Comparative Analysis of the Spectral Response to Soil Salinity of Saline-Sodic Soils under Different Surface Conditions

Desiccation cracking is a very common surface soil phenomenon of saline-sodic land. The objective of this study was to investigate the effects of salt content on the spectral reflectance of soil with and without desiccation cracks. To achieve our objective, a cracking test was performed using 17 soil samples. Following the tests, crack parameters were extracted, and correlation analysis was then performed between crack parameters and four soil properties: Na+, salinity (total concentration of ions), pH, and electric conductivity (EC). In order to select the optimum spectral measurement method and develop prediction models, spectral response to different soil properties were compared between the cracked soil samples and the comparative soil samples composed of the 2 mm particle size fraction processed by traditional methods. The results indicate that soil salinity dominated cracking propagation with a positive correlation. Since area and volume scattering are closer to what occurs in the field, a greater spectral response to soil properties was found for cracked soil samples relative to the comparative soil samples in the near-infrared and shortwave-infrared regions. The R2 of optimal linear prediction models based on the cracked soil samples were 0.74, 0.67, 0.58, and 0.67 for Na+, salinity, pH, and EC, respectively.

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Quantitative Analysis of Spectral Response to Soda Saline-AlkaliSoil after Cracking Process: A Laboratory Procedure to Improve Soil Property Estimation

Remote Sensing ◽

10.3390/rs11121406 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1406

Author(s):

Jianhua Ren ◽

Xiaojie Li ◽

Sijia Li ◽

Honglei Zhu ◽

Kai Zhao

Keyword(s):

Soil Properties ◽

Soil Property ◽

Spectral Response ◽

Texture Feature ◽

Soil Surface ◽

Soil Samples ◽

Spectral Measurements ◽

Spectral Difference ◽

Property Estimation ◽

Alkali Soil

Cracking on the surface of soda saline-alkali soil is very common. In most previous studies, spectral prediction models of soil salinity were less accurate since spectral measurements were usually performed on 2 mm soil samples which cannot represent true soil surface condition very well. The objective of our research is to provide a procedure to improve soil property estimation of soda saline-alkali soil based on spectral measurement considering the texture feature of the soil surface with cracks. To achieve this objective, a cracking test was performed with 57 soil samples from Songnen Plain of China, the contrast (CON) texture feature of crack images of soil samples was then extracted from grey level co-occurrence matrix (GLCM). The original reflectance was then measured and the mixed reflectance considering the CON texture feature was also calculated from both the block soil samples (soil blocks separated by crack regions) and the comparison soil samples (soil powders with 2 mm particle size). The results of analysis between spectra and the main soil properties indicate that surface cracks can reduce the overall reflectivity of the soda saline-alkali soil and thus increasing the spectral difference among the block soil samples with different salinity levels. The results also show that both univariate and multivariate linear regression models considering the CON texture feature can greatly improve the prediction accuracy of main soil properties of soda saline-alkali soils, such as Na+, EC and salinity, which also can reduce the intensity of field spectral measurements under natural condition.

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Bio-Compost Influences Salinity and Plant Development by Experimenting with Greenhouse Pots

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3512.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 4847-4850

Keyword(s):

Soil Salinity ◽

Saline Soil ◽

Salt Content ◽

Soil Samples ◽

Plant Cultivation ◽

Crop Development ◽

Salinity Reduction ◽

Standard Value ◽

Synthetic Fertilizers

This paper deals with this research “Role of compost in reduction of saline soil of Agra” [1] and “Soil salinity reduction by bio-compost” [2]. The salinity of the soil is the occurrence which raises the salt content from standard value. The method of increasing the salt content is called Salinization. In soils and water, salts usually occur. It can be these bilish Salinization. Characteristic methods, e.g., durability of minerals or progressive sea removal. It may also come into being with an artificial drainage and excessive use in agriculture of synthetic fertilizers. Salt content is a significant crisis in both plant and crop development. The aim of this research is to study salinity problems on plant cultivation and how soil management methods can prevent salinization problems. Bio-compost has been used to decrease the salinity of the land. With the use of bio-compost, Agra's estibilised soil hydrology model was decreased. Soilcompost combination of saline soil SA-1 and soil samples SA-2 electrical conductivity (EC).To assess the influence of biocompost on salinity on plant cultivation, greenhouse pot experiments were carry out on least salinity presence on both the soil by varying pH as 5.5, 6, 7 and 8. The plant chosen for this investigation was wheat ( Triticum Aestivum). The plant growth of wheat were obsevered significant at pH-6 and 7 in both SA-1 and SA-2 soil samples. The results of the study recommend biocompost have great potential to reduce soil salinity and could be highly potent alternative to chemical fertilizer and increase the growth of plant.

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Quantifying the uncertainty in the prediction of soil properties from soil-spectra using local and regional spectral libraries

10.5194/egusphere-egu2020-18713 ◽

2020 ◽

Author(s):

Timo Breure ◽

Alice Milne ◽

Richard Webster ◽

Stephan M. Haefele ◽

Jacqueline A. Hannam ◽

...

Keyword(s):

Soil Properties ◽

Reference Values ◽

Fixed Effects ◽

Linear Mixed Model ◽

Size Fraction ◽

Soil Samples ◽

Spectral Measurements ◽

Total N ◽

Wet Chemistry ◽

Spectral Libraries

Spectral measurements are increasingly used to predict soil properties. Libraries of soil spectra are built and statistical models are used to relate the spectra to wet chemistry measurements. These relationships can then be used to predict the properties of new samples. An important&#160; consideration is the uncertainty associated with the prediction. Often to reduce this error calibration is done at field level. This is time and resource intensive, however, and there is scope to use existing spectral libraries. Our aim was to quantify the uncertainty in the prediction of soil properties from spectral measurements using a local library and compare this to predictions made using a regional library. &#160;&#160;To investigate this, we considered two case study fields in the Cambridgeshire fens (UK) that were planted with lettuce. These fields contain complex soils which are a combination of peat with underlying alluvial and marine silts that became elevated features in the landscape due to peat oxidation and shrinkage. These elevated features are captured by a 2 m x 2 m LiDAR raster used in our study (UK Environment Agency). We took a total 467 soil samples across the fields and made spectral measurements (near- and mid-infrared). A subset of the soil samples underwent wet chemistry analysis for available pH, P, K, total N and soil particle size fraction. For the regional library we use soil the National Soil Inventory spectral database and its respective wet chemistry reference values.We used partial least squares to regress the soil spectra for the local and regional spectral libraries against the wet chemistry reference values. These two models were then used to predict the soil properties for both fields. We then mapped the variation in each soil property and the associated uncertainty by kriging. &#160;The variation in some of the soil variables was clearly affected by elevation and there were signs of spatial trend and so we used universal kriging to map the soil properties. To reduce bias, we used residual maximum likelihood estimation (REML) to estimate the variogram by fitting a linear mixed model with the trend accounted for as fixed effects. &#160;We compared these different maps to assess how the calibration regression from local and regional spectral libraries translates itself in uncertainty of kriged maps for five different soil properties within each field.&#160;

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Evaluation of soil salinity and sodicity using electromagnetic conductivity imaging

10.5194/egusphere-egu21-2872 ◽

2021 ◽

Author(s):

Mohammad Farzamian ◽

Francisco José Martinez Moreno ◽

Tiago B. Ramos ◽

Nadia Castanheira ◽

Ana Marta Paz ◽

...

Keyword(s):

Soil Properties ◽

Soil Salinity ◽

Electromagnetic Induction ◽

Lower Cost ◽

Sustainable Use ◽

Soil Sampling ◽

Soil Electrical Conductivity ◽

Sodic Soils ◽

Non Invasive ◽

Soil Exchange Complex

In order to prevent further soil degradation, it is important to understand the processes controlling salinization. Salt related problems in soils can refer to an excess of soluble salts (saline soils), a dominance of exchangeable sodium in the soil exchange complex (sodic soils), or a mixture of both situations (saline-sodic soils). These categories are important because the impacts and management vary accordingly. Traditional soil sampling methods &#8211;which require boreholes for soil sampling and analysis&#8211; difficultly lead to a comprehensive answer to this problem. This is because they cover only small and localized sites and may not be representative of the soil properties at the management scales. Furthermore, they are highly time and work consuming, resulting in costly surveys. Geophysical techniques such as electromagnetic induction (EMI) provide enormous advantages compared to soil sampling because they allow for in-depth and non-invasive analysis, covering large areas in less time and at a lower cost.EMI surveys were performed in several regions in Portugal with historic soil salinity and sodicity problems to evaluate the salinization risk. We inverted field apparent conductivity data (&#963;a) in order to obtain electromagnetic conductivity images (EMCI) of the real soil electrical conductivity (&#963;) in depth. We evaluated the potential of EMCI in the estimation of soil salinity, sodicity, and other soil properties over large areas across regions with a very different range of salinity and sodicity.&#160;AcknowledgmentsThis work was developed in the scope of SOIL4EVER &#8220;Sustainable use of soil and water for improving crops productivity in irrigated areas&#8221; project supported by FCT, grant no. PTDC/ASP-SOL/28796/2017.&#160;

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Development of a Tellurium Speciation Study Using IC-ICP-MS on Soil Samples Taken from an Area Associated with the Storage, Processing, and Recovery of Electrowaste

Molecules ◽

10.3390/molecules26092651 ◽

2021 ◽

Vol 26 (9) ◽

pp. 2651

Author(s):

Magdalena Jabłońska-Czapla ◽

Katarzyna Grygoyć

Keyword(s):

Inductively Coupled Plasma ◽

Total Concentration ◽

Soil Samples ◽

Chemical Extraction ◽

Soil Extraction ◽

Inductively Coupled ◽

Sequential Chemical Extraction ◽

Icp Ms ◽

Speciation Study ◽

Plasma Mass Spectrometry

The optimization and validation of a methodology for determining and extracting inorganic ionic Te(VI) and Te(IV) forms in easily-leached fractions of soil by Ion Chromatography-Inductively Coupled Plasma-Mass Spectrometry (IC-ICP-MS) were studied. In this paper, the total concentration of Te, pH, and red-ox potential were determined. Ions were successfully separated in 4 min on a Hamilton PRPX100 column with 0.002 mg/kg and 0.004 mg/kg limits of detection for Te(VI) and Te(IV), respectively. Soil samples were collected from areas subjected to the influence of an electrowaste processing and sorting plant. Sequential chemical extraction of soils showed that tellurium was bound mainly with sulphides, organic matter, and silicates. Optimization of soil extraction allowed 20% average extraction efficiency to be obtained, using 100 mM citric acid as the extractant. In the tested soil samples, both tellurium species were present. In most cases, the soils contained a reduced Te form, or the concentrations of both species were similar.

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Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy

Sensors ◽

10.3390/s21062195 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2195

Author(s):

Lucas de Paula Corrêdo ◽

Leonardo Felipe Maldaner ◽

Helizani Couto Bazame ◽

José Paulo Molin

Keyword(s):

Sample Preparation ◽

Prediction Models ◽

Spectral Response ◽

Nir Spectroscopy ◽

Quality Parameters ◽

Partial Least Square ◽

Least Square ◽

Sample Type ◽

Sampling Strategies ◽

Significant Difference

Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface (‘skin’) (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.

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Comparison of Different Interpolation Methods for Prediction of Soil Salinity in Arid Irrigation Region in Northern China

Agronomy ◽

10.3390/agronomy11081535 ◽

2021 ◽

Vol 11 (8) ◽

pp. 1535

Author(s):

Tonggang Fu ◽

Hui Gao ◽

Jintong Liu

Keyword(s):

Soil Salinity ◽

Subsurface Layer ◽

Salt Content ◽

Spatial Prediction ◽

Northern China ◽

Sodium Adsorption Ratio ◽

Interpolation Methods ◽

Distance Weighting ◽

Total Salt Content ◽

Inverse Distance

Numerous methods have been used in the spatial prediction of soil salinity. However, the most suitable method is still unknown in arid irrigation regions. In this paper, 78 locations were sampled in salt-affected land caused by irrigation in an arid area in northern China. The geostatistical characteristics of the soil pH, Sodium Adsorption Ratio (SAR), Total Salt Content (TSC), and Soil Organic Matter (SOM) of the surface (0–20 cm) and subsurface (20–40 cm) layers were analyzed. The abilities of the Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and CoKriging (CK) interpolation methods were compared, and the Root Mean Square Error (RMSE) was used to justify the results of the methods. The results showed that the spatial distributions of the soil properties obtained using the different interpolation methods were similar. However, the surface layer exhibits more spatial heterogeneity than the subsurface layer. Based on the RSME, the nugget/sill value and range significantly affected which method was the most suitable. Lower nugget/sill values and lower ranges can be fitted using the IDW method, but higher nugget/sill values and higher ranges can be fitted using the OK method. These results provide a valuable reference for the prediction of soil salinity.

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SOIL SALINITY AND SAND CONTENT VARIABILITY DETERMINED BY TWO STATISTICAL METHODS IN AN IRRIGATED SALINE SOIL

Canadian Journal of Soil Science ◽

10.4141/cjss88-021 ◽

1988 ◽

Vol 68 (2) ◽

pp. 209-221 ◽

Cited By ~ 3

Author(s):

C. Chang ◽

T. G. SOMMERFELDT ◽

T. ENTZ

Keyword(s):

Soil Properties ◽

Statistical Methods ◽

Management Practices ◽

Saline Soil ◽

Salt Content ◽

Sampling Strategy ◽

Spatial Relationships ◽

Sand Content ◽

Grid Pattern ◽

Classical Statistics

Knowledge of the variability of soluble salt content in saline soils can assist in designing experiments or developing management practices to manage and reclaim salt-affected soils. Geostatistical theory enables the use of spatial dependence of soil properties to obtain information about locations in the field that are not actually measured, but classical statistical methods do not consider spatial correlation and the relative location of samples. A study was carried out using both classical statistics and geostatistical methods to delineate salinity and sand content and their variability in a small area of irrigated saline soil. Soil samples were taken for electrical conductivity (EC) and particle size distribution determinations at 64 locations from a 20 × 25-m area, on an 8 × 8-grid pattern at depth intervals of 0–15, 15–30, 30–60, 60–90 and 90–120 cm. The high coefficient of variation (CV) values of both EC and sand content indicated that the soil was highly variable with respect to these soil properties. The semivariograms of sand content of the first two depth intervals and EC of all the depth intervals showed strong spatial relationships. Contour maps, generated by block kriging, based on spatial relationships provide estimated variances which are smaller than general variances calculated by the classical statistical method. The interpolated EC results by both ordinary and universal kriging methods were compared and were almost identical. The kriged maps can provide information useful for designing experiments and for determining soil sampling strategy. Key words: Salinity, texture, variability, geostatistics, semivariogram, kriging

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Dendrogeochemistry and soil geochemistry applied to exploration for alkalic Cu-Au porphyry mineralization under cover at the Racecourse prospect, NSW, Australia

The Canadian Mineralogist ◽

10.3749/canmin.2000065 ◽

2021 ◽

Vol 59 (5) ◽

pp. 1167-1186

Author(s):

Cole McGill ◽

Daniel Layton-Matthews ◽

T. Kurt Kyser ◽

Matthew I. Leybourne ◽

Paul Polito ◽

...

Keyword(s):

Pinus Radiata ◽

Size Fraction ◽

Ring Width ◽

Isotopic Signature ◽

Soil Samples ◽

Soil Geochemistry ◽

Tree Roots ◽

Monterey Pine ◽

Geophysical Surveys ◽

Transverse Zone

ABSTRACT The Racecourse Cu-Au porphyry prospect is found within the Macquarie Arc of the Lachlan Fold Belt, in the Lachlan Transverse Zone, a cross-arc structure hosting significant world-class mineralization, including the Cadia and Northparks districts. Several geochemical and geophysical surveys of the prospect have been complimented by a total of 19,819 m of drilling, with only four holes reaching a depth greater than 300 m. Positive lithogeochemistry (fertility indices, comparisons with the Cadia and Northparks systems) subtle alteration, and mineralized intercepts indicate heightened mineral potential, yet the prospect has lacked a comprehensive geochemical survey outlining the extent of the mineralized target at surface. Soil samples and Monterey pine (Pinus radiata) tree cores were collected above and distal to mineralization intercepted by prior drilling in order to outline the ore deposit footprint and test the viability of dendrogeochemistry as an exploration tool for porphyry Cu mineralization. Ultimately, this study documented the spatial extent of the Racecourse target and identified potential areas for additional Cu mineralization. Soil samples were separated with the <250 μm size fraction analyzed and show distinct anomalous populations of Au, Cu, Mo, Pb, and Zn above prior drilling. Tree cores were collected by increment borer and tree rings of the Pinus radiata were counted and measured, with an age interval of 2003–2008 exhibiting the least ring-width variability chosen to chemically analyze. Selected intervals were digested and analyzed and have elevated Cu, Mo, and Zn in an area that overlaps a previously drilled soil anomaly, whereas an anomaly in the southwest of the survey area documents a Cu, Pb anomaly corresponding to localized faulting and tertiary basalt subcrop. Tree roots are directly tapping chemical variability at depth, aided via metal mobilization through faulted fluid conduits. Lead isotope ratios from the Pinus radiata identify distinct groups of lead spatially associated with discrete metal anomalies of varied lithological ages. At the Racecourse target, anomalous Pinus radiata samples yield a similar isotopic signature to the faulted southwestern anomaly, potentially linking the source of these two metal anomalies. When these results are integrated with the current understanding of the mineralized body, geochemical media suggest that mineralization may continue down-plunge at depth.

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Assessment and monitoring of land degradation using geospatial technology in Bathinda district, Punjab, India

Solid Earth ◽

10.5194/se-9-75-2018 ◽

2018 ◽

Vol 9 (1) ◽

pp. 75-90 ◽

Cited By ~ 8

Author(s):

Naseer Ahmad ◽

Puneeta Pandey

Keyword(s):

Land Degradation ◽

Near Infrared ◽

Soil Samples ◽

Geographical Information ◽

Total Alkalinity ◽

Soil Parameters ◽

Landsat 8 ◽

Sodic Soils ◽

Barren Land ◽

Geospatial Technology

Abstract. Land degradation leads to alteration of ecological and economic functions due to a decrease in productivity and quality of the land. The aim of the present study was to assess land degradation with the help of geospatial technology – remote sensing (RS) and geographical information system (GIS) – in Bathinda district, Punjab. The severity of land degradation was estimated quantitatively by analyzing the physico-chemical parameters in the laboratory to determine saline or salt-free soils and calcareous or sodic soils and further correlating them with satellite-based studies. The pH varied between 7.37 and 8.59, electrical conductivity (EC) between 1.97 and 8.78 dS m−1 and the methyl orange or total alkalinity between 0.070 and 0.223 (HCO3−) g L−1 as CaCO3. The spatial variability in these soil parameters was depicted through soil maps generated in a GIS environment. The results revealed that the soil in the study area was exposed to salt intrusion, which could be mainly attributed to irrigation practices in the state of Punjab. Most of the soil samples of the study area were slightly or moderately saline with a few salt-free sites. Furthermore, the majority of the soil samples were calcareous and a few samples were alkaline or sodic in nature. A comparative analysis of temporal satellite datasets of Landsat 7 ETM+ and Landsat 8 OLI_TIRS of 2000 and 2014, respectively, revealed that the water body showed a slight decreasing trend from 2.46 km2 in 2000 to 1.87 km2 in 2014, while the human settlements and other built-up areas expanded from 586.25 to 891.09 km2 in a span of 14 years. The results also showed a decrease in area under barren land from 68.9847 km2 in 2000 to 15.26 km2 in 2014. A significant correlation was observed between the digital number (DN) of the near-infrared band and pH and EC. Therefore, it is suggested that the present study can be applied to projects with special relevance to soil scientists, environmental scientists and planning agencies that can use the present study as baseline data to combat land degradation and conserve land resources in an efficient manner.

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