Mapping of Spatial Distribution of Soil Salinity and Alkalinity in a Semi-arid Region

Keshavarzi, Ali; Sarmadian, Fereydoon

doi:10.2478/v10060-011-0057-x

Cited by 21 publications

(7 citation statements)

References 14 publications

(16 reference statements)

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“…The soil condition of the semi-arid regions is not suitable for providing the all required nutrients for optimum plant growth. The high pH and alkalinity of the soils are the major constraints on production in semi-arid region (Keshavarzi and Sarmadian 2012). The numerous other plant nutrients such as Fe, Mn, Zn and Cu also have limited bioavailability in the alkaline pH range.…”

Section: Introductionmentioning

confidence: 99%

Oil characteristics of safflower seeds under different nutrient and moisture management

Pasandi¹,

Janmohammadi²,

Abasi³

et al. 2018

Nova Biotechnologica Et Chimica

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Safflower is one of the most important oilseed crops in semi-arid regions. The soil of semi-arid areas often encounters micronutrient deficiencies. However, nutrients imbalance seems to affect the quantitative and qualitative aspects of the oil as well as plant growth. Current experiment was carried out to evaluate the impact of different application practices (soil application and foliar spray) of micronutrients (Fe, Zn, Mn) on oil content, fatty acid profile and yield components of safflower under full and limited irrigations. Results showed that all of investigated traits were significantly affected by fertilizer treatment and irrigation system. The highest seed protein content was recorded for plants grown by soil application of Zn under limited irrigation condition. The highest oil content was achieved by soil application of Zn under full irrigation condition. The water deficit significantly reduced some qualitative characteristics such as oleic acid, palmitic aid, stearic acid, linoleic acid, iodine value and saponification value. The highest head number per plant, seed number per head and seed yield recorded in plants grown by soil application of Fe and Zn under full irrigation condition. Although the use of micronutrients improved qualitative characteristics in comparison with control, the best qualitative characteristics were achieved with the soil application of Zn and Fe. The elimination of micronutrient deficiencies and the balanced supply of nutrients through soil along with optimal and timely irrigation can significantly increase the efficiency of safflower production systems and improve the quality of the oil.

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Section: Introductionmentioning

confidence: 99%

Oil characteristics of safflower seeds under different nutrient and moisture management

Pasandi¹,

Janmohammadi²,

Abasi³

et al. 2018

Nova Biotechnologica Et Chimica

View full text Add to dashboard Cite

show abstract

“…Other studies that have been conducted using this approach, for example [77][78][79], confirm that IDW interpolation is more efficient than OK in predicting distribution, especially of the physico-chemical properties of soil, and this was probably due to the method of sampling and the similar distances of all samples. In contrast, other studies, for example [80][81][82], considered the performance of ordinary Kriging to be the best in comparison with other predicted data and with reference to actual data, concluding that it was also very reliable and more accurate.…”

Section: Comparison Of Idw and Okmentioning

confidence: 84%

Monitoring the Variations of Soil Salinity in a Palm Grove in Southern Algeria

et al. 2020

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Soil salinity is considered the most serious socio-economic and environmental problem in arid and semi-arid regions. This study was done to estimate the soil salinity and monitor the changes in an irrigated palm grove (42 ha) that produces dates of a high quality. Topsoil samples (45 points), were taken during two different periods (May and November), the electrical conductivity (EC) and Sodium Adsorption Ratio (SAR) were determined to assess the salinity of the soil. The results of the soil analysis were interpolated using two geostatistical methods: inverse distance weighting (IDW) and ordinary Kriging (OK). The efficiency and best model of these two methods was evaluated by calculating the mean error (ME) and root mean square error (RMSE), showing that the ME of both interpolation methods was satisfactory for EC (−0.003, 0.145) and for SAR (−0.03, −0.18), but the RMSE value was lower using the IDW with both data and periods. This can explain the accuracy of the IDW interpolation method. This model showed a dominance of soil salinity distribution in the South and South-East of the study area during the first season, and for the second season, the salts were concentrated in the middle of the area. Several factors could interact in this variation such as the topographic direction of the water flow and the aridity of the climate (evaporation). From this study emerges the need to maintain a better management of agricultural water and soils, avoiding salt accumulation, to ensure a good yield and the sustainability of agriculture in arid environments.

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“…The distance between the estimated and observed sampling points, increased to the power values has a substantial impact on the weights. The impact of the distant points decreases with an increase in power while weights are distributed across adjacent points more evenly for lower power (77,78). For this interpolation approach, the following formula is used.…”

Section: Gis Interpolation Techniques For Spatial Distribution Mappingmentioning

confidence: 99%

Spatial distribution and source identification of metal contaminants in the surface soil of Matehuala, Mexico based on positive matrix factorization model and GIS techniques

et al. 2022

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The rapid growth of urban development, industrialization, mining, farming, and biological activities has resulted in potentially toxic metal pollution of the soil all over the world. This has caused degradation of soil quality, lower crop production, and risk to human health. For this work, two study sites were selected to evaluate metal concentrations in the agricultural as well as the recreational soil around the Cerrito Blanco in Matehuala, San Luis Potosi, Mexico. The concentrations of eight metals, namely As, Ca, Mg, Na, K, Sr, Mn, and Fe were analysed in order to determine the level of contamination risk as well as their spatial distributions. However, this study is mainly focused on toxic metals, e.g. As, Sr, Mn, and Fe. The contamination indices techniques were used to evaluate the risk assessment of soil. Additionally, the positive matrix factorization (PMF) model as well as the geostatistical analysis was used to identify the contamination sources based on 64 surface soil samples. After implementing PMF to analyze the soils, it was possible to differentiate the variations in factors linked to the contaminants, farming impacts, and the reference soil geochemistry. The soil in the two studied locations included high concentrations of As, Ca, Mg, K, Sr, Mn, and Fe, including variations in their spatial compositions, which were caused by direct mining activities, the movement and deposition of smelting waste, and the extensive use of irrigated contaminated groundwater for irrigation. The four possible factors were identified for soil pollution including industrial, transportation, agricultural, and naturogenic based on the PMF and geostatistical analysis. The spatial distribution of metal concentrations in the soil was also presented using a geographical information system (GIS) interpolation technique. The identification of metal sources and contamination risk mapping presents a significant role in minimizing pollution sources, and it may be performed in regions with high levels of soil contamination risk.

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Mapping of Spatial Distribution of Soil Salinity and Alkalinity in a Semi-arid Region

Cited by 21 publications

References 14 publications

Oil characteristics of safflower seeds under different nutrient and moisture management

Oil characteristics of safflower seeds under different nutrient and moisture management

Monitoring the Variations of Soil Salinity in a Palm Grove in Southern Algeria

Spatial distribution and source identification of metal contaminants in the surface soil of Matehuala, Mexico based on positive matrix factorization model and GIS techniques

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