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partition coefficient
Type of information:
Adequacy of study:
key study
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
other: The partition coefficient of the natural complex substances was calculated from the partition coefficients of the known constituents estimated by the QSAR Kowwin v 1.67.
Justification for type of information:
QSAR prediction: migrated from IUCLID 5.6
Reason / purpose for cross-reference:
reference to same study

Data source

Reference Type:
other: QSAR model
KOWWIN v1.67a
U.S. Environmental Protection Agency
Bibliographic source:
US EPA. [2008]. Estimation Programs Interface Suite™ for Microsoft® Windows, v 4.00. United States Environmental Protection Agency, Washington, DC, USA

Materials and methods

Test guideline
according to guideline
other: REACH Guidance on QSARs R.6
not applicable
Principles of method if other than guideline:
The partition coefficient of a NCS has little meaning. In all cases, the log Kow can be based on the range of Kow from the calculated or measured values of the individual constituents. Calculated and measured data on the constituents are obtained from Kowwin v1.67. The relevance and reliability of the used QSAR for these constituents is shown in the attached QMRF and QPRF.
GLP compliance:
Type of method:
other: Calculation by estimation
Partition coefficient type:

Test material

Constituent 1
Reference substance name:
Lemongrass oil
Lemongrass oil
Constituent 2
Reference substance name:
Cymbopogon flexuosus, ext.
Cymbopogon flexuosus, ext.
Constituent 3
Reference substance name:
Cymbopogon flexuosus, ext.
EC Number:
EC Name:
Cymbopogon flexuosus, ext.
Constituent 4
Reference substance name:
Cas Number:
Test material form:
other: Liquid
Details on test material:
- Name of test material (as cited in study report): Cymbopogon flexuosus oil
- Physical state: liquid

Results and discussion

Partition coefficient
log Pow
Partition coefficient:
2.06 - 6.64
Details on results:
No data

Any other information on results incl. tables

Substance CAS Estimated log Kow
Limonene (D&L) 138-86-3 4.83
Citral 5392-40-5 3.45
Citronellal 106-23-0 3.53
Geraniol 106-24-1 3.47
Citronellol 106-22-9 3.56
Geranyl acetate 105-87-3 4.48
Methyl heptenone 110-93-0 2.06
Camphene 79-92-5 4.35
Linalol 78-70-6 3.38
Nonanone  4485-09-0 2.71
beta-Caryophyllene 87-44-5 6.30
alpha-Pinene 80-56-8 4.27
beta-Myrcene 123-53-3 4.88
Ocimene, cis- 13877-91-3 4.80
Citronellyl acetate 150-84-5 4.56
delta-Cadinene 483-76-1 6.32
Terpineol 8000-41-7 3.33
DL-Borneol 507-70-0 2.85
Eugenol 97-53-0 2.73
Nerol 106-25-2 3.47
alpha-Bergamottene 6895-56-3 6.64
Terpinolene 586-62-9 4.48
Caryophyllene beta oxyde 1139-30-6 4.91
iso-Geranial 72203-98-6 3.45

Kowwin v1.67a model details

Reference to the type of model used

KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate. KOWWIN’s™s methodology is known as an Atom/Fragment Contribution (AFC) method.


Description of the applicability domain

The applicability domain is based on the maximum number of instances of that a fragment can be used in a chemical and molecular weight. The minimum and maximum values for molecular weight are the following:


Training Set Molecular Weights:

Minimum MW: 18.02

Maximum MW: 719.92

Average MW: 199.98


Validation Molecular Weights:

Minimum MW: 27.03

Maximum MW: 991.15

Average MW: 258.98

Currently there is no universally accepted definition of model domain. However, users may wish to consider the possibility that log P estimates are less accurate for compounds outside the MW range of the training set compounds, and/or that have more instances of a given fragment than the maximum for all training set compounds. It is also possible that a compound may have a functional group(s) or other structural features not represented in the training set, and for which no fragment coefficient was developed. These points should be taken into consideration when interpreting model results.


Description and results of any possible structural analogues of the substance to assess reliability of the prediction

External validation with a dataset containing 10946 substances resulted in a correlation coefficient (r2) of 0.943, a standard deviation of 0.479 and an absolute deviation of 0.358.

Predictivity assessment of the external validation set:

Validation Set Estimation Error:

within <= 0.20 - 39.6%

within <= 0.40 - 66.0%

within <= 0.50 - 75.6%

within <= 0.60 - 82.5%

within <= 0.80 - 91.6%

within <= 1.00 - 95.6%

within <= 1.20 - 97.7%

within <= 1.50 - 99.1%

Uncertainty of the prediction

All constituents for which estimations were made fall within the applicability domain of the model.

Mechanistic domain

KOWWIN (the Log Octanol-Water Partition Coefficient Program) estimates the logarithmic octanol-water partition coefficient (log P) of organic compounds. KOWWIN requires only a chemical structure to estimate a log P. The octanol-water partition coefficient is a physical property used extensively to describe a chemical's lipophilic or hydrophobic properties. It is the ratio of a chemical's concentration in the octanol-phase to its concentration in the aqueous phase of a two phase system at equilibrium. Since measured values range from less than 10^-4 to greater than 10^8 (at least 12 orders of magnitude), the logarithm (log P) is commonly used to characterize its value.

KOWWIN uses a "fragment constant" methodology to predict log P. In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate. KOWWIN’s™s methodology is known as an Atom/Fragment Contribution (AFC) method. Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values.

As all regular and common fragments are included in this method, and the constituents for which this method was applied do not contain exotic fragments, there are no limits to the mechanistic domain.

Applicant's summary and conclusion

The log Kow range of the constituents of Cymbopogon flexuosus oil is 2.06 - 6.64.
Executive summary:

As Cymbopogon flexuosus oil is a naturally complex substance consisting of multiple constituents, a partition coefficient value for this NCS has little meaning. Therefore, in line with the NCS protocol, partition coefficients for the individual known constituents were calculated using the KOWWIN v1.67 QSAR by US-EPA.

The log Kow range for Cymbopogon flexuosus oil constituents was found to be 2.06 - 6.64. The log Kow of the constituents is >=3 for 92.82% of the composition and >= 4 for 9.12% of the composition.

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