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In the irrigated areas, intensive agriculture has led to soil degradation and declining crop yields; therefore, the durability of soil resources is influenced. In order to assess the soil quality changes in the Zemamra area from the highest plain of Doukkala (523.000Ha), in the semi-arid region of Morocco, the soil samples taken from the horizon 0-30 cm were analysed for physical and chemical parameters (Clay, Sand, Silt, SOM, pH, TN, P2O5, K2O, CEC, MgO, CaO, SAR, Na2O, EC, CaCO3, NO3-N, NH4-N, B, Mn, Zn, Fe, and Cu). The data obtained were statistically processed to search for soil quality indices (SQIs). The main findings show that the soil surface has more sand than clay (Sand=55%, Clay=31%), an accumulation of phosphorus (P2O5=33.34mg/kg), moderate soil organic matter (1.789%), and carbonate contents of about (2.6%). Soil Structure Stability Index (SSSI

Knowledge of soil-landform relationships helps in understanding the dominant pedogenic processes causing variations in soil properties within and between landforms. In this study, we investigated how major pedogenic processes in three landform positions of the semi-arid Deccan Plateau (India) have led to current plant yield-limiting soil properties. For this, we characterised 26 pedons from three landforms--piedmont, alluvial plain and valley--and performed factor analysis on the dataset. As the frequency distribution of the dataset was highly skewed for most of the soil properties, landform-wise partition and log-transformation were performed before studying soil variability within landforms. Results indicated that two factors explained 56, 71 and 64% of variability in soil properties in piedmonts, alluvial plains and valleys, respectively. The major soils in lower piedmonts (Typic Haplustalfs and Typic Rhodustalfs) were spatially associated with Vertisols (Sodic Haplusterts) occurring in alluvial plains and valleys. The soil properties in alluvial plains and valleys (Verde Haplustepts, Sodic Haplusterts and Typic Ustifluvents) were modified due to regressive pedogenic processes. These soils were characterised by high pH (8.5-9.8), exchangeable sodium percentage (16.5-46.6) and poor saturated hydraulic conductivity (, Introduction Soils vary in their properties within and between landfonns (Gessler et al. 2000) due to pedogenic processes operating over different periods of time (Abdelfattah 2013; Switoniak 2014). The magnitude [...]

This study aims to identify soil quality indicators, assess soil quality index (SQI), and validate them with crop yield for India's two contrasting Agro-ecological Sub-Regions (AESRs). For this, 340 and 85 soil samples (0–15 cm) from AESRs 6.1 (semi-arid dry) and 18.4 (sub-humid dry) were analysed for 26 soil physical, chemical, and biological properties. Principal component analysis (PCA) was used to identify soil quality indicators, and the SQI and relative SQI (RSQI) were calculated using the weighted index method. We identified soil pH, active carbon pool (ACP), and available Zn as common indicators for both the AESRs apart from specific indicators. The SQI of AESR 6.1 soils under cotton and sugarcane were higher (0.48–0.75) than the AESR 18.4 soils under rice (0.26–0.70). Among the indicators, EC (35%), CEC (24%), pH (23%), clay (17%), and ACP (14%) significantly contributed to the SQI. The strong relationship of RSQI with the yield of cotton (R2 = 0.52), sugarcane (R2 = 0.68), and rice (R2 = 0.64) indicated that the selected indicators are representative to measure soil quality. We conclude that AESR specific soil quality indicators are appropriate for the evaluation and monitoring of agroecosystem functions. [ABSTRACT FROM AUTHOR]

Cotton (Gossypium sp.) is a major crop grown under rainfed conditions in Vertisols and associated soils in semi-arid tropical (SAT) regions of Peninsular India. In recent years, cotton productivity has declined due to various biophysical factors including pest and diseases, seasonal water stress soil degradation and poor crop management practices. In this study, we compare two methods for evaluating the suitability of Vertisols for cotton in contrasting two agro-ecological regions viz., sub-humid moist (SHM) region and semi-arid dry(SAD) were characterized. Twelve cotton growing Vertisols (seven from SHM and five from SAD) were evaluated for their suitability for cotton cultivation using soil quality index (SQI) and modified Sys-FAO method. SQIs were calculated using the weighted additive index from transformed scores of selected indicators by principal component analysis. For Sys-FAO method both biophysical and soil characteristics were considered for suitability evaluation. We found that the soils of SHM region were moderately suitable for cotton cultivation with soil moisture as the major limiting factor, whereas the soils of SAD region are marginally suitable due to high exchangeable sodium percentage and poor hydraulic conductivity. From this, it may be concluded that the weighted SQI has better agreement with the cotton yield. [ABSTRACT FROM AUTHOR]

Planting density is one of the important factors affecting soil properties, thereby directly impacting plantation yields. However, the effect of planting density on soil quality and productivity in plantation ecosystem mostly remain unknown. The present study aims to assess soil quality in four mature pine (Pinus kesiya) plantations with increasing planting densities i.e., 700 trees ha−1 (low planting density, LPD), 1080 trees ha−1 (moderate planting density, MPD), 1260 trees ha−1 (high planting density, HPD), and 2340 trees ha−1 (very high planting density, VHPD) respectively, up to 1 m soil depth. The soil samples collected at 0–20, 20–60, and 60–100 cm depth intervals were analyzed for a total of thirty-nine physical, chemical, and biological properties. The soil quality index (SQI) was calculated using linear scoring and weighted additive method. Total carbon, arbuscular mycorrhizal fungi (AMF) biomass, gram-positive bacteria biomass, soil moisture content, and β-glucosidase enzyme were selected as the important drivers of SQI. Total carbon, AMF, and moisture content had higher contribution to SQI. The results showed that increasing planting density adversely affected soil quality. SQI was higher in the surface (0–20 cm) soil layer, and it decreased with depth. Planting densities, soil depths, and their interaction had a significant effect on SQI. Increasing SQI promoted the stem biomass with a positive linear response. Therefore, maintaining a moderate to low planting density by thinning practices and selective logging could recover natural understory vegetation, acquire high timber yield, and sustain soil quality in pine plantations. • Planting density has significant effect on soil properties. • Total carbon, AMF, and moisture content contributed more towards SQI. • Increasing planting densities decreased SQI. • Planting densities and soil depth has significant interaction with SQI. • Increasing SQI significantly increases the stem biomass. [ABSTRACT FROM AUTHOR]