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Assessing farm-scale spatial variability of soil nutrients in central India for site-specific nutrient management

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Title Assessing farm-scale spatial variability of soil nutrients in central India for site-specific nutrient management
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Creator Sanjib Kumar Behera
Arvind Kumar Shukla
Ashok Kumar Patra
Chandra Prakash
Ajay Tripathi
Suresh Kumar Chaudhari
Ch. Srinivasa Rao
 
Subject Spatial distribution
Vertisol
Site-specific nutrient management
Geostatistics
 
Description Not Available
Proper understanding about spatial variability of phyto-available soil nutrients and their associated properties is important for precise soil nutrient management in order to obtain sustainable crop production. Soil properties namely soil organic carbon (SOC), pH, and electrical conductivity (EC) influence phyto-availability of soil nutrients. We, therefore, carried out the present study to evaluate spatial variability of phyto-available nutrients (available nitrogen (AN), available phosphorus (AP), available potassium (AK), exchangeable Ca (Ex. Ca), exchangeable Mg (Ex. Mg), available sulfur (AS), available zinc (AZn), available copper (ACu), available iron (AFe), available manganese (AMn) and available boron (AB)), and associated soil properties (soil pH, EC and SOC) of the research farm of Indian Council of Agricultural Research-Indian Institute of Soil Science, Bhopal, Madhya Pradesh, India, using ordinary kriging (OK) method for prediction mapping. The experimental semivariograms were obtained and used for generating maps. Soil pH (7.22–8.66), EC (0.10–0.26 dS m−1), and SOC (0.19–0.98%) and concentrations of phyto-available nutrients (AN 76.8–224 kg ha−1, AP 8.20–61.0 kg ha−1, AK 140–693 kg ha−1, Ex. Ca 6779–9803 mg kg−1, Ex. Mg 365–1596 mg kg−1, AS 1.12–37.0 mg kg−1, AZn 0.27–1.64 mg kg−1, ACu 0.69–1.88 mg kg−1, AFe 4.64–19.8 mg kg−1, AMn 3.31–27.2 mg kg−1, AB 0.20–5.00 mg kg−1) in farm soils varied widely with CV values of 2.38–47.3%. Pearson’s correlation coefficient analysis revealed positive and negative significant correlations among the studied soil parameters. The principal component analysis resulted in five principal components (PC), with eigenvalue > 1, which accounted for > 59% of variability. Geostatistical analysis with OK interpolation revealed strong (AN, Ex. Ca, Ex. Mg, AS, AZn and AB), moderate (pH, EC, AP, AK, ACu, AFe and AMn), and weak (SOC) spatial dependence for soil parameters. The spatial distribution maps of soil properties and phyto-available nutrients could be used for location-specific nutrients management strategies and finding the appropriate locations for initiating nutrient experiments in the farm.
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Date 2024-01-04T09:11:14Z
2024-01-04T09:11:14Z
2022-04-25
 
Type Research Paper
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/81101
 
Language English
 
Relation Not Available;
 
Publisher SpringerLink