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Monitoring of paintings under exposure to UV light by ATR-FT-IR
spectroscopy and multivariate control charts
Emilio Marengo *, Maria Cristina Liparota, Elisa Robotti, Marco Bobba
Department of Environmental and Life Sciences, University of Eastern Piedmont, Via Bellini 25/G, 15100 Alessandria, Italy
Received 8 July 2005; received in revised form 20 September 2005; accepted 28 September 2005
Available online 27 December 2005
Abstract
This paper concerns the improvement of a method, already applied for the conservation state monitoring of wooden and painted surfaces, to a
system closely simulating a real artwork, namely a canvas painted with mixtures of three organic pigments (Alizarin, Permanent Red,
Phtalocyanine Green). Ten mixtures of these pigments, according to an augmented simplex-centroid design, were prepared, mixed with linseed
oil and spread on 10 cotton canvas strips. Drying ended, all the samples were analysed by ATR-FT-IR spectroscopy to describe the superficial
variability in normal conditions of conservation, i.e. when no degradation is present. Successively, the samples were exposed to artificial UV light
simulating the action of an aggressive portion of sunlight. The IR spectra of the surfaces were regularly acquired to monitor the superficial changes
due to the UV aggression. Treatment ended, a chemometric study based on the Principal Component Analysis of the spectroscopic data collected
both in normal conditions of conservation and during the artificial accelerated ageing, was performed and the multivariate Shewhart and Cusum
control charts were built with the scores of the significant PCs (principal components). PCA based control charts showed to be able to identify the
presence of significant changes of the painted surfaces, to identify the starting of the degradations and to provide insights about the chemical
alterations induced by the UV exposure.
# 2005 Elsevier B.V. All rights reserved.
Keywords: Cultural heritage conservation; ATR-FT-IR spectroscopy; Augmented simplex-centroid design; Principal Component Analysis; Degradation
monitoring; Multivariate control charts
www.elsevier.com/locate/vibspec
Vibrational Spectroscopy 40 (2006) 225–234
1. Introduction
Among the most important contributions that chemistry can
offer to cultural heritage conservation there are the under-
standing of the original execution techniques and the
identification of the problems affecting artworks, allowing
the choice of the most effective and durable intervention. The
analytical techniques used in this field must guarantee that the
acquisition of the chemical information does not compromise
the conservation state of the handmade, in other words, they
must be non-destructive and non-invasive; they can give
‘‘elemental’’ information (as atomic absorption spectroscopy
[1], inductively coupled plasma-mass spectroscopy [2], X-ray
fluorescence spectrometry [3], particle induced X-ray emission
[4], scansion electron microscopy [5]) or ‘‘molecular’’
information (as IR [6], Raman [7], UV [8] and X-ray
* Corresponding author. Fax: +39 0131 360390.
E-mail address: [email protected] (E. Marengo).
0924-2031/$ – see front matter # 2005 Elsevier B.V. All rights reserved.
doi:10.1016/j.vibspec.2005.09.005
diffraction [9] spectroscopy, HPLC [10], GC–MS [11]). It
follows that the physico-chemical characterisation, today, plays
a fundamental role in studies about artworks authentication,
restoring and monitoring. This paper presents a new method for
the paintings conservation state monitoring by means of
principles of statistical process control: it has already been
successfully applied to wooden objects [12] and for simple
systems simulating paintings, i.e. canvas strips painted with one
single inorganic [13,14] or organic [15] pigment; here, we have
improved the method and applied it to a more complex system,
represented by canvas painted with mixtures of organic
pigments, namely Alizarin, Permanent Red and Phtalocyanine
Green, in order to approach the great complexity of a real
painting. The method gives the possibility of monitoring the
conservation state of paintings through the construction of
multivariate Shewhart and Cusum control charts using the
scores derived from Principal Component Analysis, performed
on the spectroscopic data of the painted surfaces. The analytical
technique employed is attenuated total reflection (ATR) FT-IR
spectroscopy [16,17] which is suitable to analyse works-of-art
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234226
Fig. 1. Augmented simplex-centroid design; relative proportions of the pig-
ments are indicated.
as it does not require any sample pre-treatment and it is a non-
destructive analysis. Literature reports several examples of
application of infrared spectroscopy [18–21] in the field of
cultural heritage conservation as it allows to characterise both
inorganic and organic constituents of a wide variety of
artworks, providing insights on the materials and techniques
of execution [22].
In order to evaluate if this method is able to identify a
deviation from normal condition of conservation due to a
deterioration effect, after the spectroscopic characterisation of
the surfaces, the samples were exposed to an accelerated ageing
phase, simulating one of the possible natural cause of paintings
degradation (i.e. the exposure to sunlight) by irradiation with
the UV light produced by a lamp emitting at 254 nm for about
272 h. Regularly, the exposure was stopped and the IR spectra
were collected to follow the structural changes of the surfaces;
finally, PCA was performed on both characterisation and
degradation analyses and the scores of the significant PCs were
used to build the multivariate Shewhart and Cusum control
charts to evaluate if deviations from the starting in control
situation had occurred, obviously related to the UV exposure.
This method could have possible application for real
painting conservation state monitoring as multivariate control
charts allow to quickly point out any deviation from normal
condition of conservation while PCA gives insight on the
causes of deviation (i.e. a the decay phenomenon) and also on
the specific functional groups interested by degradation.
2. Theory
The principal aim of this work is the study of the degradation
of canvas painted with mixtures of three organic pigments
(Alizarin, Permanent Red and Phtalocyanine Green) during the
exposure to UV light. The pigments chosen are representative
both of the past (Alizarin was used since ancient Egyptians) and
of the present (Permanent Red and Pthalocyanine Green have
been synthesized the first at the end of the XIX century, the
second at the beginning of XX century) to show that the our
method of monitoring the conservation state of a painting can be
applied to the ancient works-of-art as well as to the recent ones.
The problem is characterised by three components
(pigments) so that the factor space is an equilateral triangle,
where the vertices are the single-component mixtures, the
points on the edge are the binary mixtures and at the interior of
the triangle there are all possible ternary mixtures.
In order to have representative mixtures of the whole factor
space, an augmented simplex-centroid design [23] was
selected, that provides 10 mixtures (Fig. 1).
The description of the statistical variability of the surfaces
under study is obtained by means of ATR-FT-IR spectroscopy;
so the data set is an X matrix constituted by n rows (the IR
spectrum of a specific sample) and p variables (i.e. the spectrum
wavenumbers). In this case, the application of a multivariate
approach [24–26] represents a good procedure to monitor the
process and to identify trends and systematic behaviours
regarding the samples conservation state along time, in fact, a
great simplification of the problem can be obtained by means of
Principal Component Analysis (PCA) [27], a powerful data
mining technique which provides a new set of orthogonal
variables, linear combination of the original ones, to describe the
system under investigation. The new variables, the Principal
Components (PCs), are built so that each successive PC explains
the maximum possible amount of residual variance of the data
set; they are an optimal description of the original data set, with a
significant dimensionality reduction and redundancy elimina-
tion. It is important to select only the relevant PCs, which account
for the systematic information present in the complex data set.
PCA can be successfully applied to individuate relevant
changes due to a degradation process, through the analysis of the
projections (scores) of the original data (IR spectrum at different
times) in the PCs space, while the analysis of the composition of
each PC in terms of the contribution of the original variables
(loadings) may allow the identification of the structural changes.
When PCA is applied for monitoring a degradation process,
the presence of groups of observations may accounts for
‘‘special causes’’ of variation related to the occurrence of a
degradation effect. The presence of samples out of the �3s
control limits in the Shewhart control charts built using the
relevant PC scores [28,29], or of trends and systematic
behaviours in the score plots, are a clear indication of out-of-
control processes (in this case, the occurring degradation).
Given the Shewhart control charts are not very sensitive to
small changes of the process mean, another powerful tool, the
so-called CUSUM (CUmulative SUM) control chart [30] was
also applied. This chart represents the cumulative deviation of
each successive observation from a reference value, for instance
the average. One chart is built for every significant PC (as for
the Shewhart chart) and the reference value is the average score
for the corresponding PC. The occurrence of a particular event
is registered as a change of the steepness in the correspondent
graph, steepness that is proportional to the change of the mean
of the variable considered.
2.1. The applied procedure
Our previous works [12–15] report in details the procedure
applied to monitor the conservation state of the analised
samples; in this specific case we have:
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234 227
1. c
Ta
Pri
cm
Lin
haracterisation of the 10 painted surfaces by acquisition of
three genuine replicates of the IR spectra;
2. a
pplication of the simulated accelerated ageing (UVexposure) and monitoring by regularly registered IR spectra;
3. P
rincipal Component Analysis of both characterisation and‘‘degradation’’ measurements togheter; in order to identify
the significant spectroscopic variables, the Marten’s uncer-
tainty test [26] was applied;
4. m
ultivariate control charts construction; the control limits ofthe Shewhart charts were calculated on the basis of the thirty
characterisation analyses that represent the situation of
statistical control (no degradation present). The calculation
of the control limits of the Cusum charts was not necessary,
given the evident changes present in their graph;
5. P
rincipal Components Analysis of the residuals of degrada-tion analyses [31]: this step is usefull for the individuation of
new species due to the degradation of the surface exposed to
UV light, as this information could not be contained in the
results of first PCA.
3. Experimental
3.1. Materials, ATR-FT-IR spectroscopy and software
In this study, three organic pigments were chosen: Alizarin
367 (1,2-dihydroxiantraquionone, Schmincke, Germany), Per-
manent Red 252 (naphthol-as PR9, Maimeri, Italy) and
Phtalocyanine Green 321 (Cu-phthalocyanine chlorinated
PG7, Maimeri, Italy). Alizarin [32] is the synthetic version
of a pigment extracted from madder plants roots and used since
ancient Egyptians for colouring textiles. Permanent Red [33] is
a very stable azo pigment and Phtalocyanine Green [34] is
another very stable synthetic dye, discovered by chance during
the phtalimide synthesis.
The 10 mixtures required by the augmented simplex-
centroid design were prepared as follows:
1. p
igments weighing, in accordance with the amounts indicatedin Table 1 (1 g of mixture was obtained for each sample);
ble 1
ncipal vibrational assignments of all the superficial components of the samples
�1 Assignment cm�1
seed oil Alizarin
3001 v(C–H) CH 3300
2960 va(C–H)CH3 1730
2926 va(C–H)CH2 1535–1349
2885 vs(C–H)CH2 1224–1030
1747 v(C O) 896–660
1658 v(C C)
1464 d(CH2) Permanent Red
1418 wag(CH2)–CH2–CO–O 3400
1378 wag(CH2) 3080
1240 va(C–C–O) 1667
1164 v(C–O) 1600
1100 va(O–CH2–C) 1420
990 d(CH) (alkene) 1260–1000
723 g-(CH2)– 857–657
2. d
A
v
v
v
d(
d(
v
v
v
v
v
v
d(
ilution of each mixture with 1.50 g of linseed oil [35] to
obtain the suitable consistency;
3. p
ainting of the cotton canvas strips [36] (size 6 cm � 2 cm)with the prepared mixtures;
4. th
e strips, once painted, were dried for two months.When completely dried, each strip painted with a specific
mixture was characterised by thirty genuine replicates of the
ATR-IR spectrum recorded with an AVATAR 370 FT-IR
Thermo Nicolet spectrometer (Thermo Nicolet Corporation,
USA) equipped with a He–Ne laser emitting at 632.8 nm with a
power of 50 mW. The spectrophotometer is directly controlled
by a PC with the EZ OMNIC (Thermo Nicolet Corporation,
USA) software. The IR spectra were collected with the
SMART Accessory that pressed the sample over the Zn–Se
crystal. All spectra were registered from 3750 to 650 cm�1,
with a resolution of 4 cm�1 and 32 scans; the background was
collected before each spectrum. The simulation of the
exposure to sunlight was obtained by exposing the samples
surfaces to the UV light produced by a lamp emitting at 254 nm
with a power of 15 W, for a total of 272 h. Every 16 h of
irradiation, the exposure to UV rays was interrupted to collect
the IR spectra of the surfaces under study for a total of
seventeen ‘‘degradation’’ analyses. The final X data matrix,
containing both characterisation (30 replicates for each
mixture for a total of 300) and degradation (17 analyses for
each mixture for a total of 170) analyses has dimensions
(470 � 3100).
Owing to background effects, different variances in
variables, low spectra reproducibility, etc., raw data may have
a distribution that is not optimal for multivariate analysis; so, in
order to reduce the ‘‘noise’’ introduced by such effects, the
following pre-processing procedure was applied on the original
data:
1. fi
rst derivative of the original spectra: this is a baselinecorrection, usually performed when variables are them-
selves a function of some underlying variable, e.g.
absorbance at various wavenumbers; furthermore, it allows
ssignment cm�1 Assignment
Phtalocyanine Green
(OH) 3410 v(N–H)
(C O) 1567 v(C C)
(CC) 1389–1020 v(C–N)
CH) 870–657 d(CH)
C-O), g(C O)
(N–H)
CH
(C O)
(C C)
(N N)
(CO), v(CN), d(CN)
CH), ring deformation
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234228
Fig
bin
to magnify little differences among spectra having similar
behaviour;
2. m
ean centring: it ensures that all the results will beinterpretable in terms of variation around the mean.
Chemometric data treatment were performed by ‘‘The
Unscrambler’’ version 7.6 (Camo Inc., Norway), ‘‘Microsoft
Excel 2000’’ (Microsoft Corporation, USA), ‘‘Statistica’’
version 6 (StatSoft, USA) and ‘‘MatLab’’ version 6.1 (The
Mathworks, USA); the spectra transformations were obtained
by ‘‘Origin’’ version 6.1 (Microcal Software Inc., USA).
. 2. ATR-IR spectrum of: (a) Alizarin (mixture 1) (b) Permanent Red (mixture 2)
ary mixture 6 mixed with linseed oil and spread on canvas.
4. Results and discussion
Figs. 2 and 3 show the original ATR-IR spectra of the 10
mixtures before and after the exposure to UV light, while
Table 1 reports the vibrational assignments of the pure
components. It can be noticed that, owing to the high refractive
index of the pigments, only linseed oil and pigments vibrations
are present in the spectra, while no contribution from the canvas
is evident. With the aim to individuate colour differences
between samples before and after UV exposure samples not
exposed to UV light, used as a reference system were compared
(c) Phtalocyanine Green (mixture 3) (d) binary mixture 4 (e) binary mixture 5 (f)
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234 229
Fig. 3. ATR-IR spectrum of: (a) ternary mixture 7 (b) ternary mixture 8 (c) ternary mixture 9 (d) ternary mixture 10 mixed with linseed oil and spread on canvas.
Table 2
Explained variance percentage and cumulative explained variance percentage
for first five PCs calculated with characterisation and degradation analyses
Explained variance
(%)
Cumulative explained
variance (%)
PC1 68.80 68.80
PC2 14.81 83.61
PC3 3.86 87.48
PC4 3.60 91.08
PC5 1.23 92.31
with the aged ones: no colour changes, but only a loss of gloss of
all the surfaces, was observed after the UV treatment. Looking at
the IR spectra of the samples before and after the UVexposure, it
can be noticed that a general increase of the absorbance
intensities of the peaks occurred, with the exception of peak at
2930 cm�1 that decreased. As known, natural drying of linseed
oil starts with an autoxidation of the unsaturated fatty acid
components, with the development of an extensive cross-linking
and the formation of conjugated unsaturations [35]; then, a slow
consumption of some labile cross-links brings to a very stable
network, with small amounts of low molecular weigh molecules,
either formed by fragmentation or as unreacted triglycerides. The
continuation of the hardening process in natural conditions, leads
to the oxidative degradation of linseed oil, and only for long
periods of artificial ageing (for example, UV exposure),
corresponding to years of natural ageing, the oxidation takes
place on the aliphatic segments, leading to partial fragmentation
of the structure [35]. In the light of these considerations, the
spectral modification seen after exposure to UV light, can be
explained in the following way: the applied treatment accelerated
the natural drying process of the binder, in fact the increase of the
peak intensity at 1740 cm�1 relative to C O stretching and the
decrease of the peak intensities at about 2930 cm�1 relative to
aliphatic CH stretching indicates an occurring oxidation. Owing
to linseed oil oxidation, pigments signals becomes more evident
as shown by the increase of theirs peak intensities. In order to
more deeply investigate the effects of UV exposure on the
samples surfaces, PCA of both ‘‘characterisation’’ and ‘‘degra-
dation’’ analyses was performed. The obtained results are
reported in Table 2.
4.1. Principal Component Analysis of characterisation and
degradation analyses
The first three PCs, explaining about 87.5% of the total
variance of the data set, are retained as the significant ones. The
score plot of PC1 and PC2 (Fig. 4a) clearly shows the 10 mixtures
at the points of the augmented simplex-centroid design: the
analyses relative to mixtures 1, 2 and 3, i.e. the single-component
mixtures, are at the vertices of the triangle, while the analyses
corresponding to the binary mixtures (4, 5, 6) are on the edges of
the triangle and finally, the analyses relative to the ternary
mixtures (7, 8, 9, 10) are in the interior part of the triangle.
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234230
Fig. 4. Score plot and loading plot of: (a) PC1 and PC2; (b) PC1 and PC3; characterisation analyses are represented as empty points, while degradation analyses as the
full ones.
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234 231
Along PC1 there is the separation of mixtures 1, 4, 3, 9, 7, 10
at positive values, from mixtures 5, 6, 8, 2 at negative values.
Instead along PC2 there is the separation of mixtures 1, 7, 6, 4, 2
at positive values, and mixtures 8, 5, 10, 9, 3 at negative values.
Furthermore, it can be seen that the characterisation analyses
of each mixture are distributed along an oblique line oriented
toward mixture 1. Degradation analyses move from the
correspondent characterisation ones along each oblique line:
this probably means that during UV exposure structural
modifications of the surfaces occurred. The combined use of
the loading plot and the Marten’s Uncertainty test allows to
individuate the region containing the significant peak (or peaks)
correspondent to the functional group mainly affected by UV
irradiation: in particular, the loading plot of PC1 shows that
peaks at 728 and 759 cm�1 relative to d(CH) bending of the
pigments mixtures have the larger weight on this PC, while the
loading plot of PC2 shows that peak at 950 cm�1 relative to
d(CH) bending of the unsaturated chains of the binder has a
large weight. So, we can conclude that first two PCs account by
for the oxidative effect of UV light on the unsaturated
component of the analysed surfaces: in particular, as confirmed
by literature [34], UV light caused a breaking of both aromatic
rings of the pigments and of the C C bonds of the unsaturated
fatty acids of linseed oil.
Looking at the score plot of PC1 and PC3 of Fig. 4b, it can be
noticed that along PC3, from positive to negative values, there is a
very good separation between characterisation and degradation
analyses which go to more positive values of this PC, while along
PC1 the separation of all the single mixtures observed in the
previous score plot is confirmed. The loading plot of PC3 shows
that it accounts by for the peaks at 1747 and 2930 cm�1 relative to
the C O stretching and to the aliphatic C–H stretching of linseed
oil. So, it can be stated that UV exposure caused a very marked
oxidative effect on the binder as PC3 suggests that phodegrada-
tion involved also the carbonyl and the aliphatic segments that are
the last to degrade in natural ageing conditions.
4.2. Multivariate control charts
Multivariate control charts represent a very useful tool to
follow the process relative to the conservation state of the
analysed surfaces along time. In particular, for each mixture,
both the multivariate Shewhart and Cusum charts were built,
using the scores of the first three PCs, for a total of 60 charts.
For sake of brevity, only the multivariate control charts of
two mixtures are discussed, in particular mixture 2 (pure
Permanent Red) and mixture 10 (Alizarin 1/3, Permanent Red
1/3, Phtalocyanine Green 1/3); similar comments can be made
for all other mixtures as the behaviours of their multivariate
charts are practically the same.
4.2.1. Mixture 2 (pure Permanent Red)
Fig. 5 shows the multivariate control charts of mixture 2 (pure
Permanent Red) relative to the first three PCs. In the PC1
Shewhart chart (Fig. 5a) it can be seen that the first charact-
erisation analyses have a decreasing trend then stabilising on the
process mean: this can be ascribed to the stabilisation of the
linseed oil drying. Instead, degradation analyses, are charac-
terised by an increasing trend, with one point beyond the Upper
Control Limit (UCL) and the other ones very close to it: this
indicates a loss of statistical control of the sample conservation
state which is probably due to the breaking of the aromatic rings
of Permanent Red. All these consideration are confirmed by the
Cusum chart of PC1 (Fig. 5b) that shows, after the random
oscillating first points, a stable behaviour of the characterisation
analyses scattered on an horizontal line around zero; the
beginning of the UVexposure shows a significant deviation from
this behaviour, with the points on an increasing oblique line.
The Shewhart chart of PC2 (Fig. 5c) shows the trend of the
conservation state of the sample from the point of view of the
unsaturated fatty acid components of the linseed oil: in the
characterisation period the process is in statistical control as the
analyses distribute around the mean and are affected by a small
variability even if first 10 analyses show the same trend of the
Shewhath chart of PC1; instead, in the period correspondent to
UV exposure the process go out of control as the scores of
degradation analyses increase toward the initial process mean,
with last points behind the UCL. This loss of statistical control
is probably due to the breaking of the C C bonds of the
unsaturated fatty acid components of linseed oil induced by the
exposure to UV light.
The Cusum chart of PC2 (Fig. 5d) has a very similar
behaviour of that one relative to PC1: in the characterisation
period, after the same oscillation of first 10 analyses, the mean
of the process become constant as the analyses describe an
horizontal tract around zero, while during degradation period
the analyses go toward more positive values with respect to the
initial process mean.
Fig. 5e is the Shewarts chart of PC3; it contains the
information relative to the conservation state of both aliphatic
and carbonyl groups of the binder. The analyses correspondent
to the characterisation period indicate an in-control situation as
they are located around the mean of the process, with the
exception of ninth characterisation which, falling behind LCL,
is an outlier; then, with first hours of exposure to UV light, the
state-of-health of the analysed surface compromises owing to
photoxidation of aliphatic groups of the linseed oil: in fact the
process assumes an increasing trend that brings last analyses
behind UCL, and this is an evident demonstration of a loss of
statistical control. The Cusum chart of PC3 (Fig. 5f) confirms
these results: the mean of the process during the characterisa-
tion period, after the oscillation of the first 10 analyses,
becomes constant (horizontal line around zero), while when the
exposure of the sample to UV light starts, a significant deviation
of the process mean towards positive values occurs, which is
related to the oxidation of the aliphatic chains and to the
correspondent increase of carbonyl groups of the binder.
4.2.2. Mixture 10 (Alizarin1/3, Permanent Red 1/3,
Phtalocyanine Green 1/3)
In this case, we all the three organic pigments are present in
equal proportions together with the binder. Fig. 6a is the
Shewhart control charts of PC1: it contains information about
the aromatic rings of the pigments mixture. From this chart, it
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234232
Fig. 5. Multivariate control charts of mixture 2 (pure Permanent Red): (a) Shewhart control chart of PC1; (b) Cusum control chart of PC1; (c) Shewhart control chart of
PC2; (d) Cusum control chart of PC2; (e) Shewhart control chart of PC3; (f) Cusum control chart of PC3.
clearly emerges that UVexposure produced an oxidative effects
on the aromatic components of the sample surface: at the
starting of the accelerated ageing the process goes out of
statistical control, in fact the degradation analyses are
characterised by a clear increasing trend, with the last analysis
beyond the UCL. All these consideration are confirmed by the
Cusum chart of PC1 (Fig. 6b) that shows a prominent deviation
of the process mean from the initial value, which starts from the
fifth degradation measurement (time necessary to induce the
starting of the degradation), showing a shift towards positive
values during UV exposure.
Fig. 6c is the Shewhart chart of PC2, it accounts for the C C
bonds of the unsaturated fatty acids of linseed oil: there is a
clear sign of an out-of-control process, with the increasing trend
of the degradation analyses and the seven last analyses beyond
the UCL. This is confirmed by the correspondent Cusum chart
(Fig. 6d) that shows a significant deviation on the process mean
from the initial in-control situation, that starts immediately with
the application of the accelerated ageing process.
Fig. 6e is the Shewhart chart of PC3, containing the
information relative to aliphatic and carbonyl segments of the
binder. It stresses, once again, that the state-of-health of
linseed oil compromises during UV exposure: after the stable
situation of the in-control characterisation period, with the
exception of an outlier corresponding to analysis no.10, the
degradation analyses show a clear steep positive trend, with
many analyses that fall beyond the UCL. The correspondent
Cusum chart (Fig. 6f) shows, as expected, that the degradation
starts immediately after the application of the degradation
process.
4.3. Principal Component Analysis of the residual of
degradation analyses
The previous PCA had been performed on the characterisa-
tion and degradation analyses: first two PCs showed that the
conservation state of the samples surfaces has changed because
the spectral profiles have been modified during the UV
exposure. With the aim to individuate some information not
accounted by first two PCs, maybe concerning the formation of
new species due to the degradation of the samples, the resi-
duals data matrix of degradation analyses was investigated.
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234 233
Fig. 6. Multivariate control charts of mixture 10 (Alizarine 1/3, Permanent Red 1/3, Phtalocyanine Green 1/3): (a) Shewhart control chart of PC1; (b) Cusum control
chart of PC1; (c) Shewhart control chart of PC2; (d) Cusum control chart of PC2; (e) Shewhart control chart of PC3; (f) Cusum control chart of PC3.
The residual of each degradation analysis is a spectrum
containing the peaks not explained by first two PCs. A new PCA
was then performed on the residuals data matrix, of the
degradation but no systematic information emerged.
5. Conclusions
An improvement of a new method based on ATR-FT-IR
spectroscopy and on Statistical Process Control principles for
monitoring the conservation state of works-of-art is shown; the
method, developed on wooden objects and canvas painted with
a single pigment, is here applied to some canvas painted with
mixtures of three organic pigments to closely simulate the
complexity of a real painting. The final aim is to built a useful
tool to monitor the state-of-health of works-of-art. For this
purpose, 10 mixtures of three organic pigments, according to
augmented simplex-centroid design, were prepared and spread
on 10 cotton canvas strips. Each sample was characterised by
the acquisition of genuine replicates of ATR-IR spectra; then,
they were exposed to UV light for about 272 h and, regularly
interrupted the exposure, new ATR-IR spectra were collected to
follow the structural changes of the surfaces. A PCA was
performed on both characterisation and degradation spectra,
and multivariate control charts (Shewhart and Cusum charts)
were built with the scores of the relevant PCs. From the
chemometric study emerged that during the accelerated ageing
the conservation state of the surfaces went out of statistical
control owing to oxidative effect of UV light on pigments and
linseed oil; Shewhart and Cusum chart showed clearly the
precise moment when this deviation occurred. Furthermore,
PCA stresses that UV light caused a breaking of both pigment
aromatic ring and binder unsaturated fatty acid C C bonds; the
UV effect has been very marked for linseed oil as the
components degrading only after a lot of years in natural
condition of ageing (i.e. the saturated fatty acid components),
have been here oxidised. The increase of the peak intensity of
C O bond is a further confirmation of the oxidative effect of
UV light on linseed oil.
Acknowledgment
The authors gratefully acknowledge financial support by
MIUR (Ministero dell’Istruzione, dell’Universita e della
Ricerca, Rome, Italy; COFIN 2003).
E. Marengo et al. / Vibrational Spectroscopy 40 (2006) 225–234234
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