Determining soil indicators for soil sustainability assessment using principal component analysis of astan quds- east of mashhad- Iran
Soil quality indicators are measurable soil attributes that reveal the soil productivity response or soil-environment functionality that are used to know whether soil quality is improving, remain constant, or declining. These characteristics could be assessed by different indices such as sustainabil...
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| Autores principales: | , , , , |
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| Lenguaje: | English |
| Publicado: |
Chilean Society of Soil Science / Sociedad Chilena de la Ciencia del Suelo
2014
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| Materias: | |
| Acceso en línea: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-95162014000400017 |
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| Sumario: | Soil quality indicators are measurable soil attributes that reveal the soil productivity response or soil-environment functionality that are used to know whether soil quality is improving, remain constant, or declining. These characteristics could be assessed by different indices such as sustainability index approach (SI) based on the threshold levels of soil indicators and cumulative rating approach (CR) based on crop production limitations, which show the sustainability of soil ecosystem in terms of soil degradation. Since Iran is situated in arid and semi-arid climatic conditions, this research was conducted in agriculture fields of southeast of Mashhad, Iran for comparing these two approaches. Sixty three soil samples (0-30 cm) were collected and nine soil properties such as pH, electrical conductivity (EC), soil organic carbon (SOC), soil particle-size distribution, available water holding capacity (AWHC), bulk density (BD), air capacity (AC), relative field capacity (RFC) and sodium adsorption ratio (SAR) were measured. All these measurements were considered as total data set (TDS). Principal component analysis (PCA) was used to select more effective indicators to conform the minimum data set (MDS). There was a strong correlation between SI and CR (R²=0.69, p <0.05). Only six soil indicators selected as MDS (pH, SOC, AWC, BD and SAR) were correlated (p<0.01) significantly with SI and CR. These SI and CR results showed more promising effects on soil sustainability. PCA was found a suitable method for selecting the more effective indicators having R²= 0.77 (p <0.05) (CR-MDS versus CR-TDS) comparable with R²= 0.80 (p <0.05) (CR-MDS versus SI) to use less soil data input in assessing soil quality in arid zone. |
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