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MASP – Museu de Arte de São Paulo “Assis Chateaubriand”
ARCHAEOLOGICAL SITES FROM BAIXO SÃO FRANCISCO,
BRAZIL: ARCHAEOMETRIC APPROACH ON JUSTINO SITE
J.O. Santos1, C.S. Munita2, M.E.G. Valério3, C. Vergne4
1) Centro Federal de Educação Tecnológica de Sergipe, Av.Engº Gentil Tavares da Motta, 1116,
Aracaju, Sergipe, CEP 49.055-260, Brazil
2) Instituto de Pesquisas Energéticas e Nucleares, Av. Lineu Prestes, 2242, Cidade Universitária, São
Paulo, São Paulo, CEP 05508-000, Brazil.
3) Departamento de Física da Universidade Federal de Sergipe, Av. Marechal Rondon, s/n, CEP
49100-000, São Cristóvão, Sergipe, Brazil.
4) Museu de Arqueologia de Xingó, Rodovia Canindé, Piranhas, Trevo da UHE – Xingó, Canindé do
São Francisco, Sergipe CEP 43200-000, Brazil.
ABSTRACT
The study of the physical and chemical characteristics of the ceramics crafts, in association
with historical and archaeological research, has allowed for the reconstruction of the cultural
habits from ancient communities. The goal of this work was to study the chemical
composition of archaeological potteries collected from Justino site, located in Baixo São
Francisco region, Sergipe state, Brazil. The use of the Instrumental Neutron Activation
Analysis (INAA), allowed the definition of compositional groups of potteries according to the
chemical similarities of the ceramic paste, which reveals the composition of the raw materials
utilized in the manufacturing process by prehistoric man. The outliers were identified by
means of robust Mahalanobis distance. The temper effect in the ceramic paste was studied
by means of modified Mahalanobis filter. The results were interpreted by means of cluster
analysis, principal components analysis and discriminant analysis. The results obtained in
this work, in association with archaeological information, allowed for the identification of the
ceramic groups relative to ceramist occupations at Justino Site and for the definition of the
reference groups according to the chemical composition. Therefore, this work provides
contributions to the reconstruction of the prehistory of the communities which lived in the
Baixo São Francisco region, and to the reconstitution of the general frame of the ceramist
population from Brazilian Northeast.
Keywords: Archaeometry, Pottery, INAA, Dilution effects, Xingó
INTRODUCTION
Nowadays the Archeology has used a variety of methods and tools to reconstruct the
ancient cultures, such as excavation, environmental analysis, sociology, scientific and
historical dating methods, historic and iconographic source, material analysis of found
artifacts, among others1. The use of adopted method from natural sciences is currently
subsumed under the term Archaeometry. Since pottery represents a sophisticated merging of
previously separate domains of human knowledge and experience these objects are intensely
studied by means of archaeometric methods.
Pottery was probably the first synthetic material made by humans. Broken pottery
fragments are among the most common artifacts found at archaeological sites around the
world2; as a result, it is one of the most common studied materials by archaeologists. Besides
its abundance and durability, pottery has several macroscopic and microscopic attributes of
interest to archaeologists3. Visual properties such as shape and surface decoration are
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1o Simpósio Latino Americano sobre Métodos Físicos e Químicos em Arqueologia, Arte e Conservação de Patrimônio Cultural.
São Paulo, SP, Brasil, 11 a 16 de julho de 2007
MASP – Museu de Arte de São Paulo “Assis Chateaubriand”
frequently used as cultural and chronological indicators. Additionally, microscopic properties
such as the texture of the paste (i.e., the clay and temper combination) can be used to study
preparation techniques. The chemical composition can be used to locate the source(s) of
ingredients or provide evidence of geographic displacement, and the oxidation state of ironbearing constituents can be used to reconstruct firing conditions.
In a strictly geological sense, pottery should be thought of as a metamorphosed–
sedimentary rock whose main ingredients are clays to which tempering materials such as
shell, sand grit, etc. are sometimes added prior to firing at high temperatures. Clays are found
almost everywhere and their geological histories differ greatly. Generally, if the parent rock
contributions and weathering histories of two clay sources are sufficiently different, the
provenance postulate will apply4, 5.
The main components of clays (i.e., Al2O3 and SiO2) are generally present in amounts
well above 10 percent and minor impurities such as the oxides of Na, Mg, K, Ca, Ti, and Fe
are typically found in amounts between 1000 ppm and 5 percent. However, it is the trace
constituents – elements present at concentrations below 1000 ppm – whose presence in clays
is effectively accidental that usually provide the best information for provenance studies6.
In recent years a multidisciplinary research program was started between the Federal
University of Sergipe (UFS) and Research Institute of Nuclear and Energy (IPEN/CNEN-SP)
to study the ancient ceramist cultures from Xingó region, situated in Canindé do São
Francisco, Sergipe State, in the Northeast Brazilian (Figure 1). Recent studies conducted in
the area has showed the existence of an independent ceramist group without relation to the
ceramist group well established in the Brazilian Northeast, called Tupiguarani and Aratu 7.
Dating obtained by means of carbon-14 from skeletons has indicated that there is evidence of
human occupation 9,000 years before present in “Xingó” region. So this work aims to
contribute to the understanding of the Low São Francisco River occupation dynamics. This
study has done by means of the chemistry analysis of 76 samples ceramic fragments and one
clay sample from Justino site, main archaeological site situated in the area, using INAA.
EXPERIMENTAL
MATERIAL STUDIED
In this work, 76 ceramic fragments and 1 clay sample from Justino site were analyzed by
means of INAA: Cemetery A (25), Cemetery B (26), Cemetery (25), and one clay sample
collected near to Justino site. Although several chemical methods have been employed to
analyze pottery and clays, the analytical technique that has dominated pottery provenance
research from the late 1960s up to the present time has been INAA8–11.
Justino archaeological site is situated in Canindé do São Francisco, a city in the area of
São Francisco River, about 150 km from Aracaju, capital of Sergipe State, Brazil (Figure 1).
The fragments analyzed in this work are from vessels excavated during an archaeological
rescue project when the Hydroelectric “Xingó” Dam building was going to be inundated by a
large alluvial terrace in the margins of São Francisco River in the area of Canindé do São
Francisco, situated in the Brazilian Northeast.
Chronology studies about of the ceramist occupation at Justino site, accomplished
by thermoluminescence and radiocarbon dating, have showed chronology amplitude from
5.570 BP to 1.280 ±45 BP. According this study, the ceramist occupation at Justino site
corresponds for an oldest at Brazilian Northeast.
According laboratorial analysis, it was identified four human occupations at
Justino site, in different periods, which it was called cemetery A (1280 ± 45 – 2530 ± 70 BP),
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1o Simpósio Latino Americano sobre Métodos Físicos e Químicos em Arqueologia, Arte e Conservação de Patrimônio Cultural.
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cemetery B (2650 ± 150 – 3270 ± 135 BP), cemetery C (4790 ± 80 – 5570 ± 70 BP) and
cemetery D (approximately 8950 ± 70 BP). The first three cemeteries correspond to groups of
ceramist farmer and the last cemetery corresponds to hunter – collector.
The analysis of Justino site has permitted to acknowledge that archaeological groups from
Xingó practiced mortuary rituals in areas previously chosen and each individual it was chosen
different funeral complement with aim of define social structures of the ceramist groups
which lived in area. At Justino Cemeteries was identified a categorization of social
hierarchies, distinction between sexes and ages in the several buries at Cemeteries A, B and
C. But, theses distinction was not observed at Cemetery D12. Vergne (2004) has observed that
the associations between the vestiges and buries show characteristics of hunter – collectors
groups, which indicates changes from hunter – collector to ceramist culture, with more
evidence at Cemetery B. At cemetery A, these distinctions were observed with more clearness
to individual who are oldest.
SAMPLE PREPARATION AND STANDARD
Ceramic powder samples were obtained by cleaning the outer surface and drilling to a
depth of 1-2 cm using a tungsten carbide rotary file attached to the end of a flexible shaft,
variable speed drill. Depending on the thickness, 3 or 5 holes were drilled as deep into the
core of the fragment as possible without drilling through the walls. Finally, the powered
samples were dried in an oven at 105oC for 24 h and stored in desiccators.
Constituent Elements in Coal Fly Ash - NIST-SRM-1633b, were used as standard in
all analysis. The standard reference material Brinck Clay - NIST-SRM-679 was used to check
the analytical quality of the results The standard and the samples were dried in an oven at
105oC, the standards for 4 h and samples for 24 h and stored in a desiccator until weighing.
IRRADIATION AND RADIOACTIVITY MEASUREMENTS
About 100 mg of ceramics samples, and NIST-SRM-1633b were weighed in polyethylene
bags and involved in aluminum foil. Groups of 8 ceramic samples and two reference materials
were packed in aluminum foil and irradiated in the swimming pool research reactor, IEAR1m (IPEN/CNEN – SP) at a thermal neutron flux of about 5 x 1012 n.cm-2.s-1 for 8h.
Two measurement series were carried out using Ge (hyperpure) detector, model GX
2020 from Canberra, resolution of 1.90 keV at the 1332.49 keV gamma peak of 60Co, with S100 MCA of Canberra with 8192 channels. As, K, La, Lu, Na, Nd, Sm, U, and Yb were
measured after 7 days cooling time and Ba, Ce, Co, Cr, Cs, Eu, Fe, Hf, Rb, Sb, Sc, Ta, Tb,
Th, and Zn after 25-30 days. Gamma ray spectra analysis was carried out using the software
Genie 2000 NAA Procedure from Canberra.
STATISTICAL METHOD
OUTLIER DETECTION
Outlier data are points, in multidimensional space, which are far from the main mass
of datas, but their detection is challenging in higher dimensions, such as provenance study of
archaeological potteries.
On multivariate application, various methods for detecting outliers have been studied,
which are related, mainly, related to Mahalanobis distance13, 14. The well-known Mahalanobis
distance is defined for a sample x1, …, xn of n observations in the p-dimensional real space Rp
as
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

d 2  xi  T  C 1 xi  T 
t
1
2
,
for i=1, ..., n.
(Equation 1)
Where T and C are location and covariance estimators, respectively. In case of multivariate
normally distributed, the arithmetic mean and the sample covariance matrix are the best
choices. In this case, d 2 approximate a chi-square distribution  p2 with p degrees of freedom.
In generally, data points with d 2 higher than the cut-off value are considered as potential
outlier.
However, arithmetic mean and sample covariance matrix are sensitive with respect to
outlying observations. Thus, the Mahalanobis distance needs to be estimated by a robust
procedure. Several robust estimators to C and T, in Equation 1, have been proposed in the
literature, such as estimators of multivariate location and dispersion that include the minimum
covariance determinant (MCD)15, 16.
The aim of MCD is to find a subset of size h objects with the smallest determinant of
the covariance matrix15. As a compromise between robustness and efficiency, a value of
h  0.75n (n is the sample size) is frequently used. Using robust estimators of location and
scatter in the Equation 1 leads to the so-called robust distances (RDs). If squares RD for a
case is larger than  p2;0.98 , it can be declared a candidate outlier.
In this work, to identify outlier cases, the data set was submitted to principal components
analysis to reduction of the dimensionality of data set. Following reduction dimensionality, by
computing the RDs with MCD estimator, each pottery group from Justino site, it was possible
construct the ellipse corresponding to the squared Mahalanobis distance equal to  22;0.98 (often
called a tolerance ellipse). The observation found outside of the tolerance ellipse, in the space
established for the first two principal components, was considered outlier17.
PRINCIPAL COMPONENT ANALYSIS
To assist in the creation of compositional group in this work a principal component
analysis was performed on the INAA data, once PCA is a convenient way to capture and view
complex multidimensional data.
Principal components analysis (PCA) is a technique used to reduce multidimensional data
sets to lower dimensions for analysis. In PCA, the data set is transformed on the basis of
eigenvector method to determine the magnitude and direction of maximum variance of the
data set distribution18. By means of PCA is hoped that plots of the first few principal
components reveal the structure of data set, which facilitate quick identification of variables
responsible for differences between cases groups in compositional studies of archaeological
potteries. In addition, plots of two and/or three dimensions from PCA can be used to
recognition of compositional groups of potteries19.
CLUSTER ANALYSIS
Cluster analysis is a general term that applies to a variety of specific techniques but the
essential components are (a) a measure of the similarity-dissimilarity between specimens is
defined and (b) a clustering algorithm is specified that groups specimens on the basis of the
defined measure18. To illustrate the arrangement of the clusters produced by a clustering
algorithm a dendrogram, which is constitued by a tree diagram, is frequently used. In general,
cluster analysis is used to identify initial groups after which other techniques for group
refinement and classification are subsequently applied.
To identify initial groups of pottery from Justino site, it was performed a cluster
analysis using Ward’s Method and squared Euclidian distance20.
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DISCRIMINANT ANALYSIS
Discriminant Analysis was utilized in this work aiming to distinguish, statically, the
case groups defined as potteries from cemetery B and cemetery C. Discriminant Analysis is a
widely used multivariate statistical technique in Archaeometry to identify elements which are
most useful in discriminating between groups and graphically displaying the chemical
distinction between these groups.
Discriminant Analysis attempts to generate one or more linear combinations of the
discriminant variables. These discriminant functions are of the form
Di = λi1 x1 + λi 2 x 2 + ... + λip x p
Equation (2)
where Di is the score on discriminant function i, the λ’s is the weighing coefficients, and
the xp is the value of the p discriminant variables. Ideally, the discriminant scores for the cases
within a particular group will be fairly similar. At any rate, the functions are formed in such a
way as to maximize group separation21.
Before the application of Discriminant Analysis, a study to identify the outliers in the
data set was carried out by means of robust Mahalanobis distance.
DILUTION EFFECTS CORRECTION
After forming compositional groups, the concentration values for each sample were
corrected according to the dilution factor, which permit the decreasing of the spread in the
group. Dilution can be caused by different amount of additional components in a claybed or
by pottery-making practices resulting in different amounts of temper in ceramics made from
the same clay, which result in a decrease of all measured concentration values. The same
effect of a shift of all concentration values can be also technical results22.
A dilution or shift mathematically is a transformation of a vector of the original data

X 0 which is given simply by a multiplication of each component of the vector by the same

constant  , thus transforming the original data to the measured X by



Equation (3)
X 0  X  D( ) X 0
where the ‘dilution distortion matrix’ is given D( )   I , I being the m m identity matrix

and m is the number of measured elements. Considering a data point and Y a center point of
the group, both them can be diluted by different factors. Thus the values should be
transformed back to their original values (concentration values before dilution process). This
is done by applying the inverse of their dilution distortion matrices D 1 ( X ) and D 1 (Y ) to

and Y , respectively23.
Considering the modified Mahalanobis distance ( d 2 ) as the distance between a single


sample X and centroid of the group Y , d 2 is given by
 
 
1 t  
d 2 ( X ,Y ) 
( fX  Y )( f 2 S X  SY ) 1 ( fX  Y )
Equation (4)
m

where SY is a covariance matrix, S X an uncertainty matrix and f  Y which is called
X

dilution factor. By multiplying X by f , a correction takes place.
Under the assumption that a correction for dilution should bring together a data point


X and center point Y as close as possible, f can be calculated as solution of
 
 t   2
( fX  Y )( f S X  SY )( fX  Y )  0 .
Equation (5)
f


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

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A better resolution in grouping is achieved after dilution correction. All correction can be
done by using the program “Search Program”, which has been developed by Dr. Hans
Mommsen and his Archaeometry group at Bonn University. This program performs a number
of useful tasks in the grouping of pottery according to the element concentration data.
RESULTS AND DISCUSSION
ANALYTICAL CONTROL OF RESULTS
To evaluate the analytical process and to establish the chemical elements which can be
used in the data interpretation, the elemental concentrations for reference material Brick Clay
- NIST-SRM-679 were statistically compared with the data found in our laboratory. The
precision of several elements (La, Th, Sc, Fe, Eu, Ce, Zn, Hf, and Co) was better than 5% and
matched with the precision obtained by other authors. Some elements presented RSD
(Relative Standard Deviation) less than 10% (Nd, Rb, Sm, Ba, Sb, Ta, and Tb) and are similar
to those from the literature24. The interference 235U of fission in the determination of La, Ce
and Nd was negligible because U concentrations did not exceed 5 ppm and the rare earth
concentrations were not very low.
One of the basic requirements underlying the composicional characterization of the
archeological pottery is that analytical technique presents appropriate precision. Elements that
have low precision can reduce the discriminating effects of other well measured elements. In
this work all the elements with precision above 10% were considered for interpretation of the
results (Na, Lu, Yb, La, Th, Cr, Cs, Sc, Fe, Eu, Ce, Zn, Co, Ta and Hf)25. The Zn presented
RSD better than 10% but was excluded from the data set because its determination suffers
strong gamma ray interferences of 46Sc and 182Ta. The elements Co and Ta were eliminated
because their concentrations can be affected by tungsten carbides drills26, even though their
precision was smaller than 10%. The K and Sb were better than 10%, however they were
excluded because they presented 15% of missing values. Ce was removed from dataset
because samples showed high variability, which can be related with characteristics of ionic
exchange of the Ce with elements present in the clays27. Based on these screening criteria 11
elements: Na, Lu, Yb, La, Th, Cr, Cs, Sc, Fe, Eu and Hf were used for the interpretation of the
results.
STANDARDIZATION, OUTLIER STUDY AND DILUTION EFFECTS
CORRECTION
Initially, the results were transformed to log10 to compensate for the large magnitude
difference between the measured elements at the trace level and the larger ones. The log10
transformation data before a multivariate statistical method is common. One reason for this is
the belief that, within manufacture raw materials, elements have a natural lognormal
distribution, and that data normalization is desirable. Another reason is that a logarithmic
transformation tends to stabilize the variance of the variable and would, thus, give them
approximately equal weight in unstandardized multivariate statistical analysis28. After
logarithmic transformation the data set was submitted to outliers test by means of robust
Mahalanobis distance using minimum covariance determinant, where critical values were
obtained  22;0.98 . Considering the tolerance ellipse according  22;0.98 , 4 samples from Cemetery
A, 3 samples from Cemetery B and 2 samples from Cemetery C were considered outliers.
After obtaining the final database, all element concentrations for potteries from cemetery
studied were corrected according to their dilution factor. By means of Equations 4 and 5 and
by using “Search Program”23, means of dilution factor for São José, Saco da Onça and
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Curituba sites were obtained: 0.96 ± 0.04, 0.98 ± 0.07 and 0.91 ± 0.05, respectively.
Generally, dilution effects cause increase of dispersion in the compositional groups and,
consequently, in the probability of mistake classification. In Table 1 is displayed mean and
spread for Cemeteries A and B, before and after correction according dilution factors.
FORMATION OF THE COMPOSICIONAL GROUPS
Initially, to evaluate the dataset a Principal Component Analysis (PCA) were
accomplished. The PCA indicated that three first components account for the majority of the
total variance in the dataset, 74% of total variance. The Kaiser criterion was utilized to obtain
this number of principal components20. In agreement with the Kaiser criterion, 4 principal
components can be assumed to explain significantly the variability of the dataset.
Examination of space formed by first and second principal components showed that most
specimens appeared to fall into a single homogeneous compositional group, corresponding to
Cemetery B, and other group most widespread corresponding to potteries samples from
Cemetery C. The samples from Cemetery A appeared disaggregate and scatter in the space
formed by two first principal components (Figure 2). The high dispersion from potteries of
Cemetery A can be a result of cultural exchanges between ceramist group which occupied
Justino archaeological site in recent periods with others ceramist groups from Xingó area,
which influenced on the manufacture process of potteries.
In order to confirm existence of two different groups of ancient pottery fragment buried at
Justino site based on their chemical composition, corresponding to Cemetery B and C, a
Discriminant Analysis (DA) of the corrected concentration by dilution factor of 46 samples
from these cemeteries was accomplished. Figure 3 presents a bivariate plot of discriminant
function 1 versus discriminant function 2 showing that two main groups were separate by
function. Figure 3 illustrates that the pottery samples from each cemetery B and C from
Justino site are chemically homogeneous, since they concentrate in an ellipse with a
confidence of 95%. These results indicate that raw materials used to manufacture of potteries
are distinct or the chemical composition of clay paste was modified during its preparation by
ancient potters using a specific processing recipe .
Both chemical patters are compared in Figure 4, in which the concentration differences
Cemetery B minus Cemetery C are plotted as a bar diagram in units of the average spread
values. Most prominent are differences in Na, Lu, Yb, Sc, Fe and the Eu. It is possible to see
that Cemetery B is chemically different from Cemetery C, which suggests that a different
paste was used for these shreds.
According to variability presented for two cemeteries B and C in the Table 1 and Figure 3
can be seen that ceramic paste from Cemetery C is more heterogeneous than Cemetery B.
Once the Cemetery C of Justino site was occupied by an incipient ceramist group,
establishing a change from hunter – collector group to ceramist group, the variability of the
chemical composition of the pottery this cemetery can be consequence of the technological
evolution on the manufacture of the pottery in this period, indicating an experimentation
process to produce potteries. Nevertheless, in the period of occupation Cemetery C, the expert
craftsmen have detained know-how to produce potteries with some control of quality, manly,
of the homogeneity of the ceramic paste.
CONCLUSIONS
The INAA analysis of pottery from Justino site (Cemeteries A, B and C) was successful in
identifying distinct compositional groups from chemical composition of pottery. It was
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verified that samples from Cemetery C are characterized by higher dispersion, which can be
the result manufacture process. The compositional differences among potteries from site
studied can be understood in terms of cultural influences in the preparation of the ceramic
paste, changes in land use and organization of ceramic production or of the availability of raw
materials during distinct occupations in Justino area. Results from discriminant analysis
indicated that clay sample analyzed in this work was not used to prepare ceramic pastes in the
three sites studied. A systematic collection of clays in the region would reveal is raw material
sources; however, nowadays this archaeological site is submerged because this area is now
part of Xingó hydroelectric power station. The results obtained in this work provided
subsidies for formulation of hypothesis about the technological evolution of the people who
lived in Xingó area.
Acknowledgements
We thank Professor Dr. Hans Mommsen from Bonn University. We also thank the
International Atomic Energy (IAEA) for the fellowship, Conselho Nacional de
Desenvolvimento Científico e Tecnológico (CNPq) and Coordenação de Aperfeiçoamento de
Pessoal de Nível Superior (CAPES) for sponsoring this research. Special thanks to Museu
Arqueológico de Xingó (MAX) and Petróleo Brasileiro S.A (PETROBRAS) for providing
access to their collection and for giving logistical support.
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LASMAC 2007, São Paulo, SP, Brasil.
LASMAC2007
1o Simpósio Latino Americano sobre Métodos Físicos e Químicos em Arqueologia, Arte e Conservação de Patrimônio Cultural.
São Paulo, SP, Brasil, 11 a 16 de julho de 2007
MASP – Museu de Arte de São Paulo “Assis Chateaubriand”
CANINDÉ DO SÃO FRANCISCO
XINGÓ
FR
AN
CIS
CO
RIV
ER
BRAZIL
SOUTH
BAHIA
AMERICA
N
ALAGOAS
SÃ
O
SERGIPE
ATLANTIC
0
50 km
OCEAN
ARACAJU
Figure 1: Localization map of the study area
Tabela 1 – compositon Mean (M) for pottery from Justino (Cemeteries B and C). Values in ppm,
and spread in percentage of the average.
Cemetery B
Cemetery C
Without
With correction
Without
With correction
correction
(f=1,00 ± 0,03)*
correction
(f=0,90 ± 0,08)*
(M ± CV)
(M ± CV)
(M ± CV)
(M ± CV)
1,55 ± 12,79
1,53 ± 12,43
1,31 ± 23,65
1,27 ± 18,45
Na %
0,68 ± 33,22
0,65 ± 22,76
0,47 ± 39,44
0,44 ± 23,84
Lu
4,54 ± 34,48
4,32 ± 24,20
3,44 ± 47,50
3,16 ± 30,48
Yb
59,41 ± 24,18
58,13 ± 20,28
48,93 ± 40,44
45,69 ± 29,52
La
13,53 ± 37,78
13,55 ± 37,35
14,68 ± 53,58
15,27 ± 51,02
Th
37,96 ± 72,31
39,38 ± 71,44
27,91 ± 52,29
27,13 ± 45,41
Cr
6,71 ± 40,17
6,63 ± 39,91
4,77 ± 60,89
4,49 ± 59,23
Cs
17,57 ± 22,81
17,16 ± 18,68
12,91 ± 43,44
12,06 ± 31,58
Sc
5,99± 22,88
5,82 ± 14,29
4,44 ± 37,88
4,14 ± 22,82
Fe %
2,58 ± 22,03
2,51 ± 15,04
1,85 ± 50,61
1,70 ± 36,97
Eu
7,52 ± 19,88
7,42 ± 18,86
7,06 ± 36,18
6,71 ± 23,42
Hf
*f represent the mean of the dilution factor with spread
1.0
Principal Component 2 (16.27%)
Th
Cs
5
4
Principal Component 2 (16.27%)
3
B
2
D3 C
C
A
C
C
B BB
A CC
C
A
B
B
BB
AB A
BA C
AB
A A CB
C
BCBA
C
B
D4
B
AC
AB B A BCAC A
B
D2
D1AC
CC BCC
A
B
1
0
-1
-2
C
A
0.5
0.0
La
Hf
Lu
Yb
Eu
Sc
Cr
Na
Fe
-0.5
C
-1.0
C
-1.0
-0.5
0.0
0.5
Principal Component 1 (46.96%)
-3
A
A
-4
-5
-6
-10
-8
-6
-4
-2
0
2
4
6
8
Principal Component 1 (46.96%)
LASMAC 2007, São Paulo, SP, Brasil.
10
12
14
16
1.0
LASMAC2007
1o Simpósio Latino Americano sobre Métodos Físicos e Químicos em Arqueologia, Arte e Conservação de Patrimônio Cultural.
São Paulo, SP, Brasil, 11 a 16 de julho de 2007
MASP – Museu de Arte de São Paulo “Assis Chateaubriand”
Figure 2. Biplot of the first and second principal components showing two pottery groups,
Cemeteries B and C, and samples from Cemetery A dispersed in space.
6
Clay Volta
Cemetery B
Cemetery C
5
Discriminant Function 2
4
3
2
1
0
-1
-2
-3
-4
-6
-4
-2
0
2
4
6
8
Discriminant Function 1
distance/ave. spread
Figure 3. Linear discriminant analysis of the archaeological pottery samples from
Cemeteries B and C from Justino site. Ellipses represent 95% confidence.
3,0
3,0
2,5
2,5
2,0
2,0
1,5
1,5
1,0
1,0
0,5
0,5
0,0
0,0
-0,5
-0,5
-1,0
-1,0
-1,5
-1,5
-2,0
-2,0
-2,5
-2,5
-3,0
-3,0
Na
Lu
Yb
La
Th
Cr
Cs
Sc
Fe
Eu
Hf
Figure 4. Standardized differences (in units of the average spreads) of concentration
values of groups Cemetery B and Cemetery C for 11 elements, in order to compare the
chemical patterns.
LASMAC 2007, São Paulo, SP, Brasil.