Color Analysis Research Articles

A new method to detect illegal oil use and estimate mortality rates of endangered Ganges river dolphins based on Clupisoma fish catches

Gillnet entanglement is a major threat to endangered small cetacean species around the world, including Ganges river dolphins (Platanista gangetica). While conservation efforts have helped to reduce the prevalence of targeted hunts, bycatch still occurs. A serious concern is the illegal opportunistic exploitation of bycaught river dolphins to evade detection and potential penalties, where oil is extracted from the blubber and illegally traded as bait for catfish (Clupisoma garua). While this threat is well known, enforcement is weak and evidence difficult to collect as the molecular analyses required to confirm the use of dolphin oil are expensive and time‐intensive. Simpler detection methods are therefore needed to help improve enforcement. We developed a new visual test and decision‐making process to help identify the use of dolphin oil while fishing for catfish, which draws on a common understanding among local fishers that oil‐baited fish appear paler/whiter than net‐caught fish. We conducted colour analyses and visual‐perception tests, combining these results with other variables, such as catch weight, sale price and season, to identify a set of rules which can be used to determine the use of dolphin oil in a sampled catch. Based on our predicted oil‐use prevalence, we estimated that five to seven dolphins (~4% of the population in our study area) may be exploited each year to support catches landed at one of two sites in our study area. This system therefore provides a simple and efficient tool to identify instances of illegal exploitation of Ganges river dolphins.

The analysis of colour and pattern in Romanian folk dress: protecting past legacies in an uncertain future

ABSTRACT Dress may show the characteristics of an era, a country, a community or a person. As in other folk arts, clothing is one of the most vibrant documents of cultures. Since folk clothing, which is a cultural product, is directly related to people, it is an indicator of the people’s modes of living. The colours, patterns and motifs especially used in folk clothing provide important information on such matters. This article deals with the colours and patterns of the folk clothing in the regions within Romania. For this purpose, samples of folk clothing belonging to the regions considered as the most traditional are illustrated and the elements of folk clothing examined in terms of colour and pattern features. The article lists various colours and patterns and shows how their configurations serve as identifying markers for the various regional locations of their wearers.

Untangling Indian Hemp: Identifying Woodlands Bast Fibers in Collections

ABSTRACT Many textiles produced by Native American Woodlands cultures are made from bast (phloem) fibers from North American plants. While bast fibers are easy to identify with microscopy, determining the exact species has long been a challenge. Historically, bast fibers from Native American communities have been referred to as “Indian hemp,” a confusing term at best. This project undertaken as part of an Andrew W. Mellon Fellowship at the National Museum of the American Indian (NMAI) focused on a combined approach by working with both community members and scientists to provide a cultural background for these important fibers as well as useful diagnostic tools for identification. Both macroscopic and microscopic characteristics were examined including color, feel, microfibrillar orientation, crystal species, and cross section analysis. A physical and digital reference collection was created for comparison. Eight fiber samples taken from six historic objects in NMAI’s collection were then examined to test effectiveness of bast fiber identification protocol. Results from this study confirm there continues to be limited success when identifying the exact bast fiber species in historic artifacts because of small sample size and aging characteristics.

Development of meat analog patty using lion’s mane mushroom and pumpkin seeds

Abstract High meat consumption globally has caused several problems, such as environmental, animal welfare, and public health issues. Consumption of plant-based meat products or meat analog can be used as an alternative to overcome these problems. In this research, a meat analog patty was formulated using lion’s mane mushroom as a main ingredient as it contains high protein content (20.8%), along with texturized soy protein. Furthermore, pumpkin seeds were also added to provide sufficient iron to the meat analog. This research was done in two stages, in which the first stage of the research was done to observe the effect of different ratios of lion’s mane mushroom and texturized soy flour (30:50, 40:40, 50:30) on the physicochemical and sensory characteristics of the meat analog patty. The analyses done included proximate analysis, color analysis, texture profile analysis, and organoleptic analysis. On the other hand, the second stage of research was focused on determining the best concentration of pumpkin seeds added (10%, 20%, 30%) to the meat analog patty to obtain the optimum iron content. The analyses done included texture profile analysis, proximate analyses, and iron content analysis. Results showed that the selected formulation of the meat analog patty was the one made from a 50:30 ratio of lion’s mane mushroom and texturized soy flour added with 10% pumpkin seeds. It had 0.79 mg of iron/30g of sample and was most preferred by the panelists based on organoleptic tests. The addition of pumpkin seeds did not affect the proximate chemical content of the meat analog patty, except for its moisture content. Regarding textural profile, the meat analog patty made with the addition of pumpkin seeds was comparable to commercial meat analog in terms of hardness while being less springy, cohesive, and chewy. Compared to a meat patty, it had a higher hardness and chewiness value with a lower springiness and cohesiveness value.

Innovative application of microencapsulated polyphenols in cereal products: Optimization of the formulation of dairy‐ and gluten‐free pastry

AbstractDuring the last decade, consumers pay much attention to the food they eat. They try to choose functional products that have a beneficial effect on health and well‐being, beyond their typical nutritional function. For this reason, the primary aim of the study was to create a gluten‐free and dairy‐free cereal product with increased polyphenol and fiber content. Microencapsulation technology using freeze‐drying method and trehalose as matrix material was used in order to protect the polyphenols from the degradation during processing. The effect of the content of beta‐glucan concentrate, polyphenol microencapsulation and acai oil on the physicochemical properties of pastry products was studied. Response surface methodology was used to optimize the product formulation. The scope of work included analysis of process efficiency, instrumental analysis of color and texture, analysis of total antioxidant capacity, assessment of the content of polyphenols, flavonoids, and beta‐glucan, volume testing, analysis of the profile of fatty acids and volatile compounds, and assessment of sensory acceptability. Based on the obtained data, a response surface model was developed to determine the optimal recipe for the final product. The predicted data were verified using empirical methods. It was found that the optimal formulation of the product involves incorporating 6.48% polyphenol microcapsules, 7.60% beta‐glucan concentrate and 3.71% acai oil. The final product had higher content of polyphenols and beta‐glucan, as well as higher antioxidant activity compare to conventional product. Moreover, it was characterized by physical characteristics similar to the standard product and high sensory acceptability.Practical applicationsConsumers are currently eager to purchase fortified products with beneficial effects on health and well‐being. The developed functional product with increased polyphenol and beta‐glucan content, high antioxidant activity, is anticipated to garner significant consumer acceptance. The product, with its significant health‐promoting and well‐being enhancing properties, along with characteristics similar to conventional products, is poised to effectively meet consumers' needs and expectations. Additionally, it addresses a market void for bakery items tailored specifically for individuals with gluten intolerance, celiac disease, or cow's milk protein allergy. It provides a safe consumption option for these groups, offering a product similar to conventional items found on shelves that they are unable to consume.

First-ever study uncovers microplastic contamination in Nepalese table salt

Despite numerous studies on microplastic contamination in table salt worldwide, research focusing on Nepalese table salts is remarkably lacking. This study aims to address this gap by investigating microplastic contamination in salt samples collected from all seven provincial zones of Nepal. Our objective is to comprehensively assess the presence and characteristics of microplastics in salt sold within local markets across the country. Five salt packaging companies utilized by Nepalese consumers were identified. The collected salt samples were digested with Fenton's reagent to extract microplastics, which were then observed under a digital microscope. Using an OMAX stereomicroscope at 30× magnification and an OMAX A3503S digital camera, each microplastic was carefully identified and quantified. FTIR analysis was conducted to identify the polymer types. All tested salt samples (100 %) from both Nepalese and Indian packaging companies contained microplastics. Microplastic abundance exhibits variability among the samples, ranging from 80 to 1040 microplastics per kilogram of salt. The average value stands at 381 ± 219 microplastics per kilogram of salt sample. The distribution of microplastic concentrations within the salt samples reveals that the majority fall within the 301–400 microplastics per kilogram salt range, constituting 33 % of the total samples. Color analysis showed diverse contamination sources, while microplastic shapes included fibers (56 %), films (17 %), fragments (16 %) and pellets (11 %). Polymer type analysis confirmed the presence of polyethylene and polypropylene in tested microplastics. The study estimated that Nepalese individuals ingest an average of 1853 microplastics annually, indicating significant exposure from salt consumption. Surprisingly, factors such as storage conditions, date of salt packaging and thickness of packaging material did not significantly affect microplastic presence in the samples, suspecting manufacturing processes as the primary contributors to contamination. Therefore, the raw materials and purification practices for salt need improvement, as existing methods are insufficient to eliminate microplastics. These findings emphasize the need for further research and mitigation efforts to address microplastic contamination in Nepalese salt and its potential health impacts.

A Preliminary Study of Nutritional Enhancement of Duckweed (Lemna minor) through Fermentation with Saccharomyces cerevisiae and Lactobacillus sp.

Duckweed is generally only used as an alternative feed for animals and is less optimized as a source of additional food for humans. The application of duckweed, Lemna minor, is still limiting. To optimize the utilization of L. minor, increasing nutrient content of L. minor through a fermentation process is necessary. The objective of this research was to investigate the effect of fermentation on nutrient content of the duckweed. L. minor was fermented using the combination of local isolate: Saccharomyces cerevisiae and Lactobacillus sp. Variations on the length of the fermentation time are using ranges of 0, 3 and 7 days for fermentation time. The fermented samples were then subjected to proximate, pH, color analysis. Amino acid analysis was performed on the best treatment. The results showed that the fermentation process using the consortium of S. cerevisiae and Lactobacillus sp. increased the nutritional quality of L. minor which includes an increase in protein content. The results of amino acid analysis also showed good results for fermented L. minor. Hence, fermentation represents an innovative approach to enhance the protein content and overall nutritional quality of duckweed.

Pengaruh Penambahan Sari Kedelai terhadap Karakteristik Mi Tofu Shirataki Kering Berbasis Tepung Porang Glukomanan

Dry noodles are one of the fast foods that people like and are generally made from wheat flour. Rising wheat exports could threaten Indonesia's food security. Porang contains glucomannan and can be used as a substitute for flour. This study used the addition of soybean juice to add protein to Shirataki noodles. The purpose of the study was to determine the effect of the addition of soybean juice on the texture characteristics and protein content of Shirataki tofu noodles. This study used 3 treatments, namely the addition of soybean juice (2.5%, 5%, and 7.5%). Based on the results of the study, the addition of soybean juice had a significant effect on the analysis of ash content, protein content, hardness, color and sensory. Meanwhile, the results of the study did not have a significant effect on the analysis of morphology, water content, water activity, and elongation. The results of research on physical analysis showed the best sample concentration of 2.5%, in chemical analysis the best concentration of 2.5% except for the best sample protein analysis of 7.5%, and in sensory analysis of the sample preferred concentration of 5%.

어린이박물관 메타버스 전시공간의 지각적⋅심리적 색채 분석 연구 - 국내 어린이 박물관 사례를 중심으로 -

어린이박물관 메타버스 전시공간의 지각적⋅심리적 색채 분석 연구 - 국내 어린이 박물관 사례를 중심으로 -

The Effect of Different Marinades on Some Quality and Sensory Properties of Chicken Breast Meat

In this study, it was aimed to determine the effects of different marination liquids on some quality and sensory properties of chicken breast meat. Three different marination formulations (containing olive oil, red wine and yogurt) were used in the study. After cooking, cooking loss, marinade absorption, pH, color, texture analysis results and sensory test results are discussed. As a result, it was observed that the differences between cooking loss, marinade absorption and pH values of the cooked samples were statistically significant (p<0.05) as a result of analysis of variance and multiple comparison test (Tukey). When the color analysis results were examined, it was determined that different marinades could be effective on the brightness (L*), redness (a*) and yellowness (b*) values of the cooked chicken meat samples and the results obtained were statistically significant (p<0.05). Since the textural values did not show a normal distribution, the Wilcoxon test was applied and no significant difference was detected between the marinades (p>0.05). A panelist test was conducted on 25 people by examining the smell, texture, flavor and color of the samples sensory-wise and a general appreciation scale was created. As a result of the Tukey multiple comparison test applied to sensory analysis data, it was determined that the marination solution containing olive oil had the highest approval score by consumers.

P060 An analysis of eye colour and iris pattern as a risk factor for skin cancer in immunosuppressed renal transplant recipients

P060 An analysis of eye colour and iris pattern as a risk factor for skin cancer in immunosuppressed renal transplant recipients

An eco-friendly approach for analysing sugars, minerals, and colour in brown sugar using digital image processing and machine learning

Brown sugar is a natural sweetener obtained by thermal processing, with interesting nutritional characteristics. However, it has significant sensory variability, which directly affects product quality and consumer choice. Therefore, developing rapid methods for its quality control is desirable. This work proposes a fast, environmentally friendly, and accurate method for the simultaneous analysis of sucrose, reducing sugars, minerals and ICUMSA colour in brown sugar, using an innovative strategy that combines digital image processing acquired by smartphone cell with machine learning. Data extracted from the digital images, as well as experimentally determined contents of the physicochemical characteristics and elemental profile were the variables adopted for building predictive regression models by applying the kNN algorithm. The models achieved the highest predictive capacity for the Ca, ICUMSA colour, Fe and Zn, with coefficients of determination (R2) ≥ 92.33 %. Lower R2 values were observed for sucrose (81.16 %), reducing sugars (85.67 %), Mn (83.36 %) and Mg (86.97 %). Low data dispersion was found for all the predictive models generated (RMSE < 0.235). The AGREE Metric assessed the green profile and determined that the proposed approach is superior in relation to conventional methods because it avoids the use of solvents and toxic reagents, consumes minimal energy, produces no toxic waste, and is safer for analysts. The combination of digital image processing (DIP) and the kNN algorithm provides a fast, non-invasive and sustainable analytical approach. It streamlines and improves quality control of brown sugar, enabling the production of sweeteners that meet consumer demands and industry standards.

PH-indicator based on delignified jute fiber and red cabbage anthocyanins for monitoring fish spoilage using a smartphone application

Halochromic materials that show visible color changes in response to changes in pH are suitable for the real-time monitoring of fish spoilage. In this study, an easy-to-use, simple, inexpensive, and non-toxic fish freshness indicator was fabricated by combining delignified jute (Corchorus olitorius) fibers and anthocyanins (halochromic materials) from red cabbage (DFA: Delignified jute fibers incorporated with anthocyanins). A single-step decolorization/delignification using solar irradiation along with NaOH and H2O2 treatment was used for modifying the jute fibers. This method helps to overcome the self-color, mitigates the lack of affinity of jute fibers towards anthocyanins and preserves the lignin so that the strength of the fiber is not impacted. A smartphone-based color analysis was used for real-time fish quality monitoring using DFA. To the best of our knowledge, there are no reports on the use of jute fibers as substrates to incorporate anthocyanins for food spoilage monitoring. The indicator displayed an observable color response to the pH and varying concentrations of amine compounds. During the storage of fish (mackerel), the colorimetric indicator showed a visible color change from pink (for fresh fish) to blue (for spoiling fish) and then to green (for spoiled fish), corresponding to changes in pH and total volatile basic nitrogen. To offer a straightforward quantitative assessment of color changes, we utilized the freely available Android application Color Grab to measure the color using RGB and L*, a*, and b* indices. The DFA indicator providing naked-eye analysis has the potential to be an effective tool for real-time monitoring of on-site food spoilage by non-specialized personnel in resource-limited areas.

Classification of Apple Color and Deformity Using Machine Vision Combined with CNN

Accurately classifying the quality of apples is crucial for maximizing their commercial value. Deep learning techniques are being widely adopted for apple quality classification tasks, achieving impressive results. While existing research excels at classifying apple variety, size, shape, and defects, color and deformity analysis remain an under-explored area. Therefore, this study investigates the feasibility of utilizing convolutional neural networks (CNN) to classify the color and deformity of apples based on machine vision technology. Firstly, a custom-assembled machine vision system was constructed for collecting apple images. Then, image processing was performed to extract the largest fruit diameter from the 45 images taken for each apple, establishing an image dataset. Three classic CNN models (AlexNet, GoogLeNet, and VGG16) were employed with parameter optimization for a three-category classification task (non-deformed slice–red apple, non-deformed stripe–red apple, and deformed apple) based on apple features. VGG16 achieved the best results with an accuracy of 92.29%. AlexNet and GoogLeNet achieved 91.66% and 88.96% accuracy, respectively. Ablation experiments were performed on the VGG16 model, which found that each convolutional block contributed to the classification task. Finally, prediction using VGG16 was conducted with 150 apples and the prediction accuracy was 90.50%, which was comparable to or better than other existing models. This study provides insights into apple classification based on color and deformity using deep learning methods.

Multiscale assessment of artificial aging treatment of polysaccharides from tonewood species

In the acoustics of musical instruments with a resonator body, the aging of the wood leads to the improvement of the acoustic properties due to increasing the crystallinity of wood. This phenomenon could be explained by the fact that wood is a complex product based on three-dimensional polymer chains of carbohydrates, its aging being closely related to covalent cross-linking and scission of polymer chains. The aim of this study was to evaluate at a multiscale the changes produced artificial aging of tone wood by measuring the acoustic, mechanical and chemical parameters. The spruce and maple wood samples were investigated before and after exposure to ultraviolet (UV) radiation, through the tensile test, the time-of-flight method (TOF), the analysis of the wood color and the determination of the chemical fingerprint through Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD). The obtained results showed that the effects of artificial aging are manifested at the chemical level where the crystallinity increases up to the acoustic level, depending on the wood species and their quality class. These results are relevant for musical instrument manufacturers to find treatments that lead to superior acoustic properties.

The Influence of Functional Composite Coatings on the Properties of Polyester Films before and after Accelerated UV Aging.

The aim of this study was to cover biopolymeric packaging films based on PLA/PHBV blend with a functional composite coating (to retain their ecological character) and to investigate their antimicrobial properties before and after UV irradiation. As an active coating, the carrier hydroxypropyl methyl cellulose (HPMC), as well as its modified form with Achillea millefolium L., Hippophae rhamnoides L., and Hypericum L. extract (E) and a combined system based on the extracts and nano-ZnO (EZ), was used to obtain active formulations. Additionally, film surface morphology (SEM, FTIR-ATR) and color (CIELab scale) analysis of the pre- and post-UV-treatment samples were performed. The results confirmed that the E and EZ-modified films exhibited antibacterial properties, but they were not effective against phage phi6. Q-SUN irradiation led to a decrease in the activity of E coating against Staphylococcus aureus, Pseudomonas syringae, and Candida albicans. In this case, the effectiveness of EZ against C. albicans at 24 h and 72 h UV irradiation decreased. However, the irradiation boosted the antiviral effectiveness of the EZ layer. SEM micrographs of the film surface showed that UV treatment did not significantly influence the native film morphology, but it had an impact on the coated film. FTIR analysis results showed that the coatings based on HPMC altered the IR absorption of the nonpolar groups of the biopolyester material. The applied coatings only marginally affected film color changes and increased their yellowness after UV irradiation, whereas a composite layer of nano-ZnO limited these changes.

Advanced Image Processing Techniques for Automated Detection of Healthy and Infected Leaves in Agricultural Systems

Advances in computer vision and machine learning have transformed leaf disease detection by enabling efficient and accurate identification of subtle disease signs in leaves. Leveraging high-resolution imaging, pattern recognition algorithms, and deep learning models, researchers and farmers can now conduct automated detection across various plant species. The development focuses on sophisticated image processing techniques applied to diverse datasets captured under controlled conditions, ensuring comprehensive coverage of lighting, time, and weather variations. Expert annotation of infection stages and types enhances dataset reliability, while pre-processing stages such as resizing and normalization optimize image consistency for robust model training. Data augmentation techniques enrich dataset diversity, complemented by feature extraction methods like RGB color analysis, GLCM texture analysis, and shape descriptors to discern healthy and infected leaves with precision Validation through K-fold cross-validation ensures model reliability across diverse datasets, culminating in a deployable application for real-time leaf health monitoring. Results demonstrate significant advancements, with the proposed model achieving 92% accuracy, surpassing Logistic Regression (87%), Decision Tree (82%), and Support Vector Machine (79%). Over 10 epochs, the model achieves steady improvements to 95% training accuracy and 85% validation accuracy, underscoring its effectiveness. Implementing data augmentation boosts accuracy from 85% to 89%, while analysis of prediction errors refines model performance for enhanced automated plant health monitoring and precision agriculture applications. These advancements highlight the transformative impact of technology in safeguarding crop resilience and optimizing agricultural practices.

A Study of Metaphorical Color in Visual Texts in Science Fiction Films - The Matrix as an Example

This research article focuses on the symbolic and metaphorical roles that color plays in the visual text in the science fiction film The Matrix. First, the article discusses the concepts of visual text and metaphor, providing theoretical support for the subsequent analysis of color in The Matrix. Again, the article examines in detail the use of different colors and their symbolism in the film. Finally, it is pointed out that color in The Matrix not only deepens the audience's understanding of the film s themes and emotions, but also shows its far-reaching influence in the wider field of science fiction cinema. Overall, through an in-depth analysis of the use of color in The Matrix, this essay demonstrates how color plays a key role in the art of cinema, particularly in its ability to convey metaphorical and symbolic meaning.

Nanocomposite Films of Babassu Coconut Mesocarp and Green ZnO Nanoparticles for Application in Antimicrobial Food Packaging.

In this work, novel nanocomposite films based on babassu coconut mesocarp and zinc oxide nanoparticles (ZnO NPs), synthesized by a green route, were produced for application as food packaging films. The films were prepared using the casting method containing different contents of ZnO NPs (0 wt%, 0.1 wt%, 0.5 wt%, and 1.0 wt%). The films were characterized by Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), instrumental color analysis, and optical properties. The water vapor permeability (WVP) and tensile strength of films were also determined. The antimicrobial activity of the films against cooked turkey ham samples contaminated with Staphylococcus aureus was investigated. The results showed that incorporating ZnO NPs into babassu mesocarp matrices influenced the structure of the biopolymer chains and the color of the films. The BM/ZnO-0.5 film (0.5 wt% ZnO NPs) showed better thermal, mechanical, and WVP properties. Furthermore, the synergistic effect of babassu mesocarp and ZnO NPs in the BM/ZnO-0.5 film improved the antimicrobial properties of the material, reducing the microbial count of S. aureus in cooked turkey ham samples stored under refrigeration for 7 days. Thus, the films produced in this study showed promising antimicrobial packaging materials for processed foods.

Effect of different instrumental techniques and clinical experience on shade matching.

Many factors can affect the aesthetics of dental restorations, including the instrumental techniques used in shade matching, and can lead to clinical failure. The aim of this study was to investigate the effectiveness of using the cross-polarization digital photograph technique and intraoral scanners for shade matching, and also evaluate the effect of the level of clinical experience on shade matching success. Color analysis was performed on the maxillary right central incisors of 10 subject models with Vita Easyshade. Intraoral scanning was performed 10 times on each model using TRIOS 3 and color analysis was performed from the same spot. Then cross-polarized and non-polarized photographs of the models were taken with standard settings using a gray reference card. Each shade tab of the Vita System 3D-Master scale was also photographed with two different polarization techniques. Four groups (n = 12), including prosthodontics faculty staff, postgraduate students in prosthodontics, undergraduate students, and dental technicians matched the shade tabs and the model photographs obtained with both techniques on a standardized computer screen. Finally, the color differences between the shade tabs and maxillary central incisors matched by observers from four different groups were recorded using a colorimeter, Classic Color Meter, in accordance with the CIELAB system and CIEDE2000 (ΔE00) values were calculated. The data were compared with the acceptability threshold of 1.80 for ΔE00. The data obtained from the observers were analyzed with IBM SPSS Statistics 26.0 Release Notes program. Independent Samples t-test was used to compare normally distributed data according to binary groups. The level of significance was 0.05. A statistically significant difference was found in the shade matching on photographs taken with different techniques in postgraduate students (p = 0.02). Also, there was a statistically significant difference in success between the groups that made shade matching based on photographs obtained with the non-polarization technique (p = 0.00). The undergraduate students achieved statistically significantly lower results than all other groups (ΔE00 = 5.57±1.07). The kappa value between the intraoral scanner and spectrophotometer results was 0.10, and this value was not statistically significant (p = 0.32). The cross-polarization technique used especially for shade matching is not superior to the non-polarization technique. Academic and clinical experience might be correlated with shade-matching success with the non-polarization technique. The clinical acceptability threshold could not be achieved in the shade matchings made on digital photographs taken with both techniques. Shade matching performed with an intraoral scanner did not yield reliable results.