English abstract
Soil salinity is a growing problem worldwide, impacting crop production and food quality. It occurs when salt levels in the soil exceed plant tolerance, resulting in reduced yields and plant death. Natural factors like evaporation and low rainfall, as well as human activities such as improper irrigation and excessive fertilizer use, contribute to soil salinity. This hinders water absorption and nutrient uptake by plants, reducing growth and fertility. It also harms ecosystems by polluting water bodies and causing soil erosion and desertification.
This study aimed to investigate the relationship between different methods of soil salinity analysis and electrical conductivity (EC) in the Al Batinah region of the Sultanate of Oman. Additionally, this study aimed to develop a statistical model for predicting EC values based on other salinity parameters and compare different analytical methods for elemental analysis and soil texture.
In the first part of the study, it was crucial to identify the source of salinity by analyzing the soil properties in different areas. The study also analyzed the soil texture and quantified anions and cations. Furthermore, this study found that the irrigation water used in the area was saline with EC values ranging from 14-18 mS/cm.
The second part is Comparing some of EC methods used to prepare the soil samples like: 1:1, 1:5 and satureated paste method (ECe). The simple linear regression test used to compare these methods.
In the third part of the study, it aimed to compare the analysis results of calcium (Ca) and magnesium (Mg) in soil samples using different methods and instruments. Ten samples were collected from three farms and prepared using various methods. The samples were then analyzed using ICP-OES, IC, flame photometer, and XRF.
The quantification of total alkali metals (Mg²⁺ and Ca²⁺) was carried out using various analytical methods. These methods included the open digestion method by ICP-OES, the 1:2.5 soil to water extract by flame photometer, the 1:5 soil to water extract by IC, and the fused bead method by WD-XRF.
The results showed that the open acid digestion by ICP-OES and the fused bead method by XRF were the most reliable methods for determining the total concentration of Ca and Mg. These methods can be used effectively in quantifying the alkali metal content.
In addition to these methods, XRD and soil texture tests were conducted to gather valuable information about the soil mineralogy in the study area. These tests provided further insights into the composition and characteristics of the soil.
The study revealed a significant relationship between the open acid digestion method of ICP-OES and XRF results for Ca analysis. However, further analysis and statistical tests are required to fully understand this relationship. The study also found differences in the Ca and Mg concentrations between the different methods, which could be attributed to the sample preparation methods.
The final stage of this study involves constructing a model using multiple linear regression to predict the electrical conductivity (ECe) of the soil based on other soil parameters. The predicted equation is as follows:
ECe (dS m⁻¹) = 0.218 + 0.15 Na + 0.16 Ca + 0.113 Mg ± ɛ.
To validate the accuracy of the model, a comparison was made between the observed and calculated ECe values using the initial dataset used for model construction. The relationship between the experimental ECe and the calculated ECe was examined using simple linear regression, which showed a strong relationship with an r² value of 0.72.
In the second part of the validation process, mathematical modeling was applied to the research samples and the data was compared with the calculated values. The strength of this relationship was assessed using a linear regression test. However, the results indicate a weak relationship with an r² value of 0.2. This weak relationship may be attributed to the limited number of observations available for analysis.
The results of this study will be beneficial for future research focused on addressing soil salinity in the specific area under investigation. The findings offer insights into the factors contributing to soil salinity and can inform future strategies to effectively mitigate this issue.
Overall, this study contributes to the body of knowledge on soil salinity and provides valuable insights that can be used to address this issue in the specific area studied. It highlights the importance of continued research and collaboration to develop effective solutions for mitigating soil salinity and ensuring the long-term productivity and sustainability of agricultural systems in the region.
