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Intern J Environ Anal Chem 93, 2013, 811 812 .pdf


Original filename: Intern J Environ Anal Chem 93, 2013, 811-812.pdf
Title: Comment on ‘Ranking and classification of non-ionic organic pesticides for environmental distribution: a QSAR approach' by Paola Gramatica
Author: Sierra Rayne

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This article was downloaded by: [The University of British Columbia]
On: 15 July 2013, At: 14:17
Publisher: Taylor & Francis
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International Journal of Environmental
Analytical Chemistry
Publication details, including instructions for authors and
subscription information:
http://www.tandfonline.com/loi/geac20

Comment on ‘Ranking and classification
of non-ionic organic pesticides for
environmental distribution: a QSAR
approach' by Paola Gramatica
Sierra Rayne

a

a

Chemologica Research , Mortlach , SK , Canada , S0H 3E0
Published online: 29 Apr 2013.

To cite this article: Sierra Rayne (2013) Comment on ‘Ranking and classification of
non-ionic organic pesticides for environmental distribution: a QSAR approach' by Paola
Gramatica, International Journal of Environmental Analytical Chemistry, 93:7, 811-812, DOI:
10.1080/03067319.2013.791982
To link to this article: http://dx.doi.org/10.1080/03067319.2013.791982

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Intern. J. Environ. Anal. Chem., 2013
Vol. 93, No. 7, 811–812, http://dx.doi.org/10.1080/03067319.2013.791982

Comment on ‘Ranking and classification of non-ionic organic pesticides for
environmental distribution: a QSAR approach’ by Paola Gramatica
Sierra Rayne*

Downloaded by [The University of British Columbia] at 14:17 15 July 2013

Chemologica Research, Mortlach, SK, Canada S0H 3E0
(Received 27 February 2013; final version received 6 March 2013)
Keywords: pesticides; PCA; classification; QSPR

In their article, Gramatica et al. [1] employ a quantitative structure–activity relationship (QSAR)
approach to predict the environmental distribution of 54 pesticides that these authors term ‘nonionic.’ Pirimicarb is included in this list of claimed ‘non-ionic’ compounds. However, this
compound has a pKa for protonation of 4.54 and will be at least partially ionised in many
environmental systems [2]. As such, the partitioning constants for pirimicarb will be pH
dependent [3] and assumptions regarding neutrality as used by Gramatica et al. [1] are not
valid for the environmental distribution and fate of this pesticide.
References
[1] P. Gramatica, E. Papa, and F. Battaini, Int. J. Environ. Anal. Chem. 84, 65 (2004).
[2] K. Chamberlain, A.A. Evans, and R.H. Bromilow, Pest. Sci. 47, 265 (1996).
[3] S. Rayne and K. Forest, J. Environ. Sci. Heal. A 45, 1550 (2010).

Authors’ reply to the Comment on ‘Ranking and classification of non-ionic organic
pesticides for environmental distribution: a QSAR approach’ by Sierra Rayne

This is the formula of the compound Pirimicarb, highlighted by Sierra Rayne as erroneously
defined ‘non-ionic’ in our paper.
*Email: sierra.rayne@live.co.uk
© 2013 Taylor & Francis

Downloaded by [The University of British Columbia] at 14:17 15 July 2013

812

S. Rayne

This is a N-dimethyl carbamate, a pesticide (specifically an insecticide) that is commonly
included in the category of ‘non-ionic pesticides’ also by other QSAR modellers, because it
does not have ionic linkages. This widely used categorisation aims to simply distinguish
compounds where only covalent bonds are present from those with ionic bonds (such as salts
with inorganics, that are not commonly modelled by QSAR methods).
In this sense there is no reason to redevelop our modelling approach, that was based on :
(a) a multivariate analysis by Principal Component Analysis (PCA) of the main five properties
relevant for the distribution in the various environmental compartment (namely: Koc, Kow, Sw,
VP, Henry’s law constant) for 54 pesticides, all categorisable as non-ionic; based on the above
concept (b) a cluster analysis of this data set for the definition of the a priori classes of Soluble,
Sorbed, Volatile, Not Volatile/Medium. (c) the classification by three QSAR methods CART
(Classification and Regression Tree), k-NN (K-Nearest Neighbor) and RDA (Regularised
Discriminant Analysis) all with low misclassification risks, of the above pesticides in the four
classes of environmental distribution, based only on three simple structural descriptors.
In practice, our proposed method lead to an immediate assessment of the potential pesticide
tendency to partition into different environmental compartments, based only on the molecular
structure, and represented by very simple structural information (MW, number of Hydrogen
Bond donors and a topological index J). This is mainly a ranking approach based on an intrinsic
global property.
The potential influence of the possible partial ionisation of chemicals structurally similar to
pirimicarb (in fact, in the studied data set other carbamates are included), is, according to our
chemical knowledge, weak at normal environmental pH values and was not considered in our
approach. The influence of pH on the environmental distribution of pesticides could be an
interesting topic to investigate with our proposed approach in another study. However, it is
important to note that this new study would imply the availability of all the experimental
physico-chemical properties for various pH values and these data are not easily available.


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