Search Results (1,123)

Cucumber, a high-yielding crop commonly grown in facility environments, is particularly susceptible to nitrogen (N) deficiency due to its rapid growth and high nutrient demand. This study used cucumber as its experimental subject and established a spectral dataset of leaves under four nutritional conditions, normal supply, nitrogen deficiency, phosphorus deficiency, and potassium deficiency, aiming to develop an efficient and robust method for quantifying N in cucumber leaves using Raman spectroscopy (RS). Spectral data were preprocessed using three baseline correction methods—BaselineWavelet (BW), Iteratively Improve the Moving Average (IIMA), and Iterative Polynomial Fitting (IPF)—and key spectral variables were selected using 4-Dimensional Feature Extraction (4DFE) and Competitive Adaptive Reweighted Sampling (CARS). These selected features were then used to develop a N content prediction model based on Partial Least Squares Regression (PLSR). The results indicated that baseline correction significantly enhanced model performance, with three methods outperforming unprocessed spectra. A further analysis showed that the combination of IPF, 4DFE, and CARS achieved optimal PLSR model performance, achieving determination coefficients (R²) of 0.947 and 0.847 for the calibration and prediction sets, respectively. The corresponding root mean square errors (RMSEC and RMSEP) were 0.250 and 0.368, while the residual predictive deviation (RPDC and RPDP) values reached 4.335 and 2.555. These findings confirm the feasibility of integrating RS with advanced data processing for rapid, non-destructive nitrogen assessment in cucumber leaves, offering a valuable tool for nutrient monitoring in precision agriculture. Full article

In many developing African countries, milk safety is often managed through traditional methods such as fermentation or boiling over firewood. While these approaches reduce some microbial risks, they present critical limitations. Firewood dependency contributes to deforestation, depletion of agricultural residues, and loss of soil fertility, which, in turn, compromise environmental health and food security. Solar pasteurization provides a reliable and sustainable method for thermally inactivating pathogenic microorganisms in milk and other perishable foods at sub-boiling temperatures, preserving its nutritional quality. This study aimed to evaluate the thermal and microbial performance of a low-cost solar milk pasteurization system, hypothesized to effectively reduce microbial contaminants and retain milk quality under natural sunlight. The system was constructed using locally available materials and tailored to the climatic conditions of the Savanna ecological zone in West Africa. A flat-plate glass solar collector was integrated with a 0.15 cm thick stainless steel cylindrical milk vat, featuring a 2.2 cm hot water jacket and 0.5 cm thick aluminum foil insulation. The system was tested in Navrongo, Ghana, under ambient temperatures ranging from 30 °C to 43 °C. The pasteurizer successfully processed up to 8 L of milk per batch, achieving a maximum milk temperature of 74 °C by 14:00 GMT. Microbial analysis revealed a significant reduction in bacterial load, from 6.6 × 10⁶ CFU/mL to 1.0 × 10² CFU/mL, with complete elimination of coliforms. These results confirmed the device’s effectiveness in achieving safe pasteurization levels. The findings demonstrate that this locally built solar pasteurization system is a viable and cost-effective solution for improving milk safety in arid, electricity-limited regions. Its potential scalability also opens avenues for rural entrepreneurship in solar-powered food and water treatment technologies. Full article

This study aimed to develop a functional powder using whey and milk matrices, leveraging the protective capacity of chia–alginate hydrogels and the advantages of electrohydrodynamic spraying (EHDA), a non-thermal technique suitable for encapsulating probiotic cells under stress conditions commonly encountered in food processing. A hydrogel matrix composed of chia seed mucilage and sodium alginate was used to form a biopolymeric network that protected probiotic cells during processing. The encapsulation efficiency reached 99.0 ± 0.01%, and bacterial viability remained above 9.9 log₁₀ CFU/mL after lyophilization, demonstrating the excellent protective capacity of the hydrogel matrix. Microstructural analysis using confocal laser scanning microscopy (CLSM) revealed well-retained cell morphology and homogeneous distribution within the hydrogel matrix while, in contrast, scanning electron microscopy (SEM) showed spherical, porous microcapsules with distinct surface characteristics influenced by the encapsulation method. Encapsulates were incorporated into beverages flavored with red fruits and pear and subsequently freeze-dried. The resulting powders were analyzed for moisture, protein, lipids, carbohydrates, fiber, and color determinations. The results were statistically analyzed using ANOVA and response surface methodology, highlighting the impact of ingredient ratios on nutritional composition. Raman spectroscopy identified molecular features associated with casein, lactose, pectins, anthocyanins, and other functional compounds, confirming the contribution of both matrix and encapsulants maintaining the structural characteristics of the product. The presence of antioxidant bands supported the functional potential of the powder formulations. Chia–alginate hydrogels effectively encapsulated L. reuteri, maintaining cell viability and enabling their incorporation into freeze-dried beverage powders. This approach offers a promising strategy for the development of next-generation functional food gels with enhanced probiotic stability, nutritional properties, and potential application in health-promoting dairy systems. Full article

Fistulina hepatica (Schaeff.) With. and Clitocybe nuda (Bull.) H.E. Bigelow & A.H. Sm. are wild edible mushrooms with nutritional and functional potential that remain insufficiently characterized. This study provides the first comparative assessment of their nutritional profiles, phenolic composition, and antioxidant activity, using specimens collected from Montesinho Natural Park (Portugal). Proximate composition, organic and phenolic acids, free sugars, and fatty acids were analyzed by chromatographic methods, and antioxidant capacity was assessed through OxHLIA and TBARS assays. F. hepatica showed higher carbohydrates (9.3 ± 0.2 g/100 g fw) and estimated energy values (43 ± 1 kcal/100 g fw), increased phenolic acids content (2.7 ± 0.1 mg/g extract), and the exclusive presence of p-coumaric and cinnamic acids, along with OxHLIA activity (IC₅₀ = 126 ± 5 µg/mL at Δt = 60 min). C. nuda displayed higher protein (2.5 ± 0.1 g/100 g dw) and quinic acid contents (4.13 ± 0.02 mg/g extract), a PUFA-rich profile, and greater TBARS inhibition (EC₅₀ = 303 ± 17 µg/mL). These findings highlight distinct and complementary bioactive traits, supporting their valorization as natural functional ingredients. Their compositional features offer promising applications in sustainable food systems and nutraceutical development, encouraging further investigations into safety, bioaccessibility, and formulation strategies. Notably, F. hepatica is best consumed at a young developmental stage, as its sensory properties tend to decline with maturity. Full article

Sarcopenia, characterized by progressive skeletal muscle loss and functional decline, represents a major public heath challenge in aging populations. Despite increasing awareness, current management strategies—primarily resistance exercise and nutritional support—remain limited by accessibility, adherence, and inconsistent outcomes. This underscores the urgent need for novel, effective, and scalable therapeutics. Flavonoids, a diverse class of plant-derived polyphenolic compounds, have attracted attention for their muti-targeted biological activities, including anti-inflammatory, antioxidant, metabolic, and myogenic effects. This review aims to evaluate the anti-sarcopenic potential of selected flavonoids—quercetin, rutin, kaempferol glycosides, baicalin, genkwanin, isoschaftoside, naringin, eriocitrin, and puerarin—based on recent preclinical findings and mechanistic insights. These compounds modulate key pathways involved in muscle homeostasis, such as NF-κB and Nrf2 signaling, AMPK and PI3K/Akt activation, mitochondrial biogenesis, proteosomal degradation, and satellite cell function. Importantly, since muscle wasting also features prominently in cancer cachexia—a distinct but overlapping syndrome—understanding flavonoid action may offer broader therapeutic relevance. By targeting shared molecular axes, flavonoids may provide a promising, biologically grounded approach to mitigating sarcopenia and the related muscle-wasting conditions. Further translational studies and clinical trials are warranted to assess their efficacy and safety in human populations. Full article

This study presents the development and optimization of a functional soy sauce fermented with Cordyceps militaris (C. militaris), a medicinal fungus known for its high cordycepin and polysaccharide content. Using C. militaris as the sole starter culture, the process aimed to improve both nutritional and functional properties. Response surface methodology was employed to optimize the entire fermentation process. During the koji stage, temperature, aeration, and inoculum concentration were adjusted to maximize protease activity and cordycepin production. In the fermentation stage, temperature, brine concentration, and water-to-material ratio were optimized to increase amino acid nitrogen and bioactive compound levels. Under optimal conditions (24 °C, 679.60 LPM aeration, 9.6% inoculum for koji; 32 °C, 12% brine, 1.53:1 water-to-material ratio for fermentation), the resulting soy sauce contained 1.14 ± 0.05 g/100 mL amino acid nitrogen and 16.88 ± 0.47 mg/100 mL cordycepin. Compared with traditionally fermented soy sauce, the C. militaris product exhibited a darker color, enhanced umami taste, and a distinct volatile profile featuring linoleic acid, methyl palmitate, and niacinamide. These results demonstrate the feasibility of using C. militaris in soy sauce fermentation and its potential as a novel functional condiment with improved bioactivity and sensory quality. Full article

The rapid evolution of deep learning (DL) has fundamentally transformed the paradigm for detecting special components in agricultural products, addressing critical challenges in food safety, quality control, and precision agriculture. This comprehensive review systematically analyzes many seminal studies to evaluate cutting-edge DL applications across three core domains: contaminant surveillance (heavy metals, pesticides, and mycotoxins), nutritional component quantification (soluble solids, polyphenols, and pigments), and structural/biomarker assessment (disease symptoms, gel properties, and physiological traits). Emerging hybrid architectures—including attention-enhanced convolutional neural networks (CNNs) for lesion localization, wavelet-coupled autoencoders for spectral denoising, and multi-task learning frameworks for joint parameter prediction—demonstrate unprecedented accuracy in decoding complex agricultural matrices. Particularly noteworthy are sensor fusion strategies integrating hyperspectral imaging (HSI), Raman spectroscopy, and microwave detection with deep feature extraction, achieving industrial-grade performance ($RPD$ > 3.0) while reducing detection time by 30–100× versus conventional methods. Nevertheless, persistent barriers in the “black-box” nature of complex models, severe lack of standardized data and protocols, computational inefficiency, and poor field robustness hinder the reliable deployment and adoption of DL for detecting special components in agricultural products. This review provides an essential foundation and roadmap for future research to bridge the gap between laboratory DL models and their effective, trusted application in real-world agricultural settings. Full article

Obesity and metabolic dysfunction are established risk factors for luminal breast cancer, yet current preclinical models inadequately recapitulate the complex metabolic and immune interactions driving tumorigenesis. To develop and characterize an immunocompetent rat model of luminal breast cancer induced by chronic exposure to a cafeteria diet mimicking Western obesogenic nutrition, female rats were fed a cafeteria diet or standard chow from weaning. Metabolic parameters, plasma biomarkers (including leptin, insulin, IGF-1, adiponectin, and estrone), mammary gland histology, tumor incidence, and gene expression profiles were longitudinally evaluated. Gene expression was assessed by PCR arrays and qPCR. A subgroup underwent dietary reversal to assess the reversibility of molecular alterations. Cafeteria diet induced significant obesity (mean weight 426.76 g vs. 263.09 g controls, p < 0.001) and increased leptin levels without altering insulin, IGF-1, or inflammatory markers. Histological analysis showed increased ductal ectasia and benign lesions, with earlier fibroadenoma and luminal carcinoma development in diet-fed rats. Tumors exhibited luminal phenotype, low Ki67, and elevated PAI-1 expression. Gene expression alterations were time point specific and revealed early downregulation of ID1 and COX2, followed by upregulation of MMP2, THBS1, TWIST1, and PAI-1. Short-term dietary reversal normalized several gene expression changes. Overall tumor incidence was modest (~12%), reflecting early tumor-promoting microenvironmental changes rather than aggressive carcinogenesis. This immunocompetent cafeteria diet rat model recapitulates key metabolic, histological, and molecular features of obesity-associated luminal breast cancer and offers a valuable platform for studying early tumorigenic mechanisms and prevention strategies without carcinogen-induced confounders. Full article

Food addiction (FA) is an emerging psychiatric condition that presents behavioral and neurobiological similarities with other addictions, and its early identification is essential to prevent the development of more severe disorders. The aim of the present study was to determine the ability of anthropometric measures, eating habits, symptoms related to eating disorders (ED), and lifestyle features to predict the symptoms of food addiction. Methodology: A cross-sectional study was conducted in a sample of 702 university students (77.3% women; age: 22 ± 6 years). The Food Frequency Questionnaire (FFQ), the Yale Food Addiction Scale 2.0 (YFAS 2.0), the Eating Attitudes Test (EAT-26), anthropometric measurements, and a set of self-report questions on substance use, physical activity level, and other questions were administered. A total of 6.4% of participants presented symptoms compatible with food addiction, and 8.1% were at risk for ED. Additionally, 26.5% reported daily smoking, 70.6% consumed alcohol, 2.9% used illicit drugs, and 29.4% took medication; 35.3% did not engage in physical activity. Individuals with food addiction had higher BMI (p = 0.010), waist circumference (p = 0.001), and body fat (p < 0.001) values, and a higher risk of eating disorders (p = 0.010) compared to those without this condition. In the multivariate logistic model, non-dairy beverage consumption (such as coffee or alcohol), vitamin D deficiency, and waist circumference predicted food addiction symptoms (R²_Nagelkerke = 0.349). Indeed, the machine learning approaches confirmed the influence of these variables. Conclusions: The prediction models allowed an accurate prediction of FA in the university students; moreover, the individualized approach improved the identification of people with FA, involving complex dimensions of eating behavior, body composition, and potential nutritional deficits not previously studied. Full article

Background/Objectives: Body Mass Index (BMI) is a widely used indicator of children’s nutritional status and helps identify risks of being underweight and overweight during development. Understanding how BMI classifications evolve over time is crucial for early intervention and public health planning. This study aimed to determine the scope and direction of changes in BMI classification among children between the ages of 6 and 10. Methods: This longitudinal study included 1026 children (497 boys and 529 girls) from Gdansk, Poland. Standardized anthropometric measurements were collected at ages 6 and 10. BMI was calculated and classified using international reference systems (IOTF and OLAF). BMI classification changes were analyzed using rank transformations and Pearson correlation coefficients (p < 0.05) to explore relationships between body measurements. Results: Most children (76.51%) retained their BMI classifications over the four-year period. However, 23.49% experienced changes, with boys more often moving to a higher BMI category (15.29%) and girls more frequently shifting to a lower category (14.03%). The prevalence of children classified as living with obesity declined between ages 6 and 10, while both overweight and underweight classifications slightly increased. Strong correlations were observed between somatic features and BMI at both ages. Conclusions: The stability of BMI classification over time underscores the importance of early identification and sustained monitoring of nutritional status. The sex-specific patterns observed highlight the importance of targeted health promotion strategies. In this context, incorporating dietary interventions—such as promoting balanced meals and reducing unhealthy food intake—could play a significant role in maintaining healthy BMI trajectories and preventing both obesity and undernutrition during childhood. Full article

Background: Cow’s milk allergy (CMA) is the most common food allergy in children, typically resolving by adolescence. In contrast, the clinical spectrum of allergies to non-cow mammalian milk and their patterns of IgE cross-reactivity are less well documented. Nutritional differences between various mammalian milks may also impact dietary management in milk-allergic patients. Objectives: To characterize clinical features, onset age, and IgE cross-reactivity patterns of non-cow mammalian milk allergies in adult patients seen at a tertiary allergy center, and to compare these findings with published cases. Methods: A retrospective analysis of patients included in the “Extended Laboratory Investigation for Rare Causes of Anaphylaxis study” with mammalian milk allergy was performed using clinical history, skin testing, and serum-specific IgE measurements. Cross-reactivity patterns were assessed in selected cases using immunoblotting, specific IgE inhibition, and basophil activation testing, and compared with published reports of non-cow mammalian milk allergy. Results: In our case series of 22 patients with mammalian milk allergy and 10 healthy control subjects, 3 patients were identified with isolated adult-onset non-cow mammalian milk allergy (n = 1 buffalo milk; n = 2 mare milk), confirmed via immunoblotting and basophil activation testing. Streptavidin-based specific IgE measurement for buffalo cheese was positive in the buffalo milk allergic patient. The literature review identified 82 cases of non-cow mammalian milk allergy. These cases typically showed late onset (mean age 8.6 years; range 1–70 years), severe reactions (CoFAR (Consortium for Food Allergy Research) grade 3 or 4 in 66%, and one fatality), and selective sensitization (affecting sheep and/or goat, camel, mare, buffalo, donkey, or combinations thereof in 56, 10, 5, 5, 4, and 2 cases, respectively). Conclusions: Non-cow mammalian milk allergies are rare but generally present later in life with selective IgE cross-reactivity, differing from the broader cross-reactivity observed in CMA. This selectivity may allow for safe dietary alternatives. These findings underscore the need for improved diagnostics and personalized dietary management in this patient population. Full article

Oleogels are a subclass of organogels that present a healthier alternative to traditional saturated and trans solid fats in food products. The unique structure and composition that oleogels possess make them able to provide desirable sensory and textural features to a range of food products, such as baked goods, processed meats, dairy products, and confectionery, while also improving the nutritional profiles of these food products. The fact that oleogels have the potential to bring about healthier food products, thereby contributing to a better diet, makes interest in the subject ever-increasing, especially due to the global issue of obesity and related health issues. Research studies have demonstrated that oleogels can effectively replace conventional fats without compromising flavor or texture. The use of plant-based gelators brings about a reduction in saturated fat content, as well as aligns with consumer demands for clean-label and sustainable food options. Oleogels minimize oil migration in foods due to their high oil-binding capacity, which in turn enhances food product shelf life and stability. Although oleogels are highly advantageous, their adoption in the food industry presents challenges, such as oil stability, sensory acceptance, and the scalability of production processes. Concerns such as mixed consumer perceptions of taste and mouthfeel and oxidative stability during processing and storage evidence the need for further research to optimize oleogel formulations. Addressing these limitations is fundamental for amplifying the use of oleogels and fulfilling their promise as a sustainable and healthier fat alternative in food products. As the oleogel industry continues to evolve, future research directions will focus on enhancing understanding of their properties, improving sensory evaluations, addressing regulatory challenges, and promoting sustainable production practices. The present report summarizes and updates the state-of-the-art about the structure, the properties, and the applications of oleogels in the food industry to highlight their full potential. Full article

Melanin is a complex natural pigment that imparts a variety of colors to the fruiting bodies of edible fungi, influencing both their nutritional quality and commercial value. Stropharia rugosoannulata is an emerging type of edible fungus that has been widely cultivated in recent years. It can be categorized into red and yellow varieties based on cap color, while its pigment characteristics remain unclear. In this study, the melanins from the two varieties were obtained using an alkaline extraction and acid precipitation method, followed by comprehensive characterization of their chemical properties and ultrastructural features. Both melanins displayed distinct absorption maxima at approximately 211 nm. The melanin extracted from the red variety consisted of 55.63% carbon (C), 7.40% hydrogen (H), 30.23% oxygen (O), 5.99% nitrogen (N), and 0.64% sulfur (S), whereas the yellow variety comprised 52.22% C, 6.74% H, 29.70% O, 5.91% N, and 0.99% S. Both types of melanin included eumelanin and phaeomelanin forms, with eumelanin being the predominant type. Variations in the quantities and relative proportions of eumelanin and phaeomelanin contributed to the observed color differences in the mushroom caps. Ultrastructural micrographs revealed the melanins were primarily localized in the cell wall, consistent with findings in other fungal species. These findings contribute valuable insights into fundamental knowledge and potential applications of mushroom pigments. Full article

Despite the known impacts of weaning on animal health, the underlying molecular mechanisms remain unclear, particularly how psychological and nutritional stress differentially affect gut health and immune function over time. This study hypothesized that early weaning exerts distinct short- and long-term effects on lamb stress physiology, immunity, and gut health, mediated by specific molecular pathways. Twelve pairs of full-sibling male Hu sheep lambs were assigned to control (CON) or early-weaned (EW) groups. Plasma stress/immune markers were dynamically monitored, and intestinal morphology, antioxidant capacity, apoptosis, and transcriptomic profiles were analyzed at 5 and 28 days post-weaning. Early weaning triggered transient psychological stress, elevating hypothalamic–pituitary–adrenal (HPA) axis hormones (cortisol, catecholamines) and inflammatory cytokines (TNF-α) within 1 day (p < 0.05); however, stress responses were transient and recovered by 7 days post-weaning. Sustained intestinal remodeling was observed in EW lambs, featuring reduced ileal villus height, increased crypt depth (p < 0.05), and oxidative damage (MDA levels doubled vs. CON; p < 0.01). Compensatory epithelial adaptation included increased crypt depth but paradoxically reduced villus tip apoptosis. The transcriptome analysis revealed significant changes in gene expression related to immune function, fat digestion, and metabolism. Key DEGs included APOA4, linked to lipid transport adaptation; NOS2, associated with nitric oxide-mediated immune–metabolic crosstalk; and mitochondrial gene COX1, reflecting energy metabolism dysregulation. Protein–protein interaction analysis revealed NOS2 as a hub gene interacting with IDO1 and CXCL11, connecting oxidative stress to immune cell recruitment. Early weaning exerts minimal lasting psychological stress but drives persistent gut dysfunction through transcriptome-mediated changes in metabolic and immune pathways, highlighting key genes such as APOA4, NOS2, and COX1 as potential regulators of these effects. Full article

Background: The regulation of oil and protein contents in cottonseed is governed by a complex genetic network. Gaining insight into the mechanisms controlling these traits is necessary for dissecting the formation patterns of cottonseed quality. Method: In this study, Xinluzhong 37 (P₁) and Xinluzhong 51 (P₂) were selected as parental lines for two reciprocal crosses: P₁ × P₂ (F₁) and its reciprocal P₂ × P₁ (F₁′). Each F1 was selfed and backcrossed to both parents to generate the F₂ (F₂′), B₁ (B₁′), and B₂ (B₂′) generations. To assess nutritional traits in hairy (non-delinted) and lint-free (delinted) seeds, two indicators, oil content and protein content, were measured in both seed types. Joint segregation analysis was employed to analyze the inheritance of these traits, based on a major gene plus polygene model. Results: In the orthogonal crosses, the CVs for the four nutritional traits ranged at 2.710–7.879%, 4.086–11.070%, 2.724–6.727%, and 3.717–9.602%. In the reciprocal crosses, CVs ranged at 2.710–8.053%, 4.086–9.572%, 2.724–6.376%, and 3.717–8.845%. All traits exhibited normal or skewed-normal distributions. For oil content in undelinted/delinted seeds, polygenic heritabilities in the orthogonal cross were 0.64/0.52, and 0.40/0.36 in the reciprocal cross. For protein content, major-gene heritabilities in the orthogonal cross were 0.79 (undelinted) and 0.78 (delinted), while those in the reciprocal cross were both 0.62. Conclusions: Oil and protein contents in cottonseeds are quantitative traits. In both orthogonal and reciprocal crosses, oil content is controlled by multiple genes and is shaped by additive, dominance, and epistatic effects. Protein content, in contrast, is largely controlled by two major genes along with minor genes. In the P₁ × P₂ combination, major genes act through additive, dominance, and epistatic effects, while in the P₂ × P₁ combination, their effects are additive only. In both combinations, minor genes contribute through additive and dominance effects. In summary, the oil content in cottonseed is mainly regulated by polygenes, whereas the protein content is primarily determined by major genes. These genetic features in both linted, and lint-free seeds may offer a theoretical foundation for molecular breeding aimed at improving cottonseed oil and protein quality. Full article