Next Article in Journal
Diffusion of Electronic Water Payment Innovations in Urban Ghana. Evidence from Tema Metropolis
Next Article in Special Issue
Analytic Representation of the Optimal Flow for Gravity Irrigation
Previous Article in Journal
Temporal Variations of Spring Water in Karst Areas: A Case Study of Jinan Spring Area, Northern China
Previous Article in Special Issue
The Effect of Irrigation Treatment on the Growth of Lavender Species in an Extensive Green Roof System
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comparison of Soil EC Values from Methods Based on 1:1 and 1:5 Soil to Water Ratios and ECe from Saturated Paste Extract Based Method

Laboratory of Agricultural Hydraulics, Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
*
Author to whom correspondence should be addressed.
Water 2020, 12(4), 1010; https://doi.org/10.3390/w12041010
Submission received: 7 March 2020 / Revised: 30 March 2020 / Accepted: 31 March 2020 / Published: 2 April 2020
(This article belongs to the Special Issue Study of the Soil Water Movement in Irrigated Agriculture)

Abstract

:
The present study investigates the effect of three different methods of obtaining 1:1 and 1:5 soil-over-water mass ratios (soil:water) extracts for soil electrical conductivity (EC) measurements (EC1:1, EC1:5). On the same soil samples, also the electrical conductivity of the saturated paste extract (ECe) was determined and the relationships between ECe and each of the three of EC1:1 and EC1:5 values were examined. The soil samples used were collected from three areas over Greece (Laconia, Argolida and Kos) and had ECe values ranging from 0.611 to 25.9 dS m−1. From the results, it was shown that for soils with ECe < 3 dS m−1 the higher EC values were obtained by the method where the suspension remained at rest for 23 hours and then shaken mechanically for 1 h. On the contrary, no differences were observed among the three methods for soils with ECe > 3 dS m−1. Also, in the case of EC1:5, the optimal times for equilibration were much longer when ECe < 3 dS m−1. Across all soils, the relationships between ECe and each of three methods of obtaining EC1:1 and EC1:5 were strongly linear (0.953 < R2 < 0.991 and 0.63 < RMSE < 1.27 dS m−1). Taking into account the threshold of ECe = 3 dS m−1, different ECe = f(EC1:5) linear relationships were obtained. Although the linear model gave high values of R2 and RMSE for ECe < 3 dS m−1, the quadratic model resulted in better R2 and RMSE values for all methods examined. Correspondingly, in the 1:1 method, two of the three methods used exhibited similar slope values of the linear relationships independent of ECe value (ECe < 3 or ECe > 3 dS m−1), while one method (23 h rest and then shaken mechanically for 1 hour) showed significant differences in the slopes of the linear relationships between the two ranges of ECe.

1. Introduction

Soil salinity is one of the basic limiting factors in food production especially in arid and semi-arid regions since most crops are sensitive to increased salt concentration in the soil solution [1]. Soil salinization is particularly acute in arid and semi-arid areas with shallow groundwater as well irrigation water of poor quality.
Soil salinity assessment is based on measurement of the electrical conductivity of soil saturated paste extract (ECe); this has been established as the standard method [2,3]. Saline soils are considered to be the soils where the saturated paste extract has ECe values greater than 4 dS m−1. However, this method is laborious and time consuming especially in the case of ECe determination for a large number of soil samples. Additionally, the method appears to be more difficult and requires skills and expertise to obtain saturation point for clay soils.
For these reasons, many researchers have suggested easier methods to determine EC in various soils over water mass ratios extracts instead of determining ECe. The most widely used soil over water mass ratios, (soil:water), are the 1:1 and the 1:5. The ratio of 1:5 is used for soil salinity assessment (EC1:5) in Australia and China [4,5], while the ratio 1:1 (EC1:1) is commonly used in the United States [6]. Therefore, different methods for EC assessment are applied between different regions and organizations.
Many researchers have proposed linear relationships between ECe and EC1:1 or EC1:5 [7], (Table 1). However, the coefficients of the linear relationships are different and vary according to the area of interest. These coefficients are affected, among other factors, by the soil texture [8,9,10], the presence of gypsum and calcite in the soil [3,11], the chemical composition of the soil solution, the cation exchange capacity, etc. It has been documented that in the case of coarse-textured soils the slopes of the abovementioned linear relationships is greater than those of fine-textured soils [8].
The equilibration time and the method of preparation and extraction for determining EC1:1 or EC1:5 are probably additional factors that have led to the observed differences among various models [6,12]. It is worth to know that the equations ECe = f(EC1:5) and ECe = f(EC1:1) presented in Table 1 are often compared without taking into account these factors even though the equations have been obtained by different methods and at different ranges of ECe values. More specific, Aboukila and Norton [13] and Aboukila and Abdelaty [14] have used the NRCS method [15], Khorsandi and Yazdi [11] have shaken the suspension for 1 h, Sonmez et al. [10] have used the USDA method [16], while Visconti et al. [3] have applied mechanical shake for 24 h (Table 1). As regards to the ECe values range, Aboukila and Norton [13] presented their equation for ECe values up to 10.26 dS m−1, while Zhang et al. [17] and Khorsandi and Yazdi [11] for ECe values up to 108 and 170 dS m−1, respectively (Table 1). Noted that such extreme ECe values are related to very specific cases (e.g., dumping of saline water as waste from the oil industry or saline areas for large scale halophyte production). Overall, to obtain the equations ECe = f(EC1:5) and ECe = f(EC1:1) both different methods have been applied to measure EC1:5 and EC1:1 and different ranges of ECe values.
He et al. [6] reported that the EC1:5 was affected by both agitation method and agitation time. Specifically, significant differences existed within three agitation methods when ECe values ranged between 0.96 and 21.2 dS m−1. Equilibration times were significantly greater for soils having ECe < 4 dS m−1 compared to soils having ECe > 4 dS m−1. The agitation method of shaking plus centrifuging showed the greatest values of EC1:5 while the stirring method showed the smallest ones for the same soil examined. Also, Vanderheynst et al. [12], conducting an experiment with compost using various dilutions, found that as agitation time increased the EC values increased—especially when agitation time increased from 3 to 15 h. The above results showed the important role of agitation time among the different agitation methods on EC measurement, irrespective of the porous medium (e.g., soil, compost).
Among the various methods widely used—especially in the case of 1:5 ratio—there are the following three methods:
(i)
Loveday [18]: the suspension is mechanically shaken for 1 h and then kept at rest for 20 min.
(ii)
NRCS [15]: the suspension remains at rest in complete shade for 23 h and then shaken mechanically for 1 h.
(iii)
USDA [2]: the suspension is shaken by hand, 4 times, every 0.5 h for 30 s.
The difference between methods (i) and (ii) lies in the different rest times of the suspension, while methods (i) and (ii) differ from (iii) in both the shaking mode and the rest time.
Still now, no comparison has been made among the three abovementioned widely spread EC methods. Also, from international literature, it seems that there is no research work referred on the effect of different methods on the EC1:1, although different methods have been used on the EC1:1 measurement [16,17].
The objectives of present work are: (i) The comparison of EC values derived from the three most commonly used methods of 1:1 and 1:5 extracts; to investigate whether the differences between these methods are maintained across a range of soil ECe and (ii) the investigation of the relationship between ECe and EC values derived from the three methods.

2. Materials and Methods

2.1. Sample Collection Areas

The soil samples examined were collected from three areas in Greece, and more specifically, from the Prefectures of Lakonia, Argolida and from the island of Kos. Specifically, 50 soil samples were collected from Laconia from irrigated olive groves. The sampling procedure was carried out in September after the irrigation period. In Argolida, 12 samples were collected from various irrigated crops at the end of the irrigation period, while in Kos, 27 samples were collected from a horticultural greenhouse. The depth of soil samples collection was up to 30 cm.

2.2. Methods of Determining the Soil Properties

After sampling, the samples were transferred to the laboratory for air-drying and sieving through a 2 mm sieve and the soil texture, pH and calcium carbonate were determined. Soil texture was determined by means of the Bouyoucos hydrometer method [23], pH values were measured using standard glass/calomel electrodes in 1:2.5 w/v soil–water suspension [24]; CaCO3 equivalent percentage was estimated by measuring the eluted CO2 following the addition of HCl (calcimeter Bernard method).

2.3. Methods of Various Soil Extraction and Measurements

2.3.1. ECe Method

350 g of soil was used to prepare the soil saturated paste and then the paste was allowed to stand for 24 h (USDA, 1954). Subsequently, the vacuum extracts were collected and ECe was measured by a conductivity meter (WTW, Cond 315i). For the saturation percentage (SP) determination, a subsample of each paste was oven dried at 105 °C for 24 h.

2.3.2. EC1:5 Method

For the 1:5 suspension, 50 g of soil and 250 mL of distilled water were used. Three alternative methods were applied: the method of Loveday [18], the NRCS [15] and the USDA [2].
In the Loveday method, the suspension was shaken by a mechanical shaker for exactly one hour and then kept at rest for 20 min. After the rest time, the extract was obtained, and the EC was determined. For the NRCS method, the suspension remains at rest in complete shade for 23 h and then shaken mechanically for one hour. After the shaking, the extract was obtained, and the EC was determined. Finally, in the USDA method the suspension was shaken by hand, 4 times, every half hour for 30 s. After, the extract was obtained, and the EC was determined. The method of vacuum filtration in all the three methods is the same and common, followed by the measurement of EC with a conductivity meter. All the methods and EC readings were conducted at 25 °C.
In two soil samples, one from Laconia (sample L) and one from Argolida (sample A) with ECe values of 0.793 and 13.78 dS m−1, respectively, the EC1:5 values were measured after the suspensions were agitated with mechanical shaker for times 1, 2, 3, 4, 6, 24 and 48 h. After each agitation time the extraction was obtained, and the EC was determined. This process can better evaluate the role of shaking time on the EC1:5 values for the two very different ECe values.

2.3.3. EC1:1 Method

In the 1:1 method, the three above mentioned methods (Loveday, NRCS and USDA) were also applied as described in the 1:5 method. For each of the above methods, 50 g of soil was weighed and then each procedure was performed in the same way as above.

2.3.4. Statistical Analysis

For the relationships ECe = f(EC1:1) and ECe = f(EC1:5), a least-squared linear regression was applied and the coefficient of determination R2 was evaluated. The R2 coefficient is used to assessing the correlation between two independent methods. Also, the values of root mean square errors (RMSE) were determined. Analysis of variance (ANOVA) was applied to test the significant difference among the applied EC1:5 or EC1:1 methods using SPSS Statistical Software v. 17.0 (SPSS Inc., Chicago, IL, USA); the means of each method were compared using t-test at a probability level P = 0.05.

3. Results and Discussion

3.1. Soil Properties

Samples from Laconia and Argolida are characterized as clay-clay loam soils and from Kos as sandy clay soils. All soil samples presented negligible gypsum content. As regards to CaCO3, samples from Laconia presented a content lower than 2.5%, from Argolida 5–8% and from Kos 8.5–11%. The pH values ranged from 7.69 to 8.06 for soil samples from Laconia and from 7.5 to 7.7 for soil samples from Argolida and Κos.
Additionally, the soil texture analyses of the two soil samples examined separately resulted as follows: (i) soil sample L—clay soil (23.5% sand, 16% silt, 60.5% clay) and (ii) soil sample A—clay loam/loam soil (39% sand, 32% silt, 29% clay). The CaCO3 content was 0.2% and 7.66% and pH values were 7.75 and 7 for sample L and A, respectively.

3.2. Estimation of Soil Salinity

The ECe values ranged from 0.611 to 25.9 dS m−1. It should also be noted that the ECe variation range of the soil samples from Laconia is much lower than that of the other two regions (Argolida and Kos). Specifically, ECe values of the samples from Laconia ranged from 0.611 to 1.664 dS m−1, while in the other two regions they ranged from 2.32 to 25.9 dS m−1. From the measured ECe values, it appears that a relatively wide range in salinity levels was obtained for both comparing the different EC1:5 and EC1:1 methods, as well as evaluating the relationship between the ECe and each of EC1:5 or EC1:1 methods.
As regards to SP all soil samples examined (with exception of the two separated samples) have values greater than 43%, percentage which indicates that the soils are classified in fine textured soils [20]. More specifically, SP values ranged from 50.5% to 72.5% for soils from Laconia, 52–70% for soils from Argolida and 43–53% for soils from Kos.

3.3. Comparison of 1:1 and 1:5 Soil to Water Extract Electrical Conductivity Methods

In Table 2 the slope of the linear relationship (y = ax) between 1:5 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe > 3 dS m−1 and R2 are presented.
Similarly, the slope and R2 of the linear relationship between 1:1 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe >3 dS m−1 are presented in Table 3.
From the results presented in Table 2 and Table 3, it is obvious that each of the three methods examined resulted in different values of both EC1:1 and EC1:5 when ECe < 3 dS m−1. Analysis of variance (ANOVA) showed that the three methods are significantly different at a probability level P = 0.05. Furthermore, the t-test analysis (P = 0.05) showed that the NRCS and Loveday methods as well as the USDA and Loveday methods resulted in significantly different EC1:5 values, while EC1:5 values between NRCS and USDA were not significantly different. The mean value with standard deviation for NRCS, USDA and Loveday methods were 0.177 ± 0.029, 0.169 ± 0.029 and 0.151 ± 0.027 dS m−1, respectively. In the case of 1:1 ratio, the EC values between NRCS and USDA as well as NRCS and Loveday methods were also significantly different (P = 0.05). The mean value with standard deviation for NRCS, USDA and Loveday methods were 0.5 ± 0.070, 0.43 ± 0.100 and 0.423 ± 0.086 dS m−1, respectively.
The NRCS method resulted in greater EC values compared to the other two methods for both 1:1 and 1:5 ratios, whereas the Loveday method resulted in lower EC values. From these results, it appears that at low values of ECe (ECe < 3 dS m−1) the rest time seems to play an important role since the difference between the NRCS and the Loveday method is only in the duration of rest time. As regards to the NRCS and USDA methods, the slope of the linear regression between the NRCS and USDA at 1:5 ratio is 1.047, while at 1:1 is 1.161.
The EC1:5 values of the soil sample L (with ECe = 0.793 dS m−1 < 3 dS m−1) obtained by mechanical shaking for 1, 2, 3, 4 and 6 h was approximately 0.142 dS m−1 while EC1:5 values for 24 and 48 h were 0.218 and 0.274 dS m−1, respectively. Practically, after 48 h shaking the EC1:5 value was approximately doubling. The corresponding EC values obtained by the three methods used were 0.141, 0.127 and 0.158 dS m−1 for USDA, Loveday and NRCS methods, respectively. Therefore, it appears that the agitation time plays a dominant role to obtain equilibrium since the difference between the NRCS method (EC1:5 = 0.158 dS m−1) and the method with 24 h shaking (EC1:5 = 0.218 dS m−1) is in the shaking time. These results are similar to those of He et al. [6] in terms of the long shaking time required to equilibration but differ in the fact that in our experiments did not show differences in EC values obtained by shaking of at least up to 6 h. He et al. [6] explained that the higher values of EC obtained by the long shaking time method compared to other methods may be due to the fact that the mechanical shaking destroys micro-aggregates, as well as increase dissolution of salts because the dynamic concentration gradient between solid and liquid phases. Also, Vanderheynst et al. [12] found that differences occur for shaking time greater than a threshold value of 3 h.
In the case of soils with ECe > 3 dS m−1 there is no significant differences between agitation methods since all methods gave almost the same results and the slope of the linear relationship is almost 1 (Table 2 and Table 3). In addition, it is noted that the R2 values for soils with ECe > 3 dS m−1 are higher for all methods examined, in both 1:5 and 1:1 ratios, compared to R2 values for ECe < 3 dS m−1 (Table 2 and Table 3).
The EC1:5 values of the soil sample A (with ECe = 13.8 dS m−1 > 3 dS m−1) obtained by mechanical shaking for 1, 2, 3, 4, 6, 24 and 48 h ranged from 1.683 to 1.751 dS m−1. It is obvious that for soils with ECe > 3 dS m−1 the shaking times required to obtain equilibration are significantly lower compared to soils with ECe < 3 dS m−1
The different behavior depending on the ECe value shows that the solid and liquid phases is far from considered a simple system where the only process carried out is dissolution and that the concentration of ions is inversely proportional to dilution. Such situations may exist only in sandy or sandy loam soils in semi-arid areas with high salinity [25]. However, the soils are characterized by a cation exchange capacity value depending on the type and quantity of clay, the presence of slightly soluble minerals but also ion exchanges between solid and liquid phase. In the present experimental work, the existence of a relatively high clay percentage combined with the existence of slightly soluble minerals may be led to different EC values among various methods, especially when ECe < 3 dS m−1. This phenomenon may be even more pronounced in the case of clay soils where there are high content of slightly soluble minerals but less pronounced in the coarse-textured soils without slightly soluble minerals.

3.4. Relationship between ECe and 1:5 Soil to Water Extract Electrical Conductivity Methods

In Table 4, the linear relationships between ECe and EC1:5, for all soil samples, determined by the three different methods are presented. Analysis of the results showed that each 1:5 soil to water extract electrical conductivity method is strongly related with ECe since R2 values are high (0.953 < R2 < 0.972) and RMSE are low (1.02 dS m−1 < RMSE < 1.27 dS m−1). It also appears that the linear equations showed small differences regardless of the EC1:5 methods for all soils examined. These data confirm the existence of a strong linear relationship when the range of ECe is relatively great (Table 1).
As shown in Table 4, the relationship ECe = fEC1:5 using the USDA method is similar to the corresponding one reported by Kargas et al. [7], (Table 1) for Greek soils since both the two equations have almost the same slope (6.61 and 6.53, respectively).
However, analysis of the results for soils with ECe < 3 dS m−1 showed that a percentage of 70% of experimental ECe values were lower than those calculated by the equations presented in Table 4. For this reason, the data were separated into two ranges based on the threshold value ECe = 3 dS m−1 to evaluate whether the relationship ECe = fEC1:5 is described by different equations as reported by other researchers [26,27].
The slopes of linear equation describing the relation between ECe and EC1:5 determined by three different methods, as well as the R2 and RMSE for all soil examined for ECe < 3 dS m−1 and ECe > 3 dS m−1, are presented in Table 5.
As shown in Table 5, for soils with ECe < 3 dS m−1, the slope of the linear equation between ECe and EC1:5 has different value depending on EC1:5 determination method used with the smallest and the highest values obtained by the NRCS and Loveday method. Also, the values of the slopes of linear relationships, for both ECe < 3 dS m−1 and ECe > 3 dS m−1, differ significantly from each other since in the case of ECe < 3 dS m−1 these values ranged from 4.68 to 5.46, while they ranged from 6.60 to 6.71 in the case of ECe > 3 dS m−1. In addition, for ECe < 3 dS m−1 R2 values are lower (0.537 < R2 < 0.718) than those ones (0.917 < R2 < 0.942) observed for ECe > 3 dS m−1 indicating a strong linear relation between ECe and each EC1:5 determination method.
Comparison between the same methods for both ECe < 3 dS m−1 and ECe > 3 dS m−1 showed a difference between slopes ranging from 18.5% to 28.9%. Thus, in order to compare various equations describing the relationship between ECe and EC1:5, both the agitation method of EC1:5 determination and the range of ECe for which the equation has been proposed should be taken into account. Specifically, as shown in Table 5 and Figure 1, the relationship between ECe and EC1:5 determined by the NRCS method has a slope of 4.68 for ECe < 3 dS m−1 and 6.60 for ECe > 3 dS m−1. The differences among the methods may be even greater if the soil contains gypsum or larger amounts of calcite than those observed in the soil samples examined.
Similar results regarding to the effect of agitation method, the range of ECe and the gypsum content on equation describing the relationship between ECe and EC1:5 have been presented by other researchers [3,26,27].
He et al. [27] proposed a quadratic equation as a more appropriate equation to describe the relationship between ECe and EC1:5 when ECe values are lower than 4 dS m−1. The fitting of a quadratic equation to the data of this study for ECe < 3 dS m−1 gave R2 values of 0.74, 0.57 and 0.66 and RMSE values 0.096 (NRCS), 0.124 (USDA) and 0.115 dS m−1 (Loveday method), respectively. A comparison between these RMSE values and those of the linear relationships presented in Table 5, showed a significant improvement only in the case of the NRCS method. It should be noted that there is a significant difference in RMSE values presented in Table 4 compared to RMSE values whether we use the linear equation or quadratic equation to ECe estimation for ECe < 3 dS m−1.

3.5. Relationship between ECe and 1:1 Soil to Water Extract Electrical Conductivity Methods

Table 6 shows the relationship between ECe and the three methods of determining EC1:1 for all soil samples examined. The results showed that the relationship is strongly linear in all methods examined (R2 > 0.986) and RMSE values are low (0.63 < RMSE < 0.74 dS m−1). The values of both R2 and RMSE indicate that this linear relationship reliably estimates the ECe. However, ECe = fEC1:1 linear relationships have different f coefficient for each method.
In Table 7, regression equations describing the relation between ECe and EC1:1 determined by three different methods are presented taking into consideration the threshold of ECe value 3 dS m−1. The results showed that the same trends were observed for R2 and RMSE values as in the case of the results of 1:5 ratio presented in Table 5. As regards to differences observed in the slope of linear relationships between the two areas of ECe values, a notable difference was observed in the NRCS method since it resulted to a slope 1.65 for ECe < 3 dS m−1 and 2.08 for ECe > 3 dS m−1. Furthermore, the quadratic equation for the NRCS method, for ECe < 3 dS m−1, resulted almost to the same RMSE values (0.099 dS m−1) with those of linear equation. Therefore, for this method with ECe <3 dS m−1 the simple linear equation gave quite reliable results to ECe estimation. The other two methods showed similar slope values regardless of the ECe value. In particular, the ECe-USDA relationship had almost the same slope value regardless of the ECe.
The relationships between ECe and EC1:1 determined by the NRCS method taking into consideration the threshold of ECe value 3 dS m−1 are also presented in Figure 2.

4. Conclusions

The EC1:5 was affected by both agitation method and time, especially for ECe values lower than 3 dS m−1. Generally, the NRCS method resulted in the highest EC values compared to the other two methods examined. The differences among agitation methods are essentially eliminated for ECe values greater than 3 dS m−1. For soil having ECe values lower than 3 dS m−1, equilibration time was very greater than the soils having ECe values above 3 dS m−1. The most appropriate equation for ECe estimation using EC1:5 values for soils having ECe < 3 dS m−1 is a quadratic equation—especially in the case of the NRCS method—while for soils having ECe > 3 dS m−1 is the linear equation. However, if soils have a wide range of salinization levels, the linear model are recommended.
The present study shows that the shaking method and the equilibration time are additional contributing factors to the observed differences of the proposed equations for the ECe estimation by EC1:5. Therefore, in order to select each time, the appropriate method and equilibration time for measuring EC1:5, during laboratory studies, the ECe value of some samples, as well as the soil characteristics (e.g., gypsum and calcium carbonate content) should be examined in advance.
The EC1:1 was affected by ECe values only in the case of the NRCS method where the estimation of the ECe can be conducted by simple but different linear relationships whose slopes depend on ECe values. In the other two methods, the linear relationship ECe = f(EC1:1) was not affected by ECe values.
Overall, it is necessary to describe in detail the method of preparation and extraction for determining EC1:1 or EC1:5 and the range of ECe in order to properly evaluate and compare the proposed equations of ECe = f(EC1:5). Additionally, the study of soils with different characteristics than those of the group of soils examined in this work is needed.

Author Contributions

Conceptualization, G.K., P.L. and A.S.; Formal analysis, G.K., P.L. and A.S.; Methodology, G.K., P.L. and A.S.; Writing—review & editing, G.K., P.L. and A.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Libutti, A.; Cammerino, A.R.B.; Monteleone, M. Risk assessment of soil salinization due to tomato cultivation in Mediterranean climate conditions. Water 2018, 10, 1503. [Google Scholar] [CrossRef] [Green Version]
  2. USDA-Natural Resources Conservation Service. Soil Survey Laboratory Information Manual; Burt, R., Ed.; Soil Survey Investigations Report No. 45; version 2.0.; Aqueous Extraction, Method 4.3.3.; USDA-NRCS: Lincoln, NE, USA, 2011; p. 167.
  3. Visconti, F.; De Paz, J.M.; Rubio, J.L. What information does the electrical conductivity of soil water extracts of 1 and 5 ratio (w/v) provide for soil salinity assessment of agricultural irrigated lands? Geoderma 2010, 154, 387–397. [Google Scholar] [CrossRef]
  4. Rayment, G.E.; Lyons, D.J. Soil Chemical Analysis Methods-Australia; CSIRO Publishing: Collingwood, Australia, 2011. [Google Scholar]
  5. Wang, Y.; Wang, Z.X.; Lian, X.J.; Xiao, H.; Wang, L.Y.; He, H.D. Measurements of soil electrical conductivity in Tianjin coastal area. Tianjin Agric. Sci. 2011, 17, 18–21. [Google Scholar]
  6. He, Y.; DeSutter, T.; Prunty, L.; Hopkins, D.; Jia, X.; Wysocki, D.A. Evaluation of 1:5 soil to water extract electrical conductivity methods. Geoderma 2012, 185–186, 12–17. [Google Scholar] [CrossRef]
  7. Kargas, G.; Chatzigiakoumis, I.; Kollias, A.; Spiliotis, D.; Massas, I.; Kerkides, P. Soil Salinity Assessment Using Saturated Paste and Mass Soil:Water 1:1 and 1:5 Ratios Extracts. Water 2018, 10, 1589. [Google Scholar] [CrossRef] [Green Version]
  8. Slavich, P.G.; Petterson, G.H. Estimation the Electrical Conductivity of Saturated Paste Extracts from 1:5 Soil: Water Suspensions and Texture. Aust. J. Soil Res. 1993, 31, 73–81. [Google Scholar] [CrossRef]
  9. Franzen, D. Managing Saline Soils in North Dakota; North Dakota State University Extension Service: Fargo, ND, USA, 2003; Available online: https://www.ag.ndsu.edu/publications/crops/managing-saline-soils-in-north-dakota (accessed on 1 April 2020).
  10. Sonmez, S.; Buyuktas, D.; Okturen, F.; Citak, S. Assessment of different soil to water ratios (1:1, 1:2:5, 1:5) in soil salinity studies. Geoderma 2008, 144, 361–369. [Google Scholar] [CrossRef]
  11. Khorsandi, F.; Yazdi, F.A. Gypsum and Texture Effects on the Estimation of Saturated Paste Electrical Conductivity by Two Extraction Methods. Commun. Soil Sci. Plant Anal. 2007, 38, 1105–1117. [Google Scholar] [CrossRef]
  12. Vanderheynst, J.S.; Pettygrave, S.; Dooley, T.M.; Arnold, K.A. Estimating electrical conductivity of compost extracts at different extraction ratios. Compost Sci. Util. 2004, 12, 202–207. [Google Scholar] [CrossRef]
  13. Aboukila, E.F.; Norton, J.B. Estimation of Saturated Soil Paste Salinity from Soil-Water Extracts. Soil Sci. 2017, 182, 107–113. [Google Scholar] [CrossRef]
  14. Aboukila, E.F.; Abdelaty, E.F. Assessment of Saturated Soil Paste Salinity from 1:2.5 and 1:5 Soil-Water Extracts for Coarse Textured Soils. Alex. Sci. Exch. J. 2018, 38, 722–732. [Google Scholar] [CrossRef]
  15. NRCS. Method 4.3.3: Aqueous Extraction. In Soil Survey Laboratory Information Manual; Burt, R., Ed.; Version 2.0.; NRCS: Washington, DC, USA, 2011. [Google Scholar]
  16. United States Department of Agriculture (USDA). Diagnoses and Improvement of Saline and Alkali Soils; Agriculture Handbook No. 60; United States Department of Agriculture: Washington, DC, USA, 1954.
  17. Zhang, H.; Schroder, J.L.; Pittman, J.J.; Wang, J.J.; Payton, M.E. Soil Salinity Using Saturated Paste and 1:1 Soil to water extract. Soil Sci. Soc. Am. J. 2005, 69, 1146–1151. [Google Scholar] [CrossRef]
  18. Loveday, J. Methods for Analysis of Irrigated Soils; Tech. Comm. No.54, Commonwealth Bureau of Soils; Commonwealth Agricultural Bureau: Farnham Royal, UK, 1974. [Google Scholar]
  19. Rhoades, J.D. Soluble Salts. In Methods of Soil Analysis, Part 2: Chemical and Microbiological Properties, 2nd ed.; Page, A.L., Ed.; Agronomy Monograph No. 9; American Society of Agronomy: Madison, WI, USA, 1982; pp. 167–179. [Google Scholar]
  20. Chi, M.C.; Wang, Z.C. Characterizing salt affected soils of Songnen Plain using saturated paste and 1:5 soil to water extraction methods. Arid Land Res. Manag. 2010, 24, 1–11. [Google Scholar] [CrossRef]
  21. Ozcan, H.; Ekinci, H.; Yigini, Y.; Yuksel, O. Comparison of four soil salinity extraction methods. In Proceedings of the 18th International Soil Meeting on Soil Sustaining Life on Earth, Managing Soil and Technology, Sanlıurfa, Turkey, 22−26 May 2006; pp. 697–703. [Google Scholar]
  22. Hogg, T.J.; Henry, J.L. Comparison of 1:1 and 1:2 suspensions and extracts with the saturation extracts in estimating salinity in Saskatchewan. Can. J. Soil Sci. 1984, 64, 699–704. [Google Scholar] [CrossRef] [Green Version]
  23. Bouyoucos, G.H. A recalibration of the hydrometer method for making mechanical analysis of soils. Agron. J. 1951, 43, 434–438. [Google Scholar] [CrossRef] [Green Version]
  24. McLean, E.O. Soil pH and Lime Requirement. Agron. Monogr. 1983, 9, 199–223. [Google Scholar]
  25. Nadler, A. Discrepancies between soil solute concentration estimates obtained by TDR and aqueous extracts. Aust. J. Soil. Res. 1997, 35, 527–537. [Google Scholar] [CrossRef]
  26. Agarwal, R.R.; Das, S.K.; Mehrota, G.L. Interrelationship between electrical conductivity of 1:5 and saturation extracts and total soluble salts in saline alkali soils of the Gangetic alluvium in Uttar Pradesh. Indian J. Agric. Sci. 1961, 31, 284–294. [Google Scholar]
  27. He, Y.; DeSutter, T.; Hopkins, D.; Jia, X.; Wysocki, D.A. Predicting ECe of the saturated paste extract from value of EC1:5. Can. J. Soil Sci. 2013, 93, 585–594. [Google Scholar] [CrossRef]
Figure 1. Relationship between ECe and EC1:5 for NRCS extraction method. A: all soil samples, B: soil samples range ECe < 3 dS m−1, C: soil samples range ECe > 3 dS m−1.
Figure 1. Relationship between ECe and EC1:5 for NRCS extraction method. A: all soil samples, B: soil samples range ECe < 3 dS m−1, C: soil samples range ECe > 3 dS m−1.
Water 12 01010 g001
Figure 2. Relationship between ECe and EC1:1 for NRCS extraction method. A: all soil samples, B: soil samples range ECe < 3 dS m−1, C: soil samples range ECe > 3 dS m−1.
Figure 2. Relationship between ECe and EC1:1 for NRCS extraction method. A: all soil samples, B: soil samples range ECe < 3 dS m−1, C: soil samples range ECe > 3 dS m−1.
Water 12 01010 g002
Table 1. Relationships between soil saturated paste extract electrical conductivity (ECe) and 1:1 and 1:5 soil to water extract electrical conductivities (EC1:1, EC1:5) as proposed by several researchers, as well as the extraction method and the corresponding range of ECe values.
Table 1. Relationships between soil saturated paste extract electrical conductivity (ECe) and 1:1 and 1:5 soil to water extract electrical conductivities (EC1:1, EC1:5) as proposed by several researchers, as well as the extraction method and the corresponding range of ECe values.
ReferenceExpressionMethodECe Values Range
(dS m−1)
USDA [16]ECe = 3 (EC1:1) f
Khorsandi and Yazdi [11]ECe = 7.94 (EC1:5) + 0.27 d
ECe = 9.14 (EC1:5) − 15.72 e
Shake 1 h1.04–170
Sonmez et al. [10]ECe = 2.03 (EC1:1) − 0.41 c
ECe = 7.36 (EC1:5) − 0.24 c
Rhoades [19]0.22–17.68
Frazen [9]ECe = 2.96 (EC1:1) − 0.95 cN/AN/A
Aboukila and Norton [13]ECe = 5.04 (EC1:5) + 0.37 cNRCS method [15]0.624–10.26
Chi and Wang [20]ECe = 11.74 (EC1:5) − 6.15 b
ECe = 11.04 (EC1:5) − 2.41 c
ECe = 11.68 (EC1:5) − 5.77 f
USDA method [16]1.02–227
Slavich and Petterson [8]ECe = f(EC1:5)Loveday [18]0–38
Ozcan et al. [21]ECe = 1.93 (EC1:1) − 0.57 f
ECe = 5.97 (EC1:5) − 1.17 f
N/AN/A
Aboukila and Abdelaty [14]ECe = 7.46 (EC1:5) + 0.43 aNRCS method [15]0–18.3
Hong and Henry [22]ECe = 1.56 (EC1:1) − 0.06 fShake 1 h0.25–42.01
Zhang et al. [17]ECe = 1.79 (EC1:1) + 1.46 fEquilibrate 4 h0.165–108
Visconti et al. [3]ECe = 5.7 (EC1:5) − 0.2Shake 24 h0.5–14
Kargas et al. [7]ECe = 1.83 (EC1:1) + 0.117 c
ECe = 6.53 (EC1:5) − 0.108 c
USDA [16]0.47–37.5
The indices a, b and c refer to coarse, medium and fine soils, respectively. The indices d and e refer to the presence or absence of gypsum, respectively. The index f refers to combined soil texture.
Table 2. Slopes of the linear equations describing the relation between 1:5 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe > 3 dS m−1 and coefficient of determination R2.
Table 2. Slopes of the linear equations describing the relation between 1:5 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe > 3 dS m−1 and coefficient of determination R2.
EC1:5
MethodsSlopeR2
ECe < 3 dS m−1
NRCS–Loveday method 1.1660.872
NRCS–USDA1.0470.797
USDA–Loveday method1.1080.812
ECe > 3 dS m−1
NRCS–Loveday method 1.010.990
NRCS–USDA1.000.960
USDA–Loveday method1.000.976
Table 3. Slopes of the linear equations describing the relation between 1:1 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe > 3 dS m−1 and coefficient of determination R2.
Table 3. Slopes of the linear equations describing the relation between 1:1 soil to water extract electrical conductivity methods for ECe < 3 dS m−1 and ECe > 3 dS m−1 and coefficient of determination R2.
EC1:1
MethodsSlopeR2
ECe < 3 dS m−1
NRCS–Loveday method 1.1850.800
NRCS–USDA1.1610.781
USDA–Loveday method1.0120.817
ECe > 3 dS m−1
NRCS–Loveday method 1.010.984
NRCS–USDA0.970.945
USDA–Loveday method1.090.952
Table 4. Regression equations describing the relation between saturated paste extracts ECe and EC1:5 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil samples examined.
Table 4. Regression equations describing the relation between saturated paste extracts ECe and EC1:5 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil samples examined.
EC1:5
MethodsECe = fEC1:5R2RMSE (dS m−1)
ECe–NRCSECe = 6.58 EC1:50.9731.09
ECe–USDAECe = 6.61 EC1:50.9531.27
ECe–Loveday methodECe = 6.71 EC1:50.9711.02
Table 5. Regression equations describing the relation between saturated paste extracts ECe and EC1:5 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined for ECe < 3 dS m−1 and ECe > 3 dS m−1.
Table 5. Regression equations describing the relation between saturated paste extracts ECe and EC1:5 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined for ECe < 3 dS m−1 and ECe > 3 dS m−1.
EC1:5
MethodsECe = fEC1:5R2RMSE (dS m−1)
ECe < 3 dS m−1
ECe–NRCSECe = 4.68 EC1:50.7180.189
ECe–USDAECe = 4.89 EC1:50.5370.130
ECe–Loveday methodECe = 5.46 EC1:50.6470.123
ECe > 3 dS m−1
ECe–NRCSECe = 6.60 EC1:50.9341.710
ECe–USDAECe = 6.60 EC1:50.9171.800
ECe–Loveday methodECe = 6.71 EC1:50.9421.580
Table 6. Regression equations describing the relation between saturated paste extracts ECe and EC1:1 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined.
Table 6. Regression equations describing the relation between saturated paste extracts ECe and EC1:1 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined.
EC1:1
MethodsECe = fEC1:1R2RMSE (dS m−1)
ECe–NRCSECe = 2.07 EC1:10.9860.63
ECe–USDAECe = 1.93 EC1:10.9910.74
ECe–Loveday methodECe = 2.12 EC1:10.9880.68
Table 7. Regression equations describing the relation between saturated paste extracts ECe and EC1:1 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined for ECe < 3 dS m−1 and ECe > 3 dS m−1.
Table 7. Regression equations describing the relation between saturated paste extracts ECe and EC1:1 determined by three different methods with the coefficients of determination (R2) and root mean square errors (RMSE) for all soil examined for ECe < 3 dS m−1 and ECe > 3 dS m−1.
EC1:1
MethodsECe = fEC1:1R2RMSE (dS m−1)
ECe < 3 dS m−1
ECe–NRCSECe = 1.65 EC1:10.5510.102
ECe–USDAECe = 1.93 EC1:10.5660.254
ECe–Loveday methodECe = 1.96 EC1:10.6240.091
ECe > 3 dS m−1
ECe–NRCSECe = 2.08 EC1:10.9851.62
ECe–USDAECe =1.90 EC1:10.9911.06
ECe–Loveday methodECe =2.12 EC1:10.9841.62

Share and Cite

MDPI and ACS Style

Kargas, G.; Londra, P.; Sgoubopoulou, A. Comparison of Soil EC Values from Methods Based on 1:1 and 1:5 Soil to Water Ratios and ECe from Saturated Paste Extract Based Method. Water 2020, 12, 1010. https://doi.org/10.3390/w12041010

AMA Style

Kargas G, Londra P, Sgoubopoulou A. Comparison of Soil EC Values from Methods Based on 1:1 and 1:5 Soil to Water Ratios and ECe from Saturated Paste Extract Based Method. Water. 2020; 12(4):1010. https://doi.org/10.3390/w12041010

Chicago/Turabian Style

Kargas, George, Paraskevi Londra, and Anastasia Sgoubopoulou. 2020. "Comparison of Soil EC Values from Methods Based on 1:1 and 1:5 Soil to Water Ratios and ECe from Saturated Paste Extract Based Method" Water 12, no. 4: 1010. https://doi.org/10.3390/w12041010

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop