CIELAB Color Research Articles

Target-distractor similarity predicts visual search efficiency but only for highly similar features.

A major constraining factor for attentional selection is the similarity between targets and distractors. When similarity is low, target items can be identified quickly and efficiently, whereas high similarity can incur large costs on processing speed. Models of visual search contrast a fast, efficient parallel stage with a slow serial processing stage where search times are strongly modulated by the number of distractors in the display. In particular, recent work has argued that the magnitude of search slopes should be inversely proportional to target-distractor similarity. Here, we assessed the relationship between target-distractor similarity and search slopes. In our visual search tasks, participants detected an oddball color target among distractors (Experiments 1 & 2) or discriminated the direction of a triangle in the oddball color (Experiment 3). We systematically varied the similarity between target and distractor colors (along a circular CIELAB color wheel) and the number of distractors in the search array, finding logarithmic search slopes that were inversely proportional to the number of items in the array. Surprisingly, we also found that searches were highly efficient (i.e., near-zero slopes) for targets and distractors that were extremely similar (≤20° in color space). These findings indicate that visual search is systematically influenced by target-distractor similarity across different processing stages. Importantly, we found that search can be highly efficient and entirely unaffected by the number of distractors despite high perceptual similarity, in contrast to the general assumption that high similarity must lead to slow and serial search behavior.

High-performance semi-transparent organic solar cells for window applications using MoO3/Ag/MoO3 transparent anodes

The optimization of semi-transparent organic solar cells involves balancing average visible transparency (AVT) and power conversion efficiency (PCE). We propose enhancing ST-OSC performance by replacing the conventional opaque Ag electrode with a MoO3/Ag/MoO3 as a dielectric/metal/dielectric (DMD) layer structure, explored theoretically and experimentally. A prototype ST-OSC configuration, comprising ITO/ZnO/P3HT: PCBM/MoO3/Ag/MoO3, was fabricated with varying thicknesses of the MoO3/Ag/MoO3 layer, determined through theoretical calculations utilizing MATLAB software. This study investigates the impact of metal layer thickness on two active layer densities (10 and 18 mg/mL) and evaluates AVT, color rendering index, Correlated Color Temperature, and CIELAB color coordinates (a*, b*). Both theoretical calculations and experimental results confirm that the optimized configuration of the DMD structure with specific layer thicknesses for each component (MoO3 = 10nm/Ag = 6nm/MoO3 = 30 nm) achieves an AVT of over 59.60 %. This high level of transparency makes this configuration suitable for applications requiring both high transparency and efficient light transmission. The optimized device delivered high-quality light transmission, approaching white perception to the human eye. This combined approach validates empirical results and provides a deeper understanding of transparent OSC mechanisms.

Comparative Evaluation of Mechanical Properties and Color Stability of Dental Resin Composites for Chairside Provisional Restorations.

Resin composites have become the preferred choice for chairside provisional dental restorations. However, these materials may undergo discoloration, changes in surface roughness, and mechanical properties with aging in the oral cavity, compromising the aesthetics, functionality, and success of dental restorations. To investigate the color and mechanical stability of chairside provisional composite resins, this study evaluated the optical, surface, and mechanical properties of four temporary restoration resin materials before and after aging, stimulated by thermal cycling in double-distilled water. Measurements, including CIE LAB color analysis, three-point bending test, nanoindentation, scanning electron microscopy (SEM), and atomic force microscopy (AFM), were conducted (n = 15). Results showed significant differences among the materials in terms of optical, surface, and mechanical properties. Revotek LC (urethane dimethacrylate) demonstrated excellent color stability (ΔE00 = 0.53-Black/0.32-White), while Artificial Teeth Resin (polymethyl methacrylate) exhibited increased mechanical strength with aging (p < 0.05, FS = 68.40 MPa-non aging/87.21 MPa-aging). Structur 2 SC (Bis-acrylic) and Luxatemp automix plus (methyl methacrylate bis-acrylate) demonstrated moderate stability in optical and mechanical properties (Structur 2 SC: ΔE00 = 1.97-Black/1.38-White FS = 63.20 MPa-non aging/50.07 MPa-aging) (Luxatemp automix plus: ΔE00 = 2.49-Black/1.77-White FS = 87.72 MPa-non aging/83.93 MPa-aging). These results provide important practical guidance for clinical practitioners, as well as significant theoretical and experimental bases for the selection of restorative composite resins.

Utilizing color analysis and image processing for the assessment of the color of block para rubber

This research explores the use of image processing and color analysis as a reliable approach for evaluating para rubber color quality. An automated color comparator prototype, based on the CIELAB color method and employing various image processing algorithms, is introduced. The research aims to enhance the precision of color analysis for block para rubbers (BPRs), a critical raw material in the rubber industry, impacted by environmental conditions during the sun-drying process. The study follows international standards for BPR specimen preparation and employs an image acquisition system, threshold techniques, and algorithms for color analysis. The proposed method aligns with Rubber Research Institute standards. The outcomes demonstrate the effectiveness of the automated system in accurately assessing the color values of BPRs, providing valuable insights for the rubber industry. This image processing technique offers advantages in natural rubber production for products requiring specific color characteristics.

Deciphering Rind Color Heterogeneity of Smear-Ripened Munster Cheese and Its Association with Microbiota.

Color is one of the first criteria to assess the quality of cheese. However, very limited data are available on the color heterogeneity of the rind and its relationship with microbial community structure. In this study, the color of a wide range of smear-ripened Munster cheeses from various origins was monitored during storage by photographic imaging and data analysis in the CIELAB color space using luminance, chroma, and hue angle as descriptors. Different levels of inter- and intra-cheese heterogeneity were observed. The most heterogeneous Munster cheeses were the darkest with orange-red colors. The most homogeneous were the brightest with yellow-orange. K-means clustering revealed three clusters distinguished by their color heterogeneity. Color analysis coupled with metabarcoding showed that rinds with heterogeneous color exhibited higher microbial diversity associated with important changes in their microbial community structure during storage. In addition, intra-cheese community structure fluctuations were associated with heterogeneity in rind color. The species Glutamicibacter arilaitensis and Psychrobacter nivimaris/piscatorii were found to be positively associated with the presence of undesirable brown patches. This study highlights the close relationship between the heterogeneity of the cheese rind and its microbiota.

Natural Dyeing of Cotton, Wool and Viscose Fabrics with Sodium Copper Chlorophyllin

This study investigates the optimal dyeing concentrations of cotton, wool, and viscose fabrics with sodium copper chlorophyllin (SCC). Using SSC above the optimal concentration increases the amount of SCC in the wastewater, which is a disadvantage. Pre-finished 100% cotton, wool and viscose 1 x 1 rib knitted fabrics were dyed with varying SCC concentrations. Optimal dyeing concentrations were determined using UV-Vis spectrophotometry, showing dye absorption decreasing as SCC concentration increases. Equilibrium was reached at approximately 7 ml/L for cotton and viscose, and 3 ml/L for wool. Color measurement values and K/S values of the dyed samples were obtained according to the CIELab color system. The K/S values of dyed cotton, viscose, and wool fabrics rose as the concentration of SCC increased, reaching a peak at 9 ml/L for viscose and 12 ml/L for cotton and wool. Rubbing and perspiration fastness were rated good to excellent.

Colour difference detection algorithm for warp‐knitted fabric based on image colour appearance model

AbstractDetecting colour differences in warp‐knitting fabric is essential to ensure its quality. Machine vision algorithms are commonly used for automatic colour difference detection. However, the current algorithm directly extracts RGB (red, green, blue) colour stimulus values from the image without considering the image's colour attributes, leading to a significant error in colour difference detection. To solve this issue, a colour appearance model is introduced into the field of colour difference detection for warp‐knitted fabric. Initially, a colour appearance model based on CAM16 is established, and the critical parameters are calculated to obtain the colour appearance attribute of the fabric. The colour difference calculation formula is then constructed in the uniform colour space of CAM16‐UCS. A template selection algorithm based on principal component analysis was designed to select warp‐knitted cloth images with standard colours. Subsequently, a cloth colour difference detection algorithm was developed using the cloth colour profile model. The performance of the colour difference formula based on the colour profile model was evaluated using the PF/3 method. To compare the CIELab, CMC(2:1), and CIEDE2000 colour difference formulas, standardised residual sum of squares was used. The results indicated that the colour difference formula based on the colour‐appearance model is about 5.32% different from the visual colour difference perceived by the human eye. However, it can perform as well as the CMC(2:1) colour difference formula, which is widely used in the textile industry.

Anthocyanin‐Enhanced Bacterial Cellulose Nanofibers for Sustainable Hg(II) Ion Sensing

AbstractHg(II), poses a significant threat to both the environment and overall well‐being. The present indicator utilizes anthocyanin extract from roselle (Hibiscus sabdariffa), RSE, and incorporates it into bacterial cellulose nanofibers (BCNF) to detect Hg(II) ions. Through examination of the CIE Lab color variables, it is determined that the binding of Hg(II) leads to a discernible alteration in the color. The visible color changes as the Hg(II) concentration increases. ATR‐FTIR(Attenuated Total Reflectance‐Fourier transform infrared spectroscopy) and SEM(scanning electron microscopy) are utilized to analyze the bacterial cellulose nanofibers containing anthocyanin. The selectivity of the proposed sensor is assessed by conducting experiments with different types of metal ions including Co2+, Al3+, Na+, Ba2+, Ni2+, Mg2+, Cd2+, Pb2+, Fe2+, Fe3+, and Cu2+. The outcomes indicate that the sensor exhibits a remarkable ability to distinguish and respond specifically to Hg(II) ions. This particular sensing technique allows for the precise and reliable detection of Hg(II), with a detection limit of 0.72 ppm, by simply observing with the naked eye. For the effective treatment of a tap water sample, the BCNF‐RSE film provides successful results in the detection of Hg(II) ions. This innovative metallochromic sensor offers a promising solution for the on‐site, cost‐effective, portable, easy to use, and real‐time detection of Hg(II) ions.

Phenolic Composition and Bioactivities of Invasive Ailanthus altissima (Mill.) Swingle Leaf Extracts Obtained by Two-Step Sequential Extraction.

Ailanthus altissima, a highly invasive species, contains valuable compounds in different plant parts, indicating great practical potential. This paper proposes the use of non-polar (n-hexane) and polar (ethanol) solvents for the extraction of antioxidant compounds from A. altissima (family Simaroubaceae) leaves in a sequential two-step process. Fresh and dried leaves were examined for their microstructure by scanning electron microscopy, and for color changes in the CIELAB color space co-ordinates. An investigation of the harvesting season, processing (freezing and drying), and solvent indicates ethanol can be used for the highly efficient extraction of phenolics, flavonoids, tannins, and carotenoids. Statistically significant differences were found between the autumn and summer samples for phenolic content, and between dried and frozen samples for tannin content. The HPLC phenolic profile indicates more phenolics (nine polyphenols) in dried leaves harvested in both seasons compared to those in frozen ones (five to six polyphenols). Frozen leaves showed a higher antioxidant activity in a ferric-reducing antioxidant power assay than that of the dried samples, which exhibited a higher antioxidant activity using the 1, 1-diphenyl-2-picryl-hydrazyl assay, but it was not statistically significant. The phenolic, flavonoid, and carotenoid contents significantly influenced the antioxidant activities. Among the ethanolic extracts, those from dried leaves showed better antibacterial activity, in particular, on Staphylococcus aureus and Enterococcus faecalis. The high bioactive content and activity of A. altissima leaves make them suitable natural raw materials for various applications.

Evaluation of plant-derived biomaterials for the development of tissue-engineered corneal substitutes.

Corneal blindness affects over 10 million patients worldwide. Due to the limited supply of donor corneas and frequent graft failure, bioengineered alternatives are crucial. To overcome drawbacks associated with corneal substitutes from synthetic biomaterials, fabrication from plant-derived biomaterials is a potential alternative. Herein, soy protein and glutenin in combination with different crosslinkers were evaluated for fabrication of corneal substitutes. Optical, mechanical, and biochemical properties of fabricated constructs and control rabbit corneas were evaluated in vitro. Soy protein crosslinked with peroxidase/H202 possessed transparency and mechanical properties comparable to controls, although their water content and biocompatibility were inferior. In contrast, soy protein crosslinked with tannic acid showed similar water content, tensile strength, and biocompatibility as rabbit corneas; however, these constructs displayed significantly lower transparency and higher strain to failure. Finally, glutenin cross-linked using formaldehyde showed excellent transparency, strain to failure, and biocompatibility, however; they exhibited significantly lower water content and tensile strength than controls. This study is the first to establish CIELAB color values for the rabbit cornea, allowing quantitative optical evaluation of tissue-engineered substitutes. Thus, a crosslinking strategy utilizing plant-derived proteins for fabrication of constructs with properties comparable to rabbit corneas is a promising direction for development of tissue-engineered corneal substitutes.

Evaluation of the Effect of Various Beverages and Food Materials on the Color Stability of Provisional Materials: An In Vitro Study.

Aim This study aims to evaluate the color stability of four provisional materials: polymethyl methacrylate (DPI®Self-Cure), 10-ethoxylated bisphenol A dimethacrylate (Oratemp® C&B), bis-acryl composite resin (Systemp® C&B, Ivoclar Vivadent), and bis-acryl composite (Systemp® C&B, Ivoclar Vivadent) combined with light-cure composite (Fusion Flo® LC). Materials and methods A total of 40 specimens were meticulously crafted from modeling wax into discs, each precisely 2 mm thick and 20 mm in diameter. Four provisional materials were packed into molds, yielding 10 specimens for each material group. After mixing and polymerization, the specimens were trimmed and polished. Reflectance spectrophotometers were used for initial color assessments based on the CIELAB color space system. Staining solutions, including coffee, Tata Green Tea, Pepsi, and turmeric, were prepared to mimic dietary agents. Artificial saliva, replicating oral conditions, was formulated and sterilized. The specimens were then immersed in various solutions for 15 days at 37 °C. Color measurements were taken on days 2 and 15 using the same spectrophotometer, calculating color differences (ΔE) from changes in L*, a*, and b* values. Results DPISelf-Cure (polymethyl methacrylate)was found to be the most color-stable temporary restorative material, followed by Vivadent (bis-acryl composite resin), Oratemp (10-ethoxylated bisphenol A dimethacrylate), and Fusion Flo (light-cure composite). Fusion Flo exhibited the highest color change by the 15th day. Coffee and green tea demonstrated the greatest potential for causing color changes in the provisional restorative materials. Conclusion DPI Self-Cure exhibited the highest color stability among the provisional materials, with Vivadent and Oratemp following closely behind. Green tea and coffee were the most potent staining agents, while Pepsi and turmeric induced lesser color changes.

Imaging Based Techniques Combined with Color Measurements for the Enhancement of Medieval Wall Paintings in the Framework of EHEM Project.

(1) Background: This paper illustrates an innovative methodological approach chosen to study and map the colors of the medieval wall painting of Santa Maria Antiqua in the Roman Forum, one of the pilot sites of the EHEM project (Enhancement of Heritage Experiences: The Middle Ages). Digital Layered Models of Architecture and Mural Paintings over Time). (2) Methods: Two methods were employed to gather information about colors and mapping. Specifically, colorimetry was utilized for spot measurements, and hypercolorimetric multispectral imaging (HMI) was employed to map the same colors sampled through colorimetry. (3) Results: Chromatic data for all colors in the wall paintings were obtained in the CIELAB color space. Additionally, chromatic similarity maps were generated using the innovative HMI system, a multispectral imaging technique capable of obtaining color data information through advanced calibration software named SpectraPick® (Version 1.1). This comprehensive approach facilitates a thorough understanding of color characteristics and distribution. (4) Conclusions: The color measurements and mapping represent significant advancements in the interpretation of medieval wall paintings, which are often fragmentary and stratigraphically complex. This research sheds new light on the colors used and enhances our understanding of the original appearance of the iconographic patterns. Furthermore, it enables the reconstruction of colors that closely resemble the originals.

Analysis of Rock Mass Weathering Grade Using Image Processing Technique

Image processing techniques refer to the process of converting an image into a digital format and then performing various operations on it to extract useful information. In this study, image processing technique has been used to categorize rock masses according to its weathering grades. The pixel values of the sample images were in the form of RGB color space before being converted to CIELAB color space. The conversion uses ° as the illuminant. The value in CIELAB color space represents the green-red opponent colors, with negative values for green and positive values for red. In contrast, the value represents the blue-yellow opponents with negative values for blue and positive values for yellow. From the values of and of the samples, clustering was used to classify the samples. This method will group the and values into seven clusters according to the closest distance between the values and the centroids. The proposed study can differentiate between the rock mass and rejected clusters containing plants and painted numbers on the rock. The painted number is placed in a rejected cluster due to the inability to determine the exact color of the rock, thereby impacting the data accuracy. The results have been discussed, and the rock masses have been categorized based on weathering grade. Several limitations have been identified, such as the presence of shadows in the sample images and the lack of arrangement of outcome images according to their a* and b* values. This research has also been validated and compared with previous studies. The JudGeo software utilized in prior research required human input to manually estimate suitable a* and b* values, whereas the proposed method automatically computes these values during color space conversion of the sample. Additionally, the proposed method can calculate the percentage of each cluster, facilitating the classification of rock mass into its respective weathering grade.Image processing techniques refer to the process of converting an image into a digital format and then performing various operations on it to extract useful information. In this study, image processing technique has been used to categorize rock masses according to its weathering grades. The pixel values of the sample images were in the form of RGB color space before being converted to CIELAB color space. The conversion uses ° as the illuminant. The value in CIELAB color space represents the green-red opponent colors, with negative values for green and positive values for red. In contrast, the value represents the blue-yellow opponents with negative values for blue and positive values for yellow. From the values of and of the samples, clustering was used to classify the samples. This method will group the and values into seven clusters according to the closest distance between the values and the centroids. The proposed study can differentiate between the rock mass and rejected clusters containing plants and painted numbers on the rock. The painted number is placed in a rejected cluster due to the inability to determine the exact color of the rock, thereby impacting the data accuracy. The results have been discussed, and the rock masses have been categorized based on weathering grade. Several limitations have been identified, such as the presence of shadows in the sample images and the lack of arrangement of outcome images according to their a* and b* values. This research has also been validated and compared with previous studies. The JudGeo software utilized in prior research required human input to manually estimate suitable a* and b* values, whereas the proposed method automatically computes these values during color space conversion of the sample. Additionally, the proposed method can calculate the percentage of each cluster, facilitating the classification of rock mass into its respective weathering grade.

Color Biomimetics in Textile Design: Reproduction of Natural Plant Colors through Instrumental Colorant Formulation.

This paper explores the intersection of colorimetry and biomimetics in textile design, focusing on mimicking natural plant colors in dyed textiles via instrumental colorant formulation. The experimental work was conducted with two polyester substrates dyed with disperse dyes using the exhaustion process. Textiles dyed with different dye colors and concentrations were measured in a spectrophotometer and a database was created in Datacolor Match Textile software version 2.4.1 (0) with the samples' colorimetric properties. Colorant recipe formulation encompassed the definition and measurement of the pattern colors (along four defined natural plants), the selection of the colorants, and the software calculation of the recipes. After textile dyeing with the lowest expected CIELAB color difference (ΔE*) value recipe for each pattern color, a comparative analysis was conducted by spectral reflectance and visual assessment. Scanning electron microscopy and white light interferometry were also used to characterize the surface of the natural elements. Samples dyed with the formulated recipe attained good chromatic similarity with the respective natural plants' colors, and the majority of the samples presented ΔE* between 1.5 and 4.0. Additionally, recipe optimization can also be conducted based on the colorimetric evaluation. This research contributes a design framework for biomimicking colors in textile design, establishing a systematic method based on colorimetry and color theory that enables the reproduction of nature's color palette through the effective use of colorants.

Targeted metabolomics revealed the seasonal plasticity of skin color and pigment metabolites in ornamental koi carp

The koi carp is an ornamental fish that was obtained through artificial selection from the common carp (Cyprinus carpio L.). The most economically important traits of koi are their beautiful skin patterns in bright colors. As seasonality is an important factor in the biology and ecology of fish, we thus assumed that seasonal changes are involved in regulating the formation of skin color and patterns of koi carp. The white, red, cyan, and black skin colors from four varieties of scaleless koi carp (Doitsu Shiromuji (W), Doitsu Kohaku (WR), Doitsu Showa Sanke (WRI), and Kumonryu (WI)) were evaluated using the CIELab color space (lightness, redness, and yellowness) in different seasons. Compared to winter, the yellowness of the white color in all koi varieties decreased in summer and autumn. The black skin color areas in WRI and WI koi increased in summer and autumn compared to winter. The yellowness of the red color decreased only in WRI koi, while no changes were observed in WR koi. Targeted metabolomics analysis revealed that the levels of the structural pigment guanine of all koi varieties showed significant seasonal variation. Of seven detected carotenoids, the zeaxanthin and tunaxanthin contents in W, WI, and WRI koi changed with the seasons, while none of the carotenoids in WR koi were altered. Of the seven potential regulatory metabolites, epinephrine, melatonin, and cyclic adenosine monophosphate (cAMP) in all four koi varieties showed the highest levels in winter. A correlation analysis suggested that the seasonal changes in white skin color occurred through the epinephrine-cAMP pathway; melanin-dependent and carotenoid-dependent skin color changes occurred through melatonin in koi carp. This study demonstrated the seasonal plasticity of skin color in koi carp regulated by melatonin and epinephrine, associating with variety and color specificity.

Colorimetric Evaluation of a Reintegration via Spectral Imaging-Case Study: Nasrid Tiling Panel from the Alhambra of Granada (Spain).

Color reintegration is a restoration treatment that involves applying paint or colored plaster to an object of cultural heritage to facilitate its perception and understanding. This study examines the impact of lighting on the visual appearance of one such restored piece: a tiled skirting panel from the Nasrid period (1238-1492), permanently on display at the Museum of the Alhambra (Spain). Spectral images in the range of 380-1080 nm were obtained using a hyperspectral image scanner. CIELAB and CIEDE2000 color coordinates at each pixel were computed assuming the CIE 1931 standard colorimetric observer and considering ten relevant illuminants proposed by the International Commission on Illumination (CIE): D65 plus nine white LEDs. Four main hues (blue, green, yellow, and black) can be distinguished in the original and reintegrated areas. For each hue, mean color difference from the mean (MCDM), CIEDE2000 average distances, volumes, and overlapping volumes were computed in the CIELAB space by comparing the original and the reintegrated zones. The study reveals noticeable average color differences between the original and reintegrated areas within tiles: 6.0 and 4.7 CIEDE2000 units for the yellow and blue tiles (with MCDM values of 3.7 and 4.5 and 5.8 and 7.2, respectively), and 16.6 and 17.8 CIEDE2000 units for the black and green tiles (with MCDM values of 13.2 and 12.2 and 10.9 and 11.3, respectively). The overlapping volume of CIELAB clouds of points corresponding to the original and reintegrated areas ranges from 35% to 50%, indicating that these areas would be perceived as different by observers with normal color vision for all four tiles. However, average color differences between the original and reintegrated areas changed with the tested illuminants by less than 2.6 CIEDE2000 units. Our current methodology provides useful quantitative results for evaluation of the color appearance of a reintegrated area under different light sources, helping curators and museum professionals to choose optimal lighting.

Production, Extraction and Partial Characterization of Natural Pigments from Chryseobacterium sp. kr6 Growing on Feather Meal Biomass

Obtaining natural pigments from microorganisms is an alternative with high potential for biotechnological application. The use of agro-industrial wastes as substrate for cultivations enables a reduction of the production cost and may add value to potentially polluting byproducts. In this work, the extraction of pigments produced by the bacterium Chryseobacterium sp. strain kr6 was evaluated, employing feather meal as the sole carbon source for bacterial growth. The maximum production of the yellow pigments was observed for cultivation at 30 °C, during 48 h, with 5 g/L feather meal. The pigment extraction from the bacterial biomass was performed with the aid of physical methods and the testing of different organic solvents. The conditions that provided better extraction were using ultrasound with acetone as the solvent, reaching a yield of 180 μg/g biomass after optimization. The pigment was partially characterized via UV-visible, FTIR and mass spectroscopy and CIELAB color parameters, suggesting the presence of molecules belonging to the flexirubin group (aryl polyenes). The antioxidant capacity of the pigment was confirmed via the scavenging of DPPH radical and thiobarbituric acid reactive substances (TBARS) methodologies. Moreover, the pigment extract showed antimicrobial activity against Staphylococcus aureus and Enterococcus faecalis.

Assessment of Tooth Shade Measurement Precision and Consistency with Digital Photography Calibration System.

To ascertain the degree of precision and repeatability inherent in the "capture to edit" digital imaging system, namely the ColorChecker Passport Photo (X-Rite, MI, USA), and to juxtapose its performance against spectrophotometric assessments utilizing the Vita Easyshade® (Vita Zahnfabrik, H Rauter GmbH & Co. KG., Bad Sackingen, Germany) for the same set of teeth. Eighty participants aged 19-25 were included in the study; all of them were Croatian students at the School of Dental Medicine, University of Zagreb. Color measurements of the maxillary right central incisors were performed in controlled, standardized laboratory conditions. The measurements were performed on calibrated digital photographs by an experienced clinician three times in a row, and L, a, and b of CIELAB color space values were recorded. The same procedure was performed using the Vita Easyshade 5.0 spectrophotometer (Vita Zahnfabrik, Bad Säckingen, Germany) in "Tooth single" mode. The Cronbach's alpha was used as a repeatability measurement, thus revealing high consistency for both methods (α=0.94-1). Correlations were moderate (Pearson r=0.44-0.66 p<0.05). Testing confirmed that digital photography is inaccurate as spectrophotometry (p<0.05). An analysis of errors of means and their standard deviations revealed consistent discrepancies with minor deviations. The "capture to edit" method showed high consistency (Cronbach's α=0.94-0.96), and it exhibits comparability in terms of variability, reliability, and repeatability when compared to spectrophotometric measurement (VitaShade 5, VitaZahnfabrik). Disparities between the methods are evident and anticipated, yet they do not follow a consistently linear pattern. The combination of repeatability and consistency renders the "capture to edit" method a valuable tool for enhanced color mapping, thus facilitating comparisons between digital images.

Effectiveness of machine learning algorithms as a tool to meat traceability system. A case study to classify Spanish Mediterranean lamb carcasses

Establishing the traceability of meat products has been a major focus of food science in recent decades. In this context, recent advances in food nutritional biomarker identification and improvements in statistical technology have allowed for more accurate identification and classification of food products. Moreover, artificial intelligence has now provided a new opportunity for optimizing existing methods to identify animal products. This study presents a comparative analysis of the effectiveness of different machine learning algorithms based on raw data from analyses of organoleptic, sensory and nutritional meat traits to differentiate categories of commercial lamb from an indigenous Spanish breed (Mallorquina breed) obtained from the following production systems: suckling lambs; light lambs from grazing; and light lambs from grazing supplemented with grain. Six machine learning algorithms were evaluated: Artificial Neural Network (ANN), Decision Tree, K-Nearest Neighbours (KNN), Naive Bayes, Multinomial Logistic Regression, and Support Vector Machine (SVM). For each algorithm, we tested three datasets, namely organoleptic traits and sensorial traits (CIELAB colour, water holding capacity, Warner-Bratzler shear force, volatile compounds and trained tasters), and nutritional traits (proximate composition and fatty acid profile). We also tested a combination of all three datasets. All the data were combined into a dataset with 144 variables resulting from the meat characterization, which included 11,232 event records. The ANN algorithm stood out for its high score with each of the three datasets used. In fact, we obtained an overall accuracy of 0.88, 0.83, and 0.88 for the organoleptic-sensory, nutritional, and combined datasets, respectively. The effectiveness of using the SVM algorithm to assign categories of lambs according to its production system performed better with nutritional traits and the full characterization, with performances equal to those obtained with ANN. The KNN algorithm showed the worst performance, with overall accuracies of 0.54 or lower for each of the datasets used. The results of this study demonstrate that machine learning is a useful tool for classifying commercial lamb carcasses. In fact, the ANN and SVM algorithms could be proposed as tools for differentiating categories of lamb production based on the organoleptic, sensory and nutritional characteristics of Mediterranean light lambs' meat. However, in order to improve the traceability methods of lamb meat production systems as a guarantee for consumers and to improve the learning processes used by these algorithms, more studies along these lines with other lamb breeds are required.

PENGARUH MODIFIKASI PANAS OIL HEAT TREATMENT TERHADAP PERUBAHAN WARNA DAN BERAT PADA BAMBU BETUNG (Dendrocalamus asper) DAN BAMBU ANDONG (Gigantochloa pseudoarundinacea)

Betung bamboo (Dendrocalamus asper) and andong bamboo (Gigantochloa pseudoarundinacea) are non-timber forest products that can be used as a substitute for wood. However, both bamboos have light colors that are less aesthetic and susceptible to fungal and pest damage. Therefore, it is necessary to modify the bamboo. One of the modification methods used is oil heat treatment (OHT). This research aims to determine the effect of OHT on the color of betung and andong bamboo. This research was carried out the OHT using palm oil at temperatures of 180°C, 200°C, 220°C and 240°C for 2 hours. Color parameter measurements were observed using a colorimeter that implemented the CIE-Lab color system. The color parameters measured include brightness (L*), red/green chromaticity (a*), yellow/blue chromaticity (b*), and overall color change (∆E*). The percentage of bamboo weight loss after OHT was also observed. The research results show that the brightness value (L*) of betung bamboo and andong bamboo has decreased, so that the color becomes darker as the temperature increased. The a* and b* values decreased at all temperatures and durations. In addition, the value of ∆E* increased at all temperatures with a total change showing a value &gt; 12. The decrease in weight of betung bamboo occurred at all temperatures. This heat treatment can make the bamboo color darker and more exotic, thereby increasing the added value of the product and improving the quality of bamboo from fungi and pests due to cellulose degradation.