Understanding the use of colorant materials throughout history is now the objective of multiple studies centered on the identification and characterization of these materials. The main objective of this study is to increase knowledge of the degradation pathways of indigo blue dye (Indigofera tinctoria) and the detection of degradation products. This will enable the identification of the dye on historical objects, even when it is present in a degraded state. To this end, different analytical techniques were used for the identification of indigo blue and its degradation products. Capillary electrophoresis with diode array detection (CE-DAD) and fluorescence spectroscopy were used for characterization and detection of the colorant and its degradation products caused by the aging process. Nuclear magnetic resonance (NMR) spectroscopy was used to confirm the presence of degradation products. The evaluation of color variations (lightness, chroma, and tone) in indigo blue on paper samples was made with colorimetric study, while the changes in indigo solutions were evaluated with UV-visible spectrophotometry. Additionally, changes in the alkalinity and acidity of the colorant were made with pH measurements. Lastly, the main agents responsible for the modifications that resulted in the production of degradation products of indigo blue were also identified. These methods were applied to historic samples from the Collection of Drawings, Maps, and Plans (sixteenth to nineteenth centuries) and to the thread used in the binding of a notarial record book (Registro Notarial de Torres) (fifteenth century) held by the Royal Chancery Archive in Granada (Spain). This paper provides deeper insights into the materials used in artworks and helps in the identification of indigo blue despite the degradation caused by external agents or by its natural aging process.

The palette used on a small painting on copper support, with the inscription “Boceto di Pablo Veronese” on the back, was characterized. Non-invasive techniques such as X-ray diffraction (XRD) and hand-held X-ray fluorescence (XRF) were proven to be highly effective for this. The objectives of the proposed work were twofold. On the one hand, the objective was the study, in situ, of the pigments of a painting on a copper support. On the other hand, it was to enrich the literature related to the study of paintings on metal supports, since few related studies are available despite the relatively large number of such 16th and 17th century paintings from Italy and Northern Europe. The results of the analysis showed a copper support with a base layer of gypsum mixed with ochre earths. Atop this layer is a sketch with lead white in the lighter areas and bone black in the darker shadow areas, suggesting that the artist performed a preliminary study of the luminosity of the scene. Finally, the upper or pictorial layer consists of a mix of pigments with some lead white to lower saturation and increase lightness, particularly evident in the flesh tones. The resulting palette thus includes lead white, vermilion, bone black, Naples yellow, and lazurite pigments. These results are compared to Veronese’s other paintings, as well as to those of certain contemporary artists, and the use of the resulting pigments in 16th and 17th century Italian painting techniques is discussed.

Indigo blue is a natural organic color from the Indigofera tinctoria plant. It is insoluble in water and does not require mordant to fix the color; therefore, due to its nature it can be considered as a pigment or dye. The identification of indigo in cultural heritage is very difficult due to the complexity of its chemical formula and the changes that it can undergo in certain conservation and exposition conditions. For this reason, characterization of possible degradation, transformation, and reaction processes is essential for its identification. In this study, multispectral imaging has been used for the first time as noninvasive technique to characterize the aging state of indigo blue using samples aged in a controlled climate chamber under extreme conditions of humidity, temperature, and light. The technique has proven to be very promising for this application, together with classification techniques based on machine learning approaches.