USE OF A SOIL DATA FILE FOR PEDOLOGICAL RESEARCH

1974 ◽  
Vol 54 (2) ◽  
pp. 195-204 ◽  
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.

scholarly journals Mapping Soil Properties to Advance the State of Spatial Soil Information for Greater Food Security on US Tribal Lands

2021 ◽  
Vol 1 ◽  
Author(s):  
Bryan Fuentes ◽  
Amanda J. Ashworth ◽  
Mercy Ngunjiri ◽  
Phillip Owens
Keyword(s):  
Food Security ◽  
High Resolution ◽  
Soil Properties ◽  
Cation Exchange ◽  
Cation Exchange Capacity ◽  
Soil Property ◽  
Exchange Capacity ◽  
Soil Survey ◽  
Soil Information ◽  
Tribal Lands

Knowledge, data, and understanding of soils is key for advancing agriculture and society. There is currently a critical need for sustainable soil management tools for enhanced food security on Native American Tribal Lands. Tribal Reservations have basic soil information and limited access to conservation programs provided to other U.S producers. The objective of this study was to create first ever high-resolution digital soil property maps of Quapaw Tribal Lands with limited data for sustainable soil resource management. We used a digital soil mapping (DSM) approach based on fuzzy logic to model the spatial distribution of 24 soil properties at 0–15 and 15–30 cm depths. A digital elevation model with 3 m resolution was used to derive terrain variables and a total of 28 samples were collected at 0–30 cm over the 22,880-ha reservation. Additionally, soil property maps were derived from Gridded Soil Survey Geographic Database (gSSURGO) for comparison. When comparing properties modeled by DSM to those derived from gSSURGO, DSM resulted in lower root mean squared error (RMSE) for percent clay and sand at 0–15 cm, and cation exchange capacity, percent clay, and pH at 15–30 cm. Conversely, gSSURGO-derived maps resulted in lower RMSE for cation exchange capacity, pH, and percent silt at the 0–15 cm depth, and percent sand and silt at the 15–30 cm depth. Although, some of the soil properties derived from gSSURGO had lower RMSE, spatial soil property patterns modeled by DSM were in better agreement with the topographic complexity and expected soil-landscape relationships. The proposed DSM approach developed property maps at high-resolution, which sets the baseline for production of new spatial soil information for Quapaw Tribal soils. It is expected that these maps and future versions will be useful for soil, crop, and land-use decisions at the farm and Tribal-level for increased agricultural productivity and economic development. Overall, this study provides a framework for developing DSM on Tribal Lands for improving the accuracy and detail of soil property maps (relative to off the shelf products such as SSURGO) that better represents soil-forming environments and the spatial variability of soil properties on Tribal Lands.

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

2017 ◽  
Vol 135 ◽  
pp. 242-251 ◽  
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

scholarly journals SOIL PROPERTIES AND NUTRIENT ELEMENT STATUS OF COCONUT LEAVES UNDER DEFFERENT CROPPING PATTERNS

CORD ◽  
1988 ◽  
Vol 4 (01) ◽  
pp. 34
Author(s):  
Doah Dekok Tarigans
Keyword(s):  
Organic Matter ◽  
Soil Properties ◽  
Cation Exchange ◽  
Cation Exchange Capacity ◽  
Block Design ◽  
Exchange Capacity ◽  
Cropping Pattern ◽  
Nutrient Element ◽  
Cropping Patterns ◽  
Significant Difference

This study was conducted to investigate the effects of six co­conut cropping patterns on the soil properties and nutrient element status of coconut leaves. The experiments were carried out from August 1984 to May 1985 in Silang, Cavite, Philippines. Data on‑soil properties and nutrient element starus of coconut leaves were statistically analyzed in Randomized Block Design with three replications. Six cropping patterns in coconut with four species of perennial crops as intercrops, namely: banana, papaya, coffee and pineapple were used in this study. The organic matter, pH and cation exchange capacity of the soils did not differ significantly with cropping pattern although intensively cropped farms tended to have higher organic matter' and cation exchange capacity values. Nitrogen, phosphorus and potassium in the top soil were significantly higher in most intensive intercropped farms, but calcium and magnesium did not vary significantly. Moisture content, waterholding capacity, bulk density and particle density of the soil did not show significant difference with cropping patterns. Likewise, the number of bacteria, fungi and actinomycetes in the soil remained statistically the same. Leaf nitrogen and calcium, in­creased while potassium decreased with intensity of cropping. Phosphorus and magnesium showed no definite trend.

Spatial variability of uncultivated soils in derived savanna

2013 ◽  
Vol 27 (1) ◽  
pp. 57-67 ◽  
Author(s):  
S.E. Obalum ◽  
J. Oppong ◽  
C.A. Igwe ◽  
Y. Watanabe ◽  
M.E. Obi
Keyword(s):  
Organic Matter ◽  
Spatial Variability ◽  
Soil Properties ◽  
Cation Exchange ◽  
Soil Ph ◽  
Cation Exchange Capacity ◽  
Exchange Capacity ◽  
Organic Matter Concentration ◽  
Derived Savanna ◽  
Matter Concentration

Abstract The spatial variability of some physicochemical properties of topsoils/subsoils under secondary forest, grassland fallow, and bare-soil fallow of three locations was evaluated. The data were analyzed and described using classical statistical parameters. Based on the coefficient of variation, bulk density, total porosity, 60-cm-tension moisture content, and soil pH were of low variability. Coarse and fine sand were of moderate variability. Highly variable soil properties included silt, clay, macroporosity, saturated hydraulic conductivity, organic matter concentration, and cation exchange capacity. Overall, soil pH and silt varied the least and the most, respectively. Relative weighting showed that location dominantly influenced the soil variability, except for soil porosity and organic matter concentration influenced mostly by land use. Most of the soil data were normally distributed; others were positively skewed and/or kurtotic. The minimum number of samples (at 25 samples ha-1) required to estimate mean values of soil properties was highly soil property-specific, ranging from 1 (topsoil pH-H2O) to 246 (topsoil silt). Cation exchange capacity of subsoils related fairly strongly with cation exchange capacity of topsoils (R2 = 0.63). Spatial variability data can be used to extrapolate dynamic soil properties across a derived-savanna landscape.

scholarly journals Development of a composite soil degradation assessment index for cocoa agroecosystems in southwestern Nigeria

Solid Earth ◽  
2017 ◽  
Vol 8 (4) ◽  
pp. 827-843 ◽  
Author(s):  
Sunday Adenrele Adeniyi ◽  
Willem Petrus de Clercq ◽  
Adriaan van Niekerk
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Properties ◽  
Cation Exchange ◽  
Cation Exchange Capacity ◽  
Soil Degradation ◽  
Clay Content ◽  
Exchange Capacity ◽  
Southwestern Nigeria ◽  
Assessment Index

Abstract. Cocoa agroecosystems are a major land-use type in the tropical rainforest belt of West Africa, reportedly associated with several ecological changes, including soil degradation. This study aims to develop a composite soil degradation assessment index (CSDI) for determining the degradation level of cocoa soils under smallholder agroecosystems of southwestern Nigeria. Plots where natural forests have been converted to cocoa agroecosystems of ages 1–10, 11–40, and 41–80 years, respectively representing young cocoa plantations (YCPs), mature cocoa plantations (MCPs), and senescent cocoa plantations (SCPs), were identified to represent the biological cycle of the cocoa tree. Soil samples were collected at a depth of 0 to 20 cm in each plot and analysed in terms of their physical, chemical, and biological properties. Factor analysis of soil data revealed four major interacting soil degradation processes: decline in soil nutrients, loss of soil organic matter, increase in soil acidity, and the breakdown of soil textural characteristics over time. These processes were represented by eight soil properties (extractable zinc, silt, soil organic matter (SOM), cation exchange capacity (CEC), available phosphorus, total porosity, pH, and clay content). These soil properties were subjected to forward stepwise discriminant analysis (STEPDA), and the result showed that four soil properties (extractable zinc, cation exchange capacity, SOM, and clay content) are the most useful in separating the studied soils into YCP, MCP, and SCP. In this way, we have sufficiently eliminated redundancy in the final selection of soil degradation indicators. Based on these four soil parameters, a CSDI was developed and used to classify selected cocoa soils into three different classes of degradation. The results revealed that 65 % of the selected cocoa farms are moderately degraded, while 18 % have a high degradation status. The numerical value of the CSDI as an objective index of soil degradation under cocoa agroecosystems was statistically validated. The results of this study reveal that soil management should promote activities that help to increase organic matter and reduce Zn deficiency over the cocoa growth cycle. Finally, the newly developed CSDI can provide an early warning of soil degradation processes and help farmers and extension officers to implement rehabilitation practices on degraded cocoa soils.

HIGH SOIL CALCIUM SATURATION LIMITS USE OF LEAF POTASSIUM DIAGNOSIS WHEN KCL IS APPLIED IN OIL PALM PLANTATIONS

2017 ◽  
Vol 54 (5) ◽  
pp. 794-804
Author(s):  
BERNARD DUBOS ◽  
VICTOR BARON ◽  
XAVIER BONNEAU ◽  
ALBERT FLORI ◽  
JEAN OLLIVIER
Keyword(s):  
Soil Properties ◽  
Cation Exchange ◽  
Oil Palm ◽  
Cation Exchange Capacity ◽  
Positive Response ◽  
Elaeis Guineensis ◽  
Exchange Capacity ◽  
Yield Response ◽  
Soil Calcium ◽  
Exchangeable Ca

SUMMARYPotassium chloride (KCl) is the most widely used fertilizer in oil palm (Elaeis guineensis) plantations and the rates applied are based on interpretation of leaf K contents. When no positive response on leaf K contents can be detected, no optimum content can be established whatever the yield response to KCl rates. We used data from 13 fertilization trials conducted on several continents to study the responses of leaf K, leaf Cl, leaf Ca and yield to KCl rates as a function of the soil properties of each site. We found that the abundance of exchangeable Ca in the soil expressed as a percent of the cation exchange capacity (CEC) was the best soil variable to predict if leaf K content would increase with KCl rates. In addition, we found that the leaf K contents of unfertilized controls at the end of the trials were also correlated with Ca/CEC. This ratio thus appears to be a better index of soil K reserves than soil exchangeable K content.

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

2021 ◽  
Author(s):  
Mahmood Shahabi ◽  
Mohammad Ali Ghorbani ◽  
Sujay Raghavendra Naganna ◽  
Sungwon Kim ◽  
Sinan Jasim Hadi ◽  
...  
Keyword(s):  
Cation Exchange ◽  
Arid Region ◽  
Cation Exchange Capacity ◽  
Management Practices ◽  
Evaluation Criteria ◽  
Quality Parameters ◽  
Exchange Capacity ◽  
Integration Scheme ◽  
Soil Parameters ◽  
Multiple Model

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.

scholarly journals Prediction of cation exchange capacity from soil index properties

Clay Minerals ◽  
2006 ◽  
Vol 41 (4) ◽  
pp. 827-837 ◽  
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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