suitability for sustainable intensive agriculture is an appropriate tool to select the land suitable for agricultural production with the least economic and environmental costs. This study was conducted to evaluate the agricultural soil quality in the northeast area of Tadla plain (Morocco) using geographic information system (GIS) and analytical hierarchy process (AHP). Six soil quality indicators, i.e., pH, organic carbon, cation exchange capacity, texture, salinity and slope were considered and performed in 60 subsurface soil samples. AHP method was utilized to identify the weight of each indicator from the pairwise comparison matrix. The weighted sum overlay analysis was then used to generate the soil quality map in a GIS environment, by overlaying both indicator weights and subindicator weights. The studied area was classified into four soil quality categories, i.e., poor, medium, good, and excellent, the percentage of each category is 1.12, 20.98, 61.07 and 16.83%, respectively. The results indicated that 1.12% of the study area has poor suitability for sustainable intensive agriculture due to their unsuitable texture and low salinity, while about 77% of cultivated soils are adapted to agricultural production. The above results could be useful for the management of agricultural activity.

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Soil surveying and mapping is an important operation in soil science, and characterization of their properties is a key step in understanding soil quality . This study was undertaken to investigate the spatial variability of selected soil properties, such as soil pH, electrical conductivity (EC 1:5), carbonate content (CaCO 3 ) and total organic matter (TOM) and soil texture using different conventional analytical methods. Spatial distribution of these soil properties was elaborated by using the kriging method. The obtained results showed that the soil is alkaline, soil pH ranges from 7.20 to 8.78. TOM varies from 0.11 to 1.05 dS/m, and its texture varied from sand to loam content. Nonetheless, EC values fall within the slight, moderate and strong degrees of salinity. According to these results, it can be concluded that the soil is saline. Interrelationships between the parameters analyzed and the different samples were investigated by multivariate analyses, principal component analysis (PCA), and hierarchical cluster analyses (HCA). HCA classified the five groups, which were compared to PCA visualizations. The Box-plots show that the values fractions (sand, silt, clay) were very variable. Pearson correlation coefficient indicates a high correlation between carbonate content and pH, organic matter and silt fraction ARTICLE HISTORY

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