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” 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 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” 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), 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” 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 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” 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. 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” 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 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” 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 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” 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 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” 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. REFERENCES 1. Gebhard, R. Materials Analysis in Archaeology. Hyperfine Interact. 2003, 150 (1-4), 1 – 5. 2. Rice, P. M. On the Origins of Pottery. J. Archaeol. Meth. Theory 1999, 6 (1), 1 – 54. 3. Stark, M. T. Current Issues in Ceramic Ethnoarchaeology. J. Archaeol. Res. 2003, 11 (3), 193 – 242. 4. Weigand, P., Harbottle, G., Sayre, E.V. 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Radioanal. and Nuclear Chem. 244 (2000) 575. 25. 18. Munita, C.S., Paiva, R.P., Alves, M.A ., Oliveira, P.M.S., Momose, E.F. Contribution of Neutron Activation Analysis to archaelogical studies. J. Trace Microp. Techn. 2000, 18, 381-387. 26. Attas, M., Fossey, J.M., Yaffe, Y. Corrections for Drill-bit Contamination in Sampling Ancient Pottery for Neutron Activation Analysis. Archaeometry 1984, 26(1), 104-107. 27. NYAKAIRU, G. W. A., KOEBERL, C., KURZWEIL, H. The Buwambo kaolin deposit in central Uganda: Mineralogical and chemical composition. Geochemical Journal, 35 245 – 256, 2001. 28. Glascock, M. D., Neff, H., Vaughn, K. J. Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance. Hyperfine Interactions, 154, 95-105, 2004. 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.