To commemorate the 500th anniversary of Raphael's death, the Galleria Borghese in Rome utilized reflective Hyperspectral Imaging (HSI) combined with Macro X-ray Fluorescence (MA-XRF) to complete a full-frame, sub-millimeter non-destructive inspection of the Renaissance masterpiece "The Deposition" (Baglioni Entombment). This technology is like giving a famous painting a "non-invasive spectral CT scan," penetrating the pigment layers to reveal underdrawings, traces of modification, and pigment codes hidden for over 500 years, allowing us to understand the master's entire creative process.     I. What is Hyperspectral Imaging?   Hyperspectral imaging, simply put, is a "two-in-one" of "imaging + spectroscopy." It doesn't just capture a picture; it records the complete spectral information of every pixel from visible light to short-wave infrared (400–1700 nm), turning an ordinary photo into a three-dimensional data cube available for deep analysis.   The Visible-Near Infrared-Shortwave Infrared hyperspectral scanner used in this study was specifically designed for cultural relics: it adopts push-broom scanning with extremely high resolution, and the illumination is concentrated only on a narrow area, causing almost no damage to the painting; even when facing curved wooden panels, clear imaging can be guaranteed through optical correction. The research team scanned the entire painting in 8 segments and then precisely stitched them together to obtain ultra-large spectral data, achieving full-frame, zero-dead-angle analysis, completely moving away from the limitations of traditional single-point sampling.   II. Seeing Raphael's "Invisible Creations"   The greatest capability of hyperspectral imaging is seeing underlying information invisible to the naked eye. With the help of algorithms such as Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) to process spectral data, "invisible content" within the frame emerges one by one.   In the background sky, spectral processing unexpectedly discovered covered early landscapes: originally clearly outlined trees and vegetation were later softened by Raphael to blend into the blue sky, making the space feel more profound; the shapes of the mountains also changed from sharp to rounded. These traces of modification in the middle pigment layers are key evidence difficult to capture with traditional infrared or X-rays, directly restoring the master's composition adjustment process.   Even more startling is the underlying sketch. Traditional infrared reflectography can only see carbon-based lines clearly, while hyperspectral imaging—by selecting optimal infrared bands and synthesizing false-color images—clearly presents finer underdrawings: hatching on the male characters' faces and heavy outlines on the Virgin Mary's cheeks and lips, which were previously completely hidden. This proves that Raphael's underdrawings were completed in multiple stages using different materials, making the creative process far more complex than imagined.     III. Hyperspectral + XRF Cracks the Red Pigment Code   Hyperspectral imaging alone cannot fully determine pigment components; when used in conjunction with MA-XRF, they form a "molecular spectroscopy + elemental analysis" golden duo, precisely cracking the core red code of this painting.     Researchers used Spectral Angle Mapping (SAM) to divide the red into three types of spectral characteristics: two types corresponding to red lakes and one type corresponding to vermilion. Then, by cross-referencing the element distribution map from X-ray fluorescence: mercury (Hg) signals only appeared in the vermilion areas, potassium (K) signals confirmed the red lakes, and iron (Fe) was unrelated to the red, excluding iron oxide red.     Ultimately, it was confirmed: Raphael used only two red materials, vermilion and red lake, and used three techniques—single-layer thick application, multi-layer glazing, and red lake over vermilion—to create rich layers. Only the core figure, Grifonetto, used "vermilion base + red lake glazing" to highlight his status. This rigorous yet ingenious way of using color was revealed completely for the first time.   IV. The Future Core Technology of Cultural Relic Protection   This cross-border cooperation between technology and art fully demonstrates the unique value of hyperspectral imaging in cultural relic protection: completely non-destructive, deep penetration, global analysis, and data archivability.   It requires no sampling and no damage to the painting to excavate underdrawings, layering, pigments, and restoration traces, becoming a standard tool for museum research, restoration, and digital protection.   From invisible underdrawings to covered compositions and then to precise pigment formulas, hyperspectral imaging lets masterpieces "speak" their creative stories. It is not just a cutting-edge technology, but a bridge connecting art history and materials science, protecting and decoding mankind's most precious cultural heritage in the gentlest way.

In the sesame processing industry, mechanized harvesting has become a key means to improve production efficiency. However, seed damage generated during the mechanized harvesting process directly affects the quality characteristics of subsequent sesame oil and sesame paste. Color, as a core indicator of product sensory quality, not only affects consumers' willingness to purchase but also directly reflects the quality of raw materials and the stability of processing technology. Research shows that mechanical harvesting damage accelerates lipid oxidation during sesame storage, leading to a darker, more yellowish, and reddish color in sesame oil, while sesame paste exhibits a lighter color and increased fluctuations in color difference. Traditional manual sensory evaluation methods are heavily influenced by subjective factors, making it difficult to quantify color differences and unable to meet the requirements for quality consistency in large-scale production. In addition, the color of sesame products is closely related to factors such as roasting degree and storage time, requiring precise detection tools to capture subtle color changes. CHNSpec Technology's CS-821N spectrophotometer adopts the principle of spectral color measurement, which can objectively output color parameters such as L, a, and b, transforming visual perception into quantifiable data. This provides a scientific color control solution for sesame processing enterprises, helping them stabilize product quality and optimize production processes.   I. Objectively quantifying the subtle color differences of sesame oil   In order to objectively and accurately evaluate the color differences of sesame oil, researchers used the CHNSpec Technology CS-821N spectrophotometer. The instrument is based on the colorimetric system recommended by the CIE (International Commission on Illumination). By measuring the spectral data of the sample's reflection or transmission, it calculates the precise value in the color space.   In this study, the CS-821N was used to detect the color parameters of all sesame oil samples. The specific operations are as follows:   1.Sample preparation: Sesame oil samples were made from mechanically harvested sesame and manually harvested sesame with different storage periods respectively.   2.Color measurement: Using the CS-821N spectrophotometer under standard light source conditions, the L, a, and b values of each oil sample were measured. Among them:   L value represents lightness; a larger value indicates a whiter and brighter color. a value represents red-green degree; a positive value indicates a reddish tint, and a negative value indicates a greenish tint. b value represents yellow-blue degree; a positive value indicates a yellowish tint, and a negative value indicates a bluish tint.   Through this method, researchers obtained precise and repeatable color data, avoiding the subjectivity of naked-eye observation and providing a solid foundation for subsequent data analysis and conclusions.   II. Color change laws revealed by CS-821N   Experimental data clearly revealed the influence of different processing raw materials on the color of sesame oil through the measurement results of the CS-821N:   1.Mechanical harvesting leads to deeper color: Compared with manually harvested sesame, the sesame oil produced from mechanically harvested sesame generally has lower L values and higher a and b values. This indicates that the sesame oil made from mechanically harvested sesame is darker in color and tends toward red and yellow tones. This may be because mechanical harvesting damage leads to the rupture of the sesame seed coat. During the roasting process, the internal sesame kernels can contact heat more directly, resulting in a more sufficient Maillard reaction, thus forming a deeper color.   2.The trend of color change can be quantified: In subsequent accelerated storage experiments, the CS-821N also captured the dynamic changes in the color of sesame oil during the storage process. The L values of all oil samples decreased with the extension of storage time, and the a values increased, manifesting as a further deepening and reddening of the color. The precise values provided by the CS-821N enabled researchers to objectively describe the appearance changes during this oxidation process.     III. Application value   The application of the CHNSpec CS-821N spectrophotometer in the sesame processing industry has realized the transformation of color evaluation from subjective to objective. Through quantified color data, enterprises can precisely control the quality of raw materials, optimize processing technology, and stabilize the quality of finished products, effectively responding to the quality fluctuation challenges brought by the processing of mechanically harvested sesame. The instrument's characteristics of convenient operation and efficient detection adapt to the rapid detection needs of production lines, while the data traceability function provides strong support for corporate quality management.   In the sesame processing industry pursuing quality standardization, the CHNSpec CS-821N spectrophotometer, with its precise detection performance, has become an important tool for enterprises to control the sensory quality of products, helping the industry achieve the dual goals of large-scale production and stable quality.