UV-induced Fluorescence Imaging Research Articles

Unraveling the Olmec rubber balls from El Manatí, Mexico: a technological and compositional analysis

This work presents an analysis towards a description of the manufacturing technique of the Olmec rubber balls found at the offerings at El Manatí. The results present this procedure from the extraction of the Mesoamerican rubber from the Castilla elastica tree, discussing its composition and origin of the rubber balls analyzed towards the production of strips that are rolled to make the ball round form. This characterization was achieved through a series of imaging techniques (radiography imaging, UV-induced fluorescence imaging, and optical microscopy) and portable non-destructive and non-invasive analyses (XRF and FTIR) performed on the collection of archaeological rubber balls and compared with contemporary made rubber balls in the region near El Manatí. The methodology was complemented with laboratory chemical analytical techniques (13C NMR-MAS, FTIR, CEA, and GC-MS) applied to selected Olmec rubber microsamples. The new physical and chemical data obtained was also interpreted considering conservation science, to help understand the alterations and transformation processes that the balls have undergone since their recovery in the 1980s.

Predicting piperine content in javanese long pepper using fluorescence imaging and machine learning model

The conventional method for determining piperine content involves a series of labor-intensive steps, including drying the pepper samples, grinding them, and then extracting them using high-grade ethanol through a reflux method. While effective, this process is time-consuming and resource-intensive, posing limitations in terms of efficiency and the ability to address potential variations. Therefore, there is an urgent need to explore more efficient and rapid approaches for accurately measuring and predicting piperine content, with machine learning approach. This research aims to explore the potential of using fluorescence imaging methods and ANN models to increase the efficiency of measuring piperine content on Javanese long pepper. We propose a machine learning approach using UV-induced fluorescence imaging of Javanese long pepper. UV LEDs (365 nm) induced fluorescence, with color variation indicating piperine content. An artificial neural network (ANN) model, trained on color texture features from fluorescence images, predicted piperine content, achieving an R2 value of 0.88025 with ten selected features using the One-R attribute. The final ANN, configured with 'trainoss' learning, 'tansig' activation, 0.1 learning rate, and 10-40-10 nodes, demonstrated a testing R2 of 0.8943 and MSE of 0.0875. LED-induced fluorescence enhances machine learning's piperine content prediction. This research contributes to more efficient piperine content measurement methods.

Non-destructive prediction of TVB-N using color-texture features of UV-induced fluorescence image for freeze-thaw treated frozen-whole-round tilapia.

The investigation of UV-induced fluorescence imaging coupled with machine learning was conducted to non-destructively detect the total volatile basic nitrogen (TVB-N) of frozen-whole-round tilapia (FWRT) during freezing and thawing. The UV-induced fluorescence images of FWRT at the wavelength of 365 nm were acquired by self-developed fluorescence image acquisition system. In total, 169 color and texture features based on RGB, hue-saturation-intensity and L*a*b* color spaces and gray level co-occurrence matrix were extracted, respectively. Successive projections algorithm (SPA) was employed to select the optimal 16 features to achieve feature dimension reduction modeling. With full and extracted features as input, the models of partial least squares regression (PLSR), least-squares support vector machine (LSSVM) and convolutional neural network (CNN) were established for TVB-N prediction. Results indicated that the full features-based CNN performed better than SPA based prediction models (SPA-PLSR and SPA-LSSVM). The CNN model was determined to be the optimal with an RP2 value of 0.9779, RMSEP value of 1.1502 × 10-2 g N kg-1 and RPD value of 6.721 for TVB-N content predictiin. The CNN method based on UV fluorescence imaging technology has potential for quality and safety detection of FWRT. © 2023 Society of Chemical Industry.

Macroscopic and microscopic characterization of fluorescence properties of multiple sweet pepper cultivars (Capsicum annuum L.) using excitation-emission matrix and UV induced fluorescence imaging

Sweet peppers are a popular vegetable with various surface colors, such as green, purple, red, or yellow. To characterize the unique fluorescence properties associated with a broad range of sweet peppers of various colors (14 varieties), a fluorescence spectrofluorometer and imaging were used. The results showed that all cultivars in the experiment had blue fluorescence emissions when excited with light in the UV-A region, while chlorophyll fluorescence could be observed in green peppers. The emitted blue fluorescence originated from the epidermis (cuticle layer). The color distribution of these sweet peppers in the a* and b* color space were compared to the image obtained under white LED light. Yellow and red pepper cultivars have thicker, multiple cuticular wax layers and more distinct maturity stages than other sweet pepper varieties observed. With the establishment of this basic fluorescence database, further applications of fluorescence-based techniques and the unification of evaluation methods for pepper quality will be more easily established.

New Insights on the Stradivari “Coristo” Mandolin: A Combined Non-Invasive Spectroscopic Approach

In this work, one of the two existing mandolins made by Antonio Stradivari has been investigated for the first time, as a rare exemplar of the lesser-known class of plucked string instruments. The mandolin was studied by non-invasive reflection Fourier transformed infrared (FT-IR) spectroscopy and X-ray fluorescence (XRF) on different areas previously selected by UV-induced fluorescence imaging. The analytical campaign was aimed at (i) identifying the materials used by Stradivari in the finishing of the mandolin, (ii) comparing these materials with those traditionally used in violin making, and (iii) increasing the knowledge of materials and techniques applied by Stradivari in the rare production of plucked string instruments. The combined spectroscopic approach allowed us to hypothesize original materials and finishing procedures similar to those used in violin making: a possible sizing treatment of the wood with protein-based materials and silicates, externally coated with an oil–resin varnish. XRF results were essential to support FT-IR findings and to detect possible iron-based pigments in the finishing layers. Moreover, it permitted us to distinguish original areas from the restored areas, including the purflings on the top plate and the varnished area on the treble side of the mandolin for which the originality was assumed.

Potential of front face fluorescence spectroscopy and fluorescence imaging in discriminating adulterated extra-virgin olive oil with virgin olive oil

Due to the health benefits of extra virgin olive oil (EVOO) and its increasing consumption patterns, adulteration of these oils using lower grade olive oils like virgin olive oil (VOO) and then later sold as EVOO to unsuspecting consumers has become a concern in the industry. There is a need for quick, reliable and inexpensive detection techniques to unmask such vice in order to realize its benefits. In this study, adulteration of EVOO is made using VOO at different proportions; their Excitation Emission Matrices (EEM) were examined using Front-face fluorescence spectroscopy and their corresponding fluorescence images captured using 365 nm ultra-violet (UV) LED for analysis. Specific regions for both the EEM and imaging were explored using Support Vector Machine (SVM) classification analysis and their sensitivities evaluated using Partial Least Squares Regression (PLSR) analysis. It was found that EEM excitation 230–500 and emission 260–620 nm could easily discriminate between different samples as EVOO mixed (at different ratios) and VOO. The significant fluorescence peaks for the discrimination forms a combination of Tocopherols, Tocotrienols, Phenolic compounds, Oxidation products and Vitamin E. The results show that Front-face fluorescence spectroscopy and UV-induced fluorescence imaging can potentially discriminate between pure EVOO and adulterated olive oils.

Monitoring mature tomato (red stage) quality during storage using ultraviolet-induced visible fluorescence image

The potential of UV-induced fluorescence imaging was investigated as a non-destructive tool to monitor postharvest quality degradation of tomatoes harvested at the red stage and stored at 25 °C. The fluorescence images (excitation at 365 nm) were found to be a better indicator of tomato quality degradation than color images after color saturation. Tomatoes were stored at 25 °C for 9 d. The changes in color and fluorescence of tomato were evaluated by two types of images: Color and fluorescence images. A conventional colorimeter was also used for as a reference. Changes in the RGB ratio for these two types of images were opposite. In the color images, the G ratio decreased rapidly for the initial 3 or 5 d and then stabilized afterwards. On the other hand, in the fluorescence images, the G ratio increased continuously up to 9 d. Given that temperature conditions during transportation and storage of tomatoes is not always ideal, the results from this research provide the foundation for developing a postharvest monitoring system of mature tomato quality degradation.

Construction and comparison of 3D multi-source multi-band models for cultural heritage applications

Abstract 3D multi-band/multi-spectral reconstruction is a technique, which allows the use of images taken in different spectral bands for the reconstruction of spectrally-resolved 3D models of paintings. In this work, we propose a procedure for constructing and comparing 3D multi-band models obtained starting from a variety of input data (RGB and IR images, UV-induced fluorescence images, etc.) and/or acquired with different instruments. The procedure has been tested on two case studies, with the aim to highlight the critical issues associated to the specificities of the subject and of the environmental constrains: a 14th century panel painting signed by Barnaba from Modena, preserved at the Museum of San Matteo in Pisa, Italy and a 15th century panel painting preserved at the Regional Gallery of Palazzo Bellomo in Syracuse, Italy. RGB, IR and UV–VIS fluorescence models obtained with a conventional digital camera (RGB and UV) and a multisband camera (IR) were realized and compared, for revealing differences at sub-millimeter level.

Detection of Cotton Lint Trash within the Ultraviolet—Visible Spectral Range

Cotton lint trash is a serious problem in the textile industry. The principle upon which this research is based is that different materials have different spectral absorption, excitation, and emission characteristics. Although white-light imaging is widely used to detect colored foreign-matter contaminants, or "trash", it is almost useless for detecting white trash. The objective of the research described in this paper was to achieve the best trash detection result possible in the spectral range from 250 to 850 nm. Diffuse reflection spectroscopy indicated that the differences in gray value between lint and white trash become significant in the ultraviolet (UV) range, especially from 250 to 350 nm. Fluorescence spectroscopy gave reliable evidence that the UV-induced fluorescence intensity of white trash is much stronger than that of lint. To detect several types of trash simultaneously, the interaction of white-light imaging and UV-induced fluorescence imaging was studied. To avoid the spectral interference caused by white light in fluorescence imaging, a novel method--an alternating imaging detection method--is proposed. Experiments indicated that the advantages of both white-light imaging and UV-induced fluorescence imaging were preserved in the method. The novel method could effectively detect both colored and white trash in real time. This method can also be applied to trash detection in seed cotton, wool, tea leaf, and tobacco leaf.