Revealing and cleaning of an onion layer: scientific Insights into the Restoration of Giacomo Balla’s "Ritratto d’uomo / Eugenio Riva"

Revealing and cleaning of an onion layer: scientific Insights into the Restoration of Giacomo Balla’s "Ritratto d’uomo / Eugenio Riva" | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Revealing and cleaning of an onion layer: scientific Insights into the Restoration of Giacomo Balla’s "Ritratto d’uomo / Eugenio Riva" Andrea Macchia, Tilde De Caro, Marcello Colapietro, Paola Carnazza This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5633755/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The restoration of Giacomo Balla’s Ritratto d’uomo / Eugenio Riva has unveiled unexpected insights into the intersection of historical restoration practices and modern scientific techniques. This study documents the discovery and analysis of onion residues on the painting's surface, attributed to a mid-20th-century cleaning attempt. Leveraging cutting-edge analytical tools—such as FTIR ATR spectroscopy, SEM/EDS, and UV imaging—researchers explored the chemical and morphological effects of this unconventional treatment. Additionally, the article highlights innovative solutions, including enzymatic cleaning formulations and polar solvent systems, which were employed to safely restore the artwork. This multidisciplinary approach not only restored the painting’s aesthetic coherence but also contributed to the broader understanding of restoration challenges posed by historical interventions onion polysaccharides paintings cleaning green solvents enzyme Giacomo Balla Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Figure 21 Figure 22 1. Introduction This study focuses on Giacomo Balla’s Ritratto d’uomo / Eugenio Riva (“Man Portrait / Eugenio Riva,” 1900), a work created during his Divisionist period, a phase when Balla was honing his mastery of pointillist techniques to depict fine textures and subtle light effects [ 1 ]. Balla (1871–1958), a groundbreaking figure in Italian art, transitioned from realism and neo-impressionism to Futurism, greatly influencing the development of 20th-century modernism. Born in Turin and later residing in Rome, Balla was initially immersed in a cultural scene shaped by humanitarian socialism and scientific positivism. His early works, such as La fidanzata al Pincio (“Girlfriend at Pincio,” 1902) and Ritratto di signora all’aperto (“Portrait of a Lady in the Open Air,” 1903), illustrate his commitment to realism and Divisionist techniques, characterized by brushstrokes that capture nuanced light effects [ 2 ]. Balla’s artistic trajectory took a significant turn in 1910 when he embraced the Manifesto dei pittori futuristi and the Manifesto tecnico della pittura futurista. This marked the start of an experimental phase driven by themes of movement, dynamism, and avant-garde aesthetics [ 3 ]. During this period, he produced works like Compenetrazioni iridescenti (“Iridescent Interpenetrations”) and Velocità astratte (“Abstract Speed”), gradually abandoning Divisionist techniques in favor of industrial materials that aligned with the Futurist vision of modernity [ 4 – 7 ]. Archival records from the National Gallery of Modern and Contemporary Art in Rome indicate that Ritratto d’uomo underwent partial cleaning in the 1960s to remove a degraded, food-based residue that had darkened significantly. However, this cleaning, conducted with solvents, proved too aggressive for the thin paint layer, causing bleaching in the treated area on the right side (Fig. 1 ). Historically, restoration practices often included food-based materials—such as breadcrumbs, potatoes, and onions—to polish and brighten polychrome surfaces. Onions were particularly popular due to their acidic and polysaccharide-rich properties, which enhanced surface gloss but also posed risks of abrasion and residue retention on paint layers [ 8 – 11 ]. Polysaccharides from onions, such as arabinoxylans, exhibit distinct properties compared to cellulose, explaining their solubility in organic solvents and their impact on conservation challenges [ 12 ]. Cellulose is a linear polymer composed of β-(1,4)-D-glucopyranose units, forming tightly packed, crystalline structures through extensive hydrogen bonding. This regularity and crystalline organization render cellulose highly insoluble in most solvents [ 13 ]. In contrast, onion polysaccharides are characterized by branched structures, often incorporating arabinose side chains. These branches disrupt the structural regularity of the polymer and prevent the formation of tightly packed crystalline domains. As a result, the intermolecular hydrogen bonding is significantly weakened, enabling organic solvents to penetrate and interact more effectively with the polysaccharide chains [ 14 ]. Additionally, the branched structure of onion polysaccharides increases the number of exposed functional groups, creating more interaction points for organic solvents. The reduced "excluded volume" of these branched chains compared to linear polysaccharides of similar molecular weight further enhances solubility [ 15 – 17 ]. These properties explain why the polysaccharides in onion-based residues may interact strongly with paint layers, particularly through their functional groups, complicating removal with traditional aqueous or enzymatic methods. Since the 1970s, enzymes have gained popularity among conservators, initially in paper conservation and gradually in other fields. Hydrolytic enzymes, or hydrolases, are particularly valued for their ability to catalyze the hydrolysis of proteinaceous, polysaccharide, and lipid-based materials that can alter the appearance and structure of artworks [ 18 ]. Amylases, for example, target α-(1–4) glucosidic bonds in starch, enabling the effective removal of starch-based adhesives without affecting cellulose. α-Amylases cleave each α-(1–4) bond to progressively degrade the starch, while β-amylases target alternate bonds, breaking down the polymer into shorter starch fragments [ 19 ]. Amylase is an enzyme that hydrolyzes glycosidic bonds in polysaccharides, acting on both branched and linear structures with efficiency varying depending on the type of amylase. Alpha-amylase, an endoenzymatic enzyme, randomly breaks α-1,4 bonds within the chains, making it effective on both branched substrates like amylopectin, where it generates short oligosaccharides, and linear ones like amylose, which it degrades into maltose and linear dextrins [ 20 ]. Beta-amylase, an exoenzymatic enzyme, is more specific to linear substrates, cleaving maltose from the non-reducing ends but is ineffective at α-1,6 branching points [ 21 – 22 ]. Gamma-amylase, although less common, can hydrolyze both α-1,4 and α-1,6 bonds, enabling it to act on both types of structures, though with a weaker preference for linear substrates compared to the other isoforms [ 23 ]. However, using enzymes on thin polychrome paint layers presents challenges, as even amylases, could cause over-wetting or penetrate excessively into delicate paint layers. Enzymatic activity that is not carefully controlled might weaken or alter the paint structure. Additionally, enzymes such as amyloglucosidases and pullulanase, which act on both α-(1–4) and α-(1–6) linkages, may leave residues within paint layers, potentially complicating future conservation efforts [ 24 – 27 ]. Given these risks, enzyme-based applications on artworks are often conducted with gel supports that can limit the enzyme's cleaning action. The necessity of a water-based medium for enzyme use can further exacerbate risks for sensitive materials [ 28 ]. Therefore, this study investigates alternative methods to enzymatic treatments for safely removing the onion-based layer from the painting. While enzymes align well with green chemistry principles, their application in restoration may not be ideal due to the sensitivity of certain painted surfaces. A multi-analytical approach was employed to confirm the onion-based nature of the residue, using Fourier-transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM/EDS) to determine the composition and thickness of the paint layers. Additional analyses, including multispectral imaging (VIS, UV 365 nm, IR 850 nm), digital microscopy, and X-ray fluorescence (XRF), were used to assess the painting’s state of conservation and Balla’s palette, minimizing interactions between selected solvents and the paint layer. These analyses revealed significant bioactive onion compounds, including polysaccharides, sulfur-containing compounds (such as onion in A and cysteine sulfoxides), and phenolic compounds like rutin and quercetin [ 29 – 32 ]. Due to the polarity and strong bonding of these compounds with the paint layers, removal typically requires solvents such as ethanol or ethyl acetate, commonly used in other fields [ 33 , 34 ]. This study instead explores greener, safer alternatives, choosing products that align with sustainable practices in cultural heritage preservation while safeguarding the integrity of the original paint layers. In conclusion, this research offers new insights into the unconventional use of onions in historical cleaning techniques—documenting, for the first time, this method applied to a painting—and presents a pioneering approach to exploring alternative green cleaning solutions to the enzymatic method. 2. Materials and Methods 1. Multi-Analytical Approach for Residue Identification A multi-analytical approach was employed to confirm the onion-based composition of the residue, combining optical microscopy (OM), Fourier-transform infrared (FT-IR) spectroscopy in Attenuated Total Reflectance (ATR) mode and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS). • Digital Microscopy was performed using a DinoLite AM411-FVW digital microscope at 40X and 220X magnifications in visible and UV light, targeted surface analysis was conducted to identify areas of interest and select sampling locations for the invasive analysis. FT-IR ATR identified specific organic compounds indicative of onion, while SEM-EDS provided detailed data on the elemental composition and morphology of different paint layers and residues, enabling precise analysis of layer thickness and surface structure. Four samples (Fig. 1 ) were taken from the artwork with the following objectives: a) Sample S1, collected with the aim of isolating only the "onion" layer from the painting surface, was analyzed using SEM/EDS and FT-IR ATR to confirm the presence of onion residues on the surface. b) Three stratigraphic samples were collected from the painting’s edges: sample S2 from the upper-right, sample S3 from the upper-left, and sample S4 from the bottom-right. Sample S2 included a greyish ground layer and canvas; sample S3 contained three paint layers; and sample S4 consisted of the pictorial ground layer with traces of additional paint layers. These samples underwent SEM-EDS analysis to examine their stratigraphic composition in detail. The FT-IR spectra were acquired with a Nicolet Summit FTIR spectrometer equipped with an Everest™ Diamond ATR accessory, using a resolution of 8 cm⁻¹ and 32 scans per sample. SEM-EDS analysis was conducted on samples 2, 3, and 4 to assess their elemental composition. Sample 1 was analyzed specifically to capture high-resolution images of the morphology and surface structure of brownish particles present on untreated areas. A Tescan microscope with INCA 2000 EDS was employed in low vacuum mode (15 Pa) and an electron acceleration voltage of 30 kV, eliminating the need for sample pre-treatment. 2. Additional Analytical investigations Additional analyses, including multispectral imaging (VIS, UV 365 nm, IR 850 nm) and X-ray fluorescence (XRF), were conducted mainly to evaluate the state of conservation and to analyse Balla’s palette. These techniques enabled a comprehensive examination of the painting’s materials while minimizing potential interactions with solvents and cleaning agents. Multispectral Imaging: This technique captured images of the artwork across three spectral bands—visible (VIS), ultraviolet (UV), and near-infrared (NIR-MIR). Photographic documentation under visible light (400–750 nm) provided a baseline for assessing the overall technique and identifying constitutive materials. UV fluorescence imaging highlighted surface conditions, such as varnish layers, prior retouches, or other applied materials. NIR-MIR infrared reflectography allowed for the identification of preparatory sketches, alterations, and previous restorations. The imaging was conducted using a Madatec Samsung NX500 28.2 MP BSI CMOS camera, with UV lighting at 365 nm. Fluorescence emissions were captured with HOYA UV-IR cut and Yellow 495 filters, while IR reflectography utilized an 850 nm filter. X-Ray Fluorescence (XRF): XRF analysis on 18 points provided elemental characterization of the paint materials. A portable XRF instrument with a tungsten X-ray source and a Peltier-cooled silicon drift detector (Amptek MCA 8000A) was used, yielding a resolution of 140 eV at 5.9 keV (Mn Kα). XRF analyses were conducted at 38 kV and 350 µA, capturing K-lines for elements (Z = 12–52) and L-lines for elements (Z > 35). Data were normalized to the highest peak and analyzed using PyMCA software to determine the relative concentrations of identified elements. 3. Cleaning Tests To dissolve the onion-based components identified in the residue, several cleaning solutions were tested, including those derived from literature and commercially available products. Each solution was applied for a consistent duration of 1 minute (Fig. 1 , area C): Deionized water Polar Rescue in Klucel® G (5 wt%) Nanorestore Cleaning® Polar Coating S (containing 1-pentanol, ethyl acetate, and propylene carbonate) Amylase (1 wt% in deionized water) Amylase (1 wt% in deionized water, thickened with Klucel® G 5 wt%) Nasier C03 (a stabilized enzyme-based hydrogel) Among these, Nasier C03, amylase, and amylase in Klucel® G offered selective removal through targeted enzyme-based actions capable of breaking down polysaccharides [ 35 – 37 ]. Nanorestore Cleaning® Polar Coating S and Polar Rescue gel are solvent-based systems featuring low-toxicity, eco-friendly organic solvents. Nanorestore contains anionic surfactants in a blend of 1-pentanol, ethyl acetate, and propylene carbonate, developed by CSGI for removing natural and synthetic polymers with reduced solvent content. Polar Rescue, developed by Lab4green, gel includes anionic surfactants and acetal, gelled with Klucel® G to limit solvent spread on the paint surface [ 38 , 39 ]. 5. Evaluation of Cleaning Efficacy The cleaning efficacy of each solution was assessed using a DinoLite AM411-FVW digital microscope at 40X and 220X magnifications, observing the surface before and after cleaning. Criteria included removability, interactions with the original paint layers, and the gradualness of the cleaning process. Spectrocolorimetric analysis was performed pre- and post-cleaning to detect any color discrepancies in treated areas. Measurements were taken with a Y3060 3nh spectrophotometer using a D65 illuminant and 8 mm aperture in SCI mode over the 400–700 nm range. Each area was measured three times to minimize uncertainty, and color differences (∆E*) were calculated based on the Euclidean distance between color coordinates: $$\:\varDelta\:E=\sqrt{{\left({L}_{2}-{L}_{1}\right)}^{2}+{\left({a}_{2}-{a}_{1}\right)}^{2}+({b}_{2}-{b}_{1})}$$ This calculation provided quantitative data on any color changes following the cleanings treatments. Furthermore, FTIR spectroscopy in ATR mode was employed to analyze the residue left after cleaning. For each cleaning system used, except for the amylase in Klucel G, the coton swab utilized for cleaning was dried at 60°C prior to analysis by placing it in contact with the diamond of the instrument. The spectra were collected under the same operational conditions previously described, using the Summit Pro by Thermo Scientific as the measuring instrument. 6. Figure 1 and cleaning of painting Figure 1 . “Ritratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: areas analyzed by XRF (green “1–18”); sampling areas (yellow “S1-S4”); cleaning tests made with the proposed formulations (red “CT”). The system that proved to be the most effective during the experimentation was the 1% amylase solution gelled with Klucel® G (5 wt%), which was ultimately used to clean the entire painting. The cleaning agent was applied to the surface of the painting for a duration of one minute, with treatment focused on 4x4 cm sections at a time. To facilitate the removal of excess gel, two layers of Japanese paper were placed between the application and the painting surface. 3. Results 3.1 Multi-analytical approach for residue identification a) Optical Microscopy Regarding the artist’s technique, optical microscopy analyses revealed the use of briskly applied, juxtaposed brushstrokes to create vivid visual effects (Figure 2a-b). The uncleaned surface, untouched during the 1970s, is covered by a homogeneous brownish layer (Figure 3a-b), while the cleaned surface appears brighter but shows residues from the cleaning treatment (Figure 4a-b). The pictorial layer, particularly in the top-left area, appears remarkably thin, with the underlying canvas visible in several regions. This characteristic is even more evident on the right side, which underwent cleaning in the 1960s, suggesting that the restoration treatment carried out at that time caused partial abrasion of the paint layer. A comparison between untreated areas and those cleaned in the 1960s indicates that the cleaning process scrubbed the color layer but failed to remove the brownish particles (Figure 5a-b). b) SEM/EDS The surface morphology of Sample S1, observed using SEM analysis in COMBO mode (backscattered and secondary electrons), is shown in Figure 6. The image reveals a vegetal tissue containing fragments with high molecular weight elements, identifiable by their bright contrast. The tissue structure closely resembles onion tissue, as described by Adeola et al. [22]. The EDS spectrum of the tissue indicates an elemental composition consistent with onion residues, including potassium (K), sulfur (S), and calcium (Ca) (Figure 6, Table 1) [40]. The paint fragment adhered to the onion layer reveals the presence of iron-based aluminosilicate pigments, commonly known as red earth pigments, identified by the concurrent presence of iron (Fe), aluminum (Al), and silicon (Si). Additionally, cadmium-based pigments, likely Cadmium Yellow/Orange, were detected through the presence of cadmium (Cd). The analysis also shows a high lead (Pb) content, indicative of Lead White, a pigment likely used in the ground layer of the painting, as well as zinc (Zn). Table 1. EDS results acquired on sample n. 1. All results in weight%. SD=±0.2 Spectrum Al Si S Cl K Ca Fe Zn Cd Pb Spectrum 1 - - 24.8 8.0 10.9 8.8 - 47.5 - - Spectrum 2 2.7 7.2 - - - 1.4 7.0 10.4 5.2 66.1 The SEM image acquired from Sample S2 (Figure 7) reveals the complete stratigraphy of the painting. Beneath the "onion" layer lies a composite layer consisting of the pictorial layer and the ground layer, with a thickness ranging from 5 to 20 µm ± 3 µm, below which the canvas is visible. EDS analysis (table 2) of the "onion" layer confirms the elements previously identified in the study of Sample 1. The analysis of the pictorial surface identifies the presence of iron (Fe) as a possible chromophore contributing to the brown tonality, along with silicon (Si) and aluminum (Al). The ground layer is characterized by a high concentration of zinc (Zn) and, unlike Sample 1, the absence of lead (Pb). This finding aligns with Balla's documented use of Zinc White to create a priming layer on the canvas [40]. The presence of lead, on the other hand, is associated with Lead White, used to desaturate the chromatic layers of the composition [41]. Table 2. EDS results acquired on sample n. 2. All results in weight%. SD=±0.2 Spectrum C O Mg Al Si S Cl K Ca Ti Fe Zn Spectrum 1 35.0 25.6 - - 0.5 0.5 0.3 - 2.0 - - 36.2 Spectrum 2 51.7 24.8 0.8 2.3 6.8 0.7 0.2 - 1.8 0.1 1.0 9.9 Spectrum 3 38.0 19.5 - - 1.0 0.6 - - 2.3 - - 38.5 Spectrum 4 - 75.5 - - 3.8 2.9 - 1.4 1.7 - 3.7 11.0 Sample S3 was divided into two fragments. The first fragment was analyzed at the surface to identify the chromophores responsible for the red coloration. EDS analysis (table 4) revealed the presence of iron (Fe) and mercury (Hg), both chromophores of red pigments. The high lead (Pb) content corresponds to the use of Lead White as a pigment, while cadmium (Cd) indicates the presence of a yellow pigment. Spectra 1 and 4 showed elevated levels of iron, again in conjunction with aluminum (Al) and silicon (Si). However, Spectrum 1 exhibited a higher concentration of Fe, Si, and Al, along with mercury (Hg), suggesting a mixture of red pigments including Cinnabar (HgS). In contrast, Spectrum 4 displayed higher levels of zinc (Zn), lead (Pb), and calcium (Ca), likely indicative of the presence of Zinc White and Lead White, used to adjust the tonality of the red earth pigments. Table 4. EDS results acquired on the first fragment of sample n. 3. All results in weight%. SD=±0.2 Spectrum C O Na Al Si K Ca Fe Zn As Cd Hg Pb Spectrum 1 - 41.1 1.6 7.0 9.6 1.3 0.7 8.4 2.5 - - 3.6 24.4 Spectrum 2 - 34.0 - 1.3 2.1 - - 2.9 3.7 - 3.7 - 52.2 Spectrum 3 44.2 29.4 - - 0.3 - 0.9 - 25.1 0.3 - - - Spectrum 4 - 43.8 - 1.2 2.0 0.9 2.8 3.7 12.9 - - - 32.7 The second fragment of Sample S3 provides insight into the complete stratigraphy of the painting. The SEM image (figure 9) reveals surface areas with varying elemental contrasts. The white-contrast regions are characterized by the presence of lead (Pb), which is also detected by EDS analysis (table 5) in the ground layer, confirming the thinness of the paint film, measured at approximately 10 µm ± 2 µm in the SEM image. The presence of calcium (Ca) appears to be associated with sulfur (S), suggesting the use of calcium sulfate. This compound may function either as a filler for pigments or as a substrate for dyes. Table 5. EDS results acquired on the second fragment of sample n. 3. All results in weight%. SD=±0.2 Spectrum C O Na Mg Al Si S Cl K Ca Fe Zn Pb Spectrum 1 - 56.9 - 1.9 2.4 4.2 4.8 1.2 0.6 5.9 0.7 21.5 - Spectrum 2 - 46.9 3.0 - 1.4 2.9 3.9 3.4 1.4 2.0 1.6 2.8 30.7 Spectrum 3 28.8 25.2 - - 0.5 1.5 - - - 0.4 1.7 3.4 38.4 Spectrum 4 - 31.0 - - 1.7 3.5 - 1.1 0.9 0.9 3.2 2.3 55.4 Spectrum 5 26.3 5.3 - - 0.5 0.9 - - - 0.2 0.3 66.5 - The SEM image (figure 10) acquired from Sample S4 reveals areas with different elemental contrast. EDS analysis (table 6) differentiates these regions based on the content of calcium (Ca) associated with magnesium (Mg), aluminum (Al), silicon (Si), and sulfur (S), as well as the presence of iron (Fe). This result suggests that the dark layer is attributed to a blue iron-based compound, while the other elements indicate the "mixture" used to produce this pigment. Spectra 2 and 4 clearly identify Zinc White in the ground layer (Figure 14, Table 6). Table 6. EDS results acquired on sample n. 4. All results in weight%. SD=±0.2 Spectrum C O Mg Al Si S Cl K Ca Fe Zn Spectrum 1 0.0 56.7 1.1 2.8 6.6 7.9 3.3 2.7 7.9 0.7 10.2 Spectrum 2 28.4 24.6 0.3 0.3 0.5 1.3 44.6 Spectrum 3 0.0 48.3 1.5 2.6 4.0 4.4 2.8 0.8 5.2 0.6 29.9 Spectrum 4 47.4 13.5 0.2 39.0 c) FTIR -ATR FT-IR analysis in attenuated total reflection (ATR) mode was performed on Sample n. 1 to characterize the brownish particles observed in the uncleaned areas. The resulting spectra were compared to those obtained from an onion layer applied on a commercial canvas mockup (Figure 11). The mockup's onion layer exhibited residues identical to those found on the uncleaned areas of the painting, untouched during the 1960 restoration. A comparative analysis of the FT-IR ATR spectra from Sample n. 1 and the mockup demonstrated a striking similarity, confirming the presence of an onion extract-based layer. The spectral features between 1800 and 750 cm⁻¹ correspond to key biochemical and macronutrient components of onions. Both spectra showed the OH stretching band of hydroxyl groups at 3289 cm⁻¹, CH stretching of methylene groups at 2849 and 2916 cm⁻¹, CH₃ asymmetric deformation at 1405 cm⁻¹, and OH bending at 1365 cm⁻¹ [42–44]. Notable peaks at 1734, 1608, and 1008 cm⁻¹ were attributed to the ester carbonyl group stretch (C=O), aromatic ring stretching (C=C) of phenyl groups, and vibrational frequency of carbohydrate –CH₂OH groups, respectively. A minor band at 1255 cm⁻¹ was associated with amide III (random coil) vibrations, indicative of proteins [45-47]. 3.2 Additional analytical investigations Additional XRF analysis and multispectral imaging were performed to confirm the presence of previous restorations prior to cleaning testing, as well as to examine the consistency of the pigment palette with literature references. a) Multispectral Imaging: This technique gave excellent visual record, indicating any deviations or overpaint that could suggest previous interventions. Under visible light, the painting revealed thin paint layers characterized by the alternating use of colors to achieve a vivid and dynamic effect, a hallmark of the Divisionist style (Figure 12). UV fluorescence imaging highlighted chromatic variations with intense fluorescence in specific areas, such as the complexion of the cheeks and the grey background (Figure 13). The cheeks exhibited a pink-orange fluorescence, while the grey background emitted a green-yellowish fluorescence. The latter was especially evident in regions of paint loss, such as along the collar’s edge, the painting's perimeter, and some white brushstrokes on the figure's face and hair. This emission was likely attributable to the presence of zinc white. In contrast, the absence of fluorescence in the white pigment of the collar indicated the use of a different pigment, most likely lead white [48]. Additionally, UV imaging detected a non-fluorescent substance on the left side of the painting, confirming the absence of fluorescent synthetic or natural varnishes, such as terpenoid, acrylic, or urea-aldehydic resins, which are typically used as protective coatings [49–51]. Infrared reflectography, commonly employed to examine subsurface layers, including compositional changes and preparatory sketches, relies on the ability of near-infrared radiation to penetrate thin paint layers and reflect from non-absorbing media. It is absorbed by carbon-based or other absorbing materials like underdrawings [52,53]. However, the IR analysis did not reveal significant compositional changes or preparatory sketches. This suggests that the artist did not employ a detailed underdrawing but instead directly applied swift, vibrant brushstrokes to define both the figure and the background (Figure 14). b) EDXRF (Energy Dispersive X-ray Fluorescence): This technique enabled a non-invasive elemental characterisation of the pigments, guaranteeing their alignment with known materials and discovering any anomalies due to previous restoration efforts. XRF analysis provides excellent insights on the chemical composition of the pigments used in painting, giving a complete understanding of the artist's palette and technique. (table 7). The ground layer, observed in the upper-left white-grayish region, was identified as being put straight to the canvas, unaffected by subsequent paint layers. The spectrum obtained in this area revealed a significant presence of zinc (Zn), likely from Zinc White, which is a characteristic feature of Balla’s works. Minor traces of calcium (Ca), possibly used as a filler in the form of calcium carbonate or calcium sulfate, along with iron (Fe) and copper (Cu), were also detected. The presence of Cu suggests the use of a black pigment, possibly tenorite (CuO), to darken the white base. In other areas of the painting, the reddish and blue spots exhibited a complex mixture of pigments. These regions showed significant amounts of iron (Fe), mercury (Hg), and lead (Pb), with traces of cobalt (Co) and chromium (Cr). Such findings suggest the use of ochers (e.g., red ocher Fe 2 O 3 ), cinnabar (HgS), and Lead White (2PbCO 3 ·Pb(OH) 2 ) as primary components, while cobalt blue (CoAl 2 O 4 ) and chrome-based pigments (e.g., Chrome Oxide Green Cr 2 O 3 ) were likely employed to adjust the hues. Higher concentrations of mercury and lead in certain areas, compared to others, indicate the deliberate use of Lead White as a lightening pigment. In contrast, cobalt was predominant in the light-blue areas, with a notable presence of zinc and lead suggesting the use of Zinc White and Lead White to lighten the hue. Prussian Blue (C 18 Fe 7 N 18 ) was detected in the darker blue regions, along with cobalt blue and traces of barium sulfate, likely used as a filler. Green areas revealed high levels of chromium, confirming the presence of Chrome Oxide Green. This pigment was particularly prominent in the green bow tie and, to a lesser extent, in the man’s jacket, where it appeared combined with Prussian Blue and cobalt blue. In the brown regions, the analysis detected only zinc, pointing to the use of Zinc White for the background, with the absence of other characteristic elements suggesting that an organic pigment was likely responsible for the brown coloration. Cadmium was found exclusively in the orange areas, indicating the presence of Cadmium Yellow or Cadmium Orange, often in combination with cinnabar and red ocher. In the red areas, the predominance of iron and the comparatively lower mercury levels suggest a greater reliance on ocher rather than cinnabar. The pink regions, such as the cheeks, showed no characteristic elements, suggesting the use of an organic pigment, likely a red lake, consistent with the pinkish fluorescence observed under UV light and documented in other works by Balla [54]. Similarly, the nostril displayed a mixture of cinnabar, ocher, Zinc White, and Lead White. The white collar was characterized by the exclusive use of Lead White, in contrast to the green-yellowish fluorescence of the surrounding white background, which indicated the presence of Zinc White. This distinction was further supported by UV imaging, highlighting Balla’s intentional use of different white pigments to achieve specific effects. Overall, the results of the XRF analysis, in conjunction with other techniques, demonstrate the artist’s sophisticated approach to color and his use of both traditional and modern pigments to achieve vibrant, dynamic effects in his work [55-57]. Table 7. XRF Analyis A Chromatic aspect of surface Elements relative concentration Interpretation Ca% Cr% Fe% Co% Cu% Zn% Ba% Cd% Hg% Pb% 1 Grey 0.8 - 0.6 - 1.6 97.0 - - - - Zinc White 2 Brown-green 0.8 - 0.7 - 2.4 96.0 - - - - Organic pigment 3 Red 0.4 0.7 6.1 1.5 1.6 72.6 - - 2.2 14.9 Red ocher, Cinnabar, Cobalt Blue, Lead White 4 Pink 0.4 0.4 4.7 1.6 1.6 61.8 - - 3.6 26.0 Red ocher, Cinnabar, Cobalt Blue, Lead White 5 Light blue 0.2 0.2 2.1 2.5 1.9 47.8 - - 1.0 44.3 Cobalt Blue, Lead White 6 Dark blue 0.3 0.6 10.1 36.2 0.9 39.0 1.4 - 1.9 9.7 Cobalt Blue, Prussian Blue, Barium Sulphate 7 Light green 0.2 3.1 4.5 2.1 1.7 51.8 - - 1.7 34.8 Chrome Oxide Green; Lead White 8 Red 0.5 0.8 4.9 2.4 1.8 53.2 - - 6.8 29.5 Red ocher, Cinnabar, Lead White 9 Brown 0.4 0.3 1.6 0.4 1.6 88.1 - - - 7.6 Organic pigment 10 Orange 0.1 0.2 4.2 1.5 2.7 19.4 - 0.4 13.8 57.7 Cinnabar, Red Ocher, Cadmium Yellow/Orange; Lead White 11 Reddish-brown 0.1 0.2 24.4 1.3 1.5 48.7 - - 0.9 22.8 Red ocher; Lead White 12 Pink 0.1 - 0.6 - 1.9 55.5 - - 0.2 41.8 Red lake, Lead White 13 Light pink - - 0.5 1.5 2.2 34.6 - - 0.5 60.7 Red lake, Lead White 14 Black 0.7 0.9 7.1 3.9 1.7 57.8 0.8 - 0.9 26.3 Prussian Blue, Cobat Blue, Lead White, Barium Sulphate 15 Greyish-pink - 0.1 1.1 0.7 1.6 65.4 - - 2.5 28.5 Cinnabar, Carbon Black, Lead White 16 White - 0.2 0.8 0.8 2.7 4.6 - - 0.8 90.1 Lead White 17 Dark green 0.3 22.1 1.7 1.3 1.8 60.0 - - 0.1 12.6 Chrome Oxide Green 18 Blue-green 0.5 8.2 7.5 2.6 2.1 57.3 0.4 - 0.7 20.7 Prussian Blue, Cobalt Blue, Chrome Oxide Green, Lead White; Barium Sulphate 3.3 Cleaning tests Different water-based cleaning systems, including the Polar Rescue in gel form (5 wt% in Klucel G) and the Nanorestore Cleaning® Polar Coating S, were tested and compared to identify a more sustainable solution capable of removing the degraded layer while preserving the underlying materials [58]. a) Optical microscopy The products Polar Varnish Rescue, Nanorestore Cleaning® Polar Coating S, and Nasier C03 demonstrated effective removal of the onion layer: the microscopical observations showed a reduced presence of the onion patina after cleaning. In contrast, while water did not interact with the onion layer, both the amylase solution and the amylase gel formulation were very effective. Post-treatment microscopical images showed increased brightness and saturation, with no apparent loss of color. b) Spectrocolorimetric analysis The spectrocolorimetric analyses partially validate the observations made through optical microscopy (Table 8). Deionized water did not induce any chromatic alteration on the surface, indicating a lack of cleaning effect from this method. When applied to remove the "onion" layer, cleaning systems 2 and 6 exhibited a greater overall variation in the surface appearance compared to system 3. Specifically, this variation is characterized by a shift towards lighter and more reddish tones. This result suggests that only a partial cleaning of the surface was achieved. Conversely, cleaning systems 4 and 5 resulted in a more significant change in the L parameter, indicating a more uniform removal of the onion material on the surface. This finding is further confirmed by observing variations in both the a* and b* parameters, reflecting a noteworthy change in the surface appearance. Table 8. ∆L*, ∆a*, ∆b*, and ∆E* values obtained from the comparison between the treated areas before and after the cleaning tests. Standard deviation max of single parameter (SD) <0.9 ID Cleaning system ΔL* Δa* Δb* ΔE 1 Deionized water 0.23 -0.51 -0.24 0.61 2 Polar Rescue Gel 5 wt% in Klucel® G -0.77 2.11 2.96 3.72 3 Nanorestore Cleaning® Polar Coating S -0.74 -1.18 -1.24 1.86 4 Amylase 1% in deionized water 1.65 1.67 6.7 7.10 5 Amylase 1% in deion. water gelled with Klucel® G (5 wt%) 1.67 -1.28 -6.11 6.46 6 Nasier C03 -0.1 2.12 2.42 3.22 c) FTIR -ATR The spectra acquired from the cleaning swab following the first pass are shown below. The spectrum highlighted in Figure 15 use water as the solvent and shows no differences compared to the spectrum collected from cotton used as an analytical blank. The typical bands of cellulose are present. The spectrum displays bands around 3400 cm⁻¹ associated with O-H bond stretching; bands in the range of 2900–2800 cm⁻¹; and bands in the spectral region between 1500–1200 cm⁻¹ related to C-O and C-C groups. Lastly, the bands corresponding to C-O-C vibrations, characteristic of glycosidic bonds between glucose units, are observed in the region between 1100–1000 cm⁻¹. The comparison of the spectra highlights that water has not removed any substances. The spectrum collected from the cleaning swab, using Polar Rescue as the solvent, compared to the spectrum collected from cotton, is characterized by the presence of bands attributable to compounds derived from onions (flavonoids). In particular, the band to1497 cm-1 originating from the C=C double bond in the central heterocyclic ring, a band at 1250 cm-1 associated with the stretching of the C–O–C single bonds in the ring . The spectrum collected from the Nanorestore Cleaning® Polar Coating S swab shows, compared to the cotton swab spectrum (Figure 17), resolved bands in the spectral region between 2900–3000 cm⁻¹. The bands at 2916 cm⁻¹ and 2852 cm⁻¹ are attributed to C–H stretching modes, suggesting the extraction of the phenolic component of the onion residue. Additionally, bands at approximately 1250 cm⁻¹ and 1070 cm⁻¹ correspond to the asymmetrical and symmetrical stretching of C–O–C bonds. The spectrum obtained using 1% Amylase in deionized water, compared to that collected on the cotton swab, is characterized by more intense bands in the spectral region between 1500 and 1700 cm⁻¹, which appears with a broad peak. This range is related to stretching motions common in aromatic structures and in some phenolic and flavonoid substances frequently present in onion extracts. The band at the wavenumber of 1679 cm⁻¹ is assigned to C=O stretching vibrations that are H-bonded. The band at the wavenumber of 1630 cm⁻¹ is from the ring C=C stretch of phenyl, while the band at the wavenumber of 1559 cm⁻¹ is due to the ring base. The band at the wavenumber of 1510 cm⁻¹ is assigned to in-plane CH bending vibrations from the phenyl rings. This result highlights how the degradation of the polysaccharide structure by amylase, which catalyzes the hydrolysis of α-1,4-glycosidic linkages, makes phenolic compounds more accessible, allowing for better observation of the spectral bands associated with these groups. The spectrum obtained from the swab using Nasier C03 exhibits a behaviour similar to that achieved with amylase, although the cleavage of glycosidic bonds and the corresponding release of phenolic groups are less pronounced. d) Cleaning of the painting The cleaning of the painting surface was performed using a 1% amylase solution gelled with Klucel® G (5 wt%), applied for 1 minute with two layers of Japanese paper interposed to facilitate the removal of excess gel (Figure 15). The procedure was repeated until the removal of the degraded coating was deemed satisfactory (Figure 21a-b). The most challenging aspect was achieving a uniform result by blending the over-cleaned area with the one still to be cleaned, while ensuring a gradual removal process. However, the darker colors on the left side of the face allowed for a smooth transition between the two areas, preventing damage to the paint layer. 4. Discussion Analyses conducted using FTIR ATR spectroscopy, SEM/EDS, and optical microscopy identified and characterized the presence of onion residues on the surface of Giacomo Balla’s painting “Portrait of a Man / Eugenio Riva.” These residues were attributed to a previous restoration intervention. While the use of onion in cleaning painted surfaces is recognized in the empirical practice of historical restoration, it has never been analytically documented in the literature. This study offers the first detailed chemical and morphological characterization of such a treatment. Specifically, optical and SEM/EDS microscopy images of sample S1 confirmed the morphological presence of plant tissue residues, while FTIR spectroscopy performed on the surface powder revealed characteristic bands of onion biochemical components. The primary bands observed included hydroxyl (-OH) stretching at 3289 cm⁻¹, methylene (CH 2 ) stretching at 2849 and 2916 cm⁻¹, and asymmetric methyl (CH 3 ) deformation stretching at 1405 cm⁻¹. Additional significant peaks included signals at 1734 cm⁻¹, attributed to carbonyl (C=O) ester groups, 1608 cm⁻¹, related to aromatic phenolic (C=C) groups, and 1008 cm⁻¹, corresponding to terminal alcohol groups (-CH₂OH) typical of carbohydrates. These results confirm the chemical composition of the onion layer, characterized by polysaccharides and phenolic compounds that contributed to chromatic degradation over time. Incomplete surface washing after the onion treatment left residues that aged and darkened the pictorial surface. The 1960 restoration revealed the difficulty of restoring the legibility of the painting. Interaction between the cleaning systems used at the time and the paint layer led restorers to limit cleaning to only half of the painting. Analysis indicated that this challenge was due to the extremely thin paint layer, as revealed by SEM/EDS. The painting technique in “Portrait of a Man / Eugenio Riva” involves simple layering with few paint layers. The upper left area of the painting consists of a single preparatory layer applied across the entire surface by Balla. Elemental composition analysis of the white-grayish base layer, revealed by EDXRF and SEM/EDS, indicated the presence of zinc as the main element, suggesting the use of zinc white pigment to prime the canvas. Over this base, thin chromatic layers were applied, composed of the following pigments: Gray (preparation of canvas layer): Zinc white and possibly a pigment undetectable via XRF and SEM/EDS, such as tenorite or carbon black. Brown-green (signature): Organic pigment undetectable via XRF and SEM/EDS. Red (color test in left area): Red earth containing Al, Si, Mg, and S, combined with Ca in all red layers analyzed by SEM/EDS; cinnabar; traces of cobalt blue and lead white. Pink (color test in left area): Red earth; cinnabar; lead white (used in higher quantities than in point 3 to lighten the tone); traces of cobalt blue. Light blue (color test in left area): Cobalt blue; lead white. Dark blue (color test in left area): Cobalt blue; Prussian blue; barium sulfate as filler. Light green (color test in left area): Chromium green oxide; lead white. Red (color test in left area): Red earth; cinnabar; lead white. Brown (brushstroke in left area): Organic pigment. Orange (background): Red earth; cinnabar; cadmium yellow/orange; lead white. Reddish brown (background): Red earth; lead white. Pink (cheek): Red lake; lead white. Pink (facial skin color): Red lake; lead white. Black (pupil): Prussian blue; cobalt blue; lead white; traces of barium sulfate (filler). Grayish pink (nostril): Cinnabar and possibly carbon black, undetectable via XRF and SEM/EDS. White (collar): Lead white. Dark green (bow tie): Chromium green oxide. Blue-green (jacket): Prussian blue; cobalt blue; chromium green oxide; traces of barium sulfate (filler). The results of EDXRF and SEM/EDS analyses correlate the detected pigments with those found in other works by Giacomo Balla. Lead white, cinnabar, ochres, red lake, cobalt blue, and Prussian blue—often mixed—were identified in “Bambina coi fiori” (1902-1903). Zinc white, Prussian blue, chromium green oxide, ochres, and alizarin crimson were found in “Grido di dimostrazione in piazza del Quirinale” (1915). UV imaging confirmed the thinness of the paint layer, facilitating the identification of the white pigments used for the background and the central figure. Variations in fluorescence between the white collar and the pigment used for the background and certain facial details suggested the use of lead white and zinc white, respectively, as confirmed by EDXRF and SEM/EDS analyses. The study evaluated alternative methods to remove the vegetable residues without compromising the underlying paint layer. Enzymatic hydrolysis of polysaccharides using amylase solutions proved the most effective cleaning system. This enzyme, a hydrolase highly specific for α-1,4-glycosidic bonds, enabled selective removal of the onion layer, producing degradation products that dissolved easily in the aqueous medium. However, the thinness of the paint layers poses risks, particularly in sensitive areas. Optical microscopical observation and spectropolarimeter analysis revealed a more chromatically uniform surface, with significant darkening reduction achieved through amylase applications (in gel and liquid forms) and Nasier CO 3 . Among tested alternatives, commercial solvents like Nanorestore Cleaning® Polar Coating S and Polar Rescue Gel exhibited varying efficacy. The use of prevalidated products ensures compatibility with cultural heritage conservation standards. The cleaning efficacy of these systems was attributed to their polarity, as observed in FTIR spectra acquired from cleaning swabs. Polar Rescue Gel demonstrated a greater capacity to extract phenolic compounds with more hydrophobic characteristics, while Nanorestore Cleaning® Polar Coating S showed higher efficacy in removing polar phenolic components. Figure 22 highlights, in the Hansen solubility parameter diagram, the distance between the two solvents, illustrating how Cleaning® Polar Coating S is characterized by higher polarity compared to Polar Rescue Gel and a broader solubility range. In synthesis, enzyme-based formulations, specifically amylase solutions, proved to be highly specific and safe for preserving original paint layers, offering a non-toxic and selective tool for the removal of specific materials from cultural heritage artifacts. While polar solvents exhibited lower overall cleaning efficiency, they effectively solubilized onion residues through their interaction with the phenolic components of the onion. 5. Conclusion The restoration of Giacomo Balla's Ritratto d’uomo / Eugenio Riva highlights the intricate challenges posed by historical restoration practices and the opportunities presented by modern scientific techniques. The discovery of onion residues, a byproduct of earlier cleaning attempts, underscored the impact of empirically driven methods on the long-term condition of cultural artifacts. Advanced analytical tools documented the morphological effects of these residues, revealing their contribution to chromatic alterations that affected the painting's readability over time. Enzyme-based cleaning formulations, particularly amylase solutions, proved to be the most effective and non-invasive approach for addressing these residues. The complementary use of polar solvent systems, guided by Hansen solubility parameters, emphasized an alternative approach to enzymatic solutions, especially valuable for paintings with exceptionally thin paint layers. Ultimately, this intervention not only restored the visual harmony of the painting but also established a replicable framework for addressing complex restoration challenges. By bridging the disciplines of scientific innovation, art history, and conservation, this study contributes to a deeper understanding of preserving the integrity and legacy of cultural heritage. The multidisciplinary methodology serves as a guide for future restorations, emphasizing the importance of integrating empirical evidence with advanced solutions. Declarations 6. Acknowledgements This article is the outcome of a collaborative project between YOCOCU and the Galleria Nazionale. The experimental work is also part of the PhD program in Earth Sciences (Curriculum: "Environment and Cultural Heritage") carried out by Chiara Biribicchi at the University of Rome "La Sapienza". Chiara provided input during the early stages of the interpretation of results but chose not to be involved in the final publication. The authors express their gratitude to Chiara for her contributions to the project. They also extend their thanks to YOCOCU APS for providing materials and to the Director of the Galleria Nazionale of Rome for enabling the project's development. 7. Availability of data and materials The data presented in this study, including all quantitative and qualitative datasets, are available upon reasonable request from the corresponding author. All human figure images included in this manuscript have been anonymized and are presented with appropriate permissions in compliance with ethical and legal standards. Additional raw data that support the findings are provided in supplementary materials or can be accessed under specific conditions, as outlined in the repository linked to this publication. Author Contributions: Conceptualization, A.M.; methodology, A.M. and P.C; validation, M.C.; investigation, A.M. and T.C.; resources, P.C. and A.M.; data curation, A.M.; writing—original draft preparation, A.M.; writing—review and editing, T.C.. and A.M.; supervision, A.M.; project administration, A.M. All authors have read and agreed to the published version of the manuscript. 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Elisa Boccalon, Gianluca Viscusi, Elena Lamberti, Francesco Fancello, Severino Zara, Paola Sassi, Maura Marinozzi, Morena Nocchetti, Giuliana Gorrasi, Composite films containing red onion skin extract as intelligent pH indicators for food packaging, Applied Surface Science, Volume 593, 2022, 153319, ISSN 0169-4332, https://doi.org/10.1016/j.apsusc.2022.153319. Lu, X, Wang, J, Al-Qadiri, HM, Ross, CF, Powers, JR, Tang, J, Rasco, BA: Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy. Food Chem. 129, 637–644 (2011) H. Peng, X. Zhang, J. Xu. Apigenin-7-O-β-D-glycoside isolation from the highly copper-tolerant plant Elsholtzia splendens. Journal of Zhejiang University-SCIENCE B (Biomedicine & Biotechnology), 17 (6) (2016), pp. 447-454, 10.1631/jzus.B1500242 Heitor Ribeiro da Silva, Daniele da Cruz de Assis, Ariadna Lafourcade Prada, José Otávio Carrera Silva, Mayara Brito de Sousa, Adriana Maciel Ferreira, Jesus Rafael Rodríguez Amado, Helison de Oliveira Carvalho, Abrahão Victor Tavares de Lima Teixeira dos Santos, José Carlos Tavares Carvalho. Obtaining and characterization of anthocyanins from Euterpe oleracea (açaí) dry extract for nutraceutical and food preparations. Revista Brasileira de Farmacognosia, Volume 29, Issue 5, 2019, Pages 677-685, ISSN 0102-695X, https://doi.org/10.1016/j.bjp.2019.03.004. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5633755","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":391596950,"identity":"d5840dae-2b07-4e49-95af-583010c2015c","order_by":0,"name":"Andrea Macchia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnElEQVRIiWNgGAWjYHACxgcka2E2IFkLmwRp6vlntz+r5qmwk+OfkcD44WMOEVok7pwxu81zJtlY4kYCs+TMbcRYcyOH7TZv24HEDRIJbMy8xGiRv5H+rJg0LQY3EsyYSdNieOeMseQckF/OPGwmzi9yt9sffngDCrH25IMfPhLlfWCkMPGAWYwNxKiHaGH8QaTaUTAKRsEoGKEAAD2WM1ao4A4oAAAAAElFTkSuQmCC","orcid":"","institution":"YOCOCU, Youth in Conservation of Cultural Heritage","correspondingAuthor":true,"prefix":"","firstName":"Andrea","middleName":"","lastName":"Macchia","suffix":""},{"id":391596951,"identity":"4b7c8a59-b47f-4e00-83f1-3761ade3fb51","order_by":1,"name":"Tilde De Caro","email":"","orcid":"","institution":"CNR-ISMN","correspondingAuthor":false,"prefix":"","firstName":"Tilde","middleName":"","lastName":"De Caro","suffix":""},{"id":391596952,"identity":"ba464365-6eac-41e9-a7d1-5c3a28e334bc","order_by":2,"name":"Marcello Colapietro","email":"","orcid":"","institution":"YOCOCU, Youth in Conservation of Cultural Heritage","correspondingAuthor":false,"prefix":"","firstName":"Marcello","middleName":"","lastName":"Colapietro","suffix":""},{"id":391596953,"identity":"25588978-8d82-45cb-83a9-03ef23c29f08","order_by":3,"name":"Paola Carnazza","email":"","orcid":"","institution":"Galleria Nazionale d’Arte Moderna e Contemporanea","correspondingAuthor":false,"prefix":"","firstName":"Paola","middleName":"","lastName":"Carnazza","suffix":""}],"badges":[],"createdAt":"2024-12-12 18:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5633755/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5633755/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72415972,"identity":"a1a4596c-acfc-4766-8df7-7d0828772650","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":287584,"visible":true,"origin":"","legend":"\u003cp\u003e“Ritratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: areas analyzed by XRF (green “1-18”); sampling areas (yellow “S1-S4”); cleaning tests made with the proposed formulations (red “CT”).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/cfe1bc1eed45639dc67c1728.png"},{"id":72416345,"identity":"26b41c97-552b-43b1-863a-975aa7aefaaf","added_by":"auto","created_at":"2024-12-26 20:40:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":259841,"visible":true,"origin":"","legend":"\u003cp\u003eDetail of the pictorial layer (uncleaned area, face) captured under visible light (VIS) (a) and ultraviolet light (UV) (b) at 50x magnification.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/602acceaadd751db0045b43a.png"},{"id":72415981,"identity":"08232ae0-91fc-442f-83c9-5b62b7ab113d","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":272368,"visible":true,"origin":"","legend":"\u003cp\u003eBrownish layer (uncleaned area) in VIS (a) and (UV (b) lights at 50x magnification.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/5af03c303858d35e75cfe646.png"},{"id":72415961,"identity":"7cba5268-338f-4ab0-90d5-fa27e17cab83","added_by":"auto","created_at":"2024-12-26 20:32:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":310535,"visible":true,"origin":"","legend":"\u003cp\u003eArea cleaned in the 1960’ in VIS (a) and (UV (b) lights at 50x magnification.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/fc144422f389438e697cb2d6.png"},{"id":72415973,"identity":"b3bd05ed-cbee-49f5-98a5-c992f6753d06","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196869,"visible":true,"origin":"","legend":"\u003cp\u003eDetail of the face (area cleaned in the 1960’) in VIS (a) and (UV (b) lights.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/3a7f9c15c6c722513cd59982.png"},{"id":72415962,"identity":"c0bbc991-463d-49f7-9e55-90a26085d527","added_by":"auto","created_at":"2024-12-26 20:32:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":212678,"visible":true,"origin":"","legend":"\u003cp\u003eSEM image of sample n. 1\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/62e6314e0734dd676f523e11.png"},{"id":72416034,"identity":"07ea623d-2f1b-4023-ac47-c77276af37d0","added_by":"auto","created_at":"2024-12-26 20:32:53","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":96661,"visible":true,"origin":"","legend":"\u003cp\u003eSEM image of sample n. 2.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/7582da6efbd63056228337d2.png"},{"id":72415978,"identity":"6fde0294-18c9-41d6-9cb1-3ea9f4f18194","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":120855,"visible":true,"origin":"","legend":"\u003cp\u003eSEM image of first fragment of sample n. 3\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/777acc349aa030bd209a7b08.png"},{"id":72415986,"identity":"f691f159-9963-48e9-a26f-22ba2b5f072e","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":68230,"visible":true,"origin":"","legend":"\u003cp\u003eSEM image of second fragment of sample n. 3\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/763803f8b316c3cd09ac1791.png"},{"id":72415971,"identity":"446270dc-0c45-4c3d-a873-c9ced3b61023","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":78080,"visible":true,"origin":"","legend":"\u003cp\u003eSEM image of sample n. 4\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/d38fa929d5faa43bc5c8d641.png"},{"id":72416005,"identity":"d6d497eb-55a1-4039-aa4c-78a6f29d909c","added_by":"auto","created_at":"2024-12-26 20:32:52","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":149133,"visible":true,"origin":"","legend":"\u003cp\u003eFTIR ATR spectra of the onion layer on canvas (mockup) and sample n. 1 (S1) comprising the brownish particle sampled from the painting surface.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/87b7a8a48cfca22c8d795b90.png"},{"id":72416409,"identity":"b6d46f28-c874-413a-94ef-50fce23783ca","added_by":"auto","created_at":"2024-12-26 20:48:52","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":618230,"visible":true,"origin":"","legend":"\u003cp\u003e“Ritratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: sx) Image in VIS light; dx) detail of the face in VIS light.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/24eea40628dcb6db058852e5.png"},{"id":72415977,"identity":"75df449e-fb3a-46df-9cfb-b815f652c863","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":712338,"visible":true,"origin":"","legend":"\u003cp\u003e“Ritratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: left) Image in UV light (365 nm); right) detail of the face in UV light (365 nm)\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/c658159b8cf40557448a14f1.png"},{"id":72415964,"identity":"ed622c62-2f86-43aa-aedd-ff6dfa32dd11","added_by":"auto","created_at":"2024-12-26 20:32:50","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":524340,"visible":true,"origin":"","legend":"\u003cp\u003eRitratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: left) Image in IR light (850 nm); right) detail of the face in IR light (850 nm).\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/847b670735360fc786f40b55.png"},{"id":72416331,"identity":"c6a9966f-59a4-4eb9-a296-7c9371a2774b","added_by":"auto","created_at":"2024-12-26 20:40:52","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":53122,"visible":true,"origin":"","legend":"\u003cp\u003eRed line: IR spectrum of unprocessed cotton; blue line: spectrum of the swab after cleaning using water as the solvent.\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/692795793fbd4d1046d73395.png"},{"id":72416018,"identity":"7b875ba3-2d10-4fe3-9f7d-9c22a7bfaf3f","added_by":"auto","created_at":"2024-12-26 20:32:52","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":53948,"visible":true,"origin":"","legend":"\u003cp\u003eRed line: IR spectrum of the cleaning swab using Polar Rescue; Blue line: spectrum of the cotton swab\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/1488c905a6c1e2d77686e844.png"},{"id":72415987,"identity":"7162196a-a61b-4faf-91eb-1558d911bd34","added_by":"auto","created_at":"2024-12-26 20:32:51","extension":"png","order_by":17,"title":"Figure 17","display":"","copyAsset":false,"role":"figure","size":52354,"visible":true,"origin":"","legend":"\u003cp\u003eRed line: IR spectrum of the cleaning swab using Nanorestore Cleaning® Polar Coating S; Pink line: spectrum of the cotton swab\u003c/p\u003e","description":"","filename":"17.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/3b47eee90202bc7ba2090a91.png"},{"id":72416040,"identity":"8e932390-d4cc-46fc-a640-1e5ec6ff13ac","added_by":"auto","created_at":"2024-12-26 20:32:53","extension":"png","order_by":18,"title":"Figure 18","display":"","copyAsset":false,"role":"figure","size":48170,"visible":true,"origin":"","legend":"\u003cp\u003eRed line: IR spectrum of the cleaning swab using 1% Amylase in deionized water; pink line: spectrum of the cotton swab\u003c/p\u003e","description":"","filename":"18.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/890a0975e9a5e4b60b524ccc.png"},{"id":72416327,"identity":"3dca58fc-4668-4bb5-904f-dedb884b89b2","added_by":"auto","created_at":"2024-12-26 20:40:51","extension":"png","order_by":19,"title":"Figure 19","display":"","copyAsset":false,"role":"figure","size":59136,"visible":true,"origin":"","legend":"\u003cp\u003eRed line: IR spectrum of the cleaning swab using Nasier C03 in deionized water; Pink line: spectrum of the cotton swab\u003c/p\u003e","description":"","filename":"19.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/92f03c8be122c1cbb3d00af9.png"},{"id":72416339,"identity":"8e919bd3-bc9c-4a53-845a-8fe06136b753","added_by":"auto","created_at":"2024-12-26 20:40:52","extension":"png","order_by":20,"title":"Figure 20","display":"","copyAsset":false,"role":"figure","size":172791,"visible":true,"origin":"","legend":"\u003cp\u003eApplication of the 1% amylase solution gelled with Klucel G (5 wt%) by interposing two layers of Japanese paper.\u003c/p\u003e","description":"","filename":"20.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/b4329506b2c7b6ef8fd686ed.png"},{"id":72416329,"identity":"fad832f4-6813-4364-8b76-6bf644764b4b","added_by":"auto","created_at":"2024-12-26 20:40:51","extension":"png","order_by":21,"title":"Figure 21","display":"","copyAsset":false,"role":"figure","size":648115,"visible":true,"origin":"","legend":"\u003cp\u003e“Ritratto d’uomo / Eugenio Riva” (1900) by Giacomo Balla: \u003cstrong\u003ea)\u003c/strong\u003e image in visible light acquired after the cleaning treatment; \u003cstrong\u003eb)\u003c/strong\u003edetail of the face after the cleaning treatment.\u003c/p\u003e","description":"","filename":"21.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/b72ded47aaa10dfe2be10d3d.png"},{"id":72416323,"identity":"2520e5b3-a740-406f-a265-6d616541c0ea","added_by":"auto","created_at":"2024-12-26 20:40:51","extension":"png","order_by":22,"title":"Figure 22","display":"","copyAsset":false,"role":"figure","size":75837,"visible":true,"origin":"","legend":"\u003cp\u003eThe distance between Polar Rescue Gel (blue) and Nanorestore Cleaning® Polar Coating S is represented in the Hansen solubility parameter diagram. The sphere delineates the solubility volume, indicating the range of solubility parameters where effective cleaning or dissolution occurs. D, H, P= Hansen parameters\u003c/p\u003e","description":"","filename":"22.png","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/5153a961b7f72b63a085a40d.png"},{"id":78485042,"identity":"3e87d0c6-e782-4a92-976c-7a13dcb066bb","added_by":"auto","created_at":"2025-03-13 21:46:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7842780,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5633755/v1/855e7373-bf1e-4277-8690-555798b19117.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Revealing and cleaning of an onion layer: scientific Insights into the Restoration of Giacomo Balla’s \"Ritratto d’uomo / Eugenio Riva\"","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThis study focuses on Giacomo Balla\u0026rsquo;s Ritratto d\u0026rsquo;uomo / Eugenio Riva (\u0026ldquo;Man Portrait / Eugenio Riva,\u0026rdquo; 1900), a work created during his Divisionist period, a phase when Balla was honing his mastery of pointillist techniques to depict fine textures and subtle light effects [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Balla (1871\u0026ndash;1958), a groundbreaking figure in Italian art, transitioned from realism and neo-impressionism to Futurism, greatly influencing the development of 20th-century modernism. Born in Turin and later residing in Rome, Balla was initially immersed in a cultural scene shaped by humanitarian socialism and scientific positivism. His early works, such as La fidanzata al Pincio (\u0026ldquo;Girlfriend at Pincio,\u0026rdquo; 1902) and Ritratto di signora all\u0026rsquo;aperto (\u0026ldquo;Portrait of a Lady in the Open Air,\u0026rdquo; 1903), illustrate his commitment to realism and Divisionist techniques, characterized by brushstrokes that capture nuanced light effects [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBalla\u0026rsquo;s artistic trajectory took a significant turn in 1910 when he embraced the Manifesto dei pittori futuristi and the Manifesto tecnico della pittura futurista. This marked the start of an experimental phase driven by themes of movement, dynamism, and avant-garde aesthetics [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. During this period, he produced works like Compenetrazioni iridescenti (\u0026ldquo;Iridescent Interpenetrations\u0026rdquo;) and Velocit\u0026agrave; astratte (\u0026ldquo;Abstract Speed\u0026rdquo;), gradually abandoning Divisionist techniques in favor of industrial materials that aligned with the Futurist vision of modernity [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eArchival records from the National Gallery of Modern and Contemporary Art in Rome indicate that Ritratto d\u0026rsquo;uomo underwent partial cleaning in the 1960s to remove a degraded, food-based residue that had darkened significantly. However, this cleaning, conducted with solvents, proved too aggressive for the thin paint layer, causing bleaching in the treated area on the right side (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Historically, restoration practices often included food-based materials\u0026mdash;such as breadcrumbs, potatoes, and onions\u0026mdash;to polish and brighten polychrome surfaces. Onions were particularly popular due to their acidic and polysaccharide-rich properties, which enhanced surface gloss but also posed risks of abrasion and residue retention on paint layers [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePolysaccharides from onions, such as arabinoxylans, exhibit distinct properties compared to cellulose, explaining their solubility in organic solvents and their impact on conservation challenges [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Cellulose is a linear polymer composed of β-(1,4)-D-glucopyranose units, forming tightly packed, crystalline structures through extensive hydrogen bonding. This regularity and crystalline organization render cellulose highly insoluble in most solvents [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In contrast, onion polysaccharides are characterized by branched structures, often incorporating arabinose side chains. These branches disrupt the structural regularity of the polymer and prevent the formation of tightly packed crystalline domains. As a result, the intermolecular hydrogen bonding is significantly weakened, enabling organic solvents to penetrate and interact more effectively with the polysaccharide chains [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, the branched structure of onion polysaccharides increases the number of exposed functional groups, creating more interaction points for organic solvents. The reduced \"excluded volume\" of these branched chains compared to linear polysaccharides of similar molecular weight further enhances solubility [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These properties explain why the polysaccharides in onion-based residues may interact strongly with paint layers, particularly through their functional groups, complicating removal with traditional aqueous or enzymatic methods.\u003c/p\u003e \u003cp\u003eSince the 1970s, enzymes have gained popularity among conservators, initially in paper conservation and gradually in other fields. Hydrolytic enzymes, or hydrolases, are particularly valued for their ability to catalyze the hydrolysis of proteinaceous, polysaccharide, and lipid-based materials that can alter the appearance and structure of artworks [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Amylases, for example, target α-(1\u0026ndash;4) glucosidic bonds in starch, enabling the effective removal of starch-based adhesives without affecting cellulose. α-Amylases cleave each α-(1\u0026ndash;4) bond to progressively degrade the starch, while β-amylases target alternate bonds, breaking down the polymer into shorter starch fragments [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmylase is an enzyme that hydrolyzes glycosidic bonds in polysaccharides, acting on both branched and linear structures with efficiency varying depending on the type of amylase. Alpha-amylase, an endoenzymatic enzyme, randomly breaks α-1,4 bonds within the chains, making it effective on both branched substrates like amylopectin, where it generates short oligosaccharides, and linear ones like amylose, which it degrades into maltose and linear dextrins [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Beta-amylase, an exoenzymatic enzyme, is more specific to linear substrates, cleaving maltose from the non-reducing ends but is ineffective at α-1,6 branching points [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Gamma-amylase, although less common, can hydrolyze both α-1,4 and α-1,6 bonds, enabling it to act on both types of structures, though with a weaker preference for linear substrates compared to the other isoforms [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, using enzymes on thin polychrome paint layers presents challenges, as even amylases, could cause over-wetting or penetrate excessively into delicate paint layers. Enzymatic activity that is not carefully controlled might weaken or alter the paint structure. Additionally, enzymes such as amyloglucosidases and pullulanase, which act on both α-(1\u0026ndash;4) and α-(1\u0026ndash;6) linkages, may leave residues within paint layers, potentially complicating future conservation efforts [\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven these risks, enzyme-based applications on artworks are often conducted with gel supports that can limit the enzyme's cleaning action. The necessity of a water-based medium for enzyme use can further exacerbate risks for sensitive materials [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, this study investigates alternative methods to enzymatic treatments for safely removing the onion-based layer from the painting. While enzymes align well with green chemistry principles, their application in restoration may not be ideal due to the sensitivity of certain painted surfaces.\u003c/p\u003e \u003cp\u003eA multi-analytical approach was employed to confirm the onion-based nature of the residue, using Fourier-transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM/EDS) to determine the composition and thickness of the paint layers. Additional analyses, including multispectral imaging (VIS, UV 365 nm, IR 850 nm), digital microscopy, and X-ray fluorescence (XRF), were used to assess the painting\u0026rsquo;s state of conservation and Balla\u0026rsquo;s palette, minimizing interactions between selected solvents and the paint layer.\u003c/p\u003e \u003cp\u003eThese analyses revealed significant bioactive onion compounds, including polysaccharides, sulfur-containing compounds (such as onion in A and cysteine sulfoxides), and phenolic compounds like rutin and quercetin [\u003cspan additionalcitationids=\"CR30 CR31\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Due to the polarity and strong bonding of these compounds with the paint layers, removal typically requires solvents such as ethanol or ethyl acetate, commonly used in other fields [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This study instead explores greener, safer alternatives, choosing products that align with sustainable practices in cultural heritage preservation while safeguarding the integrity of the original paint layers.\u003c/p\u003e \u003cp\u003eIn conclusion, this research offers new insights into the unconventional use of onions in historical cleaning techniques\u0026mdash;documenting, for the first time, this method applied to a painting\u0026mdash;and presents a pioneering approach to exploring alternative green cleaning solutions to the enzymatic method.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e1. Multi-Analytical Approach for Residue Identification\u003c/h2\u003e\n \u003cp\u003eA multi-analytical approach was employed to confirm the onion-based composition of the residue, combining optical microscopy (OM), Fourier-transform infrared (FT-IR) spectroscopy in Attenuated Total Reflectance (ATR) mode and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS). \u0026bull; Digital Microscopy was performed using a DinoLite AM411-FVW digital microscope at 40X and 220X magnifications in visible and UV light, targeted surface analysis was conducted to identify areas of interest and select sampling locations for the invasive analysis. FT-IR ATR identified specific organic compounds indicative of onion, while SEM-EDS provided detailed data on the elemental composition and morphology of different paint layers and residues, enabling precise analysis of layer thickness and surface structure.\u003c/p\u003e\n \u003cp\u003eFour samples (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) were taken from the artwork with the following objectives:\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003ea) Sample S1, collected with the aim of isolating only the \u0026quot;onion\u0026quot; layer from the painting surface, was analyzed using SEM/EDS and FT-IR ATR to confirm the presence of onion residues on the surface.\u003c/p\u003e\n \u003c/span\u003e \u003cspan\u003e\n \u003cp\u003eb) Three stratigraphic samples were collected from the painting\u0026rsquo;s edges: sample S2 from the upper-right, sample S3 from the upper-left, and sample S4 from the bottom-right.\u003c/p\u003e\n \u003c/span\u003e\n \u003cp\u003eSample S2 included a greyish ground layer and canvas; sample S3 contained three paint layers; and sample S4 consisted of the pictorial ground layer with traces of additional paint layers.\u003c/p\u003e\n \u003cp\u003eThese samples underwent SEM-EDS analysis to examine their stratigraphic composition in detail. The FT-IR spectra were acquired with a Nicolet Summit FTIR spectrometer equipped with an Everest\u0026trade; Diamond ATR accessory, using a resolution of 8 cm⁻\u0026sup1; and 32 scans per sample. SEM-EDS analysis was conducted on samples 2, 3, and 4 to assess their elemental composition. Sample 1 was analyzed specifically to capture high-resolution images of the morphology and surface structure of brownish particles present on untreated areas. A Tescan microscope with INCA 2000 EDS was employed in low vacuum mode (15 Pa) and an electron acceleration voltage of 30 kV, eliminating the need for sample pre-treatment.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e2. Additional Analytical investigations\u003c/h3\u003e\n\u003cp\u003eAdditional analyses, including multispectral imaging (VIS, UV 365 nm, IR 850 nm) and X-ray fluorescence (XRF), were conducted mainly to evaluate the state of conservation and to analyse Balla\u0026rsquo;s palette. These techniques enabled a comprehensive examination of the painting\u0026rsquo;s materials while minimizing potential interactions with solvents and cleaning agents.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eMultispectral Imaging: This technique captured images of the artwork across three spectral bands\u0026mdash;visible (VIS), ultraviolet (UV), and near-infrared (NIR-MIR). Photographic documentation under visible light (400\u0026ndash;750 nm) provided a baseline for assessing the overall technique and identifying constitutive materials. UV fluorescence imaging highlighted surface conditions, such as varnish layers, prior retouches, or other applied materials. NIR-MIR infrared reflectography allowed for the identification of preparatory sketches, alterations, and previous restorations. The imaging was conducted using a Madatec Samsung NX500 28.2 MP BSI CMOS camera, with UV lighting at 365 nm. Fluorescence emissions were captured with HOYA UV-IR cut and Yellow 495 filters, while IR reflectography utilized an 850 nm filter.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eX-Ray Fluorescence (XRF): XRF analysis on 18 points provided elemental characterization of the paint materials. A portable XRF instrument with a tungsten X-ray source and a Peltier-cooled silicon drift detector (Amptek MCA 8000A) was used, yielding a resolution of 140 eV at 5.9 keV (Mn K\u0026alpha;). XRF analyses were conducted at 38 kV and 350 \u0026micro;A, capturing K-lines for elements (Z\u0026thinsp;=\u0026thinsp;12\u0026ndash;52) and L-lines for elements (Z\u0026thinsp;\u0026gt;\u0026thinsp;35). Data were normalized to the highest peak and analyzed using PyMCA software to determine the relative concentrations of identified elements.\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003ch3\u003e3. Cleaning Tests\u003c/h3\u003e\n\u003cp\u003eTo dissolve the onion-based components identified in the residue, several cleaning solutions were tested, including those derived from literature and commercially available products. Each solution was applied for a consistent duration of 1 minute (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, area C):\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eDeionized water\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePolar Rescue in Klucel\u0026reg; G (5 wt%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNanorestore Cleaning\u0026reg; Polar Coating S (containing 1-pentanol, ethyl acetate, and propylene carbonate)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAmylase (1 wt% in deionized water)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eAmylase (1 wt% in deionized water, thickened with Klucel\u0026reg; G 5 wt%)\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eNasier C03 (a stabilized enzyme-based hydrogel)\u003c/p\u003e\n \u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAmong these, Nasier C03, amylase, and amylase in Klucel\u0026reg; G offered selective removal through targeted enzyme-based actions capable of breaking down polysaccharides [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]. Nanorestore Cleaning\u0026reg; Polar Coating S and Polar Rescue gel are solvent-based systems featuring low-toxicity, eco-friendly organic solvents. Nanorestore contains anionic surfactants in a blend of 1-pentanol, ethyl acetate, and propylene carbonate, developed by CSGI for removing natural and synthetic polymers with reduced solvent content. Polar Rescue, developed by Lab4green, gel includes anionic surfactants and acetal, gelled with Klucel\u0026reg; G to limit solvent spread on the paint surface [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003e5. Evaluation of Cleaning Efficacy\u003c/h3\u003e\n\u003cp\u003eThe cleaning efficacy of each solution was assessed using a DinoLite AM411-FVW digital microscope at 40X and 220X magnifications, observing the surface before and after cleaning. Criteria included removability, interactions with the original paint layers, and the gradualness of the cleaning process. Spectrocolorimetric analysis was performed pre- and post-cleaning to detect any color discrepancies in treated areas. Measurements were taken with a Y3060 3nh spectrophotometer using a D65 illuminant and 8 mm aperture in SCI mode over the 400\u0026ndash;700 nm range. Each area was measured three times to minimize uncertainty, and color differences (∆E*) were calculated based on the Euclidean distance between color coordinates:\u003c/p\u003e\n\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:\\varDelta\\:E=\\sqrt{{\\left({L}_{2}-{L}_{1}\\right)}^{2}+{\\left({a}_{2}-{a}_{1}\\right)}^{2}+({b}_{2}-{b}_{1})}$$\u003c/div\u003e\u003c/div\u003e\u003cp\u003eThis calculation provided quantitative data on any color changes following the cleanings treatments. Furthermore, FTIR spectroscopy in ATR mode was employed to analyze the residue left after cleaning. For each cleaning system used, except for the amylase in Klucel G, the coton swab utilized for cleaning was dried at 60\u0026deg;C prior to analysis by placing it in contact with the diamond of the instrument. The spectra were collected under the same operational conditions previously described, using the Summit Pro by Thermo Scientific as the measuring instrument.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e6.\u003c/strong\u003e Figure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cstrong\u003eand cleaning of painting\u003c/strong\u003e\u003c/p\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eFigure \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. \u0026ldquo;Ritratto d\u0026rsquo;uomo / Eugenio Riva\u0026rdquo; (1900) by Giacomo Balla: areas analyzed by XRF (green \u0026ldquo;1\u0026ndash;18\u0026rdquo;); sampling areas (yellow \u0026ldquo;S1-S4\u0026rdquo;); cleaning tests made with the proposed formulations (red \u0026ldquo;CT\u0026rdquo;).\u003c/p\u003e\u003cp\u003eThe system that proved to be the most effective during the experimentation was the 1% amylase solution gelled with Klucel\u0026reg; G (5 wt%), which was ultimately used to clean the entire painting. The cleaning agent was applied to the surface of the painting for a duration of one minute, with treatment focused on 4x4 cm sections at a time. To facilitate the removal of excess gel, two layers of Japanese paper were placed between the application and the painting surface.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Multi-analytical approach for residue identification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) Optical Microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegarding the artist\u0026rsquo;s technique, optical microscopy analyses revealed the use of briskly applied, juxtaposed brushstrokes to create vivid visual effects (Figure 2a-b). The uncleaned surface, untouched during the 1970s, is covered by a homogeneous brownish layer (Figure 3a-b), while the cleaned surface appears brighter but shows residues from the cleaning treatment (Figure 4a-b). The pictorial layer, particularly in the top-left area, appears remarkably thin, with the underlying canvas visible in several regions. This characteristic is even more evident on the right side, which underwent cleaning in the 1960s, suggesting that the restoration treatment carried out at that time caused partial abrasion of the paint layer. A comparison between untreated areas and those cleaned in the 1960s indicates that the cleaning process scrubbed the color layer but failed to remove the brownish particles (Figure 5a-b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb) SEM/EDS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe surface morphology of Sample S1, observed using SEM analysis in COMBO mode (backscattered and secondary electrons), is shown in Figure 6. The image reveals a vegetal tissue containing fragments with high molecular weight elements, identifiable by their bright contrast. The tissue structure closely resembles onion tissue, as described by Adeola et al. [22].\u003c/p\u003e\n\u003cp\u003eThe EDS spectrum of the tissue indicates an elemental composition consistent with onion residues, including potassium (K), sulfur (S), and calcium (Ca) (Figure 6, Table 1) [40].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe paint fragment adhered to the onion layer reveals the presence of iron-based aluminosilicate pigments, commonly known as red earth pigments, identified by the concurrent presence of iron (Fe), aluminum (Al), and silicon (Si). Additionally, cadmium-based pigments, likely Cadmium Yellow/Orange, were detected through the presence of cadmium (Cd). The analysis also shows a high lead (Pb) content, indicative of Lead White, a pigment likely used in the ground layer of the painting, as well as zinc (Zn).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eEDS results acquired on sample n. 1. All results in weight%. SD=\u0026plusmn;0.2\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpectrum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSpectrum 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e8.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSpectrum 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e10.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e66.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe SEM image acquired from Sample S2 (Figure 7) reveals the complete stratigraphy of the painting. Beneath the \u0026quot;onion\u0026quot; layer lies a composite layer consisting of the pictorial layer and the ground layer, with a thickness ranging from 5 to 20 \u0026micro;m \u0026plusmn; 3 \u0026micro;m, below which the canvas is visible. EDS analysis (table 2) of the \u0026quot;onion\u0026quot; layer confirms the elements previously identified in the study of Sample 1. The analysis of the pictorial surface identifies the presence of iron (Fe) as a possible chromophore contributing to the brown tonality, along with silicon (Si) and aluminum (Al). The ground layer is characterized by a high concentration of zinc (Zn) and, unlike Sample 1, the absence of lead (Pb). This finding aligns with Balla\u0026apos;s documented use of Zinc White to create a priming layer on the canvas [40]. The presence of lead, on the other hand, is associated with Lead White, used to desaturate the chromatic layers of the composition [41].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eEDS results acquired on sample n. 2. All results in weight%. SD=\u0026plusmn;0.2\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpectrum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e25.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e51.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e9.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e38.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e38.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e75.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSample S3 was divided into two fragments. The first fragment was analyzed at the surface to identify the chromophores responsible for the red coloration. EDS analysis (table 4) revealed the presence of iron (Fe) and mercury (Hg), both chromophores of red pigments. The high lead (Pb) content corresponds to the use of Lead White as a pigment, while cadmium (Cd) indicates the presence of a yellow pigment. Spectra 1 and 4 showed elevated levels of iron, again in conjunction with aluminum (Al) and silicon (Si). However, Spectrum 1 exhibited a higher concentration of Fe, Si, and Al, along with mercury (Hg), suggesting a mixture of red pigments including Cinnabar (HgS). In contrast, Spectrum 4 displayed higher levels of zinc (Zn), lead (Pb), and calcium (Ca), likely indicative of the presence of Zinc White and Lead White, used to adjust the tonality of the red earth pigments.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4. EDS results acquired on the first fragment of sample n. 3. All results in weight%. SD=\u0026plusmn;0.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpectrum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCd\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e41.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e8.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e34.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e52.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e44.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e29.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e25.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSpectrum 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e43.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e12.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e32.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe second fragment of Sample S3 provides insight into the complete stratigraphy of the painting. The SEM image (figure 9) reveals surface areas with varying elemental contrasts. The white-contrast regions are characterized by the presence of lead (Pb), which is also detected by EDS analysis (table 5) in the ground layer, confirming the thinness of the paint film, measured at approximately 10 \u0026micro;m \u0026plusmn; 2 \u0026micro;m in the SEM image.\u003c/p\u003e\n\u003cp\u003eThe presence of calcium (Ca) appears to be associated with sulfur (S), suggesting the use of calcium sulfate. This compound may function either as a filler for pigments or as a substrate for dyes.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5. EDS results acquired on the second fragment of sample n. 3. All results in weight%.\u003c/strong\u003e \u003cstrong\u003eSD=\u0026plusmn;0.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpectrum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePb\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpectrum 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e56.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e21.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpectrum 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e46.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e30.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpectrum 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e28.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e25.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e38.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpectrum 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e31.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e55.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eSpectrum 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e66.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 6px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe SEM image (figure 10) acquired from Sample S4 reveals areas with different elemental contrast. EDS analysis (table 6) differentiates these regions based on the content of calcium (Ca) associated with magnesium (Mg), aluminum (Al), silicon (Si), and sulfur (S), as well as the presence of iron (Fe). This result suggests that the dark layer is attributed to a blue iron-based compound, while the other elements indicate the \u0026quot;mixture\u0026quot; used to produce this pigment. Spectra 2 and 4 clearly identify Zinc White in the ground layer (Figure 14, Table 6).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"12\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6. EDS results acquired on sample n. 4. All results in weight%.\u0026nbsp;\u003c/strong\u003e \u003cstrong\u003eSD=\u0026plusmn;0.2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpectrum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMg\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eK\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFe\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eZn\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eSpectrum 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e56.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e7.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eSpectrum 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e24.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e44.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eSpectrum 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e48.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e29.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eSpectrum 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e47.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 7px;\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ec) FTIR -ATR\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFT-IR analysis in attenuated total reflection (ATR) mode was performed on Sample n. 1 to characterize the brownish particles observed in the uncleaned areas. The resulting spectra were compared to those obtained from an onion layer applied on a commercial canvas mockup (Figure 11).\u003c/p\u003e\n\u003cp\u003eThe mockup\u0026apos;s onion layer exhibited residues identical to those found on the uncleaned areas of the painting, untouched during the 1960 restoration. A comparative analysis of the FT-IR ATR spectra from Sample n. 1 and the mockup demonstrated a striking similarity, confirming the presence of an onion extract-based layer.\u003c/p\u003e\n\u003cp\u003eThe spectral features between 1800 and 750 cm⁻\u0026sup1;\u0026nbsp;correspond to key biochemical and macronutrient components of onions. Both spectra showed the OH stretching band of hydroxyl groups at 3289 cm⁻\u0026sup1;, CH stretching of methylene groups at 2849 and 2916 cm⁻\u0026sup1;, CH₃\u0026nbsp;asymmetric deformation at 1405 cm⁻\u0026sup1;, and OH bending at 1365 cm⁻\u0026sup1;\u0026nbsp;[42\u0026ndash;44].\u003c/p\u003e\n\u003cp\u003eNotable peaks at 1734, 1608, and 1008 cm⁻\u0026sup1; were attributed to the ester carbonyl group stretch (C=O), aromatic ring stretching (C=C) of phenyl groups, and vibrational frequency of carbohydrate \u0026ndash;CH₂OH groups, respectively. A minor band at 1255 cm⁻\u0026sup1; was associated with amide III (random coil) vibrations, indicative of proteins [45-47].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Additional analytical investigations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditional XRF analysis and multispectral imaging were performed to confirm the presence of previous restorations prior to cleaning testing, as well as to examine the consistency of the pigment palette with literature references.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) Multispectral Imaging:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis technique gave excellent visual record, indicating any deviations or overpaint that could suggest previous interventions. Under visible light, the painting revealed thin paint layers characterized by the alternating use of colors to achieve a vivid and dynamic effect, a hallmark of the Divisionist style (Figure 12).\u003c/p\u003e\n\u003cp\u003eUV fluorescence imaging highlighted chromatic variations with intense fluorescence in specific areas, such as the complexion of the cheeks and the grey background (Figure 13). The cheeks exhibited a pink-orange fluorescence, while the grey background emitted a green-yellowish fluorescence. The latter was especially evident in regions of paint loss, such as along the collar\u0026rsquo;s edge, the painting\u0026apos;s perimeter, and some white brushstrokes on the figure\u0026apos;s face and hair. This emission was likely attributable to the presence of zinc white. In contrast, the absence of fluorescence in the white pigment of the collar indicated the use of a different pigment, most likely lead white [48]. Additionally, UV imaging detected a non-fluorescent substance on the left side of the painting, confirming the absence of fluorescent synthetic or natural varnishes, such as terpenoid, acrylic, or urea-aldehydic resins, which are typically used as protective coatings [49\u0026ndash;51].\u003c/p\u003e\n\u003cp\u003eInfrared reflectography, commonly employed to examine subsurface layers, including compositional changes and preparatory sketches, relies on the ability of near-infrared radiation to penetrate thin paint layers and reflect from non-absorbing media. It is absorbed by carbon-based or other absorbing materials like underdrawings [52,53]. However, the IR analysis did not reveal significant compositional changes or preparatory sketches. This suggests that the artist did not employ a detailed underdrawing but instead directly applied swift, vibrant brushstrokes to define both the figure and the background (Figure 14).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb)\u003c/strong\u003e \u003cstrong\u003eEDXRF (Energy Dispersive X-ray Fluorescence):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis technique enabled a non-invasive elemental characterisation of the pigments, guaranteeing their alignment with known materials and discovering any anomalies due to previous restoration efforts. XRF analysis provides excellent insights on the chemical composition of the pigments used in painting, giving a complete understanding of the artist\u0026apos;s palette and technique. (table 7). The ground layer, observed in the upper-left white-grayish region, was identified as being put straight to the canvas, unaffected by subsequent paint layers. The spectrum obtained in this area revealed a significant presence of zinc (Zn), likely from Zinc White, which is a characteristic feature of Balla\u0026rsquo;s works. Minor traces of calcium (Ca), possibly used as a filler in the form of calcium carbonate or calcium sulfate, along with iron (Fe) and copper (Cu), were also detected. The presence of Cu suggests the use of a black pigment, possibly tenorite (CuO), to darken the white base.\u003c/p\u003e\n\u003cp\u003eIn other areas of the painting, the reddish and blue spots exhibited a complex mixture of pigments. These regions showed significant amounts of iron (Fe), mercury (Hg), and lead (Pb), with traces of cobalt (Co) and chromium (Cr). Such findings suggest the use of ochers (e.g., red ocher Fe\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e), cinnabar (HgS), and Lead White (2PbCO\u003csub\u003e3\u003c/sub\u003e\u0026middot;Pb(OH)\u003csub\u003e2\u003c/sub\u003e) as primary components, while cobalt blue (CoAl\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e4\u003c/sub\u003e) and chrome-based pigments (e.g., Chrome Oxide Green Cr\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e) were likely employed to adjust the hues. Higher concentrations of mercury and lead in certain areas, compared to others, indicate the deliberate use of Lead White as a lightening pigment. In contrast, cobalt was predominant in the light-blue areas, with a notable presence of zinc and lead suggesting the use of Zinc White and Lead White to lighten the hue. Prussian Blue (C\u003csub\u003e18\u003c/sub\u003eFe\u003csub\u003e7\u003c/sub\u003eN\u003csub\u003e18\u003c/sub\u003e) was detected in the darker blue regions, along with cobalt blue and traces of barium sulfate, likely used as a filler.\u003c/p\u003e\n\u003cp\u003eGreen areas revealed high levels of chromium, confirming the presence of Chrome Oxide Green. This pigment was particularly prominent in the green bow tie and, to a lesser extent, in the man\u0026rsquo;s jacket, where it appeared combined with Prussian Blue and cobalt blue. In the brown regions, the analysis detected only zinc, pointing to the use of Zinc White for the background, with the absence of other characteristic elements suggesting that an organic pigment was likely responsible for the brown coloration.\u003c/p\u003e\n\u003cp\u003eCadmium was found exclusively in the orange areas, indicating the presence of Cadmium Yellow or Cadmium Orange, often in combination with cinnabar and red ocher. In the red areas, the predominance of iron and the comparatively lower mercury levels suggest a greater reliance on ocher rather than cinnabar. The pink regions, such as the cheeks, showed no characteristic elements, suggesting the use of an organic pigment, likely a red lake, consistent with the pinkish fluorescence observed under UV light and documented in other works by Balla [54]. Similarly, the nostril displayed a mixture of cinnabar, ocher, Zinc White, and Lead White.\u003c/p\u003e\n\u003cp\u003eThe white collar was characterized by the exclusive use of Lead White, in contrast to the green-yellowish fluorescence of the surrounding white background, which indicated the presence of Zinc White. This distinction was further supported by UV imaging, highlighting Balla\u0026rsquo;s intentional use of different white pigments to achieve specific effects. Overall, the results of the XRF analysis, in conjunction with other techniques, demonstrate the artist\u0026rsquo;s sophisticated approach to color and his use of both traditional and modern pigments to achieve vibrant, dynamic effects in his work [55-57].\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"643\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"14\" style=\"width: 643px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 7. XRF Analyis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChromatic aspect of surface\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"10\" style=\"width: 416px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElements relative concentration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInterpretation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003eCa%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eCr%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eFe%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eCo%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eCu%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003eZn%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003eBa%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eCd%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003eHg%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003ePb%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eGrey\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e97.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eZinc White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBrown-green\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e96.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOrganic pigment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eRed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e72.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed ocher, Cinnabar, Cobalt Blue, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e61.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed ocher, Cinnabar, Cobalt Blue, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eLight blue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e47.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e44.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCobalt Blue, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDark blue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e10.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCobalt Blue, Prussian Blue, Barium Sulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eLight green\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e51.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e34.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eChrome Oxide Green; Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eRed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e53.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e29.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed ocher, Cinnabar, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBrown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e88.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e7.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOrganic pigment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eOrange\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e19.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e57.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCinnabar, Red Ocher, Cadmium Yellow/Orange; Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eReddish-brown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e48.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e22.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed ocher; Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003ePink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e55.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e41.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed lake, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eLight pink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e34.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e60.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eRed lake, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e57.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e26.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ePrussian Blue, Cobat Blue, Lead White, Barium Sulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eGreyish-pink\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e65.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e28.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eCinnabar, Carbon Black, Lead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e90.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eLead White\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eDark green\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e22.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e60.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eChrome Oxide Green\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003eBlue-green\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 38px;\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e7.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 46px;\"\u003e\n \u003cp\u003e57.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003ePrussian Blue, Cobalt Blue, Chrome Oxide Green, Lead White; Barium Sulphate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Cleaning tests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferent water-based cleaning systems, including the Polar Rescue in gel form (5 wt% in Klucel G) and the Nanorestore Cleaning\u0026reg; Polar Coating S, were tested and compared to identify a more sustainable solution capable of removing the degraded layer while preserving the underlying materials [58].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ea) Optical microscopy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe products Polar Varnish Rescue, Nanorestore Cleaning\u0026reg; Polar Coating S, and Nasier C03 demonstrated effective removal of the onion layer: the microscopical observations showed a reduced presence of the onion patina after cleaning. In contrast, while water did not interact with the onion layer, both the amylase solution and the amylase gel formulation were very effective. Post-treatment microscopical images showed increased brightness and saturation, with no apparent loss of color.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"491\" height=\"733\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eb) Spectrocolorimetric analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe spectrocolorimetric analyses partially validate the observations made through optical microscopy (Table 8). Deionized water did not induce any chromatic alteration on the surface, indicating a lack of cleaning effect from this method. When applied to remove the \u0026quot;onion\u0026quot; layer, cleaning systems 2 and 6 exhibited a greater overall variation in the surface appearance compared to system 3. Specifically, this variation is characterized by a shift towards lighter and more reddish tones. This result suggests that only a partial cleaning of the surface was achieved. Conversely, cleaning systems 4 and 5 resulted in a more significant change in the L parameter, indicating a more uniform removal of the onion material on the surface. This finding is further confirmed by observing variations in both the a* and b* parameters, reflecting a noteworthy change in the surface appearance.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"bottom\" style=\"width: 63.8535%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 8. ∆L*, ∆a*, ∆b*, and ∆E* values obtained from the comparison between the treated areas before and after the cleaning tests.\u0026nbsp;Standard deviation max of single parameter (SD) \u0026lt;0.9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCleaning system\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;L*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5.078%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;a*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;b*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026Delta;E\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003eDeionized water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003ePolar Rescue Gel 5 wt% in Klucel\u0026reg; G\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e-0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003eNanorestore Cleaning\u0026reg; Polar Coating S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003eAmylase 1% in deionized water\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e7.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003eAmylase 1% in deion. water gelled with Klucel\u0026reg; G (5 wt%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e-6.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e6.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 3.1333%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 40.3001%;\"\u003e\n \u003cp\u003eNasier C03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.1056%;\"\u003e\n \u003cp\u003e-0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.078%;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5.2941%;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 6.8067%;\"\u003e\n \u003cp\u003e3.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ec) FTIR -ATR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe spectra acquired from the cleaning swab following the first pass are shown below. The spectrum highlighted in Figure 15 use water as the solvent and shows no differences compared to the spectrum collected from cotton used as an analytical blank. The typical bands of cellulose are present. The spectrum displays bands around 3400 cm⁻\u0026sup1; associated with O-H bond stretching; bands in the range of 2900\u0026ndash;2800 cm⁻\u0026sup1;; and bands in the spectral region between 1500\u0026ndash;1200 cm⁻\u0026sup1; related to C-O and C-C groups. Lastly, the bands corresponding to C-O-C vibrations, characteristic of glycosidic bonds between glucose units, are observed in the region between 1100\u0026ndash;1000 cm⁻\u0026sup1;. The comparison of the spectra highlights that water has not removed any substances.\u003c/p\u003e\n\u003cp\u003eThe spectrum collected from the cleaning swab, using Polar Rescue as the solvent, compared to the spectrum collected from cotton, is characterized by the presence of bands attributable to compounds derived from onions (flavonoids). In particular, the band to1497 cm-1 originating from the C=C double bond in the central heterocyclic ring, a band at 1250 cm-1 associated with the stretching of the C\u0026ndash;O\u0026ndash;C single bonds in the ring .\u003c/p\u003e\n\u003cp\u003eThe spectrum collected from the Nanorestore Cleaning\u0026reg; Polar Coating S swab shows, compared to the cotton swab spectrum (Figure 17), resolved bands in the spectral region between 2900\u0026ndash;3000 cm⁻\u0026sup1;. The bands at 2916 cm⁻\u0026sup1; and 2852 cm⁻\u0026sup1; are attributed to C\u0026ndash;H stretching modes, suggesting the extraction of the phenolic component of the onion residue. Additionally, bands at approximately 1250 cm⁻\u0026sup1; and 1070 cm⁻\u0026sup1; correspond to the asymmetrical and symmetrical stretching of C\u0026ndash;O\u0026ndash;C bonds.\u003c/p\u003e\n\u003cp\u003eThe spectrum obtained using 1% Amylase in deionized water, compared to that collected on the cotton swab, is characterized by more intense bands in the spectral region between 1500 and 1700 cm⁻\u0026sup1;, which appears with a broad peak. This range is related to stretching motions common in aromatic structures and in some phenolic and flavonoid substances frequently present in onion extracts. The band at the wavenumber of 1679 cm⁻\u0026sup1; is assigned to C=O stretching vibrations that are H-bonded. The band at the wavenumber of 1630 cm⁻\u0026sup1; is from the ring C=C stretch of phenyl, while the band at the wavenumber of 1559 cm⁻\u0026sup1; is due to the ring base. The band at the wavenumber of 1510 cm⁻\u0026sup1; is assigned to in-plane CH bending vibrations from the phenyl rings. This result highlights how the degradation of the polysaccharide structure by amylase, which catalyzes the hydrolysis of \u0026alpha;-1,4-glycosidic linkages, makes phenolic compounds more accessible, allowing for better observation of the spectral bands associated with these groups.\u003c/p\u003e\n\u003cp\u003eThe spectrum obtained from the swab using Nasier C03 exhibits a behaviour similar to that achieved with amylase, although the cleavage of glycosidic bonds and the corresponding release of phenolic groups are less pronounced.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ed) Cleaning of the painting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cleaning of the painting surface was performed using a 1% amylase solution gelled with Klucel\u0026reg; G (5 wt%), applied for 1 minute with two layers of Japanese paper interposed to facilitate the removal of excess gel (Figure 15).\u003c/p\u003e\n\u003cp\u003eThe procedure was repeated until the removal of the degraded coating was deemed satisfactory (Figure 21a-b). The most challenging aspect was achieving a uniform result by blending the over-cleaned area with the one still to be cleaned, while ensuring a gradual removal process. However, the darker colors on the left side of the face allowed for a smooth transition between the two areas, preventing damage to the paint layer.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAnalyses conducted using FTIR ATR spectroscopy, SEM/EDS, and optical microscopy identified and characterized the presence of onion residues on the surface of Giacomo Balla\u0026rsquo;s painting \u003cem\u003e\u0026ldquo;Portrait of a Man / Eugenio Riva.\u0026rdquo;\u003c/em\u003e These residues were attributed to a previous restoration intervention. While the use of onion in cleaning painted surfaces is recognized in the empirical practice of historical restoration, it has never been analytically documented in the literature. This study offers the first detailed chemical and morphological characterization of such a treatment.\u003c/p\u003e\n\u003cp\u003eSpecifically, optical and SEM/EDS microscopy images of sample S1 confirmed the morphological presence of plant tissue residues, while FTIR spectroscopy performed on the surface powder revealed characteristic bands of onion biochemical components. The primary bands observed included hydroxyl (-OH) stretching at 3289 cm⁻\u0026sup1;, methylene (CH\u003csub\u003e2\u003c/sub\u003e) stretching at 2849 and 2916 cm⁻\u0026sup1;, and asymmetric methyl (CH\u003csub\u003e3\u003c/sub\u003e) deformation stretching at 1405 cm⁻\u0026sup1;. Additional significant peaks included signals at 1734 cm⁻\u0026sup1;, attributed to carbonyl (C=O) ester groups, 1608 cm⁻\u0026sup1;, related to aromatic phenolic (C=C) groups, and 1008 cm⁻\u0026sup1;, corresponding to terminal alcohol groups (-CH₂OH) typical of carbohydrates.\u003c/p\u003e\n\u003cp\u003eThese results confirm the chemical composition of the onion layer, characterized by polysaccharides and phenolic compounds that contributed to chromatic degradation over time. Incomplete surface washing after the onion treatment left residues that aged and darkened the pictorial surface. The 1960 restoration revealed the difficulty of restoring the legibility of the painting. Interaction between the cleaning systems used at the time and the paint layer led restorers to limit cleaning to only half of the painting. Analysis indicated that this challenge was due to the extremely thin paint layer, as revealed by SEM/EDS.\u003c/p\u003e\n\u003cp\u003eThe painting technique in \u003cem\u003e\u0026ldquo;Portrait of a Man / Eugenio Riva\u0026rdquo;\u003c/em\u003e involves simple layering with few paint layers. The upper left area of the painting consists of a single preparatory layer applied across the entire surface by Balla. Elemental composition analysis of the white-grayish base layer, revealed by EDXRF and SEM/EDS, indicated the presence of zinc as the main element, suggesting the use of zinc white pigment to prime the canvas. Over this base, thin chromatic layers were applied, composed of the following pigments:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eGray (preparation of canvas layer): Zinc white and possibly a pigment undetectable via XRF and SEM/EDS, such as tenorite or carbon black.\u003c/li\u003e\n \u003cli\u003eBrown-green (signature): Organic pigment undetectable via XRF and SEM/EDS.\u003c/li\u003e\n \u003cli\u003eRed (color test in left area): Red earth containing Al, Si, Mg, and S, combined with Ca in all red layers analyzed by SEM/EDS; cinnabar; traces of cobalt blue and lead white.\u003c/li\u003e\n \u003cli\u003ePink (color test in left area): Red earth; cinnabar; lead white (used in higher quantities than in point 3 to lighten the tone); traces of cobalt blue.\u003c/li\u003e\n \u003cli\u003eLight blue (color test in left area): Cobalt blue; lead white.\u003c/li\u003e\n \u003cli\u003eDark blue (color test in left area): Cobalt blue; Prussian blue; barium sulfate as filler.\u003c/li\u003e\n \u003cli\u003eLight green (color test in left area): Chromium green oxide; lead white.\u003c/li\u003e\n \u003cli\u003eRed (color test in left area): Red earth; cinnabar; lead white.\u003c/li\u003e\n \u003cli\u003eBrown (brushstroke in left area): Organic pigment.\u003c/li\u003e\n \u003cli\u003eOrange (background): Red earth; cinnabar; cadmium yellow/orange; lead white.\u003c/li\u003e\n \u003cli\u003eReddish brown (background): Red earth; lead white.\u003c/li\u003e\n \u003cli\u003ePink (cheek): Red lake; lead white.\u003c/li\u003e\n \u003cli\u003ePink (facial skin color): Red lake; lead white.\u003c/li\u003e\n \u003cli\u003eBlack (pupil): Prussian blue; cobalt blue; lead white; traces of barium sulfate (filler).\u003c/li\u003e\n \u003cli\u003eGrayish pink (nostril): Cinnabar and possibly carbon black, undetectable via XRF and SEM/EDS.\u003c/li\u003e\n \u003cli\u003eWhite (collar): Lead white.\u003c/li\u003e\n \u003cli\u003eDark green (bow tie): Chromium green oxide.\u003c/li\u003e\n \u003cli\u003eBlue-green (jacket): Prussian blue; cobalt blue; chromium green oxide; traces of barium sulfate (filler).\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe results of EDXRF and SEM/EDS analyses correlate the detected pigments with those found in other works by Giacomo Balla. Lead white, cinnabar, ochres, red lake, cobalt blue, and Prussian blue\u0026mdash;often mixed\u0026mdash;were identified in \u003cem\u003e\u0026ldquo;Bambina coi fiori\u0026rdquo;\u003c/em\u003e (1902-1903). Zinc white, Prussian blue, chromium green oxide, ochres, and alizarin crimson were found in \u003cem\u003e\u0026ldquo;Grido di dimostrazione in piazza del Quirinale\u0026rdquo;\u003c/em\u003e (1915).\u003c/p\u003e\n\u003cp\u003eUV imaging confirmed the thinness of the paint layer, facilitating the identification of the white pigments used for the background and the central figure. Variations in fluorescence between the white collar and the pigment used for the background and certain facial details suggested the use of lead white and zinc white, respectively, as confirmed by EDXRF and SEM/EDS analyses.\u003c/p\u003e\n\u003cp\u003eThe study evaluated alternative methods to remove the vegetable residues without compromising the underlying paint layer. Enzymatic hydrolysis of polysaccharides using amylase solutions proved the most effective cleaning system. This enzyme, a hydrolase highly specific for \u0026alpha;-1,4-glycosidic bonds, enabled selective removal of the onion layer, producing degradation products that dissolved easily in the aqueous medium. However, the thinness of the paint layers poses risks, particularly in sensitive areas.\u003c/p\u003e\n\u003cp\u003eOptical microscopical observation and spectropolarimeter analysis revealed a more chromatically uniform surface, with significant darkening reduction achieved through amylase applications (in gel and liquid forms) and Nasier CO\u003csub\u003e3\u003c/sub\u003e.\u003c/p\u003e\n\u003cp\u003eAmong tested alternatives, commercial solvents like Nanorestore Cleaning\u0026reg; Polar Coating S and Polar Rescue Gel exhibited varying efficacy. The use of prevalidated products ensures compatibility with cultural heritage conservation standards. The cleaning efficacy of these systems was attributed to their polarity, as observed in FTIR spectra acquired from cleaning swabs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePolar Rescue Gel demonstrated a greater capacity to extract phenolic compounds with more hydrophobic characteristics, while Nanorestore Cleaning\u0026reg; Polar Coating S showed higher efficacy in removing polar phenolic components. Figure 22 highlights, in the Hansen solubility parameter diagram, the distance between the two solvents, illustrating how Cleaning\u0026reg; Polar Coating S is characterized by higher polarity compared to Polar Rescue Gel and a broader solubility range.\u003c/p\u003e\n\u003cp\u003eIn synthesis, enzyme-based formulations, specifically amylase solutions, proved to be highly specific and safe for preserving original paint layers, offering a non-toxic and selective tool for the removal of specific materials from cultural heritage artifacts. While polar solvents exhibited lower overall cleaning efficiency, they effectively solubilized onion residues through their interaction with the phenolic components of the onion.\u003c/p\u003e"},{"header":"5. Conclusion ","content":"\u003cp\u003eThe restoration of Giacomo Balla\u0026apos;s\u0026nbsp;\u003cem\u003eRitratto d\u0026rsquo;uomo / Eugenio Riva\u003c/em\u003e highlights the intricate challenges posed by historical restoration practices and the opportunities presented by modern scientific techniques. The discovery of onion residues, a byproduct of earlier cleaning attempts, underscored the impact of empirically driven methods on the long-term condition of cultural artifacts. Advanced analytical tools documented the morphological effects of these residues, revealing their contribution to chromatic alterations that affected the painting\u0026apos;s readability over time.\u003c/p\u003e\n\u003cp\u003eEnzyme-based cleaning formulations, particularly amylase solutions, proved to be the most effective and non-invasive approach for addressing these residues. The complementary use of polar solvent systems, guided by Hansen solubility parameters, emphasized an alternative approach to enzymatic solutions, especially valuable for paintings with exceptionally thin paint layers.\u003c/p\u003e\n\u003cp\u003eUltimately, this intervention not only restored the visual harmony of the painting but also established a replicable framework for addressing complex restoration challenges. By bridging the disciplines of scientific innovation, art history, and conservation, this study contributes to a deeper understanding of preserving the integrity and legacy of cultural heritage. The multidisciplinary methodology serves as a guide for future restorations, emphasizing the importance of integrating empirical evidence with advanced solutions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e6. Acknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article is the outcome of a collaborative project between YOCOCU and the Galleria Nazionale. The experimental work is also part of the PhD program in Earth Sciences (Curriculum: \"Environment and Cultural Heritage\") carried out by Chiara Biribicchi at the University of Rome \"La Sapienza\". Chiara provided input during the early stages of the interpretation of results but chose not to be involved in the final publication. The authors express their gratitude to Chiara for her contributions to the project. They also extend their thanks to YOCOCU APS for providing materials and to the Director of the Galleria Nazionale of Rome for enabling the project's development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7. Availability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this study, including all quantitative and qualitative datasets, are available upon reasonable request from the corresponding author. All human figure images included in this manuscript have been anonymized and are presented with appropriate permissions in compliance with ethical and legal standards. Additional raw data that support the findings are provided in supplementary materials or can be accessed under specific conditions, as outlined in the repository linked to this publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, A.M.; methodology, A.M. and P.C; validation, M.C.; investigation, A.M. and T.C.; resources, P.C. and A.M.; data curation, A.M.; writing—original draft preparation, A.M.; writing—review and editing, T.C.. and A.M.; supervision, A.M.; project administration, A.M. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings:\u003c/strong\u003e The authors did not receive support from any organization for the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial and non-financial interest:\u0026nbsp;\u003c/strong\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eF. Benzi, \u003cem\u003eGiacomo Balla. Genio Futurista\u003c/em\u003e, Electa, Milan, 2007.\u003c/li\u003e\n\u003cli\u003eL.M. Cupini, P. 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La Russa, Multi-Analytical Investigation of the Oil Painting \u0026ldquo;Il Venditore di Cerini\u0026rdquo; by Antonio Mancini and Definition of the Best Green Cleaning Treatment, Sustainability (Switzerland). 14 (2022). https://doi.org/10.3390/su14073972.\u003c/li\u003e\n\u003cli\u003eA. Macchia, E. Cerafogli, L. Rivaroli, I.A. Colasanti, H. Aureli, C. Biribicchi, V. Brunori, Marble Chromatic Alteration Study Using Non-Invasive Analytical Techniques and Evaluation of the Most Suitable Cleaning Treatment: The Case of a Bust Representing Queen Margherita di Savoia at the U.S. Embassy in Rome, Analytica. 3 (2022) 406\u0026ndash;429. https://doi.org/10.3390/analytica3040028.\u003c/li\u003e\n\u003cli\u003eArslanoglu, T. Learner, The evaluation of Laropal A81: Paraloid B‐72 polymer blend varnishes for painted and decorative surfaces \u0026ndash; appearance and practical considerations, The Conservator. 25 (2001) 62\u0026ndash;72. https://doi.org/10.1080/01410096.2001.9995165.\u003c/li\u003e\n\u003cli\u003eVickramjeet Singh, Shikha Indoria, K.J. Jisha, Ramesh L. Gardas. Structure and Solubility of Polysaccharides - Polysaccharides - Wiley Online Library 2021 https://doi.org/10.1002/9781119711414.ch15\u003c/li\u003e\n\u003cli\u003eM. Verma, C. Charan Singh, S.S. Jeet Singh, N.M. Rose, Phytochemical screening of onion skin (Allium cepa) dye extract, ~ 1414 ~ Journal of Pharmacognosy and Phytochemistry. 7 (2018).\u003c/li\u003e\n\u003cli\u003eX. Lu, C.F. Ross, J.R. Powers, B.A. Rasco, Determination of quercetins in onion (Allium cepa) using infrared spectroscopy, J Agric Food Chem. 59 (2011) 6376\u0026ndash;6382. https://doi.org/10.1021/jf200953z.\u003c/li\u003e\n\u003cli\u003eH. Schulz, M. Baranska, Identification and quantification of valuable plant substances by IR and Raman spectroscopy, Vib Spectrosc. 43 (2007) 13\u0026ndash;25. https://doi.org/10.1016/j.vibspec.2006.06.001.\u003c/li\u003e\n\u003cli\u003eX. Lu, M. Webb, M. Talbott, J. Van Eenennaam, A. Palumbo, J. Linares-Casenave, S. Doroshov, P. Struffenegger, B. Rasco, Distinguishing ovarian maturity of farmed white sturgeon (Acipenser transmontanus) by fourier transform infrared spectroscopy: A potential tool for caviar production management, J Agric Food Chem. 58 (2010) 4056\u0026ndash;4064. https://doi.org/10.1021/jf9038502.\u003c/li\u003e\n\u003cli\u003eZ. Movasaghi, S. Rehman, I.U. Rehman, Fourier transform infrared (FTIR) spectroscopy of biological tissues, Appl Spectrosc Rev. 43 (2008) 134\u0026ndash;179. https://doi.org/10.1080/05704920701829043.\u003c/li\u003e\n\u003cli\u003eV. Lanzotti, The analysis of onion and garlic, J Chromatogr A. 1112 (2006) 3\u0026ndash;22. https://doi.org/10.1016/j.chroma.2005.12.016.\u003c/li\u003e\n\u003cli\u003eJ. Arslanoglu, T. Learner, The evaluation of Laropal A81: Paraloid B‐72 polymer blend varnishes for painted and decorative surfaces \u0026ndash; appearance and practical considerations, The Conservator. 25 (2001) 62\u0026ndash;72. https://doi.org/10.1080/01410096.2001.9995165.\u003c/li\u003e\n\u003cli\u003eA. Phenix, J. Townsend, A brief survey of historical varnishes, in: Conservation of Easel Paintings, Routledge, Abingdon, 2012: pp. 252\u0026ndash;263.\u003c/li\u003e\n\u003cli\u003eE. Rene De La Rie, C.W. Mcglinchey, New synthetic resins for picture varnishes, Studies in Conservation, 1990, 35, 168-173 https://api.semanticscholar.org/CorpusID:93447154}\u003c/li\u003e\n\u003cli\u003eJ.K. Delaney, M. Thoury, J.G. Zeibel, P. Ricciardi, K.M. Morales, K.A. 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De Viguerie, V.A. Sole, P. Walter, Multilayers quantitative X-ray fluorescence analysis applied to easel paintings, in: Anal Bioanal Chem, 2009: pp. 2015\u0026ndash;2020. https://doi.org/10.1007/s00216-009-2997-0.\u003c/li\u003e\n\u003cli\u003eA. Macchia, L.M. Schuberthan, D. Ferro, I.A. Colasanti, S. Montorsi, C. Biribicchi, F.I. Barbaccia, M.F. La Russa, Analytical Investigations of XIX\u0026ndash;XX Century Paints: The Study of Two Vehicles from the Museum for Communications of Frankfurt, Molecules. 28 (2023). https://doi.org/10.3390/molecules28052197.\u003c/li\u003e\n\u003cli\u003eR. Slimestad, T. Fossen, I.M. V\u0026aring;gen, Onions: A source of unique dietary flavonoids, J Agric Food Chem. 55 (2007) 10067\u0026ndash;10080. https://doi.org/10.1021/jf0712503.\u003c/li\u003e\n\u003cli\u003eElisa Boccalon, Gianluca Viscusi, Elena Lamberti, Francesco Fancello, Severino Zara, Paola Sassi, Maura Marinozzi, Morena Nocchetti, Giuliana Gorrasi, Composite films containing red onion skin extract as intelligent pH indicators for food packaging, Applied Surface Science, Volume 593, 2022, 153319, ISSN 0169-4332, https://doi.org/10.1016/j.apsusc.2022.153319.\u003c/li\u003e\n\u003cli\u003eLu, X, Wang, J, Al-Qadiri, HM, Ross, CF, Powers, JR, Tang, J, Rasco, BA: Determination of total phenolic content and antioxidant capacity of onion (Allium cepa) and shallot (Allium oschaninii) using infrared spectroscopy. Food Chem. 129, 637\u0026ndash;644 (2011)\u003c/li\u003e\n\u003cli\u003eH. Peng, X. Zhang, J. Xu. Apigenin-7-O-\u0026beta;-D-glycoside isolation from the highly copper-tolerant plant Elsholtzia splendens. Journal of Zhejiang University-SCIENCE B (Biomedicine \u0026amp; Biotechnology), 17 (6) (2016), pp. 447-454, 10.1631/jzus.B1500242\u003c/li\u003e\n\u003cli\u003eHeitor Ribeiro da Silva, Daniele da Cruz de Assis, Ariadna Lafourcade Prada, Jos\u0026eacute; Ot\u0026aacute;vio Carrera Silva, Mayara Brito de Sousa, Adriana Maciel Ferreira, Jesus Rafael Rodr\u0026iacute;guez Amado, Helison de Oliveira Carvalho, Abrah\u0026atilde;o Victor Tavares de Lima Teixeira dos Santos, Jos\u0026eacute; Carlos Tavares Carvalho. Obtaining and characterization of anthocyanins from Euterpe oleracea (a\u0026ccedil;a\u0026iacute;) dry extract for nutraceutical and food preparations. Revista Brasileira de Farmacognosia, Volume 29, Issue 5, 2019, Pages 677-685, ISSN 0102-695X, https://doi.org/10.1016/j.bjp.2019.03.004.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"onion, polysaccharides, paintings, cleaning, green solvents, enzyme, Giacomo Balla","lastPublishedDoi":"10.21203/rs.3.rs-5633755/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5633755/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe restoration of Giacomo Balla\u0026rsquo;s \u003cem\u003eRitratto d\u0026rsquo;uomo / Eugenio Riva\u003c/em\u003e has unveiled unexpected insights into the intersection of historical restoration practices and modern scientific techniques. This study documents the discovery and analysis of onion residues on the painting's surface, attributed to a mid-20th-century cleaning attempt. Leveraging cutting-edge analytical tools\u0026mdash;such as FTIR ATR spectroscopy, SEM/EDS, and UV imaging\u0026mdash;researchers explored the chemical and morphological effects of this unconventional treatment. Additionally, the article highlights innovative solutions, including enzymatic cleaning formulations and polar solvent systems, which were employed to safely restore the artwork. This multidisciplinary approach not only restored the painting\u0026rsquo;s aesthetic coherence but also contributed to the broader understanding of restoration challenges posed by historical interventions\u003c/p\u003e","manuscriptTitle":"Revealing and cleaning of an onion layer: scientific Insights into the Restoration of Giacomo Balla’s \"Ritratto d’uomo / Eugenio Riva\"","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-26 20:32:44","doi":"10.21203/rs.3.rs-5633755/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"168c6b96-24ab-4953-98d7-c1f78870087d","owner":[],"postedDate":"December 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-13T21:38:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-26 20:32:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5633755","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5633755","identity":"rs-5633755","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}