Search Results (41)

An indirect, novel, fast, and facile assay was developed for the colorimetric determination of fluoride anions using 96-well plates. The proposed method relies on the colorimetric degradation caused by fluoride ions after their reaction with the iron–thiocyanate complex in an acidic medium. The procedure required the addition of minimal amounts of ferric iron and thiocyanate anion solutions to form the corresponding complex with an intense blood-red color, after which, upon addition of fluoride ions, this complex would dissociate, and its color would gradually fade depending on the analyte concentration. The colorimetric differences were measured using a simple imaging device such as a flatbed scanner. Various parameters affecting the analytical performance of the proposed method were optimized, including solution concentrations, pH values, and reaction time for Fe(III)-SCN complex formation and its disintegration process. The proposed assay was successfully applied to the determination of F⁻ in oral hygiene product samples. The method exhibited acceptable detection limits (3.2 mg L⁻¹) with sufficient precision, good intra-day and inter-day reproducibility (ranging from 1.5 to 5.2%), and high selectivity against other anions and components of the samples under study. Full article

Continued population growth demands a significant increase in agricultural production to ensure food security. However, agricultural output is limited by environmental crises and the negative impacts of open-field farm practices. As an alternative, vertical farming techniques, such as aeroponics, can be utilized to optimize the use of resources. However, the uneven size and distribution of spray droplets in aeroponics, issues that affect root development and nutrient delivery, continue to be problematic in spray performance analysis. In aeroponics, nutrient solutions are delivered to plant roots through pressurized nozzles, and the effectiveness of this delivery depends on the spray characteristics. Variations in flow rates directly affect droplet size, density, and coverage, which in turn influence nutrient uptake and crop growth. In this study, the flow rate was adjusted (3, 4.5, and 6 L/min) to quantitatively analyze spray performance using water-sensitive paper (WSP) as a deposit collector via a quick assessment method. Subsequently, image-processing techniques such as threshold segmentation and morphological operations were applied to isolate individual spray droplets on the WSP images. This technique enabled the quantification of the droplet’s coverage area, size, density, and uniformity to effectively evaluate spray performance. One-way ANOVA indicated that all the spray parameters varied significantly with respect to the flow rate (p < 0.05): For example, the average diameters of the droplets increased from 0.73 mm at 3 L/min to 1.29 mm at 6 L/min. The droplets’ densities decreased from 85.53 drops/cm² to 30.00 drops/cm² across the same flow range. The average uniformity index improved from 30.53 to 15.95 as the flow rate increased. These results indicate that the application of WSP is an effective and scalable approach for analyzing spray performance in aeroponics, as WSP can be rapidly digitized with simple tools, such as a cell phone camera, avoiding the limitations of flatbed scanners or specialized imaging systems. Full article

This paper presents the results of laboratory research regarding the influence of the structure and color of decorative renders on the accuracy of measurements conducted using Leica ScanStation P40 terrestrial laser scanning (TLS). The study examined whether and how differences in render structure and color (brightness) affect the quality of data acquired via TLS. The color and brightness measurements of the test fields were performed using a flatbed scanner. The RGB color and luminance analysis of the test fields were conducted using the software “ImageJ” version 1.54g. The measurements were conducted for light-colored renders (average brightness from 143 to 243). The research found no clear relationship established between the type and color of render and the accuracy of laser scanning. The results indicate increased measurement dispersion with decreasing render brightness. It was found that the standard deviation of distance measurements for Scratched-type renders is approximately 26% higher than for Roughcast-type render. Full article

This work presents a Fricke radiochromic gel dosimeter with xylenol orange (XO) and a gelatin matrix modified with sorbitol. The dosimeter, combined with 2D scanning using a flatbed scanner and data processing using dedicated software packages, creates a radiotherapy dosimetry measurement system. The dosimeter reacts to ionizing radiation by changing color as a result of the formation of complexes of Fe³⁺ and XO molecules. It was characterized in terms of thermal and chemical stability and mechanical properties. The presence of sorbitol improved the mechanical and thermal properties of the dosimeter. The dosimeter maintains chemical stability, enabling its use in dosimetric applications, for at least six weeks. The dose–response characteristics of the dosimeter are discussed and indicate a dynamic dose–response of the dosimeter (up to saturation) of about 20 Gy and a linear dose–response of about 12.5 Gy. The following applications of the dosimeter are discussed: (i) as a 2D dosimeter in a plastic container for performing a coincidence test of radiation and mechanical isocenters of a medical accelerator, and (ii) for in vivo dosimetry as a 2D dosimeter alone and simultaneously as a bolus and a 2D dosimeter. Research has shown that the dosimeter has promise in many applications. Full article

Earthworms are important in agriculture in the process of soil fertilization and influence its physicochemical properties. The taxonomic classification of earthworms using morphological characteristics requires experts, is difficult, and can require specimen dissection to extract detailed anatomical studies. Molecular techniques are time-consuming and expensive. The objective of this study was to distinguish earthworms belonging to different genera, Eisenia, Dendrobaena, and Lumbricus, using an innovative approach involving machine learning models built based on image texture parameters from individual color channels R, G, B, L, a, b, X, Y, Z, U, V, and S. The earthworms Eisenia fetida, Dendrobaena ssp., and Lumbricus terrestris were used as research materials. Image acquisition was performed using a flatbed scanner on a black background. In the case of each earthworm, 2172 texture parameters from images in individual color channels R, G, B, L, a, b, X, Y, Z, U, V, and S were extracted. Textures after selection were used to develop classification models using machine learning algorithms. The earthworms Eisenia fetida, Dendrobaena ssp., and Lumbricus terrestris were distinguished with the accuracy reaching 100% for models built using Logistic, Ensemble, and Narrow Neural Network. All earthworms were correctly classified. Also, in the case of other models, earthworm classes were distinguished with high accuracies, such as 99% (Naive Bayes, Random Forest, SVM, KNN), 97% (Simple Logistic), and 94% (KStar). For the most important species, E. fetida, the correctness of the species identification was confirmed by direct RNA sequencing. The application of image analysis and machine learning turned out to be a non-destructive, inexpensive, and objective approach to distinguishing earthworms belonging to different genera. Full article

The two-dimensional (2D) measurement of radiation dose distribution on non-planar surfaces requires the use of a flexible dosimeter. This work concerns the use of a unique cotton textile-based dosimeter to characterize the dose distribution of a ⁶⁰Co source used in the research and sterilization of products. Alternatively, for high-dose-rate experiments, an electron beam accelerator has been used. The dosimeter was prepared by the padding-squeezing-drying of a cotton textile made of cellulose, where a 10% solution of nitrotetrazolium blue chloride (NBT) was used for the padding process. NBT served as a radiation-sensitive compound, which transformed into a purple-brown NBT formazan upon exposure to ionizing radiation. The NBT dosimeter is scanned after irradiation using a flatbed scanner, and the data is processed using dedicated software packages, which together constitute a 2D dose distribution measurement system. The green channel of the RGB color model contributes the most to the color change of the dosimeter. The calibration relation obtained for the green channel showed that the dosimeter responds to doses of 0.8–45 kGy. Conversions of the green channel signal were performed using the calibration relation to analyze the 2D dose at a large distance and close to a ⁶⁰Co source shielded by a solid metal and a cylindrical metal structure with holes. Additionally, the dose distribution was assessed using a dosimeter placed on metal implant models undergoing radiation serialization. This work demonstrates the potential of such a dosimeter for characterizing high-dose-rate ⁶⁰Co sources and measuring the dose distribution on non-planar surfaces. Full article

The emergence of new technologies focusing on “computer vision” has contributed significantly to the assessment of fruit quality. In this study, an innovative approach based on image analysis was used to assess the external quality of fresh and frozen ‘Mejhoul’ and ‘Boufeggous’ date palm cultivars stored for 6 months at −10 °C and −18 °C. Their quality was evaluated, in a non-destructive manner, based on texture features extracted from images acquired using a digital camera and flatbed scanner. The whole process of image processing was carried out using MATLAB R2024a and Q-MAZDA 23.10 software. Then, extracted features were used as inputs for pre-established algorithms–groups within WEKA 3.9 software to classify frozen date fruit samples after 0, 2, 4, and 6 months of storage. Among 599 features, only 5 to 36 attributes were selected as powerful predictors to build desired classification models based on the “Functions-Logistic” classifier. The general architecture exhibited clear differences in classification accuracy depending mainly on the frozen storage period and imaging device. Accordingly, confusion matrices showed high classification accuracy (CA), which could reach 0.84 at M0 for both cultivars at the two frozen storage temperatures. This CA indicated a remarkable decrease at M2 and M4 before re-increasing by M6, confirming slight changes in external quality before the end of storage. Moreover, the developed models on the basis of flatbed scanner use allowed us to obtain a high correctness rate that could attain 97.7% in comparison to the digital camera, which did not exceed 85.5%. In perspectives, physicochemical attributes can be added to developed models to establish correlation with image features and predict the behavior of date fruit under storage. Full article

Background and Objectives: The vertical dimension of occlusion’s (VDO) assessment is a highly important issue in the everyday dentist’s practice. Patients with unstable occlusion, lost occlusal stops, extensive tooth loss in the lateral area, or complete edentulism need a proper assessment of the VDO before the prosthetic restoration is carried out. Subjective and objective methods were used over time for the restoration of VDO. The study aimed to investigate the possible correlation between finger length, palm width and the vertical dimension of occlusion. Materials and Methods: Assessment of the VDO for 236 subjects, Romanian and French dental students, was performed using the Willis Bite Gauge. The left hand of the subjects was scanned using a flat-bed scanner, and then measurements of palm width and finger length were carried out for each subject. Comparison between VDO values and finger length/palm width was conducted using one-way ANOVA and Student t-Test. Results: Higher VDO average values were found in French subjects compared with Romanian students. The same results were found according to gender; in both female and male subjects, lower values of VDO were found in the Romanian group. Higher values were obtained for women within each group when comparing to men. Statistically significant correlations of the analyzed parameters and VDO values were found. Higher statistical correlations of the studied variables were found for men compared to women in both groups. The highest statistical correlation was obtained between the VDO and the palm width measured at the fingerbase, followed by the middle finger length. Conclusions: The results showed the highest statistical correlation between the vertical dimension of occlusion and the palm width measured at the fingers’ base. Statistical correlations were also found between the VDO and the middle finger length. Simple formulas using finger length/palm width can be used for a rapid VDO determination. Full article

Phaseolus lunatus L. is a species of landrace bean widely cultivated in Northeast Brazil. The integration of new technologies in the agricultural sector has highlighted the significance of seed images analysis as a valuable asset in the characterization process. The objective was to assess the morphology of 18 P. lunatus varieties gathered from four states in the Brazilian Northeast. To achieve this, 100 seeds from each variety were utilized, and their images were acquired using a flatbed scanner with a digital resolution of 400 dpi. Subsequently, the images were processed using the ImageJ software package for analyzing seed size, shape and color characteristics. Statistical analyses were performed with SPSS software applying stepwise Linear Discriminant Analysis (LDA). The overall accuracy rate for correct identification was 80.5%. Among the varieties, the lowest classification percentage was attributed to the ‘Coquinho Vermelha’ variety (39%), while the highest rates were observed for ‘Fava Roxa’ and ‘Fava de Moita’ (98%). The morpho-colorimetric classification system successfully discriminated the varieties of P. lunatus produced in the northeastern region of Brazil, highlighting the -+*/high degree of diversity within them. In particular, seeds with uniform coloring or clearly defined secondary color patterns were easier to classify. The varieties showed low correlation, forming distinct groups based on background color, secondary color, or seed size. Full article

This work presents a 2D radiochromic dosimeter for ultraviolet (UV) radiation measurements, based on cotton fabric volume-modified with nitroblue tetrazolium chloride (NBT) as a radiation-sensitive compound. The developed dosimeter is flexible, which allows it to adapt to various shapes and show a color change from yellowish to purple-brown during irradiation. The intensity of the color change depends on the type of UV radiation and is the highest for UVC (253.7 nm). It has been shown that the developed dosimeters (i) can be used for UVC radiation dose measurements in the range of up to 10 J/cm²; (ii) can be measured in 2D using a flatbed scanner; and (iii) can have the obtained images after scanning be filtered with a medium filter to improve their quality by reducing noise from the fabric structure. The developed cotton–NBT dosimeters can measure UVC-absorbed radiation doses on objects of various shapes, and when combined with a dedicated computer software package and a data processing method, they form a comprehensive system for measuring dose distributions for objects with complex shapes. The developed system can also serve as a comprehensive method for assessing the quality and control of UV radiation sources used in various industrial processes. Full article

The industrial adoption of material extrusion of polymers (MEX/P) is hindered by the geometric quality of manufactured parts. Contact image sensors (CISs), commonly used in flatbed scanners, have been proposed as a suitable technology for layer-wise characterization of contour deviations, paving the way for the application of corrective measures. Nevertheless, despite the high resolution of CIS digital images, the accurate characterization of layer contours in MEX/P is affected by contrast patterns between the layer and the background. Conventional edge-recognition algorithms struggle to comprehensively characterize layer contours, thereby diminishing the reliability of deviation measurements. In this work, we introduce a novel approach to precisely locate contour points in the context of MEX/P based on evaluating the similarity between the grayscale pattern near a particular tentative contour point and a previously defined gradient reference pattern. Initially, contrast patterns corresponding to various contour orientations and layer-to-background distances are captured. Subsequently, contour points are identified and located in the images, with coordinate measuring machine (CMM) verification serving as a ground truth. This information is then utilized by an adaptive edge-detection algorithm (AEDA) designed to identify boundaries in manufactured layers. The proposed method has been evaluated on test targets produced through MEX/P. The results indicate that the average deviation of point position compared to that achievable with a CMM in a metrology laboratory ranges from 8.02 µm to 13.11 µm within the experimental limits. This is a substantial improvement in the reliability of contour reconstruction when compared to previous research, and it could be crucial for implementing routines for the automated detection and correction of geometric deviations in AM parts. Full article

Studying the evolution of seed morphology and, in turn, the evolution of cultivars across time and space is of fundamental importance to agriculture and archaeology. The identification of ancient and modern grapevine (Vitis vinifera L.) cultivars is essential for understanding the historical evolution of grape cultivation. Grape seed morphology provides valuable information to explore the evolution of grape cultivars over time and space. The main aim of our study was to build a comprehensive regional database of grape seed morphological traits from modern and archaeological wine cultivars and wild grape species. We aimed to identify which seeds of modern grape cultivars exhibited morphological similarities to archaeological cultivars. This study focused on fifteen distinct modern types of seeds and two archaeological samples from the Byzantine-to-Early Medieval period. We acquired digital images of seeds using a flatbed scanner. For each sample, 100 seeds were randomly selected, and morphometric data on each seed were gathered using ImageJ. Differences among the seed cultivars were investigated using linear discriminant analysis. Archaeological seeds were found to be more similar to cultivated V. vinifera cultivars rather than V. sylvestris populations. Among the cultivated cultivars, Sangiovese and Tosta antica resulted to be cultivars most similar cultivars to the archaeological ones. The morphometric analysis of grape seeds proved to be a valuable resource for investigating the evolution of vine cultivars throughout history. Combining image analysis techniques with genetic data will open new perspectives for studying the origins of and variations in grape cultivars, contributing to the conservation and enhancement of viticultural heritage. Full article

Among the technological tools used in precision agriculture, the convolutional neural network (CNN) has shown promise in determining the nutritional status of plants, reducing the time required to obtain results and optimizing the variable application rates of fertilizers. Not knowing the appropriate amount of nitrogen to apply can cause environmental damage and increase production costs; thus, technological tools are required that identify the plant’s real nutritional demands, and that are subject to evaluation and improvement, considering the variability of agricultural environments. The objective of this study was to evaluate and compare the performance of two convolutional neural networks in classifying leaf nitrogen in strawberry plants by using RGB images. The experiment was carried out in randomized blocks with three treatments (T1: 50%, T2: 100%, and T3: 150% of recommended nitrogen fertilization), two plots and five replications. The leaves were collected in the phenological phase of floral induction and digitized on a flatbed scanner; this was followed by processing and analysis of the models. ResNet-50 proved to be superior compared to the personalized CNN, achieving accuracy rates of 78% and 48% and AUC of 76%, respectively, increasing classification accuracy by 38.5%. The importance of this technique in different cultures and environments is highlighted to consolidate this approach. Full article

This work describes the development of a reusable 2D detector based on radiochromic reaction for radiotherapy dosimetric measurements. It consists of a radiochromic gel dosimeter in a cuboidal plastic container, scanning with a flatbed scanner, and data processing using a dedicated software package. This tool is assessed using the example of the application of the coincidence test of radiation and mechanical isocenters for a medical accelerator. The following were examined: scanning repeatability and image homogeneity, the impact of image processing on data processing in coincidence tests, and irradiation conditions—monitor units per radiation beam and irradiation field are selected. Optimal conditions for carrying out the test are chosen: (i) the multi-leaf collimator gap should preferably be 5 mm for 2D star shot irradiation, (ii) it is recommended to apply ≥2500–≤5000 MU per beam to obtain a strong signal enabling easy data processing, (iii) Mean filter can be applied to the images to improve calculations. An approach to dosimeter reuse with the goal of reducing costs is presented; the number of reuses is related to the MUs per beam, which, in this study, is about 5–57 for 30,000–2500 MU per beam (four fields). The proposed reusable system was successfully applied to the coincidence tests, confirming its suitability as a new potential quality assurance tool in radiotherapy. Full article

Date palm (Phoenix dactylifera L.) fruit samples belonging to the ‘Mejhoul’ and ‘Boufeggous’ cultivars were harvested at the Tamar stage and used in our experiments. Before scanning, date samples were dried using convective drying at 60 °C and infrared drying at 60 °C with a frequency of 50 Hz, and then they were scanned. The scanning trials were performed for two hundred date palm fruit in fresh, convective-dried, and infrared-dried forms of each cultivar using a flatbed scanner. The image-texture parameters of date fruit were extracted from images converted to individual color channels in RGB, Lab, XYZ, and UVS color models. The models to classify fresh and dried samples were developed based on selected image textures using machine learning algorithms belonging to the groups of Bayes, Trees, Lazy, Functions, and Meta. For both the ‘Mejhoul’ and ‘Boufeggous’ cultivars, models built using Random Forest from the group of Trees turned out to be accurate and successful. The average classification accuracy for fresh, convective-dried, and infrared-dried ‘Mejhoul’ reached 99.33%, whereas fresh, convective-dried, and infrared-dried samples of ‘Boufeggous’ were distinguished with an average accuracy of 94.33%. In the case of both cultivars and each model, the higher correctness of discrimination was between fresh and infrared-dried samples, whereas the highest number of misclassified cases occurred between fresh and convective-dried fruit. Thus, the developed procedure may be considered an innovative approach to the non-destructive assessment of drying impact on the external quality characteristics of date palm fruit. Full article