Mid-infrared spectroscopy and partial least-squares regression to estimate soil arsenic at a highly variable arsenic-contaminated site

International Journal of Environmental Science and Technology

Volumn 12, Issue 6, 2015, Pages 1965-1974

  Niazi, N K ^a,b   Singh, B ^a   Minasny, B ^a  

^a UNIVERSITY OF SYDNEY   (Australia)

^b UNIVERSITY OF AGRICULTURE   (Pakistan)

Author keywords

(Phyto)remediation; Cattle dip sites; Contamination; Mid infrared; Partial least squares; Prediction model; Principal component

Indexed keywords

ARSENIC; CONTAMINATION; INFRARED DEVICES; INFRARED SPECTROSCOPY; LEAST SQUARES APPROXIMATIONS; ORGANIC MINERALS; SOIL SURVEYS; SOILS; STATISTICS;

CATTLE-DIP SITES; MIDINFRARED; PARTIAL LEAST SQUARE (PLS); PREDICTION MODEL; PRINCIPAL COMPONENTS;

PRINCIPAL COMPONENT ANALYSIS;

ARSENIC; INFRARED SPECTROSCOPY; LEAST SQUARES METHOD; PHYTOREMEDIATION; REGRESSION ANALYSIS; SOIL POLLUTION; SOIL REMEDIATION; SOIL TYPE;

BOS;

EID: 84928155060     PISSN: 17351472     EISSN: 17352630     Source Type: Journal    
DOI: 10.1007/s13762-014-0580-5     Document Type: Article

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