Spatial Variability of Soil Fertility Properties for Precision Agriculture in Southern Iran

Yasrebi, Jafar; Saffari, Mahboub; Fathi, Hamed; Karimian, N.; Emadi, Mostafa; Baghernejad, Majid

doi:10.3923/jas.2008.1642.1650

Cited by 36 publications

(11 citation statements)

References 24 publications

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“…For most natural environments such as soils, it is known that quantitatively soil properties within a site on the landscape are relatively similar. It is noted that spatial characterization of soil properties is necessary in order to locate homogenous areas to be carefully managed for agricultural sustainable development [13][14][15]. In this regard, the major problems are how to identify some of the factors which influence variations in soil properties and use this knowledge to design agricultural management practices that would be both environment friendly and highly productive.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Variability in the Quality of an Acrisol under Different Land Use Systems in Ghana

Ghartey¹,

Dowuona²,

Nartey³

et al. 2012

OJSS

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Three land use types (natural fallow, Leucaena leucocephala woodlot and cultivated plots) on a Ferric Acrisol in a semi-arid tropical zone of Ghana were compared to assess their effects on variability in selected soil properties and plant biomass accumulation. Organic carbon accumulation in the representative natural fallow profile was 22.7 g/kg, followed by 16.5 g/kg for the Leucaena woodlot and lastly 11.8 g/kg for the cultivated site. The mean bulk density of the natural fallow, Leucaena woodlot and cultivated sites were from 1.36 Mg/m3, 0.92 Mg/m3 and 1.33 Mg/m3 with corresponding range in mean weight diameter of 0.5 mm - 1.2 mm, 0.6 mm - 1.2 mm and 1.0 mm - 1.2 mm, respectively. The lower bulk density observed for the woodlot corresponds to increased total porosity, aeration, and root proliferation due to the stronger and extensive rooting system. Significant differences (P < 0.05) in bulk density, mean weight diameter (MWD), clay content, organic carbon and total nitrogen existed among the land use types. Variability in pH and bulk density of the surface soils was less than 15%, in the three land use types. Generally, clay content and exchangeable Na recorded the highest variability (>36%). For the surface soils, exchangeable Na was very variable in the natural fallow. Exchangeable Na, Ca and K and total nitrogen were very variable in the Leucaena woodlot and the cultivated sites. Variability in clay content was very high in the cultivated soils only. The order cultivated land > Leucaena woodlot > natural fallow was noted for properties with high variability (CV > 36%). Plant biomass accumulation was 1834 kg/ha (natural fallow) and 830 kg/ha (Leucaena woodlot) indicating that natural fallows do not only maintain soil quality but they also decrease variability in soil properties which is desirable for soil productivity and quality

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Section: Introductionmentioning

confidence: 99%

Assessment of Variability in the Quality of an Acrisol under Different Land Use Systems in Ghana

Ghartey¹,

Dowuona²,

Nartey³

et al. 2012

OJSS

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“…Awe et al (2018aAwe et al ( , b, 2020a) also reported soil chemical properties showed moderate to strong spatial dependence. Strong and moderate spatial structure could be due to the influence of intrinsic soil properties such as soil texture, geology, climate, organism or time and weak spatial structure by extrinsic factors and processes, such as land 2 Semivariograms with fitted models for soil properties, i.e., (a1) pH, (b1) electrical conductivity, and (c1) exchangeable calcium management practices (Cambardella et al 1994;Warrick 1998;Yasrebi et al 2008;Parfitt et al 2009). Furthermore, weak spatial dependence on available soil P was observed (Ozgoz et al 2013;Costa et al 2015).…”

Section: Semivariograms and Evaluation Of The Geostatistical Interpolation Methodsmentioning

confidence: 99%

Spatial variability modeling of soil fertility for improved nutrient management in Northwest Ethiopia

et al. 2021

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In the study, two geostatistical methods-Ordinary Kriging (OK) and Least Distance Weighting (IDW)-were utilized to predict the spatial variability and distribution of soil properties for improved nutrient management in the Fogera plain, Northwest Ethiopia. In an area of 5646 ha, 60 composite soil samples were collected at a 0-20-cm soil depth and analyzed for soil pH, organic carbon (OC), total nitrogen (TN), available phosphorus (av.P), exchangeable calcium (Ca 2+ ), potassium (K + ), sodium (Na + ), and magnesium (Mg 2+ ), electrical conductivity (EC), and cation exchange capacity (CEC) using standard analytical procedures. The data were then incorporated into a GIS database and semi-variogram, and geostatistical analyses were performed with ArcGIS software version 10.5. Descriptive statistical treatments were applied using IBM Statistical Packages for Social Sciences (SPSS) software version 24. The performance of interpolation methods was assessed using the mean error (ME), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and coefficient of determination (R 2 ) extracted from cross-validation of predicted maps. Analysis of different semi-variogram models depicts different degrees of spatial dependence. An exponential model is detected for the soil pH, CEC, OC, and TN; a spherical one for EC and Ca 2+ ; a moderate one for soil K + ; and a weak spatial dependence for soil av. P. This result demonstrates a high spatial continuity and dependence between adjacent soil samples. The inverse distance weighting (IDW) and ordinary kriging (OK) models well described the variation of all soil fertility parameters except organic carbon (OC) and available phosphorus (av. P), which had low NSE (≤ 50%) for both IDW and OK methods. Consequently, the generated maps revealed that the spatial variability of soil properties was adequate to predict the values of soil fertility indicators in the non-sampled locations within the study area and similar regions. The geostatistical-based soil fertility maps will be helpful for farmers, researchers, and policymakers to improve soil management methods, optimize fertilization strategies, and enhance crop productivity. By means of the methodological approach applied, we have succeeded in demonstrating the strong spatial dependence of the studied soils; however, a particular attention to the implementation of site-specific soil management practices in the Fogera plain is essential.

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“…These results indicate that the distribution of the soil properties in space is not random. Strong spatial dependence on soil properties is an indication that such properties are controlled by variability in intrinsic soil properties such as geology, soil forming factors, texture and so on [31], whereas moderate and weak spatial dependence could be due to management such as land use, tillage, cropping system, irrigation, among others. By using the kriging algorithm of the geospatial analyst tool in ArcGIS, the contour maps of the individual soil property are shown in Figs.…”

Section: Spatial Variability and Mapping Of Soil Physical Propertiesmentioning

confidence: 99%

Geostatistical Evaluation of Spatial Variability of Selected Soil Physical Properties under Different Crops in Ado Ekiti, Nigeria

Awe

Nurudeen

Amiola

et al. 2018

AJSSPN

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The characterization of spatial variability of soil physical and chemical characteristics is very important for precision farming and managing agricultural production. Therefore, the objective of this study was to evaluate the spatial variability of selected physical properties of a soil under different crops in Ado Ekiti, Nigeria using descriptive statistics and geostatistical techniques. Grids of 10 m x 10 m were set up on the field within three land uses. The field was about 3 hectares, out of which 1ha was apportioned for cowpea, 1ha was for sole maize and the rest for maize/cassava intercrop. A total of one hundred and eighty-four (184) georeferenced surface samples were collected for analysis of texture, bulk density (BD), particle density (Pd), porosity (Pt) and saturated hydraulic conductivity (Ks). The study used descriptive statistics to investigate the striking features in each soil property and further adopted semi-variogram and kriged maps to assess the spatial dependence and classification of the soil properties respectively. The soil properties showed varying degrees of spatial variability, with Ks highly variable (118%) than others. There was weak correlation between Ks versus BD (12%) and Pt (-14%) but the correlation was significant with Original Research Article

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Spatial Variability of Soil Fertility Properties for Precision Agriculture in Southern Iran

Cited by 36 publications

References 24 publications

Assessment of Variability in the Quality of an Acrisol under Different Land Use Systems in Ghana

Assessment of Variability in the Quality of an Acrisol under Different Land Use Systems in Ghana

Spatial variability modeling of soil fertility for improved nutrient management in Northwest Ethiopia

Geostatistical Evaluation of Spatial Variability of Selected Soil Physical Properties under Different Crops in Ado Ekiti, Nigeria

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