Search Results (172)

Punica granatum L. is a nutritionally relevant fruit with a complex phytochemical profile that varies across its anatomical fractions, including peel, arils, juice, seeds, and seed oil. Although pomegranate is widely recognized for its health-promoting potential, the nutritional significance of its matrix-dependent composition, bioavailability, and gut microbiota-mediated metabolism remains insufficiently integrated. This review aimed to critically evaluate the phytochemical diversity of pomegranate and its nutrition-related multi-target biological functions, with particular emphasis on food matrices, bioaccessibility, and translational relevance. A structured review of peer-reviewed studies indexed in major scientific databases from 2000 to January 2026 was conducted. Eligible reports included analytical, preclinical, and clinical studies addressing the composition of pomegranate-derived materials and their biological effects, with attention to extraction matrix, processing, bioavailability, microbial biotransformation, and mechanisms of action. Pomegranate exhibits marked matrix-specific phytochemical diversity. Peel is particularly rich in ellagitannins, especially punicalagin and punicalin; arils and juices are enriched in anthocyanins and flavonols; and seed oil contains high levels of punicic acid. Reported biological activities include antioxidant, anti-inflammatory, antimicrobial, metabolic, anti-aging, and anticancer effects. These actions appear to result from synergistic interactions among multiple bioactive compounds rather than from a single dominant constituent. Importantly, gut microbiota-driven conversion of ellagitannins and ellagic acid into urolithins is a major determinant of systemic bioactivity and may contribute to interindividual variability in response. The health effects of pomegranate should be interpreted within a nutrition-focused, matrix-dependent framework integrating composition, processing, bioavailability, and microbiota-derived metabolism. Full article

Recent automated search methods have improved lower bounds for several Ramsey numbers, but the strongest gains often depend on structured seeding and cell-specific heuristic discovery. This leaves open a more fundamental question: Can a useful search structure be transferred across related Ramsey cells rather than rediscovered independently for each target instance? This work proposes a teacher–student framework for transferable structural search in Ramsey graph construction, inspired by the structure-distillation logic of Physics Structure-Informed Neural Networks (Ψ-NNs). The framework builds compressed structural representations from teacher witnesses and search traces, extracts reusable motifs and relations, and reconstructs transfer candidates. These are refined by balanced search and, for weak R(3, s) cells, by exact small-cell supervision. The framework is evaluated as a proof of concept across five Ramsey cells under transfer, matched-compute, search, ablation, and interpretability settings, including a proportional shift-scaling baseline and a greedy triangle-closing baseline that probe the structure-validity frontier from complementary directions. Supplementary experiments cover seed robustness, budget sensitivity, transfer-neighborhood variation, structural-resolution changes, stronger exact supervision, cross-r teacher pooling, single-teacher configurations, and scaling behavior across graph sizes. The results show that the portfolio version of the framework is the strongest balanced transfer method in the current study, while a structure-dominant oracle achieves stronger witness-shape agreement but worse Ramsey-valid construction. These findings reveal a clear structure-validity frontier and suggest that transferable Ramsey search should be evaluated by how well structural priors survive the validity constraints of new cells. Full article

This study employed UPLC-MS/MS to determine the contents of major polyphenolic compounds and proanthocyanidins (PCs) in Kyoho grape seeds, optimized the extraction method and conditions for PCs using response surface methodology (RSM), and further evaluated the scavenging activities of PCs against 2,2-diphenyl-1-picrylhydrazyl (DPPH) and hydroxyl (•OH) radicals as well as their effects on growth, immunity, and oxidative stress in mice. Three hundred and sixty 3-week-old male mice (42.28 ± 0.31 g) were assigned to a single factor complete randomized trial design and fed with six different diets including 0 mg/kg vitamin E(VE) + 0 mg/kg PCs, 100 mg/kg VE, 25 mg/kg PCs + 75 mg/kg VE, 50 mg/kg PCs + 50 mg/kg VE, 75 mg/kg PCs + 25 mg/kg VE and 100 mg/kg PCs, respectively. The results demonstrated that PCs were identified as the predominant phenolic compounds, accounting for 29.6% of total phenolic substances in Kyoho grape seeds. Additionally, the ultrasound-assisted extraction method was superior to the shaker-assisted and low-temperature infiltration extraction methods, with optimal conditions of 60% ethanol concentration, material-to-liquid ratio of 1:20 g/mL, temperature of 30 °C, and extraction time of 50 min. Scanning electron microscopy (SEM) revealed that ultrasound treatment effectively disrupted the seed surface structure, facilitating PC release. In vitro, PCs exhibited significantly stronger DPPH and hydroxyl radical (•OH) scavenging activities than vitamin C (VC), Trolox, and gallic acid. Compared with the control group, mice fed diets containing PCs and VE showed higher superoxide dismutase (SOD) activity, glutathione peroxidase (GSH-PX) activity, and total antioxidant capacity (TAOC), Catalase (CAT), GPX and inflammation factor 10 (IL-10) genes levels in the serum and liver (p < 0.05), whereas the levels of immunoglobulin G (IgG), immunoglobulin A (IgA), immunoglobulin M (IgM), tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6), as well as the mRNA expression of IL-1β and TNF-α, showed the opposite trend (p < 0.05). In conclusion, the antioxidant capacity of PCs was stronger than that of VC and VE. The addition of PCs improved the antioxidant activity and immune function of mice. Full article

The endosperm of Gleditsia japonica var. delavayi seeds is a valued medicinal and edible material, rich in polysaccharides exhibiting excellent functional properties for food applications. However, conventional methods for extracting Gleditsia japonica var. delavayi polysaccharides (GJP) are often inefficient and environmentally unfriendly. Thus, we developed a green, ultrasound-assisted process for extracting GJP. We systematically optimized key parameters (liquid-solid ratio and ultrasonic time, temperature, and power) using single-factor, Plackett–Burman and Box–Behnken experimental designs to maximize yield and characterize the product. The optimized process (200 mL/g, 62 min, 51 °C and 180 W) exhibited an extraction yield of 76.11%, producing GJP with a purity of 79.89%, which satisfies standards for food additives. The extracted GJP exhibited a semi-crystalline structure, high solubility (80.06%), low esterification degree (2.60%) and high viscosity and thermal stability between 30 °C and 70 °C. Crucially, this process required no chemical reagents and consumed only 0.18 kW·h of energy. Analysis indicates that the optimized ultrasound-assisted extraction of GJP is a green and efficient method with high extraction rates and reduced processing time and energy consumption; furthermore, it does not require any chemical reagents, making it a promising alternative to conventional techniques. Full article

Low extraction efficiency limits the availability and application of aescins, which exhibit various pharmacological activities. Here, we optimized parameters for ultrasound-assisted extraction of aescins from Aesculus chinensis seeds using deep eutectic solvent (DES)-water mixtures. Seven DES formulations were screened, and one providing the highest yield was selected for optimizing the molar ratio. The effects of four parameters were investigated using single-factor experiments combined with response surface methodology. The optimal extraction conditions were as follows: DES, a 1:1 mixture of 1,3-butanediol and lactic acid, with 42.5% water, used at a liquid-solid ratio of 25 mL/g; ultrasonic frequency, 40 kHz; extraction temperature, 70 °C; and extraction time, 27.5 min. The extraction yield under these conditions was significantly higher than that obtained via traditional methods. Aescin was purified from the DES extract using macroporous resin. AB-8 resin was most efficient in adsorbing aescin in static adsorption tests. Based on dynamic adsorption experiments, optimal separation, with a 100% recovery rate, was achieved by passing four bed volume (BV) of extract through AB-8 column, removing impurities with two BV of deionized water and four BV of 30% ethanol, and eluting with four BV of 60% ethanol at 5–10 mL/min. This green method should be suitable for large-scale applications. Full article

The valorization of agro-industrial by-products is a sustainable approach to recovering high-value bioactive compounds. In this study, Opuntia ficus-indica (L.) Mill. seed press residues were investigated as a source of phenolic and flavonoid compounds using microwave-assisted extraction (MAE). A multi-step optimization strategy was implemented, combining preliminary single-factor experiments (OVAT), response surface methodology based on a Box–Behnken design (BBD), and machine learning modeling using K-nearest neighbors coupled with the dragonfly algorithm (KNN_DA), followed by desirability-based validation. The effects of ethanol concentration (50–100%), microwave power (400–800 W), extraction time (2–4 min), and liquid-to-solid ratio (30–50 mL/g) were evaluated on Folin–Ciocalteu reducing capacity (FCRC), AlCl₃ complexation response, and antioxidant activity assessed by DPPH radical scavenging and reducing power assays. Optimal conditions were identified at 50% ethanol, 800 W microwave power, 4 min extraction time, and a liquid-to-solid ratio of 47.28 mL/g. Under these conditions, FCRC reached 376.85 ± 0.23 mg GAE/100 g DW and 49.16 ± 0.33 mg QE/100 g DW for AlCl₃ complexation response, with prediction errors of 2.80% and 0.82%, respectively. The optimized extracts exhibited enhanced antioxidant activity. These findings confirm MAE as a rapid and environmentally friendly technique and highlight the predictive performance of the KNN_DA model for process optimization. Full article

Background/Objectives: Mucuna pruriens (Linn.) DC. var. pruriens is a leguminous plant whose seeds have been used in traditional medicine, including for the enhancement of sexual function. However, scientific evidence regarding its toxicological safety remains limited. Accordingly, the present study aimed to investigate the acute and chronic oral toxicity of the ethanolic seed extract of M. pruriens var. pruriens in Sprague–Dawley rats. Methods: Acute oral toxicity was assessed in female rats following a single oral administration of the ethanolic seed extract of M. pruriens var. pruriens at a dose of 5000 mg/kg body weight, with animals monitored for general behavior, clinical signs, and mortality over a 14-day period. Chronic oral toxicity was evaluated in female and male rats administered the ethanolic seed extract of M. pruriens var. pruriens at doses of 100, 500, and 2500 mg/kg body weight daily for 270 days. Animals were monitored for general behavior, clinical signs, and health status throughout the study. Hematological, blood chemistry, gross pathological, and histopathological assessments were conducted at study termination. Results: In the acute oral toxicity study, no mortality or treatment-related behavioral abnormalities or clinical signs were observed in female rats receiving the ethanolic seed extract of M. pruriens var. pruriens, and findings were comparable to those of the control group. In the chronic oral toxicity study, no mortality occurred in any treatment group. Although statistically significant increases or decreases were observed in certain body weight, organ weight, hematological, and blood biochemical parameters compared with the control group, all values remained within established reference ranges. When considered together with the absence of abnormal behavioral changes, clinical signs, and gross pathological or histopathological alterations in major organs, these findings indicate that long-term oral administration of the ethanolic seed extract of M. pruriens var. pruriens did not result in chronic toxicity. Conclusions: The ethanolic seed extract of M. pruriens var. pruriens did not produce acute or chronic oral toxicity in Sprague–Dawley rats. Nevertheless, further clinical investigations are recommended to confirm its long-term safety for human use. Full article

Sugar beet (Beta vulgaris L.) is one of the most important sugar crops and potential energy crops in China. The utilization of its heterosis is crucial for breaking through the bottlenecks in yield and quality, while the fertility identification of binary male-sterile lines is the core link to ensure the purity of hybrid seeds. Due to its indeterminate inflorescence, artificial emasculation of sugar beet is not feasible, which significantly increases the difficulty in hybrid seed production. To rapidly and accurately identify the fertility composition of monogerm binary male-sterile lines of sugar beet, ensure the maternal line purity in sugar beet hybrid seed production, and improve breeding efficiency, this study conducted fertility identification using molecular marker technology with 7 monogerm binary male-sterile line germplasm resources (297 plants) provided by three research institutions in different regions of China. Genomic DNA was extracted from young sugar beet leaves by the CTAB method. The cytoplasmic fertility types were identified using the TR1 primer, and the fertility gene composition at the nuclear Rf1 locus was verified by the s17 molecular marker combined with Hap II and Hind III double digestion. The results showed that in the cytoplasmic fertility identification, the proportion of S-type cytoplasm in Lines 2 to 7 reached 100%, indicating stable sterility without maintainer line contamination; Line 1 had 93.33% S-type cytoplasm, mixed with 6.67% N-type cytoplasm. For the nuclear Rf1 locus identification, 93.27% (277 plants) of the tested materials yielded the target 1800 bp band by PCR amplification, which were preliminarily identified as homozygous recessive type. Among them, Lines 1 to 3 all showed a single 1800 bp band pattern, indicating homozygous and consistent nuclear fertility genotypes; 20 plants (6.73%) in Lines 4 to 7 exhibited a composite 1800/1300 bp band pattern, suggesting the presence of restorer allele contamination in some lines. Genotype analysis based on 35 enzyme-digested verification samples revealed that the 4/4 genotype had the highest proportion. This study realized the rapid and accurate identification of cytoplasmic and nuclear fertility in monogerm binary male-sterile lines of sugar beet through molecular marker technology, clarified the fertility purity status of 7 germplasm resources, and verified the application value of this technology in the fertility identification of sugar beet binary male-sterile lines. These results provide a scientific basis and technical support for controlling maternal line purity and improving breeding efficiency in sugar beet hybrid seed production. Full article

The pursuit of sustainable alternatives has spurred interest in plant-derived bioherbicides with multi-target actions to combat resistance. This study explored the herbicidal potential of Agave lechuguilla extract (AGE) against the widely problematic weed Chenopodium album L. (lambsquarters). Various methods, including germination assays, biochemical profiling, measurements of antioxidant enzyme activity, isothermal microcalorimetry, and both macroscopic and microscopic morphological analyses, were employed to evaluate the effects of AGE relative to glyphosate (1.5%). The results indicated that AGE inhibited seed germination in a concentration-dependent manner, with the 30 g/L dose exhibiting the most significant effect. Treatment with 30 g/L of AGE led to a notable decrease in total carbohydrate content and catalase activity, an increase in total lipids, and an enhancement of glutathione reductase activity. Additionally, it suppressed metabolic heat output and severely disrupted root and cellular architecture, resulting in a reduction of cell area by 51.1%. In contrast, glyphosate primarily increased lipid content and induced near-complete metabolic suppression while causing distinct morphological and enzymatic alterations. The findings demonstrate that AGE functions as a multi-target pre-emergence bioherbicide, disrupting processes related to germination, metabolism, oxidative balance, and morphology through mechanisms that differ from the single-target action of glyphosate. This underscores its potential for sustainable weed management. Full article

This paper addresses the issue of low detection accuracy in underwater optical images for unmanned underwater vehicles (UUVs) during practical operations, caused by factors such as uneven lighting, blur, complex backgrounds, and target occlusion. To enhance the autonomous perception and control capabilities of UUVs, a high-precision algorithm named MBACA-YOLO is proposed based on the YOLOv13n model. Firstly, the convolutional layers in the backbone network of YOLOv13n are optimized by replacing stride-2 convolutions with stride-1 and embedding SPD layers to enable richer feature extraction. Secondly, the newly proposed MBACA attention mechanism is integrated into the final layer of the backbone network, enhancing effective features and suppressing background noise interference. Thirdly, traditional upsampling in the neck network is replaced with CARAFE upsampling to mitigate noise pollution. Finally, an Alpha-Focal-CIoU loss function is designed to improve the accuracy of bounding box regression for underwater targets. To validate the algorithm’s effectiveness, experiments were conducted on the URPC dataset with the following evaluation protocol: 640 × 640 input resolution, batch size 1, FP32 precision, and standard NMS. All results are from a single random seed with 300 epochs of training. The proposed MBACA-YOLO algorithm outperforms the baseline YOLOv13n model, improving mAP@0.5 and mAP@0.5:0.95 by 3.1% and 2.8% respectively, while adding only 0.49M parameters and 1.0 GFLOPs, with an FPS drop of just 2 frames. This makes it an efficient, deployable perception solution for automated Unmanned Underwater Vehicles (UUVs), significantly advancing intelligent underwater systems. Full article

Flax (Linum usitatissimum L.) is a crop widely cultivated for fiber and oil production. The screening method for flax breeding must effectively address the biochemical characteristics of flaxseeds. In this study, to characterize flax cultivars, we extracted oil, defatted kernel, hull, and mucilage from whole seeds for the ATR-FT-MIR and FT-Raman spectroscopic measurements. In addition, for ATR-FT-MIR analysis, oil samples were obtained by pressing the flaxseed directly onto the crystal surface. After removing any seed residues, a grease stain was used for the measurement, allowing for the acquisition of the oil spectrum from a single seed. This method also enabled the detection of free fatty acids, serving as evidence of seed damage. Both methods effectively estimated the degree of unsaturation as a cultivar marker. The vibrational spectra of defatted kernels showed strong protein features; polysaccharide bands dominated in hull and mucilage spectra. Discrimination of flax cultivars using principal component analysis of vibrational spectra in specific regions was the most promising for flaxseed oil and mucilage. Multivariate analysis of a set of selected variables sensitive to the flaxseed oil composition successfully distinguished all flax cultivars of this study. The strong correlation observed between ATR-FT-MIR and FT-Raman results confirmed that these methods are comparable for characterizing different grades of flaxseed oil. Full article

The global citrus-processing industry generates 15–32 million tonnes of waste annually. Lemon-processing residues—peels, seeds, and pomace—constitute 45–55% of fruit mass and harbour high-value bioactive compounds amenable to cascade valorisation. This review (Part I of a two-part series) examines green extraction technologies for recovering bioactive compounds from lemon waste streams. Following bibliometric analysis of 847 publications (2003–2025), this work delineates the compositional heterogeneity of lemon fractions and establishes a hierarchical framework for value-added products encompassing essential oils, pectin, polyphenols, seed oils, citric acid, industrial enzymes, α-cellulose, and nanocrystalline cellulose. Four sustainable extraction methodologies are systematically evaluated: ultrasound-assisted extraction, microwave-assisted extraction, supercritical CO₂ extraction, and enzyme-assisted extraction. Comparative assessment demonstrates yield improvements of 16–112% over conventional approaches, processing-time reductions of 89–98%, and energy savings up to 95%. Critical research gaps include fragmented single-product valorisation, insufficient techno-economic assessment, and limited industrial-scale validation. Integrated cascade biorefineries employing sequential green extraction protocols offer economically viable pathways for transforming lemon waste into diversified revenue streams. Industrial implementation, circular-economy integration, and techno-economic feasibility are addressed in Part II. Full article

To improve the accuracy of detecting external defects in seed potatoes and address the reliance of current hyperspectral imaging methods on single-dimensional data, this study proposes a multi-dimensional spectral–spatial information fusion approach via concatenation based on a one-dimensional convolutional neural network (1DCNN) within the framework of deep learning. Hyperspectral three-dimensional data were acquired for normal seed potatoes and for samples presenting six types of external defects—decay, mechanical damage, wormhole, common scab, black scurf, and frostbite—across a wavelength range of 935–1721 nm. From the hyperspectral images, one-dimensional spectral data and two-dimensional spatial data were extracted. The one-dimensional spectral data were preprocessed using six methods: Savitzky–Golay smoothing (SG), standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (FD), second derivative (SD), and orthogonal signal correction (OSC). Feature wavelengths were subsequently selected through the successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS), serving as inputs for traditional machine learning models. Two-dimensional spatial data were first subjected to dimensionality reduction via principal component analysis (PCA). Texture features were then extracted from each principal component using the gray-level co-occurrence matrix (GLCM). Following normalization, all spatial texture data were fused with the preprocessed spectral data to form the inputs for the deep learning models Basic1DCNN and Stacked1DCNN. The results demonstrate that the fusion data with the Stacked1DCNN model yielded the best performance in identifying normal seed potatoes and six types of external defects. The overall accuracy, precision, recall, F1 score, and mean average precision reached 98.77%, 98.77%, 98.93%, 98.73%, and 99.66%, respectively, outperforming traditional machine learning approaches. Compared with the Stacked1DCNN model trained using spectral data alone, these metrics improved by 2.81%, 2.78%, 3.20%, 3.01%, and 1.11%. This study offers theoretical and technical insights into the development of automated sorting and non-destructive detection systems for seed potatoes. Full article

Leachate from the Magtaa Kheira landfill exhibits complex physicochemical characteristics that restrict the efficacy of single-treatment processes. This study assessed a sustainable two-stage treatment strategy combining coagulation–flocculation and adsorption. During the initial stage of the study, both aluminum sulfate (AS) and a bio-based coagulant derived from Moringa oleifera seeds (MOS) were evaluated for their effectiveness in the pretreatment of leachate. Box–Behnken Design combined with Response Surface Methodology was used to optimize the coagulation process using aluminum sulfate (AS). The highest removal efficiencies were 91% for turbidity and 85% for chemical oxygen demand (COD) removal, achieved at an AS concentration of 1.44 g·L⁻¹ and an initial pH of 8. In parallel, the performance of MOS extract was investigated as an eco-friendly alternative to AS. An FTIR analysis revealed the presence of protein-associated hydroxyl (3288 cm⁻¹) and carboxyl and amine groups (1647 cm⁻¹), which are integral to destabilization via hydrogen bonding, while SEM confirmed a surface morphology conducive to effective floc formation. MOS demonstrated comparable turbidity removal to AS, significantly reducing both sludge generation and chemical consumption. Following the coagulation stage, treated leachates were passed through a granular activated carbon (GAC) column, enhancing overall COD removal to over 94% to reach acceptable discharge and reuse levels. The coagulation–adsorption sequence, incorporating both chemical and bio-based coagulants, provides an efficient and sustainable approach for the treatment of complex leachate, addressing both performance and environmental considerations. Full article

Guava fruit is widely consumed in tropical countries and beyond. The phenolic fraction of guava pulp and processing waste (a single fraction containing seeds, skins, and pulp residues) have been reported to carry in vitro biological activities, acting on biomarkers of metabolic diseases such as type 2 diabetes and obesity (enzymatic inhibition of α-glucosidase and pancreatic lipase), atherosclerosis (mitigation of LDL-cholesterol oxidation), and mutagenesis (suppression of DNA strand scission). However, such bioactivities may be compromised by the exposure of guava phenolics to the harsh conditions found along the human gastrointestinal (GI) tract. To overcome this limitation, guava phenolic extracts were microencapsulated with maltodextrin through freeze-drying. The effect of crude and microencapsulated extracts on biomarkers of metabolic diseases was compared before and after in vitro simulated GI digestion. Moreover, guava waste extracts were tested for their ability to interfere with the intracellular redox status of Caco-2 and HeLa cells incubated with free radicals. Microencapsulation considerably improved the bioaccessibility of guava phenolics across digestion stages, which reflected on the enhancement of most bioactivities measured, with the exception of pancreatic lipase inhibition (both pulp and waste extracts) and LDL oxidative protection (pulp extract). Meanwhile, microencapsulation accentuated intracellular antioxidant activity in Caco-2 cells induced by guava waste extract whereas a prooxidant effect in HeLa cells was intensified. This highlights the selectivity of the same extract toward different cell lines. Overall, microencapsulation was demonstrated as a promising tool for protecting and even enhancing the nutraceutical power of guava phenolics, reinforcing their relevance in the development of functional foods and nutraceutical products. Full article