Dataset Information

Near-infrared hyperspectral imaging to map collagen content in prehistoric bones for radiocarbon dating.

ABSTRACT: Many of the rarest prehistoric bones found by archaeologists are enormously precious and are considered to be part of our cultural and historical patrimony. Radiocarbon dating is a well-established technique that estimates the ages of bones by analysing the collagen still present. However, this method is destructive, and its use must be limited. In this study, we used imaging technology to quantify the presence of collagen in bone samples in a non-destructive way to select the most suitable samples (or sample regions) to be submitted to radiocarbon dating analysis. Near-infrared spectroscopy (NIR) that was connected to a camera with hyperspectral imaging (HSI) was used along with a chemometric model to create chemical images of the distribution of collagen in ancient bones. This model quantifies the collagen at every pixel and thus provides a chemical mapping of collagen content. Our results will offer significant advances for the study of human evolution as we will be able to minimise the destruction of valuable bone material, which is under the protection and enhancement of European cultural heritage and thus allow us to contextualise the valuable object by providing an accurate calendar age.

SUBMITTER: Malegori C

PROVIDER: S-EPMC10090164 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Near-infrared hyperspectral imaging to map collagen content in prehistoric bones for radiocarbon dating.

Malegori Cristina C Sciutto Giorgia G Oliveri Paolo P Prati Silvia S Gatti Lucrezia L Catelli Emilio E Benazzi Stefano S Cercatillo Silvia S Paleček Dragana D Mazzeo Rocco R Talamo Sahra S

Communications chemistry 20230411 1

Many of the rarest prehistoric bones found by archaeologists are enormously precious and are considered to be part of our cultural and historical patrimony. Radiocarbon dating is a well-established technique that estimates the ages of bones by analysing the collagen still present. However, this method is destructive, and its use must be limited. In this study, we used imaging technology to quantify the presence of collagen in bone samples in a non-destructive way to select the most suitable samp ...[more]

PMID: 37041241

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Project description:Collagen is the dominant organic component of bone and is intimately locked within the hydroxyapatite structure of this ubiquitous biomaterial that dominates archaeological and palaeontological assemblages. Radiocarbon analysis of extracted collagen is one of the most common approaches to dating bone from late Pleistocene or Holocene deposits, but dating is relatively expensive compared to other biochemical techniques. Numerous analytical methods have previously been investigated for the purpose of screening out samples that are unlikely to yield reliable dates including histological analysis, UV-stimulated fluorescence and, most commonly, the measurement of percentage nitrogen (%N) and ratio of carbon to nitrogen (C:N). Here we propose the use of collagen fingerprinting (also known as Zooarchaeology by Mass Spectrometry, or ZooMS, when applied to species identification) as an alternative screening method for radiocarbon dating, due to its ability to provide information on collagen presence and quality, alongside species identification. The method was tested on a series of sub-fossil bone specimens from cave systems on Cayman Brac (Cayman Islands), chosen due to the observable range in diagenetic alteration, and in particular, the extent of mineralisation. Six (14)C dates, of 18 initial attempts, were obtained from remains of extinct hutia, Capromys sp. (Rodentia; Capromyidae), recovered from five distinct caves on Cayman Brac, and ranging from 393 ± 25 to 1588 ± 26 radiocarbon years before present (yr BP). All of the bone samples that yielded radiocarbon dates generated excellent collagen fingerprints, and conversely those that gave poor fingerprints also failed dating. Additionally, two successfully fingerprinted bone samples were screened out from a set of 81. Both subsequently generated (14)C dates, demonstrating successful utilisation of ZooMS as an alternative screening mechanism to identify bone samples that are suitable for 1(4)C analysis.

Project description:The trace element boron (Boron, B) is an important factor in crops' development, pollination, and fertilization. Available boron (AB) in soil is the main source of boron nutrient absorption for crops. Rapid detection of AB is of great significance for crop nutrition diagnosis, soil testing and fertilization, precision agriculture development, scientific production management, and guarantee of stable yield and high quality. In this study, we propose a new method to predict soil available boron content using handheld nonimaging hyperspectroscopy in the visible-near-infrared range (350-1655 nm). As boron content is one of the fewest soil chemical elements, a rapid and accurate method has yet to be developed to detect and quantify the soil available boron. Visible-near-infrared ray (VIS-NIR) spectroscopy is widely utilized in the detection and quantification of soil available nutrients. There is, however, scant research on the detection of soil boron based on NIR data, and the performance of current regression model is still far from satisfactory. Our soil samples were collected from southern Anhui, China, with their NIR spectroscopy examined and the NIR data pretreated by 29 transformations and modeled with 10 regression algorithms. Of all the tested methods, SVM_RBF, BPNN, and PLS_RBF algorithms demonstrated the best performance and gave 0.80∼0.82 coefficient of determination value. At the same time, Random Forest algorithm (RFA), Successive Projection Algorithm (SPA), and Variable Importance in Projection (VIP) were used to extract the spectral characteristic wavelength data of soil available boron, and then the characteristic wavelength data were modeled with three regression algorithms: SVM_RBF, PLS_RBF, and BPNN. A comparative analysis of the prediction performance (R 2, RPD, RMSE, and RPIQ) of the models established at the full band showed that the RFA-MSC/BPNN model achieved the best performance. Compared with the best full-wavelength model DT/SVM_RBF, the test set achieved a 3.06% increase in R 2, a 7.12% drop in RMSE, a 7.71% gain in RPD, and a 7.78% increase in RPIQ. Our work sheds lights on how to achieve rapid quantification of the soil available boron concentration.

Project description:Collagen glue has been used for nearly two centuries to consolidate bone material, although its prevalence in museum collections is only now becoming visible. Identifying and removing collagen glue is crucial before the execution of any geochemical or molecular analyses. Palaeolithic bone objects from old excavations intended for radiocarbon dating were first analysed using ZooMS (Zooarchaeology by Mass Spectrometry) to identify the animal species, however peaks characteristic of both cattle and whale were discovered. Two extraction methods for ZooMS were tested to identify the authentic animal species of these objects, which revealed that these were originally whale bone objects that had been consolidated with cattle collagen glue. This is the first time animal collagen glue has been identified in archaeological remains with ZooMS, illustrating again the incredible versatility of this technique. Another technique, Fourier Transform Infrared Spectroscopy in Attenuated Total Reflectance mode (FTIR-ATR), was also tested if it could rapidly identify the presence of collagen glue in archaeological bone material, which was not the case. Two other cleaning methods were tested to remove bone glue contamination prior to radiocarbon dating, along with two modified collagen extraction methods for ZooMS. These methods were applied to bone blank samples (FmC = 0.0031 ± 0.0002, (n = 219), 47 336 ± 277 yr BP) that were experimentally consolidated with collagen glue and to the Palaeolithic bone material (ca. 15 000 and 12 000 yr BP). The experimental bone blanks produced excellent 14C ages, suggesting the cleaning methods were successful, however the 14C ages for some of the Palaeolithic material remained too young considering their contextual age, suggesting that the collagen glue contamination had most likely cross-linked to the authentic collagen molecule. More research is needed in order to gain a deeper understanding of the occurrence and elimination of cross-linked collagen-based glues in material from museum collections.

Dataset Information

Near-infrared hyperspectral imaging to map collagen content in prehistoric bones for radiocarbon dating.

Publications

Near-infrared hyperspectral imaging to map collagen content in prehistoric bones for radiocarbon dating.

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