Assessment of the quality of the Harran Plain soils under long-term cultivation

• Published in: Environmental monitoring and assessment 2017-09, Vol.189 (9), p.460-460, Article 460
• Main Authors: Bilgili, Ali Volkan, Küçük, Çiğdem, Van Es, Harold M.
• Format: Article
• Language: English
• Subjects: Agricultural practices; Agriculture - methods; Atmospheric Protection/Air Quality Control/Air Pollution; Bulk density; Catalase; Clay; Corn; Cotton; Crop management; Crop production; Crop rotation; Cropping systems; Crops; Cultivation; Data; Earth and Environmental Science; Ecology; Ecotoxicology; Environment; Environmental Management; Environmental Monitoring; Environmental science; Enzymatic activity; Enzyme activity; Grain cultivation; Hydraulic conductivity; Interactions; Iron; Irrigation; Low level; Management; Mathematical models; Moisture content; Monitoring/Environmental Analysis; Organic matter; Organic soils; pH effects; Planting density; Principal Component Analysis; Principal components analysis; Quality; Quality assessment; Soil; Soil - chemistry; Soil analysis; Soil organic matter; Soil Pollutants - analysis; Soil quality; Soil types; Soil water; Soils; Statistical analysis; Statistical methods; Triticum; Turkey; Variance analysis; Water - analysis; Water content; Wheat; Zea mays
• ISSN: 0167-6369; 1573-2959
• DOI: 10.1007/s10661-017-6177-y

Soil quality refers to the ability of soils to perform their functions well. The soils of the Harran Plain, Turkey, have been put into intensive crop production with the introduction of an irrigation scheme and become increasingly degraded due to unsustainable management and cropping systems that resulted in the loss of production potential. The goal of this study was to quantify the quality of common soil series in the Plain using soil quality indexes (SQI) and to compare SQIs of two long-term crop rotations, cotton and wheat-corn cultivation, and different soil types. Over 400 samples were collected at a 0- to 30-cm depth and analyzed for 31 soil variables. The best representative soil quality variables forming a minimum data set (MDS) were selected using principal component analysis (PCA), and soil quality scores were obtained using both linear and non-linear scoring functions. The MDS included three physical (hydraulic conductivity, bulk density, and plant available water content), two biological (soil organic matter and catalase enzyme activity), and nine chemical soil quality indicators (CEC, pH, plant available Cu and Fe, exchangeable Na and K, soluble Ca, Mg, and Na). Because of the low level of SOM, soil qualities were overall low with indexes obtained using two scoring functions ranging from 38.0/100 to 48.7/100. Correlations between SQI obtained using two approaches (linear vs. non-linear; r  > 0.61) and using two data sets (all data vs. MDS; r  > 0.79) were high. Non-linear scoring functions were more sensitive to management impacts. ANOVA models testing the individual impacts of soil types and crop management on soil quality were statistically different ( p