Assessment and field-scale mapping of soil quality properties of a saline-sodic soil

Corwin, Dennis L.; Kaffka, Stephen; Hopmans, Jan W.; Mori, Yasushi; Groenigen, J.W. van; Kessel, Chris van; Lesch, Scott M.; Oster, J. D.

doi:10.1016/s0016-7061(03)00043-0

Cited by 122 publications

(73 citation statements)

References 22 publications

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“…Prediction of the edaphic properties variability in soils used for livestock production tively associated with ECa. These high correlations are expected because they reflect the influence of salts and pH on the measured ECa and because these properties are highly correlated (Corwin et al, 2003;. Salts concentration and pH increased soil solution conductivity and is consistent with findings in previous studies (Rhoades et al, 1989;Kaffka et al, 2005).…”

Section: Regression Analysissupporting

confidence: 91%

“…In agricultural soils, ECa has been used to characterize soil salinity (Rhoades et al, 1989); soil texture (Sudduth et al, 2003); soil depth ; soil moisture (Hossain et al, 2010); soil organic matter (OM) (Corwin & Lesch, 2005a) and cation exchange capacity (Kitchen et al, 2000). However, various authors have shown inconsistent relationships between ECa and soil characteristics, probably due to the fact that ECa is influenced by complex site dependent soil properties interactions (Corwin et al, 2003;Sudduth et al, 2005). Some studies have shown that ECa values are related to soil properties variability in extensive livestock production systems and are also related to pasture productivity (Serrano et al, 2010(Serrano et al, , 2014a.…”

Section: Data Collection Using the Veris 3100mentioning

confidence: 99%

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Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Peralta

Cicore

Marino

et al. 2015

Span. j. agric. res.

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The spatial variability in soils used for livestock production (i.e. Natraquoll and Natraqualf) at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa), a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM) content, pH, the saturation extract electrical conductivity (EC ext ), available phosphorous (P), and anaerobically incubated Nitrogen (Nan). Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA), and stepwise regression. Principal components (PC) and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and EC ext exhibited a high correlation with ECa (R 2 =0.76; 0.70 and 0.65, respectively). Whereas P and Nan showed a lower correlation (R 2 =0.54 and 0.11 respectively). The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, EC ext , pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors>0.4). Results showed that ECa is associated with the spatial distribution of some important soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use.Additional key words: multivariate techniques; soil properties; geographic information system; lowland soils; spatial variability. Abbreviations used: ECa (apparent soil electrical conductivity); EC ext (electrical conductivity of the saturation extract); GWR (geographically weighted regression); Nan (anaerobically incubated nitrogen); OM (soil organic matter content); P (available phosphorous); PCA (principal component analysis); PC (principal component).Citation: Peralta, N. R.; Cicore, P. L.; Marino, M. A.; Marques da Silva, J. R.; Costa, J. L. (2015). Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production.

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Section: Regression Analysissupporting

confidence: 91%

Section: Data Collection Using the Veris 3100mentioning

confidence: 99%

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Peralta

Cicore

Marino

et al. 2015

Span. j. agric. res.

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“…The most commonly used method is electromagnetic (EM) induction. EM instruments measure the apparent soil electrical conductivity (EC a ), which is a function of various soil properties including salinity, clay content, moisture content, and mineralogy (Triantafilis et al, 2002;Corwin et al, 2003). In the Netherlands, EM survey data have been used to identify the depth to (i) boulder clay and (ii) a soft layer in the western marine districts (Knotters et al, 1995).…”

Section: Introductionmentioning

confidence: 99%

Mapping clay content variation using electromagnetic induction techniques

Triantafilis

Lesch

2005

Computers and Electronics in Agriculture

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“…Increase of sodium on the exchange complex in the cultivation system can be explained by the quality of the irrigation water. The irrigation water samples for the cultivated soil had a remarkable bicarbonate content ( Corwing et al (2003) and Pal et al (2003). Long-term cropping induced a decrease, although not significant, in CEC compared to those of the grassland and forestland in both Cambisols and Vertisols, probably as a result of destruction in SOC and variation in clay minerals (illite and smectite).…”

Section: Soil Chemical and Fertilitical Characteristicsmentioning

confidence: 95%

Response of some soil attributes to different land use types in calcareous soils with Mediterranean type climate in north-west of Iran

Rezapour

2013

Environ Earth Sci

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Monitoring general variability of soil attributes is a fundamental requirement from the point of view of understanding and predicting how ecosystems yield. In order to monitor impact of different land use types on the combination of morphological, clay mineralogical and physicochemical characterizes, 42 soil samples (0-30 cm) were described and analyzed. Soil samples belonging to Cambisols and Vertisols reference soil groups collected from three neighboring land use types included cropland (under long-term continuous cultivation), grassland, and forestland. The soils were characterized by high pH (mean of 7.1-7.5) and calcium carbonate equivalent (CCE) (mean of 35-97 g kg -1 ) in the three land use types. The weakening in soil structure, hardening of consistency, and lighting of soil color occurred for the cropland under comparable condition with grassland and forest. Changes in land use types produced a remarkable change in the XRD patterns of clay minerals containing illite and smectite due the dynamic and removal of potassium. Continuous cultivation resulted in an increase in sand content up to 35 % while silt and clay content decreased up to 22 and 18 %, respectively, as compared to the adjoining grassland and forest mainly as a result of the difference of dynamic alterational and erosional process in the different land use. Long-term cultivation caused a negative and degradative aspects on soil heath as is manifested by the increasing in soil pH (a rise of 0.3-0.46 unit), electrical conductivity (EC) (a rise of 1.78-5.5 times), sodium absorption ration (SAR) (a rise of 10-51 %), exchangeable sodium percentage (ESP) (a rise of 3-46 %), and the decrease in soil organic C (a drop of 12-41 %), along with soil fertility attributes. Overall, the general distribution of soil organic C, total N, available P and K, cation exchange capacity (CEC), and exchangeable cations (Ca, Mg, and K) followed the order: forestland [ grassland [ cropland. The general distribution of EC, SAR, ESP, and exchangeable Na, however, followed the order: cropland [ grassland [ forestland. Soil quality index (SQI), calculated based on some physicochemical properties, specified that cultivation led to a negative effect in SQI for both Cambisols (a drop of 10-17 %) and Vertisols (a drop of 17 %) as compared to those of under grassland and forestland.

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Assessment and field-scale mapping of soil quality properties of a saline-sodic soil

Cited by 122 publications

References 22 publications

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production

Mapping clay content variation using electromagnetic induction techniques

Response of some soil attributes to different land use types in calcareous soils with Mediterranean type climate in north-west of Iran

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