Saturated Paste Extract Research Articles

Evaluation analysis of the saturated paste method for determining typical coastal saline soil salinity

The electrical conductivity of saturated paste extracts (ECe) is more widely used as the laboratory method for estimating soil salinity compared to the soil-water ratio method. However, the current saturated paste process is time consuming and mainly based on subjective experience, and the quantitative relationships among the factors influencing the saturated paste process are not clear. In order to understand and optimize the process of soil salinity determination by saturated paste method, an experiment involving the process of making saturated paste and the key factors in salt determination was carried out on coastal saline silt and sandy loam soils: amount of water added, soaking time, number of centrifugations, and soil particle size. These test factors had clear impact on soil salinity results (both ECe and mass salt content) and pH. Based on the principle of obtaining more mass salt content in this study, suitable parameters for the production of saturated slurries were proposed as follows: (1) the amount of distilled water added to the soil sample should be 2.2 times the saturated water content of the soil; (2) the equilibration time of saturated paste was reduced from 18 to 12 h; (3) only 40 % of the full salt content was obtained by one centrifugation and obtaining 80 % requires three centrifugations; and (4) 0.25–0.50 and 1–2 mm of particle-size sieving should be used to prepare samples of silt and sandy loam soils, respectively.

Plastic film buried in a low-lying strongly salt-affected wasteland: An effective desalinization approach should not be ignored for Amorpha fruticosa afforestation

Cutting off the upward movement of salts by capillary barriers may be an effective approach to control the root-zone salt accumulation in a low-lying salt-affected wasteland with high evaporation. This study aimed to determine whether buried plastic film (BPF), as an ignored desalinization approach, could better sustainably ameliorate salt-affected soil environment especially soil salinity than common capillary barriers (buried maize straw, BMS; buried sand, BS) and CK (a control without buried material) during Amorpha fruticosa afforestation. All the capillary barriers especially BPF effectively reduced electrical conductivity of saturated paste extracts (ECe) compared to CK in both years mainly due to its greater effectiveness of salts isolation, and gravitational washing increasingly via more preferential pathways indicated by its higher fine-root mass density (FRMD). Capillary barriers varyingly improved the fertility and structure in different soil layers. BPF reduced soil organic carbon (SOC) in 0–20 cm most in 2016, but increased it most in 2017; while BMS increased SOC in 20–40 cm most in both years. In both years, available nitrogen (AN) in 0–20 cm increased most for BPF, while AN in 20–40 cm did for BMS. Similarly, BPF improved better in soil structure (mean weight diameter, MWD; soil total porosity, STP) in 0–20 cm while BMS did in 20–40 cm. As the salinity declined, BPF was more beneficial to the stand establishment and plant growth which in turn further bio-physicochemically improved salt-affected soil environment. BPF was not only far less costly than BMS or BS, but also obviously produced more yield and thus greater net revenue in the second year. Thus, BPF is a promising alternative for desalinization during the afforestation of salt-tolerant plants in the similar strongly salt-affected areas.

Comparison of solution extraction methods for estimating electrical conductivity in soils with contrasting mineralogical assemblages and textures

Characterization of the soil solution is of fundamental importance for monitoring plant nutrient availability, environmental contamination, and evaluation of salt-affected soils. Due to the diversity of methodologies adopted in various parts of the world, comparison of the most common extraction methods in different types of soils is warranted. This study compared the efficiency of five soil solution extraction methods for five soils with different mineralogical assemblages and textures with the most commonly used saturated paste extract method. The extraction methods compared were: centrifugation, porous extractor capsules, and soil–water extracts (soil:water ratio of 1:2, 1:5, or 1:10). The soil types evaluated were: Regosol, Luvisol, Gleysol, Nitisol and Ferrosol in the soil surface and subsurface horizons. Linear regression equations were developed that allowed accurate estimation of electrical conductivity of the saturated paste extract (ECse). Ten equations were developed for the porous capsule method, eight were developed for the centrifugation method (with the exception of the Regosol with 900 g k−1 of total sand, which was not suitable for this method due to the high sand content), and 30 equations were developed for the soil–water extract method (at each of the soil:water ratios tested). The diversity of equations developed for soils with different mineralogical assemblages and textures should assist growers and extension workers who need to know the soil electrical conductivity for making soil management decisions.

Ensemble HYDRUS-2D modeling to improve apparent electrical conductivity sensing of soil salinity under drip irrigation

Monitoring and mapping soil salinity are valuable for irrigation management and reclamation of salt-affected agricultural soils in arid and semi-arid regions. Proximal measurements of apparent soil electrical conductivity (ECa) can help characterize soil salinity spatial distributions. However, ECa is not solely a function of salinity. ECa is strongly influenced by soil salinity, water content, and edaphic properties such as texture and bulk density. Consequently, monitoring and mapping salinity based on geospatial ECa measurements is challenging in fields with dynamic and spatially complex patterns of salinity and water content, such as occurs under drip irrigation. We conducted a numerical modeling study to evaluate protocols for using proximal ECa sensing in drip irrigated systems, focusing specifically on the measurement distance from the drip-line that consistently identifies areas of high salinity in the rootzone. The measurement distance was evaluated as a function of six irrigation management parameters: soil hydraulic conductivity, irrigation discharge, irrigation interval, solute concentration, root-zone volume, and leaching fraction. HYDRUS-2D was used to run a 729 member ensemble of drip irrigation simulations of water and solute dynamics under different irrigation management scenarios. Two case studies were simulated for clay loam soil: (1) low salinity soil irrigated with high salinity irrigation water and (2) high salinity soil irrigated with low salinity water. Depth-averaged ECa measurements down to the 75 and 150 cm depths, such as can be obtained using an electromagnetic induction (EMI) sensor, were evaluated in the simulations. According to the ensemble results, a reliable EMI measurement distance from the drip-line was about 100 cm for the case of low salinity irrigation in saline soil and adjacent to the drip-line for the high salinity irrigation. The ensemble ECa and EC of saturated paste extract (ECe) distributions were twice as sensitive to the irrigation water salinity level as compared to the other irrigation management parameters. The probabilistic ensemble approach can be extended to a variety of case studies to aid soil scientists and agricultural consultants monitoring and mapping soil salinity with ECa-directed soil sampling for micro-irrigation systems.

Depth-Specific Soil Electrical Conductivity and NDVI Elucidate Salinity Effects on Crop Development in Reclaimed Marsh Soils

Agricultural management decision-making in salinization-prone environments requires efficient soil salinity monitoring methods. This is the case in the B-XII irrigation district in SW Spain, a heavy clay reclaimed marsh area where a shallow saline water table and intensively irrigated agriculture create a fragile balance between salt accumulation and leaching in the root zone, which might be disrupted by the introduction of new crops and increasing climate variability. We evaluated the potential of electromagnetic induction (EMI) tomography for field-scale soil salinity assessment in this hyper-conductive environment, using EMI and limited analytical soil data measured in 2017 and 2020 under a processing tomato–cotton–sugar beet crop rotation. Salinity effects on crop development were assessed by comparing Sentinel 2 NDVI imagery with inverted depth-specific electrical conductivity (EC). Average apparent electrical conductivity (ECa) for the 1-m depth signal was 20% smaller in 2020 than in 2017, although the spatial ECa pattern was similar for both years. Inverted depth-specific EC showed a strong correlation (R ≈ 0.90) with saturated paste extract EC (ECe), [Na+] and sodium absorption ratio (SAR), resulting in linear calibration equations with R2 ≈ 0.8 for both years and leave-one-out cross validation Nash–Sutcliffe Efficiency Coefficient, ranging from 0.57 to 0.74. Overall, the chemical parameter estimation improved with depth and soil wetness (2017), yielding 0.83 < R <0.98 at 0.9 m. The observed spatial EC distributions showed a steadily increasing inverse correlation with NDVI during the growing season, particularly for processing tomato and cotton, reaching R values of −0.71 and −0.85, respectively. These results confirm the potential of EMI tomography for mapping and monitoring soil salinity in the B-XII irrigation district, while it allows, in combination with NDVI imagery, a detailed spatial assessment of soil salinity impacts on crop development throughout the growing season. Contrary to the popular belief among farmers in the area, and despite non-saline topsoil conditions, spatial EC and subsoil salinity patterns were found to affect crop development negatively in the studied field.

The Clean Water Act and biosolids: A 45‐year chronological review of biosolids land application research in Colorado

The 1972 U.S. Clean Water Act set forth the generation of biosolids. In Colorado, biosolids land application research began in 1976 and continues today. Pastureland research suggested that sewage effluent could effectively be land applied to benefit aboveground plant growth and to polish water prior to reaching receiving waters. Forest wildfire-affected ecosystems can also benefit from biosolids applications; application rates of up to 80 Mg ha-1 can lead to greater plant establishment, soil microbial activity, and nutrient turnover and reduced nutrient and heavy metal concentrations in runoff below livestock and USEPA drinking water standards. Long-term (24-yr) observations in oil shale-mined lands showed that biosolids (up to 224 Mg ha-1 ) can have a positive effect on microbial-mediated nutrient cycling and, in turn, on aboveground plant community structure. Biosolids applications of up to 40 Mg ha-1 in high-elevation shrubland ecosystems, dominated by Mo-containing shale deposits, can aid in reducing imbalances between Mo and Cu in soils and plants; excessive plant Mo, when consumed by ruminants, can lead to molybdenosis. Biosolids and lime applications (both at 224 Mg ha-1 ) have been shown to improve long-term reclamation success on acid-generating, heavy metal-containing fluvial mine tailings. Thirty years of grazing land research, focused on soil and aboveground plant benefits, illustrate that soil health and plant productivity can be improved to the greatest extent at biosolids application rates close to 10 Mg ha-1 . Finally, 40 yr of dryland agroecosystem research (a) have helped identify biosolids N fertilizer equivalency (∼8kg N Mg-1 ) and thus dryland winter wheat application rates (e.g., 4.5-6.7 dry Mg ha-1 ); (b) have identified first-year mineralization rates of 25-32%; (c) dispute the "time bomb" theory by showing that plant metal uptake follows an exponential rise to a maximum; (d) showcase economic return to producers via increased wheat grain protein content; (e) suggest that biosolids-borne proteins and their degradation products are labile C and N sources; (f) have led to long-term tracking of micronutrients and heavy metals in soils and revealed that plants-soil concentrations will not lead to groundwater degradation and that plants are safe for human consumption; and (g) have shown that biosolids provide Zn, helping to overcome soil deficiencies and enhancing Zn biofortification in wheat grain. This latter point is important because ∼2 billion people globally suffer from Zn deficiencies. Forty-five years of research in Colorado have proven that biosolids can enhance environmental quality, improve soil health, and produce healthy food products.

Soil texture affects the conversion factor of electrical conductivity from 1:5 soil-water to saturated paste extracts

Electrical conductivity (EC) of soil-water extracts is commonly used to assess soil salinity. However, its conversion to the EC of saturated soil paste extracts (EC e ), the standard measure of soil salinity, is currently required for practical applications. Although many regression models can be used to obtain EC e from the EC of soil-water extracts, the application of a site-specific model to different sites is not straightforward due to confounding soil factors such as soil texture. This study was conducted to develop a universal regression model to estimate a conversion factor (CF) for predicting EC e from EC of soil-water extracts at a 1:5 ratio (EC 1:5 ), by employing a site-specific soil texture ( i.e ., sand content). A regression model, CF = 8.910 5e 0.010 6sand /1.298 4 ( r 2 = 0.97, P < 0.001), was developed based on the results of coastal saline soil surveys ( n = 173) and laboratory experiments using artificial saline soils with different textures ( n = 6, sand content = 10%–65%) and salinity levels ( n = 7, salinity = 1–24 dS m -1 ). Model performance was validated using an independent dataset and demonstrated that EC e prediction using the developed model is more suitable for highly saline soils than for low saline soils. The feasibility of the regression model should be tested at other sites. Other soil factors affecting EC conversion factor also need to be explored to revise and improve the model through further studies.

Evaluating soil salts dynamics under biodegradable film mulching with different disintegration rates in an arid region with shallow and saline groundwater: Experimental and modeling study

Soil salinization caused by shallow, saline groundwater represents a serious threat to field productivity, especially in arid regions with intense soil evaporation. Plastic film mulching (PM) has been increasingly applied to reduce soil evaporation and alleviate soil salinity stress. However, PM introduces into the soil a significant amount of plastic residues. Although biodegradable film mulching (BM) is an ideal alternative to PM due to the degradability of these films, unreasonably high disintegration rates may reduce the benefits of the proposed solution. Understanding the effects of these factors on soil salinity is essential for designing management options for improving water productivity. A two-year cornfield experiment was therefore carried out during 2019–2020 to evaluate differences in soil salt dynamics among treatments with BMs with low, medium, and high disintegration rates (BML, BMM, BMH), one polyethylene film mulching (PM), and no mulching (NM). Additionally, the HYDRUS-2D model was used to evaluate the electrical conductivity of the saturation paste extract (ECe), soil salt fluxes, salt distributions, and salt mass balances in two-dimensional soil profiles under BML, BMM, BMH, PM, and NM. The results showed that calibrated HYDRUS-2D could precisely simulate soil salinity under different mulching treatments. There were large differences between various treatments in the middle and late crop growth stages (Days After Sowing [DAS] 61–140). The highest ECe among different BM treatments occurred in BMH. Additionally, the two-dimensional distribution of soil salinity under BM was affected by irrigation events. The high soil salinity stress area (ECe > 3.80 dS m−1) occurred one day after irrigation (DAS 108) only under BMH among different BM treatments. Meanwhile, root water uptake (RWU) and crop yield (CY) under BMH were significantly reduced due to excessive accumulation of soil salinity in the root zone under intensive soil evaporation conditions. Compared with BMH and BMM, BML increased CY and the leaching ratio of soil salts from the root zone due to its good performance in water conservation. Thus, BM with a low disintegration rate is more efficient in controlling soil salinization in soils with a shallow groundwater table than BMs with higher disintegration rates due to lower soil evaporation. The findings of this study improve the understanding of the mechanisms of salt dynamics under biodegradable film mulching with different disintegration rates. The study also recommends to the farmers and government a suitable disintegration rate of the biodegradable film that can be adopted to promote field productivity.

Spatial characterization of total salt in non-saline soil solutions through electromagnetic induction

Apparent electrical conductivity (ECa) surveys can indirectly spatially characterise total salt in saline soil solutions, i.e., electrical conductivity of a saturated paste extract (ECe). Due to complexity of ECa-readings a 10-step protocol, including an analytical procedure (Dual Pathway Parallel Conductance, DPPC) and software (Electrical conductivity Sampling Assessment and Prediction), have been developed to facilitate with the process. Studies where ECa readings have been used to spatially characterise ECe in soil solutions below 2 dS m−1 (non-saline) are limited to non-existing. The aim was to collectively use above-mentioned tools to determine the success with which ECe can be spatially characterised in non-saline soil solutions with variable and uniform texture across the field. Dataset 1 consisted of ECe, gravimetric moisture and clay measurements from 277 grid sampling sites across 320 ha (seven fields). Dataset 2 contained a mean 443 ECa readings ha−1 together with measurements of ECe, clay, gravimetric moisture, and bulk density from 12 ECa-directed sampling sites per field. Dataset 1; the r between calculated ECa (ECac) and ECe at all fields were >0.9. Dataset 2; deep ECa readings (i.e., 1 m coil separation for both dipole orientations) remained stable during surveys (not true for shallow readings). At 3 fields, uniform in depth and spatially in terms of clay content (±10% clay), relatively low ECa readings (±50 mS m−1) significantly correlated with low ECe values (<1.5 dS m−1). Hence, proactive management of excessive irrigation-induced drainage and salt leaching by spatial monitoring of ECe in non-saline soil, spatially uniform in texture, through electromagnetic induction is conceivable.

The Effect of Soil Texture on the Conversion Factor of 1:5 Soil/Water Extract Electrical Conductivity (EC1:5) to Soil Saturated Paste Extract Electrical Conductivity (ECe)

The electrical conductivity of soil saturated paste extract (ECe) is used as an indicator for estimating soil salinity. This method is time consuming and laborious and therefore, easier and faster methods are usually used with different soil/water ratios, such as 1:5 (EC1:5), for estimating the ECe. Usually, the relationship between ECe and EC1:5 is described by a simple linear empirical equation. The value of the conversion factor (CF) of EC1:5 to ECe is affected by the particular characteristics of the soil, such as its texture. The objective of this study is to investigate models that allow the inclusion of soil texture in the calculation of the CF, in order to improve the prediction of the ECe. A total of 148 soil samples with different soil texture and salinity levels were selected from three regions of Greece, and ECe, EC1:5, as well as clay and sand contents were determined. The results show that the CF can be estimated from an equation which incorporates the clay and sand contents through the soil saturation percentage (SP) and can give a fairly good prediction of ECe from EC1:5 (R2 = 0.9887 and RMSE = 1.39 dSm−1).

Hyperspectral remote sensing-based prediction of the soil pH and salinity in the soil to water suspension and saturation paste extract of salt-affected soils of the west coast region

The study aimed to investigate hyperspectral remote sensing to predict the soil pH and salinity in the soil to water suspension and saturation paste extract of salt-affected soils of the west coast region. About 216 soil samples were collected from the salt-affected areas of the west coast region of India (State of Maharashtra, Goa, Karnataka and Kerala). The soil pH and electrical conductivity (EC) in fixed ratios of 1:1, 1:2, 1:2.5 and 1:5 soil to water extracts and soil saturation paste extract were determined and the spectral data measurement in the wavelength range of 350–2500 nm was carried out. The data was divided into a calibration dataset (70% of the total) and a validation dataset (30% of the total dataset). The spectral data (raw spectral reflectance averaged at 10 nm) was modeled using multivariate analysis techniques - partial least square regression, principal component regression and support vector regression. The average values of soil pH of 1:1, 1:2, 1:2.5, 1:5 soil: water extract and soil saturation paste (pHe) extract were 4.32, 4.96, 5.01, 5.15 and 5.33, respectively, whereas, the corresponding EC values were 14.00, 7.65, 6.37, 3.52 and 19.96 dS m−1, respectively. The pHe and EC of soil saturation paste extract (ECe) were in the range of 3.067.39 and 0.61–59.18 dS m−1. The coefficient of determination (R2) of pHe with pH of 1:1, 1:2, 1:2.5 and 1:5 soil extract ratio was 0.73, 0.73, 0.72 and 0.73 (p<0.05) respectively. The ECe had a R2 of 0.85, 0.84, 0.85 and 0.84 (p<0.05) with EC of 1:1, 1:2, 1:2.5 and 1:5 soil: water extract ratio, respectively. All these relationships were linear and significant. Thus, the regression relation of ECe with EC1:2, ECe = 2.5272 x (EC1:2) + 2.77 (R2=0.84, p<0.05) could be more useful for studies related to the salinity of salt-affected soil of the west coast region of India where soil salinity is typically associated with the acidity. A good agreement between the actual and predicted pH and EC for different ratios and the extract were exhibited by the coefficient of correlation ranging from 0.48–0.79 and 0.70–0.87, respectively. Among different multivariate techniques tested, partial least square regression outperformed principal component regression and support vector regression. Among all the parameters, the best prediction was achieved for ECe accuracy as r=0.87, R2=0.76, RMSE=5.65 and rank=4 (lowest) with partial least square regression. Thus, the soil saturation paste extract salinity of the salt-affected soils of the west coast region can be monitored using visible near-infrared remote sensing

Evaluation of soil salinity using the dielectric sensor WET-2

Context The electrical conductivity of the soil saturated paste extract (ECe) is used to estimate the soil salinity. Aims This study aims to develop simple or multiple linear regression models to estimate the ECe using soil properties measured by a dielectric sensor in the field. Methods The measurements of bulk electrical conductivity (ECb), soil temperature (T) and dielectric permittivity (εb) in agricultural fields were conducted using the WET-2 sensor. A total of 105 soil samples were obtained from agricultural fields in three regions of Greece. Key results A very strong positive correlation between ECb and ECe (r &gt; 0.6 and P &lt; 0.001) was obtained by using the Spearman’s correlation coefficients. Multiple linear regression models (MLR) were developed using only the parameters εb, ECb and T measured by the WET-2 in estimating ECe. Considering that the MLR models are site specific, the ECe could be reliably estimated by applying MLR models in regions with coarse textured soils. Contrarily, in regions with finer textured soils characterised by ECb values &lt;1 dS m−1, additional soil parameters are required to be included in MLR models to estimate of ECe more accurately. In regions with soils characterised by high salinity (4 dS m−1 &lt; ECe &lt; 25 dS m−1), a simple linear regression model seems to be sufficient. Conclusions and implications As the WET-2 sensor measures simultaneously three soil properties in situ, it might be a valuable tool for estimating ECe, for the first centimetres of soil, in the case that the soil is not dry with relatively low clay content.

Ground Observations and Environmental Covariates Integration for Mapping of Soil Salinity: A Machine Learning-Based Approach

Soil salinization is a severe danger to agricultural activity in arid and semi-arid areas, reducing crop production and contributing to land destruction. This investigation aimed to utilize machine learning algorithms to predict spatial soil salinity (dS m−1) by combining environmental covariates derived from remotely sensed (RS) data, a digital elevation model (DEM), and proximal sensing (PS). The study is located in an arid region, southern Iran (52°51′–53°02′E; 28°16′–28°29′N), in which we collected 300 surface soil samples and acquired the spectral data with RS (Sentinel-2) and PS (electromagnetic induction instrument (EMI) and portable X-ray fluorescence (pXRF)). Afterward, we analyzed the data using five machine learning methods as follows: random forest—RF, k-nearest neighbors—kNN, support vector machines—SVM, partial least squares regression—PLSR, artificial neural networks—ANN, and the ensemble of individual models. To estimate the electrical conductivity of the saturated paste extract (ECe), we built three scenarios, including Scenario (1): Synthetic Soil Image (SySI) bands and salinity indices derived from it; Scenario (2): RS data, PS data, topographic attributes, and geology and geomorphology maps; and Scenario (3): the combination of Scenarios (1) and (2). The best prediction accuracy was obtained for the RF model in Scenario (3) (R2 = 0.48 and RMSE = 2.49), followed by Scenario (2) (RF model, R2 = 0.47 and RMSE = 2.50) and Scenario (1) for the SVM model (R2 = 0.26 and RMSE = 2.97). According to ensemble modeling, a combined strategy with the five models exceeded the performance of all the single ones and predicted soil salinity in all scenarios. The results revealed that the ensemble modeling method had higher reliability and more accurate predictive soil salinity than the individual approach. Relative improvement (RI%) showed that the R2 index in the ensemble model improved compared to the most precise prediction for the Scenarios (1), (2), and (3) with 120.95%, 56.82%, and 66.71%, respectively. We applied the best model in each scenario for mapping the soil salinity in the selected area, which indicated that ECe tended to increase from the northwestern to south and southeastern regions. The area with high ECe was located in the regions that mainly had low elevations and playa. The areas with low ECe were located in the higher elevations with steeper slopes and alluvial fans, and thus, relief had great importance. This study provides a precise, cost-effective, and scientific base prediction for decision-making purposes to map soil salinity in arid regions.

Assessment and mapping of the agro-ecological risk in the Mina plain (northwestern Algeria): Soil salinity and irrigation water quality

Abstract The objective of this study is to contribute in assessing and mapping of the salinity risks level of soil and groundwater for irrigation in the Mina plain. The experimentation was carried out on a surface area of 4000 ha. Electromagnetic conductivity (EM) measurements and soil and well water samples were taken and analysed. The results showed an important spatial variability of the electrical conductivity (EC) of saturated paste extracts (ECe), which varied between 1.35 and 28.8 dS/m. The isovalues map of ECe was estimated by the regression equation and interpolated by the ordinary kriging (OK) method which showed that the area of saline soils (ECe &gt; 4 dS/m) represented 90% of the study area. The results also showed poor to unsuitable well water quality. To find the risk of salinity and sodium, the water points were classified as C3S3 (2.5%), C4S2 (5%), C4S3 (30%) and C4S4 (62.5%). Spatial distribution maps of total dissolved solids (TDS), electrical conductivity of water (ECw) and sodium adsorption ratio (SAR) interpolated by inverse distance weighting (IDW) showed too high risk levels of ECw (&gt;5000 μS/cm) and TDS (&gt;3000 mg/l) occupying a large wellfield (70%); with regard to SAR (&gt;18), 36% of the groundwater had a high risk of sodium. These results showed that the choice of tolerant crops, redevelopment of drainage systems and irrigation with less saline water should be designed for the sustainability of soil productivity and agro-ecosystems.

Morphophysiological responses of table beet irrigated with saline water under application of humic substances

The use of saline water is an alternative for irrigating agricultural crops, especially in the Brazilian Northeastern semi-arid region, where water quality is limited in most cases. Thus, the objective was to evaluate the morphophysiological responses of table beet cv. “Wonder” irrigated with saline waters under the application of humic substances. The experiment was conducted under a randomized block design, with six replications in a 6 x 4 x 5 factorial scheme, referring to six electrical conductivities of irrigation water (ECw): 0.5; 1.5; 2.5; 3.5; 4.5 and 5.5 dS m-¹, four humic substances rates (HS) (0; 10; 20 and 30 ml per plant), and five stages of assessment (23, 38, 53, 68 and 83 days after emergency). The characteristics evaluated were: plant height, number of leaves, leaf area, chlorophyll content (a, b and total), stomatal conductance, transpiration, net photosynthesis and CO2 internal concentration, and in the soil, the soil pH and the electrical conductivity of saturated paste extract. The increase of salinity reduced growth, chlorophyll a content, and the stomatal conductance of beet plants. The application rate of 30 ml per plant of humic substances promotes an increase in stomatal conductance. The application of humic substances raises the pH in sandy acidic soils. It is recommended to irrigate table beet plants with water of 0.5 dS m-1 associated with the application of 30 mL per plant of humic substances

Effects of Equilibrium Time on Electrical Conductivity Measurements Using Soil-Water Extracts and Soil Saturated Paste

Electrical conductivity (EC) is a robust indicator of soil salinity. In South Korea, EC of 1:5 of soil:water extracts (EC1:5) and soil saturated paste extracts (ECe) are often used. The standard shaking time is 0.5 hr for EC1:5 and standing time after soil saturation is 16 hrs for ECe. In this study, we investigated the effects of equilibrium time (shaking and standing time for EC1:5 and ECe, respectively) to test if the standard time is enough for precise and accurate measurement of EC. Two soils (silt loam and sandy loam) with seven levels of EC were prepared by adding salt solutions (1, 2, 4, 8, 12, 16, and 24 dS m-1) to the soils. The soils were used for experiments after 2-months aging. The EC1:5 was measured after shaking soil-water mixture for 0.5, 1, 2, and 3 hrs, and ECe was determined after standing the saturated soils for 4, 8, 16, 24, and 48 hrs. The results showed that 4 hrs of standing time for ECe are sufficient for most saline soils regardless of soil texture. However, occasional occurrence of large variations in ECe up to 25% indicates a necessity of longer (e.g., 24 hrs) standing time for some soils. Therefore, for long-term monitoring of ECe, it may be necessary to determine site-specific standing time for ECe. Unlike ECe, the variations in EC1:5 with shaking time was negligible. However, for soils treated with solution of high EC (24 dS m-1), the variability increased up to 6% variations. Therefore, it may be necessary to increase shaking time to 1 hr to ensure a precise measurement of EC1:5 particularly for high-saline soils. For precise measurement of EC by achieving equilibrium of ions, shaking for 1 hr is required for EC1:5 and standing for 24 hrs is appropriate for ECe.

The effects of salinity on changes in characteristics of soils collected in a saline region of the Mekong Delta, Vietnam

Abstract Due to the impacts of climate change and the reduction in the flow of the Mekong River, saline intrusion into the inland has been an emergent and pressing issue. The purpose of this study is to analyze the effects of various saline conditions (0–25‰) on changes in some soil properties under laboratory conditions. Ten topsoil samples were collected from a depth of 0–20 cm in the dry seasons in the rice–corn rotation fields with low salinity, in Thanh Phu district, Ben Tre province, Vietnam. The examined criteria consisted of soil pH, soil electrical conductivity of the saturated paste extract (ECe), exchangeable Na, percentage of exchangeable Na, and content (%) of nitrogen and phosphorus. The results revealed that the pH range of soil decreased from 5.14–5.72 to 4.08–5.14 when the soil salinity increased from 0 to 25‰. At the salinity of 10‰ and higher, the available nitrogen began to decline. Meanwhile, the available phosphorus tended to decrease as the salinity increased past 12‰. Some measures are also discussed, with the aim of ensuring sustainable rice farming in the circumstances of increased salinity.

Drip‐irrigation using highly saline groundwater increases sunflower yield in heavily saline soil

AbstractTo improve global food security, techniques for sustainability managing salinity are needed. The objective of this study was to find a sustainable cultivating method for grain production using saline groundwater. A field experiment was conducted to determine the effect of drip irrigation with saline water (EC = 9.5 dS m–1) (DIS), drip irrigation with freshwater (electrical conductivity [EC] = 1.3 dS m–1) (DIF), and flood irrigation with freshwater (CK) on sunflower (Helianthus annuus L.) yields. The cultivation pattern of “scheduled drip irrigation + mulched ridge” was adopted in DIS and DIF, while that in CK was the local pattern of “flood irrigation + flat mulch”. Results showed that drip irrigation with saline water and drip irrigation with freshwater saved 95% and 43 freshwater when compared with CK. After 2 yr, soil electrical conductivity of saturated paste extracts (ECe) in the surface 40 cm decreased from 22.9 to 6.4 dS m–1 in DIS and from 17.9 to 5.4 in DIF. The calculated desalinization rates were 72.1% for DIS and 69.3% for DIF. The sunflower yield in DIS and DIF increased by 12.1 and 37.0% and the economic benefit correspondingly increased by 29.6 and 52.5% when compared with CK after 2 yr. The drip irrigation with saline groundwater had remarkable advantages in saving freshwater, leaching salt, and increasing income.

Effect of amendment sources under subsurface drainage system on physical and chemical properties of sodic soil

The present investigation was undertaken to study the effect of amendment sources under subsurface drainage system on physical and chemical properties of sodic soil classified as a fine montmorillonite hyperthermic family of Sodic Calciustert. The field experiment was conducted at Post Graduate Institute, Research Farm, Department of Soil Science and Agricultural Chemistry, MPKV, Rahuri, during Kharif 2019. Experimental soil showed strongly alkaline reaction, normal electrical conductivity, medium organic carbon content and moderately calcareous. The experiment was laid out in a randomized block design with three replication and twelve treatments. The treatment comprised of T1: Absolute control, T2: Gypsum as per 100% GR, T3: Elemental sulphur as per 1/5th of GR, T4: Zeolite @ 600 kg ha-1, T5: Gypsum as per 100% GR + zeolite @ 600 kg ha-1, T6: Gypsum as per 50% GR + zeolite @ 600 kg ha-1, T7: Gypsum as per 100% GR + zeolite @ 300 kg ha-1, T8: Gypsum as per 50% GR + zeolite @ 300 kg ha-1, T9: Elemental sulphur as per 1/5th of GR + zeolite @ 600 kg ha-1, T10: Elemental sulphur as per 50% of 1/5th GR + zeolite @ 600 kg ha-1, T11: Elemental sulphur as per 1/5th of GR + zeolite @ 300 kg ha-1 and T12: Elemental sulphur as per 50% of 1/5th GR + zeolite @ 300 kg ha-1. The results of investigation revealed that, the amendments applications in sodic soil under SSD system was influenced the soil physical and chemical characteristics. Significant results were found in reclamation of sodic soil. The physical properties of soil i.e. hydraulic conductivity and bulk density of sodic soil in SSD field was significantly improved by treatment Gypsum as per 100% GR + zeolite @ 600 kg ha-1 at harvest of crop.ESP and exchangeable cations i.e. Ca2+, Na+, Mg+ and K+ content of sodic soils in SSD field after harvest of crop was significantly influenced by treatment Gypsum as per 100% GR + zeolite @ 600 kg ha-1 except exchangeable Mg2+ which shows nonsignificant effect. Soil organic carbon, calcium carbonate and cation exchange capacity of sodic soils in SSD field are influenced by the inorganic amendments after harvest of crop. The organic carbon content of sodic soils in SSD field was significantly higher in treatment Gypsum as per 100% GR + zeolite @ 600 kg ha-1, applied Elemental sulphur as per 1/5th of GR + zeolite @ 600 kg ha-1 was found significantly lower values of CaCO3 and cation exchange capacity was significantly increased by the Gypsum as per 100% GR + zeolite @ 600 kg ha-1. The SAR in which cations and anions in saturation paste extract of sodic soil in SSD system was significantly influenced by treatment Gypsum as per 100% GR + zeolite @ 600 kg ha-1 after harvest of crop. Whereas, sulphate content was non-significant and carbonates was in trace amount.

Estimation of saturated paste electrical conductivity using three modelling approaches: Traditional dilution extracts; saturation percentage and artificial neural networks

Soil salinity is best estimated by saturated paste extract (ECe), the most reliable monitoring method to assess plant growth that is directly related to the field water content. However, this procedure is laborious and time-consuming, therefore, more convenient methods such as 1:5 soil: water extract is commonly used to estimate the ECe. Traditionally, a conversion factor (CF) based on a linear correlation between the diluted extract and ECe is employed for the estimation purposes. However, CF is affected by site-specific conditions. The objective of this research is to demonstrate a novel modelling approach that allows incorporating site-specific soil and irrigation water parameters to improve the accuracy of the ECe estimation. A total of 177 soil samples were collected from agricultural soils in the Jordan Valley representing different soil textures, crops and water qualities. ECe, EC1:5, clay and sand content, soil texture and saturation percentage (θSP) were determined. The collected data were used to construct models using three distinct approaches: traditional CF; incorporating θSP as a surrogate of soil texture to cater the CF to the site-conditions, and Artificial Neural Networks to incorporate site-specific parameters. The neural network model gave the most accurate estimates (R2 = 0.987, MSE = 2.39) and was able to handle the heteroscedasticity of the data. Meanwhile, the incorporation of θSP to estimate the CF that best represent the site has shown improved prediction quality over the traditional CF approach as it was more capable of handling the heteroscedasticity of the data. The neural network model allows for the incorporation of location-specific parameters and therefore offers a flexible tool for better management of agricultural soils. Although, this work used a case study location to demonstrate the concepts discussed, the approach is generalizable and can be easily adapted to other locations.