Modeling Soil Cation Exchange Capacity in Arid Region of Iran: Application of Novel Hybrid Intelligence Paradigm.

Abstract The potential of the soil to hold plant nutrients is governed by cation exchange capacity (CEC) of any soil. Estimating soil CEC aids in conventional soil management practices to replenish the soil solution that supports plant growth. In the present study, a multiple model integration scheme driven by hybrid GANN (MM-GANN) was developed and employed to predict the accuracy of soil CEC in Tabriz plain, an arid region of Iran. The standalone models (i.e., artificial neural network (ANN) and extreme learning machine (ELM)) were implemented for incorporating in the MM-GANN. In addition, it was tested to enhance the prediction accuracy of the standalone models. The soil parameters such as clay, silt, pH, carbonate, calcium equivalent (CCE), and soil organic matter (OM) were used as model inputs to predict soil CEC. By the use of several evaluation criteria, the results showed that the MM-GANN model involving the predictions of ELM and ANN models calibrated by considering all the soil parameters (e.g., Clay, OM, pH, Silt, and CCE) as inputs provided superior soil CEC estimates with an NSE = 0.87. The proposed MM-GANN model is a reliable intelligence based approach for the assessment of soil quality parameters intended for sustainability and management prospects.

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Modeling soil cation exchange capacity using soil parameters: Assessing the heuristic models

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2017.02.016 ◽

2017 ◽

Vol 135 ◽

pp. 242-251 ◽

Cited By ~ 26

Author(s):

Jalal Shiri ◽

Ali Keshavarzi ◽

Ozgur Kisi ◽

Ursula Iturraran-Viveros ◽

Ali Bagherzadeh ◽

...

Keyword(s):

Cation Exchange ◽

Cation Exchange Capacity ◽

Exchange Capacity ◽

Soil Parameters ◽

Soil Cation Exchange Capacity

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Acidification of soils on a transect from plains to slopes, south western New-South-Wales

Soil Research ◽

10.1071/sr9900539 ◽

1990 ◽

Vol 28 (4) ◽

pp. 539 ◽

Cited By ~ 21

Author(s):

CJ Chartres ◽

RW Cumming ◽

JA Beattie ◽

GM Bowman ◽

JT Wood

Keyword(s):

Cation Exchange ◽

Soil Acidification ◽

Cation Exchange Capacity ◽

Management Practices ◽

New South ◽

Exchange Capacity ◽

Soil Types ◽

The West ◽

South Wales ◽

Red Earth

Samples were collected from unimproved road reserves and adjacent paddocks on a 90 km transect crossing red-brown earth soils in the west and red earth soils in the east. Measurements of pH in water and CaCl2 indicated that the red earths have been acidified by approximately 0.5 pH units over the last 30-40 years. Small increases in CaCl2-extractable A1 were also recorded for the acidified red earths. The red-brown earths do not appear to have been markedly affected by soil acidification to date. Clay mineralogical data and measurements of cation exchange capacity of the <2 �m fraction indicate that red-brown earths are better buffered against acidification than red earths. However, small differences in management practices and rainfall along the transect may also be partially responsible for differences in acidification between soil types.

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USE OF A SOIL DATA FILE FOR PEDOLOGICAL RESEARCH

Canadian Journal of Soil Science ◽

10.4141/cjss74-026 ◽

1974 ◽

Vol 54 (2) ◽

pp. 195-204 ◽

Cited By ~ 4

Author(s):

B. KLOOSTERMAN ◽

L. M. LAVKULICH ◽

M. K. JOHN

Keyword(s):

Soil Properties ◽

Cation Exchange ◽

Cation Exchange Capacity ◽

Data File ◽

Exchange Capacity ◽

Soil Survey ◽

Soil Parameters ◽

Soil Drainage ◽

Normal Distributions ◽

Podzolic Soils

The potential application of a computer soil data file to the study of soil concepts is discussed. This method aids the pedologist to analyze, summarize and correlate large quantities of data. For applied objectives the data file allows the prediction of soil properties for interpretive purposes. The computerized soil data file was used to explore its usefulness in studying the concept of the modal profile, confirmation of definitions of the Podzolic and Gleysolic Great Groups, derivation of equations for estimating soil drainage and cation-exchange capacity, and studying some interrelationships among soil properties. Soil parameters used to define soils at the Order and Great Group levels did trend toward normal distributions for Gleysolic but less for Podzolic soils. The prediction equations for cation-exchange capacity accounted for a higher percentage of the variation than did equations for soil drainage. Many soil property interrelationships were confirmed. The study illustrates some of the weaknesses of using routine soil survey data collected over a 10-yr period.

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Long-Term Effects of Wheat Production Management Practices on Exchangeable Base Cations and Cation Exchange Capacity of a Plinthosol in Semi-arid South Africa

Communications in Soil Science and Plant Analysis ◽

10.1080/00103624.2013.867060 ◽

2014 ◽

Vol 45 (8) ◽

pp. 1083-1105 ◽

Cited By ~ 3

Author(s):

P. F. Loke ◽

E. Kotzé ◽

C. C. Du Preez

Keyword(s):

South Africa ◽

Cation Exchange ◽

Cation Exchange Capacity ◽

Production Management ◽

Management Practices ◽

Base Cations ◽

Exchange Capacity ◽

Long Term Effects ◽

Semi Arid

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Soil Quality of a Rice Organic Farm in Langkong, M'lang, Cotabato

Southeastern Philippines Journal of Research and Development ◽

10.53899/spjrd.v24i1.11 ◽

2019 ◽

Vol 24 (1) ◽

pp. 35-53

Author(s):

Kathleen Cedeño

Keyword(s):

Organic Matter ◽

Soil Fertility ◽

Cation Exchange ◽

Soil Quality ◽

Cation Exchange Capacity ◽

Management Practices ◽

Exchange Capacity ◽

Water Holding Capacity ◽

Water Holding

Soil quality is crucial to global food production security. However, research data on soil quality, which is vital to enhancing soil fertility and crop yield, is limited particularly on the soil in the rice fields located in Langkong, Mlang, Cotabato. This study aims to assess the soil quality of one of the organic rice farms in said area. Soil samples were collected in thirty-one (31) paddies for two sampling periods: thirty (30) days after harvest and thirty (30) days after rice transplanting. Eight (8) soil indicators representing soil physicochemical characteristics were measured from 0-15 cm depth; the indicators were soil texture, water holding capacity, pH, exchangeable phosphorus, extractable potassium, total organic matter, electrical conductivity, and cation exchange capacity. Results reveal that soils in the studied area are characterized by clay loam with moderate water-holding capacity of about 62.57% and 60.57% for both sampling periods, respectively. The soil is strongly acidic (5.3 and 5.5) and has a low amount of organic matter (2.16% and 1.57%) and exchangeable P (8.55 ppm and 2.48 ppm), although it has marginal extractable K (80.77 ppm and 91.10 ppm). Also, the soils are non-saline and have low cation exchange capacity. The findings signify that the soils have insufficient fertility to sustain the optimal growth of the rice plants which can potentially reduce the yield of rice production. Thus, amendment of the soil quality and enhancement of soil management practices should be taken into consideration to further improve soil fertility to ensure productivity and profitability of farmers.

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Prediction of cation exchange capacity from soil index properties

Clay Minerals ◽

10.1180/0009855064140222 ◽

2006 ◽

Vol 41 (4) ◽

pp. 827-837 ◽

Cited By ~ 26

Author(s):

Y. Yukselen ◽

A. Kaya

Keyword(s):

Cation Exchange ◽

Correlation Coefficient ◽

Cation Exchange Capacity ◽

Clay Fraction ◽

Exchange Capacity ◽

Atterberg Limits ◽

Engineering Properties ◽

Soil Parameters ◽

Quick Method ◽

Swell Index

AbstractIn many areas of geotechnical engineering it is necessary to have an estimate of the cation exchange capacity (CEC) of a soil in order to allow preliminary design estimates. Standard methods of CEC determination are time-consuming and involve several steps (e.g. displacement of the saturating cation requires several washings with alcohol). Therefore, a rapid method of CEC estimation would be very useful. During preliminary site investigations, the soil engineering parameters can be estimated from the considerable number of correlations available in the literature. In this study, relationships between CEC and various other soil engineering properties have been investigated, resulting in a quick method for estimating CEC.Simple correlations were developed between CEC and specific surface area (SSA), soil organic matter (OM), clay fraction (CF), activity (A), Atterberg limits (liquid (LL), plastic (PL), and shrinkage (SL)), and modified free swell index (MFSI) of the soils. Strong correlations are observed between the CEC values and those for ethylene glycol monoethyl ether (EGME) uptake and methylene blue (MB) titration. However, no significant correlation was found between CEC and N2_SSA. No unique relationship was seen between CEC and CF (r2 <0.5). No relationship was observed between CEC and OM in this study. The best correlation coefficient between the CEC and Atterberg limits exists between CEC and LL (r2 = 0.61). No significant relationship was seen between CEC and PL or SL. The correlation coefficient between CEC and MFSI was 0.65. Multiple linear regression analyses were developed to investigate the contributions of different soil parameters to CEC. These analyses show that EGME_SSA, in combination with LL, accounted for 91% of the variation in CEC. Correlations between CEC and EGME_SSA, MB_SSA and LL appear to be sufficiently good to enable an indication of CEC to be estimated from these parameters.

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Concrete Grinding Residue: Management Practices and Reuse for Soil Stabilization

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198119854292 ◽

2019 ◽

Vol 2673 (11) ◽

pp. 748-763

Author(s):

Bo Yang ◽

Yang Zhang ◽

Bora Cetin ◽

Halil Ceylan

Keyword(s):

Electrical Conductivity ◽

Cation Exchange ◽

Cation Exchange Capacity ◽

Management Practices ◽

Soil Stabilization ◽

Cooling Water ◽

Exchange Capacity ◽

Residue Management ◽

Unit Weight ◽

State Regulations

Concrete grinding residue (CGR) is a slurry byproduct produced from diamond grinding operations used to smooth concrete pavement surface. As a waste material, CGR consists of cooling water for blades and concrete fines from the removed concrete layer. Since the composition of CGR reflects high pH, it can be a critical environmental issue and should be managed properly to reduce its impact to the ecological system. To understand the current management practices of CGR throughout the U.S.A., a comprehensive review of state regulations and a survey of departments of transportation and contractors were conducted in this study, with results showing that in many states detailed guidance for disposal of CGR to reduce risks was lacking. In addition, this study investigated the potential use of CGR for roadbed soil stabilization. To evaluate the performance of CGR for soil stabilization purpose, this study mixed 10%, 20%, 30%, and 40% of CGR by weight with two types of soils classified as A-4 and A-6 according to AASHTO. Unconfined compressive strength and California bearing ratio, pH, electrical conductivity, alkalinity, and cation-exchange capacity tests were conducted on specimens. Results of the strength tests showed that the soils treated with 20% of CGR had the highest strength. Other laboratory tests revealed that CGR treatment could reduce the maximum dry unit weight (γdmax) and plasticity and increase the pH, alkalinity, electrical conductivity and cation-exchange capacity of soils.

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Developing Multiple-Linear Regression Model to Predict Soil Cation Exchange Capacity for Nagaland Soils

Agropedology ◽

10.47114/j.agroped.2019.j6 ◽

2019 ◽

Vol 29 (1) ◽

Author(s):

Gaurav Mishra ◽

◽

Avishek Sarkar ◽

Gopal Tiwari ◽

Abhishek Jangir ◽

...

Keyword(s):

Regression Model ◽

Cation Exchange ◽

Cation Exchange Capacity ◽

Multiple Linear Regression Model ◽

Exchange Capacity ◽

Training Dataset ◽

Validation Dataset ◽

Soil Parameters ◽

Eastern Region ◽

Strong Basis

Cation exchange capacity (CEC) is an important parameter to assess the soil health and fertility. The procedure for measuring CEC is complicated and time consuming. To overcome this issue, researchers have developed and tested models to estimate CEC, but no such model has been developed for North-eastern region (NER) of India. In the present study, a training dataset of 198 numbers of soil samples having data of soil texture, bulk density (BD), pH, soil organic carbon (SOC) and CEC was used to develop step-wise regression model for CEC. Correlation analysis was done to extract the influential parameters for predicting CEC. Results showed that basic soil parameters were able to predict CEC and can define 90 % of variability with SSE value of 2.76. The agreement between observed and predicted CEC in validation dataset with R2 value of 0.665 provided a strong basis to identify input variables for predicting CEC in the region.

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