Search Results (134)

In this work, we present a Physics-Informed Neural Network (PINN) framework for the classification of oil palm fresh fruit bunch (FFB) ripeness using RGB images. Unlike conventional Convolutional Neural Networks (CNNs) that learn solely from visual patterns, the proposed PINN integrates a physics-based index—derived from the red-to-green pixel intensity ratio—directly into the network architecture and loss function. This hybrid design embeds wavelength-dependent physical knowledge related to chlorophyll degradation during ripening, enabling the model to learn more robust and generalizable features even with limited and imbalanced training data. The PINN model achieves a peak accuracy of 0.73, outperforming the purely data-driven CNN baseline (0.68) by a margin of 5%. Overall, the PINN demonstrates superior performance in minority-class detection and maintains stable convergence under three different lighting conditions (different light spectra). These results highlight the effectiveness of integrating domain-specific physical insights into deep learning models, offering a promising pathway toward reliable, non-destructive, and automated ripeness assessment for agricultural applications. Full article

Maintaining color constancy in polymer extrusion processes is a key difficulty in manufacturing applications, as fluctuations in processing parameters greatly influence pigment dispersion and the quality of the finished product. Preliminary historical data mining analysis was conducted in 2009. This work concentrates on Opaque PC Grade 5, which constituted 2.43% of the pigment; it contained 10 PPH of resin2 with a Melt Flow Index (MFI) of 6.5 g/10 min and 90 PPH of resin1. It also employs a fixed resin composition with an MFI of 25 g/10 min. This research identified the significant processing parameters (PPs) contributing to the lowest color deviation. Interactions between processing parameters, for the same color formulation, were analyzed using statistical methods under various processing conditions. A principle-driven General Trends (GT) diagnostic procedure was applied, wherein each parameter was individually varied across five levels while holding others constant. Particle size distribution (PSD) and colorimetric data (CIE Lab*) were systematically measured and analyzed. To complete this, correlations for the impact of temperature (Temp) on viscosity, particle characteristics, and color quality were studied by characterizing viscosity, Digital Optical Microscopy (DOM), and particle size distribution at various speeds. The samples were characterized for viscosity at three temperatures (230, 255, 280 °C) and particle size distribution at three speeds: 700, 750, 800 rpm. This study investigates particle processing features, such as screw speed and pigment size distribution. The average pigment diameter and the fraction of small particles were influenced by the speed of 700–775 rpm. At 700 rpm, the mean particle size was 2.4 µm, with 61.3% constituting particle numbers. The mean particle size diminished to 2 µm at 775 rpm; however, the particle count proportion escalated to 66% at 800 rpm. This research ultimately quantifies the relative influence of particle size on the reaction, resulting in a color value of 1.36. The mean particle size and particle counts are positively correlated; thus, reduced pigment size at increased speed influences color response and quality. The weighted contributions of the particles, 51.4% at 700 rpm and 48.6% at 800 rpm, substantiate the hypothesis. Further studies will broaden the GT analysis to encompass multi-parameter interactions through design experiments and will test the diagnostic assessment procedure across various polymer grades and colorants to create robust models of prediction for industrial growth. The global quality of mixing polycarbonate compounding constituents ensured consistent and smooth pigment dispersion, minimizing color streaks and resulting in a significant improvement in color matching for opaque grades. Full article

This study aimed to evaluate the feasibility of producing vinegar from organic third-category apples, peaches, and clementines on a laboratory scale. Two-step fermentation with Saccharomyces cerevisiae and Gluconobacter oxydans was applied, monitoring production of ethanol and acetic acid and microbial dynamics. Fruit vinegars were subjected to analyses of sensory traits, color, volatile organic compounds (VOCs), and antioxidant activity. Comparable ethanol yields across substrates were obtained, ensuring consistent acetous fermentation and achieving acetic acid concentrations of 5.0–5.6%. Dynamics of yeasts and acetic acid bacteria reflected the production of and subsequent decrease in ethanol. Overall, fermentation proceeded a bit faster in peach juice. Overall, the fruit vinegars, particularly those from peaches and clementines, exhibited darker and more saturated tones. The values of colorimetric indexes fell within the range reported for vinegars. Sensory analysis highlighted large differences among the vinegars. Notwithstanding the highest scores of color, aroma intensity, and floral aroma received by the peach vinegar (PV), it received the lowest acceptability. Clementine vinegar (CV) was especially appreciated. Multivariate analysis based on the VOC profile showed that apple vinegar (AV) was quite similar to the commercial one, whereas PV and CV were well distinguished from it. CV showed the highest antioxidant activity followed by PV. Full article

Efficient and reliable estimation of rice phenological stages is crucial for improving yield prediction, optimizing irrigation, and guiding fertilization management. Spectral indices (SIs) derived from remote sensing have demonstrated strong potential for phenology detection. However, the suitability of specific spectral indices (SIs) for individual growth stages remains unclear due to data limitations. This study addresses this gap using a 7-year (2019–2025) daily in situ hyperspectral dataset that includes shortwave infrared (SWIR) bands. We evaluated various SIs to determine their effectiveness in identifying key phenological stages. The results demonstrate that no single index captures the entire cycle; instead, a multi-index approach is required. The SWIR-based Normalized Difference Vegetation Index (SNDVI) proved superior for detecting irrigation, transplanting, and flowering. The Green–Red Vegetation Index (GRVI) effectively tracked tillering and heading, while the Normalized Difference Vegetation Index (NDVI) and Hue identified the maximum tillering stage. For the ripening phase, the Normalized Difference Yellowness Index (NDYI) exhibited the highest accuracy in detecting maturity. Validation against Sentinel-2 simulations revealed strong correlations ($R^2>0.81$) for greenness-related indices (NDVI, GRVI, SNDVI, EVI), whereas colorimetric indices showed weaker agreement. These findings establish a robust, multi-index framework for high-frequency rice phenology monitoring. Full article

Grapevines face the dual challenge of sustaining yield and fruit quality under arid and increasingly variable environmental conditions. This study characterized the phenotypic variability and multi-year stability of 49 grapevine (Vitis spp.) accessions conserved in the Chincha germplasm bank over three consecutive growing seasons, with the aim of identifying promising material for table grape, pisco (a traditional grape-based distilled spirit from Peru), and wine production. Morphological traits (cluster weight, berry weight and dimensions), colorimetric parameters (CIELAB), and physicochemical attributes (moisture, dry matter, soluble solids, pH, titratable acidity, maturity index, and reducing sugars) were evaluated. Multivariate analyses (PCA, hierarchical clustering), genotype × environment interaction models (AMMI and GGE), stability indices (ASV and WAASBY), and assessments of interannual stability were applied, together with a multi-criteria selection index tailored to the intended end use. The results revealed two contrasting phenotypic profiles: one characterized by high berry volume/weight and elevated water content and another with smaller berries but higher dry matter, sugars, balanced acidity, and superior maturity indices. Genotypic effects were predominant for size-related traits such as berry weight, whereas titratable acidity and reducing sugars exhibited a more pronounced genotype × year interaction, supporting the use of AMMI models and the WAASBY index to select genotypes that are both productive and stable. The ranking identified accessions PER1002061, PER1002062, and PER1002168 as outstanding candidates for table grape production; PER1002076, PER1002097, and PER1002156 for pisco; and PER1002122, PER1002131, PER1002135, and PER1002098 as accessions with high oenological potential. Overall, these findings highlight the value and diversity of Peruvian grapevine germplasm and provide a foundation for breeding programs targeting varieties adapted to specific market niches, including table grape, wine, and pisco. Full article

Coffee quality arises from the interaction among genotype, environment, and postharvest management, yet few large-scale studies jointly integrate agronomic, phytochemical, and processing traits. We characterized 150 Coffea arabica L. accessions from six Peruvian regions, evaluated in the INIA coffee germplasm collection, quantifying agro-morphological traits, colorimetric parameters in cherries and beans, fermentation indicators, bioactive compounds, and antioxidant activity. Correlation analyses showed that total phenolics (TPCs) and total flavonoids (TFCs) were strongly associated with antioxidant activity, whereas caffeine content (CAF) varied, largely independently. Several chromatic parameters in parchment and green coffee (a*, b*, C*) showed positive correlations with phenolic content and antioxidant activity (ABTS, DPPH, FRAP), while final fermentation pH (FPH) was negatively associated with these compounds, supporting both color metrics and pH as operational indicators of chemical quality. Principal component analysis disentangled a morphometric gradient from a functional (phenolic–antioxidant) gradient, indicating that bean size and antioxidant potential can be improved in a semi-independent manner. Hierarchical clustering identified complementary ideotypes, and a multi-trait selection index highlighted promising accessions—PER1002197 (Cajamarca), PER1002222 (Cajamarca), PER1002288 (Pasco), and PER1002184 (Cajamarca)—that combine high phenolic/antioxidant levels, favorable chlorogenic acid (CGA)/trigonelline (TGN) profiles, contrasting (high/low) caffeine, and competitive yield (YPP)/bean size. These accessions represent promising candidates for breeding climate-smart and nutraceutical-oriented coffee. Full article

Background: Cannabinoids (CBs) are FDA-approved for mitigating chemotherapy-induced side effects such as pain, nausea, and loss of appetite. Beyond palliative care, CBs exhibit anti-tumor properties in various cancers, including non-Hodgkin’s lymphoma (NHL). Previously, we demonstrated the cytotoxic effect of endogenous and exogenous cannabinoids on human and canine B- and T-cell-type NHL cell lines. The purpose of this study was to establish the cytotoxic effect of cannabinoids in combination with the components of CHOP and lomustine. This traditional NHL chemotherapy regimen comprises cyclophosphamide, doxorubicin, vincristine, and prednisolone. Methods: In this study, we studied three cannabinoids, one from each of the three major categories of cannabinoids (endocannabinoid AEA, phytocannabinoid CBD, and synthetic cannabinoid WIN-55 212 22). Each cannabinoid was selected based on potency, as determined in our previous experiments. For the combination, we used five NHL chemotherapy drugs. We analyzed the cytotoxicity of each drug alone and in combinations using canine malignant B-type NHL cell line 1771 and a colorimetric MTT (3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyl tetrazolium bromide) cell proliferation assay and combination index (CI) based on the Chou–Talalay method. Results: Our results demonstrate that the cytotoxic effects of all traditional NHL chemotherapy drugs are synergistically enhanced (interaction with CI < 1) by each of the three cannabinoids at sub-IC₅₀ concentrations. Conclusions: This work provides a proof of concept for using cannabinoids and traditional NHL drugs in combination to reduce the dose, and thereby potentially reducing the toxicity, of chemotherapeutic drugs and increasing the survival benefit in lymphoma clinical translation studies, offering a significant advancement in cancer treatment. Full article

Aiming to compare the applicability and the successfulness of reactive dye printing papers’ coloration, two laboratory-synthesized anthraquinone reactive dyes are studied in comparison with two commercially available anionic and cationic direct dyes. Reactive dye 1 is monochlorotriazine and reactive dye 2 is bifunctional (contains two reactive groups—one is a monochlorotriazine atom and one an unsaturated allylic group). The synthesized reactive dyes are investigated through a paper slurry, white waters and paper sample properties comparative analysis. The drainage ability, flocculation volume and sedimentation index of paper slurries are determined. The turbidity, conductivity, pH and dye concentration in the white waters are also examined to ensure dye fixation. Through SEM, the paper structure is evaluated. The strength properties, colorimetric characteristics and stability at accelerated light aging of all 15 paper samples are investigated. The dewatering ability is enhanced, the white waters are clarified, the conductivity and pH level are stable and the dye concentration is on the same levels as for the direct dyes. The paper structure is uniform, the strength is slightly enhanced and color differences are indistinguishable compared to those of the direct dyes, when the ratio of the fixing agent to dye is appropriately optimized. Full article

Thanks to both endogenous and exogenous antioxidants (AOs), the antioxidant defense system ensures redox homeostasis, which is crucial for protecting the body from oxidative stress and maintaining overall health. The food industry also exploits the antioxidant properties to prevent or delay the oxidation of other molecules during processing and storage. There are many classical methods for assessing antioxidant capacity/activity, which are based on mechanisms such as hydrogen atom transfer (HAT), single electron transfer (SET), electron transfer with proton conjugation (HAT/SET mixed mode assays) or the chelation of selected transition metal ions (e.g., Fe²⁺ or Cu¹⁺). The antioxidant capacity (AOxC) index value can be expressed in terms of standard AOs (e.g., Trolox or ascorbic acid) equivalents, enabling different products to be compared. However, there is currently no standardized method for measuring AOxC. Nanoparticle sensors offer a new approach to assessing antioxidant status and can be used to analyze environmental samples, plant extracts, foodstuffs, dietary supplements and clinical samples. This review summarizes the available information on nanoparticle sensors as tools for assessing antioxidant status. Particular attention has been paid to nanoparticles (with a size of less than 100 nm), including silver (AgNPs), gold (AuNPs), cerium oxide (CeONPs) and other metal oxide nanoparticles, as well as nanozymes. Nanozymes belong to an advanced class of nanomaterials that mimic natural enzymes due to their catalytic properties and constitute a novel signal transduction strategy in colorimetric and absorption sensors based on the localized surface plasmon resonance (LSPR) band. Other potential AOxC sensors include quantum dots (QDs, <10 nm), which are particularly useful for the sensitive detection of specific antioxidants (e.g., GSH, AA and baicalein) and can achieve very good limits of detection (LOD). QDs and metallic nanoparticles (MNPs) operate on different principles to evaluate AOxC. MNPs rely on optical changes resulting from LSPR, which are monitored as changes in color or absorbance during synthesis, growth or aggregation. QDs, on the other hand, primarily utilize changes in fluorescence. This review aims to demonstrate that, thanks to its simplicity, speed, small sample volumes and relatively inexpensive instrumentation, nanoparticle-based AOxC assessment is a useful alternative to classical approaches and can be tailored to the desired aim and analytes. Full article

This study aimed to evaluate the antiproliferative, apoptotic, and oxidative stress-inducing effects of the combination of metformin and doxorubicin (adriamycin) in OVCAR3 and SKOV3 ovarian cancer cell lines and to investigate the potential synergistic interactions between the two agents. Cell viability was assessed using the MTT assay. Apoptosis was quantified via Annexin V/PI staining followed by flow cytometry. Caspase-8 and caspase-9 activities were measured using colorimetric assays. Oxidative stress parameters, including reactive oxygen species (ROS) and nitric oxide (NO), were determined using DCFH-DA fluorescence and the Griess assay, respectively. The mRNA expression levels of apoptosis-related genes (Bcl-2, Survivin, Bax, and Caspase-3) were analyzed by qRT-PCR. Drug interaction and synergy were evaluated using the Chou–Talalay combination index (CI) model and the highest single agent (HSA) model. Prognostic relevance of target genes and protein interaction networks was examined through TCGA and STRING databases. The metformin–doxorubicin combination demonstrated strong synergistic antiproliferative effects in both cell lines (CI < 0.7 in OVCAR3). The combination significantly increased apoptosis compared with single-agent treatments, yielding a total apoptotic rate of 62.5 ± 4.2% in OVCAR3. Caspase-8 and caspase-9 activities were elevated by 5.6 ± 0.7-fold and 7.3 ± 0.8-fold, respectively. Combination treatment also induced marked oxidative stress, increasing NO levels to 12.4 ± 1.1 µM and ROS levels to 412 ± 25% in OVCAR3 cells. qRT-PCR analyses revealed downregulation of anti-apoptotic Bcl-2 (0.28 ± 0.04-fold) and Survivin (0.25 ± 0.03-fold), along with upregulation of pro-apoptotic Bax (5.8 ± 0.6-fold) and Caspase-3 (6.5 ± 0.7-fold). Bioinformatic analyses indicated that high Bcl-2 and Survivin expression correlated with poorer overall survival in ovarian cancer patients. Metformin enhances the anticancer efficacy of doxorubicin through synergistic activation of intrinsic and extrinsic apoptotic pathways, induction of oxidative and nitrosative stress, and transcriptional regulation of key apoptotic markers. These findings support the potential use of metformin as an adjuvant agent to strengthen doxorubicin-based chemotherapy in ovarian cancer. Full article

Grape pomace is the principal by-product of the winemaking industry, with an estimated global production of 14 million tonnes annually. Traditional livestock systems often incorporate local agroindustrial by-products into ruminant diets, and grape pomace is particularly notable for its high concentrations of bioactive compounds. These grape-derived molecules may exert beneficial effects on animal oxidative balance, biochemical status and productive performance, offering an environmentally and economically sustainable alternative to conventional feed ingredients that may be incorporated into the milk produced. This study evaluated the impact of incorporating varying inclusion levels (0, 5, 10 and 15% DM) of ensiled white grape pomace (WGP) into isoenergetic and isoproteic diets on the nutritional and technological characteristics of goat milk. Eighty-eight Murciano-Granadina dairy goats were selected and allocated into eight homogeneous batches (n = 11 per batch) based on physiological traits. Following a pre-experimental sampling, each diet was randomly assigned to two batches, and the feeding trial lasted eight weeks. After a two-week dietary adaptation period, four biweekly samplings were conducted to obtain representative bulk tank milk samples from each batch. Milk samples were analysed for gross composition, pH, mineral profile, fatty acid composition, coagulation properties, colorimetric parameters and antioxidant capacity. WGP consumption significantly increased milk fat content, improved the lipid profile from a human health perspective, accelerated curd aggregation and elevated the yellowness index. Moreover, notable changes were observed in the antioxidant activity of the milk. Despite these effects, the overall composition of the milk remained largely unchanged, which is a key factor in preserving its technological properties. Nevertheless, the final product demonstrated enhanced biological quality, reinforcing its value as a functional food for human consumption. Full article

Natural rubber quality assessment traditionally relies on subjective visual inspection, leading to inconsistent grading and processing inefficiencies. This study presents a colorimetric imaging system integrating 48-megapixel image acquisition with automated colorimetric analysis for objective rubber classification. Five rubber grades—white crepe, STR5, STR5L, RSS3, and RSS5—were analyzed using standardized 25 × 25 mm² specimens under controlled environmental conditions (25 ± 2 °C, 50 ± 5% relative humidity, 3200 K illumination). The image processing pipeline employed color space transformations from RGB through CIE1931 $XYZ$ to CIELAB coordinates, with yellowness index calculation following ASTM E313-20 standards. The classification algorithm achieved 100% accuracy across 100 validation specimens under controlled laboratory conditions, with a processing time of 1.01 ± 0.09 s per specimen. Statistical validation via one-way ANOVA confirmed measurement reliability (p > 0.05) with yellowness index values ranging from 8.52 ± 0.52 for white crepe to 72.15 ± 7.47 for RSS3. Image quality metrics demonstrated a signal-to-noise ratio exceeding 35 dB and a spatial uniformity coefficient of variation below 5%. The system provides 12-fold throughput improvement over manual inspection, offering objective quality assessment suitable for industrial implementation, though field validation under diverse conditions remains necessary. Full article

Enzymatic browning markedly reduces the processing quality and economic value of potatoes. This study evaluated the effects of copper sulfate (CuSO₄) on potato growth, yield, and enzymatic browning. Quantitative analysis of browning-related enzymes, organic acids, free amino acids, and the browning index (BI) was conducted using high-performance liquid chromatography and non-contact colorimetric technology. Moderate Cu²⁺ (0.078–0.157 mmol·L⁻¹) supply enhanced photosynthetic capacity, biomass, and starch accumulation, whereas excessive Cu induced oxidative stress, increased PPO activity, phenolic accumulation, and BI. Metabolic profiling revealed that Cu²⁺ activates PPO via its copper-binding sites and reprograms amino acid and organic acid metabolism—upregulating arginine and proline while downregulating isoleucine, leucine, phenylalanine, lysine, citrate, and chlorogenic acid, all strongly correlated with BI. These findings highlight the dual role of copper in yield formation and enzymatic browning, introducing metabolic reprogramming as a potential mechanism for optimizing Cu fertilization to balance productivity and postharvest quality. Full article

Background: Visceral leishmaniasis (VL) is a neglected tropical disease with limited therapeutic options, often restricted by toxicity, high costs, and resistance. Chalcones are promising scaffolds for the development of antiparasitic agents. Objectives: This study aimed to synthesize novel acetamides derived from 4-hydroxychalcones and evaluate their antileishmanial activity, cytotoxicity, potential synergy with amphotericin B (AmB), and mechanisms of action through in silico analyses. Methods: Six chalcone–acetamides (3a–c, 4a–c) were synthesized and characterized by IR, NMR, and HRMS. In vitro activity against Leishmania infantum promastigotes and axenic amastigotes was assessed by colorimetric assays. Cytotoxicity was tested in human erythrocytes and PBMCs. Synergy with AmB was analyzed by the combination index. Molecular docking targeted parasite enzymes, and ADMET tools predicted pharmacokinetic and safety profiles. Results: Phenyl-substituted derivatives (3a–c) were inactive, while cyclohexyl-substituted analogs (4a–c) were active. Compound 4b displayed the strongest effect (IC₅₀: 7.02 μM for promastigotes, 3.4 μM for amastigotes), with low cytotoxicity and high Selectivity Indices. In combination with AmB, compound 4b reduced the effective dose (DRI: 2.87) and increased the therapeutic window. Docking revealed favorable interactions of compound 4b with deubiquitinase DUB16 and tryparedoxin peroxidase I, suggesting enzyme inhibition. ADMET predictions supported good absorption and low toxicity. Conclusions: Compound 4b demonstrated potent and selective antileishmanial activity, synergism with AmB, and predicted safety. These findings highlight chalcone derivative 4b as a promising lead for future preclinical development in VL therapy. Full article

In recent years, lab-grown diamonds have become more popular in both domestic and international markets for their rich color palette. Research on yellow lab-grown diamonds has primarily focused on spectroscopic and defect characteristics currently, while the study has largely focused on nitrogen content and related color-causing mechanisms, such as NV series defects. However, the relationship between nitrogen content and defects and color is limited. In this study, eight lab-grown diamonds with varying yellow shades were selected as samples to be studied by photoluminescence spectra, infrared spectra, Raman spectra, and colorimetry testing. Based on the colorimetric parameters L*, a*, and b*, the standard formula for the yellowness index, the intensities of the NV⁰ and NV⁻ peaks in the photoluminescence spectra and the absorptivity in the infrared spectra, the hue angle h, the yellowness index YI E313, the concentration ratio of NV⁻ defect in NV color centers R, and the nitrogen content N_C were calculated. Results indicate that characteristic peaks of NV series defects as a specific photoluminescence signature, notably the absence of [Si-V]⁻ defect, demonstrate that the samples are high-temperature, high-pressure diamonds derived from graphite that underwent post-growth irradiation. The specific infrared signature indicates that the type of samples is type Ib, attributed to isolated nitrogen (C aggregate). The intrinsic peak of diamond is detected in Raman spectra, with symmetric stretching vibrations of C and N and the ‘D’ peak of graphite is detected as well. Meanwhile, the yellowness index shows a negative correlation with hue angle, a positive correlation with concentration ratio, and a positive linear correlation with nitrogen content, the equation $y=0.17x+124.40$. The yellowness index is divided into three levels: 70–80, 80–90, and 90–100. The yellow hue of samples is light between 70–80, intense between 80–90, and deep between 90–100. Full article