Spatial variability of some soil properties varies in oil palm (&amp;lt;i&amp;gt;Elaeis guineensis&amp;lt;/i&amp;gt; Jacq.) plantations of west coastal area of India

Behera, Sanjib Kumar; Suresh, K.; Rao, B. N.; Mathur, R. K.; Shukla, Arvind Kumar; Manorama, K.; Ramachandrudu, K.; Harinarayana, Parasa; Prakāsh, Chandra

doi:10.5194/se-7-979-2016

Cited by 42 publications

(21 citation statements)

References 59 publications

(58 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The soil EC was negatively and significantly correlated with the concentration of available Fe, Cu, Mn and Mo and positively and significantly correlated with the concentration of available Zn and B. Behera et al . () reported a positive and significant correlation between soil EC and available S in soils of west coastal area of India. Soil EC does not directly affect plant growth but has been used as an indirect indicator of the amount of nutrients available for plant uptake and salinity levels (Corwin & Lesch, ).…”

Section: Resultsmentioning

confidence: 97%

Spatial Distribution and Management Zones for Sulphur and Micronutrients in Shiwalik Himalayan Region of India

et al. 2017

Self Cite

View full text Add to dashboard Cite

Agricultural land degradation due to nutrient deficiencies is a threat to agricultural sustainability. As nutrients availability is influenced by soil heterogeneity, climatic conditions and anthropogenic activities; hence, delineation of nutrient management zones (MZs) based on spatial variability could be an effective management option at regional scale. Thus, the present study was carried out to delineate MZs in the Shiwalik Himalayan region of India by capturing spatial variability of soil properties and secondary and micronutrients status because of the emerging nutrient deficiencies. For the study, a total of 2575 geo‐referenced representative surface (0–15 cm depth) soil samples were collected from the study region covering an area of 53,483 km2. The soils were analysed for pH, electrical conductivity, soil organic carbon, available sulphur (S) and micronutrients (Zn, Fe, Cu, Mn, B and Mo) concentrations. There was a wide variation in soil properties with coefficient of variation values of 14 (for pH) to 86% for available Mo. Geostatistical analysis revealed spherical, Gaussian, exponential, stable, circular and K‐Bessel best‐fit models for soil properties. Most of the soil properties were having moderate spatial dependence except soil pH and S (strong spatial dependence) and Zn (weak spatial dependence). About 49%, 10%, 2%, 13%, 11%, 12% and 8% area of the study region were found to be deficient (including acute and marginal deficiency) in S, Zn, Fe, Cu, Mn, B and Mo, respectively. The principal component analysis and fuzzy c‐mean clustering were performed to develop the MZs. Four principal components with eigenvalues greater than 1 and accounting 65·4% of total variance were retained for further analysis. On the basis of fuzzy performance index and normalized classification entropy, four potential MZs were identified. Analysis of variance confirmed the heterogeneity in most of the studied soil properties among the MZs. The study indicated that the methodology of delineating MZs can be effectively used in site‐specific S and micronutrients management in the Shiwalik Himalayan region of India. Copyright © 2016 John Wiley & Sons, Ltd.

show abstract

Section: Resultsmentioning

confidence: 97%

Spatial Distribution and Management Zones for Sulphur and Micronutrients in Shiwalik Himalayan Region of India

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Since soils are highly heterogeneous and distribution of soil properties (Behera & Shukla, ; Bogunovic, Pereira, & Brevik, ) and Zn, Fe, Cu, and Mn concentrations in soils varies spatially (Fageria et al, ; Pereira & Ubeda, ; Shukla et al, ; Shukla et al, ), blanket application of these nutrients leads to imbalanced addition of Zn, Fe, Cu, and Mn (Ferguson, Lark, & Slater, ). Thus, the balanced and site‐specific management through varied nutrient application rate holds the key for economically sustainable agricultural production (Behera et al, ; Tesfahunegn, Tamene, & Vlek, ). Hence, knowledge regarding spatial distribution of nutrients in soil is needed to address this problem.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of spatial distribution and regional zone delineation for micronutrients in a semiarid Deccan Plateau Region of India

et al. 2018

Self Cite

View full text Add to dashboard Cite

Emerging micronutrient deficiencies in different soils of the world is a threat for sustainability of agriculture. As distribution of micronutrients in soil varies spatially, site‐specific management of micronutrients by delineating regional zones (RZs) is an effective strategy for precision agriculture. The current investigation was performed to delineate RZs in a Deccan Plateau Region (DPR) of India by considering spatial variability of some soil properties and available micronutrients for efficient management of micronutrients. Altogether, 4,939 representative soil samples (with geographical coordinates) from surface (0–0.15 m depth) layers were obtained from Telangana state lying in DPR of India. After processing, soil samples were analysed for pH, electrical conductivity, soil organic carbon and available zinc, copper, iron, and manganese. Soil pH, electrical conductivity, and soil organic carbon content had mean values of 7.48 ± 0.95, 0.42 ± 0.22 dS/m and 0.48 ± 0.17%, respectively. Whereas, the mean values of available zinc, iron, copper, and manganese concentrations were 0.83 ± 0.36, 8.79 ± 4.15, 0.99 ± 0.43, and 8.79 ± 4.06 mg/kg, respectively. Geostatistical analysis divulged different distribution pattern of soil properties and available micronutrients with strong to moderate spatial dependency. The four principal components (with >1 eigenvalue) responsible for 73% of total variance were considered for analysis. Six RZs from the study area were created through geostatistical, principal component, and clustering analysis. The measured soil properties and available micronutrients in the RZs varied significantly highlighting the usefulness of RZ delineation technique for precise micronutrients management in DPR of India.

show abstract

“…The spatial variability of soil nutrients is affected by parent material characteristics, topography, climate, vegetation, time and anthropogenic activities (Fenton and Lauterbach, 1998;Johnson et al, 2000;Umali et al, 2012;Keesstra et al, 2016;Mulder et al, 2016). Several studies have investigated the spatial variability of soil pH (Robinson and Metternicht, 2006;Fu et al, 2010;Bogunovic et al, 2014;Behera and Shukla, 2015), organic matter (Bogunovic et al, 2014;Behera and Shukla, 2015;Yang et al, 2016a), electrical conductivity (EC) (Robinson and Metternicht, 2006;Heilig et al, 2011; Behera and Shukla, 2015; Ranjbar and Jalali, 2016), phosphorus (Fu et al, 2010;Romic et al, 2012;Bogunovic et al, 2014;Behera et al, 2016;Wilson et al, 2016) and potassium (Fu et al, 2010;Bogunovic et al, 2014;Behera and Shukla, 2015). A good understanding of soil properties distribution will contribute to better soil management in agricultural areas (Brevik et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution of soil chemical properties in an organic farm in Croatia

Bogunović

Pereira

Brevik

2017

Science of The Total Environment

112

View full text Add to dashboard Cite

Soil pH, electrical conductivity (EC), organic matter (OM), available phosphorus (AP), and potassium (AK) are some of the most important indicators of soil fertility. These soil parameters are highly variable in space and time, especially in agricultural areas, with implications for crop production. The aim of this work was to study the spatial variability of pH, EC, OM, AP and AK using kriging and co-kriging methods in the Rasa River Valley (Croatia). As co-variates for each variable we considered the distance from the sea (DFS), distance from the river channels (DFC), pH, EC, OM, AP and AK. Only the variables with a significant correlation with the predictor were used as predictor variables. The results showed that soils of the study area had high pH, EC, OM and AK values and a low concentration of AP. The spatial variability was high for EC and low for pH levels. pH, EC, OM and AK had significant positive correlations. All these variables had significant negative correlations with AP. The exponential model was the best to model OM, AK and AP. Spherical and Gaussian models were the most accurate to model pH and EC. Spatial dependence was high for soil AK, EC and pH, and moderate for soil OM and AP. The incorporation of auxiliary variables increased the precision of the estimations. CoK_DFS was the best method to predict soil EC and AP, while Cok_EC, was better to estimate soil pH and Cok_pH and Cok_OM predicted soil OM and AK with the best accuracy. The maps produced with the best predictors showed that pH, EC, OM and AK had high levels in the northern and eastern parts of the study area. The opposite trend was identified in relation to the AP spatial pattern.

show abstract

Spatial variability of some soil properties varies in oil palm (<i>Elaeis guineensis</i> Jacq.) plantations of west coastal area of India

Cited by 42 publications

References 59 publications

Spatial Distribution and Management Zones for Sulphur and Micronutrients in Shiwalik Himalayan Region of India

Spatial Distribution and Management Zones for Sulphur and Micronutrients in Shiwalik Himalayan Region of India

Evaluation of spatial distribution and regional zone delineation for micronutrients in a semiarid Deccan Plateau Region of India

Spatial distribution of soil chemical properties in an organic farm in Croatia

Contact Info

Product

Resources

About