es6b04956_si_001.pdf (975.12 kB)
Soil-Bacterium Compatibility Model as a Decision-Making Tool for Soil Bioremediation
journal contribution
posted on 2016-12-21, 00:00 authored by Benjamin Horemans, Philip Breugelmans, Wouter Saeys, Dirk SpringaelBioremediation
of organic pollutant contaminated soil involving
bioaugmentation with dedicated bacteria specialized in degrading the
pollutant is suggested as a green and economically sound alternative
to physico-chemical treatment. However, intrinsic soil characteristics
impact the success of bioaugmentation. The feasibility of using partial
least-squares regression (PLSR) to predict the success of bioaugmentation
in contaminated soil based on the intrinsic physico-chemical soil
characteristics and, hence, to improve the success of bioaugmentation,
was examined. As a proof of principle, PLSR was used to build soil-bacterium
compatibility models to predict the bioaugmentation success of the
phenanthrene-degrading Novosphingobium sp. LH128.
The survival and biodegradation activity of strain LH128 were measured
in 20 soils and correlated with the soil characteristics. PLSR was
able to predict the strain’s survival using 12 variables or
less while the PAH-degrading activity of strain LH128 in soils that
show survival was predicted using 9 variables. A three-step approach
using the developed soil-bacterium compatibility models is proposed
as a decision making tool and first estimation to select compatible
soils and organisms and increase the chance of success of bioaugmentation.
History
Usage metrics
Categories
Keywords
Soil-Bacterium Compatibility Modelphysico-chemical treatment20 soilsPLSRsoil characteristics impactsoil characteristicsDecision-Making ToolSoil Bioremediation Bioremediationstrain LH 128show survivalsoil-bacterium compatibility modelsleast-squares regressionbioaugmentation successsound alternativephenanthrene-degrading Novosphingobium sp12 variables9 variablesbiodegradation activityPAH-degrading activityphysico-chemical soil characteristicsLH 128.
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC