Search Results (17,726)

Dark chocolate is a confectionery product traditionally made from cocoa beans, sugar, and vanilla essence. The aim of the study was to investigate the thermal properties of dark chocolates and fats extracted from these chocolates using thermal methods of food analysis, such as differential scanning calorimetry (DSC) and thermogravimetry (TG). The profile of fatty acids in the fat extracted from the chocolates was also determined. The presence of three fatty acids (palmitic P, stearic S, and oleic O) constituting triacylglycerols—SOS, POP, POS, POO, and SOO—was observed in all the samples. The presence of linoleic acid (L) was also found, which forms triacylglycerols such as PLP and PLS. The researched chocolates were characterized by a diverse composition of fatty acids. In all the obtained DSC melting curves of fats, the presence of endothermic peaks was observed. The peaks, appearing at negative temperatures, may be caused by the transition of low-melting triacylglycerols. The differences between the melting curves for the obtained dark chocolate fats may have resulted from the presence of less stable polymorphic forms of cocoa butter. Based on the shape of the TG and DTG curves, it could be possible to indicate the adulteration of chocolates. Full article

Background/Objectives: We investigated the effects of ultraprocessed food (UPF) consumption on metabolic disorders (e.g., adiposity, metabolic associated steatotic liver disease [MASLD], and insulin resistance) in children and adolescents with obesity to improve dietary guidelines and public health strategies. Methods: The dietary intake of 149 participants (aged 8–17 years) was assessed with food diaries. The NOVA classification system was used to classify food according to the degree of processing. Metabolic outcomes, including the fat mass index (FMI), hepatic fat percentage, and insulin resistance, were measured via dual-energy X-ray absorptiometry (DXA), magnetic resonance imaging proton density fat fraction (MRI-PDFF), and biochemical analysis, respectively. Results: Greater UPF consumption from baseline to the 6-month follow-up was significantly associated with increased insulin and decreased total cholesterol and LDL-cholesterol. UPF consumption was positively associated with the prevalence of MASLD (liver MRI-PDFF ≥ 5%; odds ratio _{T3 vs. T1} = 1.75; 95% confidence interval [CI] 1.03, 3.00), moderate-to-severe MASLD (liver MRI-PDFF ≥ 10%; OR _{T3 vs. T1} = 4.19; 95% CI 1.72, 10.22), and insulin resistance (OR _{T3 vs. T1} = 2.44; 95% CI 1.33, 4.48), after adjusting for covariates. A linear dose-response relationship was observed between UPF consumption and the odds of moderate-to-severe MASLD and insulin resistance. Conclusions: Greater UPF consumption was strongly associated with MASLD and insulin resistance in children and adolescents with obesity, underscoring the importance of reducing UPF consumption through dietary guidelines and public health interventions to mitigate the risk of obesity-related metabolic conditions in young populations. Full article

The sunflower, an important oilseed crop and food source across the world, is susceptible to several pathogens, which cause severe losses in sunflower production. The utilization of genetic resistance is the most economical, effective measure to prevent infectious diseases. Based on the sunflower pangenome, in this study, we explored the variability of resistance gene analogs (RGAs) within the species. According to a comparative analysis of RGA candidates in the sunflower pangenome using the RGAugury pipeline, a total of 1344 RGAs were identified, comprising 1107 conserved, 199 varied, and 38 rare RGAs. We also identified RGAs associated with resistance against Sclerotinia sclerotiorum (S. sclerotiorum) in sunflower at the quantitative trait locus (QTL). A total of 61 RGAs were found to be located at four quantitative trait loci (QTLs). Through a detailed expression analysis of RGAs in one susceptible and two tolerant sunflower inbred lines (ILs) across various time points post inoculation, we discovered that 348 RGAs exhibited differential expression in response to Sclerotinia head rot (SHR), with 17 of these differentially expressed RGAs being situated within the QTL regions. In addition, 15 RGA candidates had gene introgression. Our data provide a better understanding of RGAs, which facilitate genomics-based improvements in disease resistance in sunflower. Full article

Imbalanced data situations exist in most fields of endeavor. The problem has been identified as a major bottleneck in machine learning/data mining and is becoming a serious issue of concern in food processing applications. Inappropriate analysis of agricultural and food processing data was identified as limiting the robustness of predictive models built from agri-food applications. As a result of rare cases occurring infrequently, classification rules that detect small groups are scarce, so samples belonging to small classes are largely misclassified. Most existing machine learning algorithms including the K-means, decision trees, and support vector machines (SVMs) are not optimal in handling imbalanced data. Consequently, models developed from the analysis of such data are very prone to rejection and non-adoptability in real industrial and commercial settings. This paper showcases the reality of the imbalanced data problem in agri-food applications and therefore proposes some state-of-the-art artificial intelligence algorithm approaches for handling the problem using methods including data resampling, one-class learning, ensemble methods, feature selection, and deep learning techniques. This paper further evaluates existing and newer metrics that are well suited for handling imbalanced data. Rightly analyzing imbalanced data from food processing application research works will improve the accuracy of results and model developments. This will consequently enhance the acceptability and adoptability of innovations/inventions. Full article

The paper aims to analyze the consumer joint choice behavior on fresh food purchase channels and terminal delivery services during major public health events, with the purpose of revealing the underlying influencing factors and behavioral characteristics. First, based on random utility maximization theory, the cross-nested logit model is formulated, which takes into account the influence of socioeconomic attribute factors, service attribute factors, risk perception attribute factors and trust perception attribute factors. Second, a questionnaire survey is conducted, and the obtained data are used to estimate the model parameters and perform an elasticity analysis of the utility variables. The parameter estimation results demonstrate that in the context of major public health events, consumers consider adjusting their attitudes toward e-commerce platforms first when the utility variables are altered, and fresh food purchase channels are easily replaced for consumers who choose unmanned equipment home delivery. The elasticity analysis results suggest that consumers are more willing to buy fresh food through community group-buying channels, are more sensitive to the convenience of the purchase process and are less concerned with delivery time. Although person-to-person contact increases the risk of infection, consumers still prefer attended terminal delivery services. Furthermore, consumers least agree with the effectiveness of body temperature detection methods in public places but feel that an effective way to increase consumer trust in enterprises is to strengthen personnel protection measures. Full article

As one of the major greenhouse gas emission contributors, the food service industry, particularly buffet-style restaurants, is responsible for reducing food waste. This study explores the factors that shape consumer behavior toward food waste reduction in buffet-style restaurants based on the Theory of Reasoned Action (TRA) and Social Exchange theory (SET), as well as analyzing the gender differences in these determinants, offering practical insights for the restaurant industry. This study also uses structural equation modeling and group analysis to examine a total of 547 valid responses gathered through an online survey, including 286 male (52.3%) and 258 female (47.2%) respondents. The findings underscore the attitudes, subjective norms, and establishment policies that emerge as critical drivers of consumer behavior in buffet-style dining settings. Notably, significant gender differences are observed in attitudes and establishment policies. In light of these results, we recommend strategies that include enhancing consumer attitudes and implementing penalty policies within restaurant operations. Restaurants could display visual signs and images related to reducing food waste, provide detailed portion size information, and apply monetary fines for excess waste to reduce consumers’ food waste intentions. These strategies are particularly effective for male consumers, who are more influenced by these factors compared to female consumers. This research contributes valuable guidance for the industry’s efforts to address food waste concerns, emphasizing gender differences and promoting environmentally responsible behavior among consumers. Full article

This study investigates the relationship between diet quality and body image disturbance among young women aged 18–24, a crucial period for establishing lifelong health behaviors. Given the increasing exposure to social media, which often promotes unrealistic beauty standards, this research aims to explore associations between eating behaviors, diet quality, and body image disturbance. A mixed-methods approach was employed, combining qualitative focus group discussions with quantitative analysis. Focus groups (n = 19) explored themes of body image dissatisfaction. The Body Image Disturbance Questionnaire (BIDQ) was administered to 50 participants (young women aged 18–24) to quantitatively assess body image disturbance, while diet quality was evaluated using the Australian Recommended Food Scores (ARFS). The Three-Factor Eating Questionnaire (TFEQ-R18) was also used to assess eating behaviors, including cognitive restraint, uncontrolled eating, and emotional eating. A social influence questionnaire (SIQ) was administered to measure the effect of social influence. Pearson’s correlation coefficient was used to determine the relationship between ARFS, BIDQ, and TFEQ-R18 scores. Qualitative findings revealed persistent dissatisfaction with body shape, largely influenced by social media. Quantitatively, 65% of participants scored above the clinical threshold for body image disturbance (mean BIDQ score = 4.2, SD = 0.8). The correlation between ARFS and BIDQ scores was weak and not statistically significant (r = 0.057, p = 0.711). However, a significant positive correlation was observed between time spent on social media and body image disturbance (r = 0.58, p < 0.01). Additionally, TFEQ-R18 results indicated that 45% of participants displayed moderate levels of uncontrolled eating, and 36.5% demonstrated moderate levels of emotional eating. While social media is associated with body image concerns, its effect on eating behaviors and diet quality shows weak correlations, suggesting that other factors may mediate these outcomes. These results suggest the complexity of the associations between body image, eating behaviors, and diet quality, indicating that interventions should consider psychological drivers behind these concerns alongside social media usage. Full article

Analytical instrumentation is essential for chemical analysis in many fields, including biology and chemistry, but it can be costly and inaccessible to many educational institutions because it often requires expensive and sophisticated equipment. To address this issue, there has been growing interest in developing new and accessible alternatives. In this study, we developed a low-cost and user-friendly spectrophotometric detector based on an Arduino UNO platform. This detector was coupled with a flow injection analysis system (FIA) and used to quantify the concentration of tartrazine in commercial beverages and candy samples. The proposed miniaturized detector offers an affordable and portable alternative to conventional spectrophotometers. We evaluated the performance of our detector by comparing its results with those obtained using high-performance liquid chromatography (HPLC-DAD), and the accuracy and precision were comparable. The results demonstrate the potential of the Arduino-based spectrophotometric detector as a cost-effective and accessible tool, with potential applications in food science, environmental monitoring, and other fields. Full article

Approximately one-third of the entire world’s food resources are deemed to be wasted. Palm kernel meal (PKM), a product that is extensively generated by the palm oil industry, exhibits a unique nutrient-rich composition. However, its recycling is seldom prioritized due to numerous factors. To evaluate the impact of enzymatic pretreatment and Lactobacillus plantarum and Lactobacillus reuteri fermentation upon the antioxidant activity of PKM, we implemented integrated metagenomics and metabolomics approaches. The substantially enhanced (p < 0.05) property of free radicals scavenging, as well as total flavonoids and polyphenols, demonstrated that the biotreated PKM exhibited superior antioxidant capacity. Non-targeted metabolomics disclosed that the Lactobacillus fermentation resulted in substantial (p < 0.05) biosynthesis of 25 unique antioxidant biopeptides, along with the increased (p < 0.05) enrichment ratio of the isoflavonoids and secondary metabolites biosynthesis pathways. The 16sRNA sequencing and correlation analysis revealed that Limosilactobacillus reuteri, Pediococcus acidilactici, Lacticaseibacillus paracasei, Pediococcus pentosaceus, Lactiplantibacillus plantarum, Limosilactobacillus fermentum, and polysaccharide lyases had significantly dominated (p < 0.05) proportions in PMEL, and these bacterial species were strongly (p < 0.05) positively interrelated with antioxidants peptides. Fermented PKM improves nutritional value by enhancing beneficial probiotics, enzymes, and antioxidants and minimizing anti-nutritional factors, rendering it an invaluable feed ingredient and gut health promoter for animals, multifunctional food elements, or as an ingredient in sustainable plant-based diets for human utilization, and functioning as a culture substrate in the food sector. Full article

Childhood nutrition is a cornerstone of long-term health, yet many children exhibit reluctance to consume healthy foods such as vegetables. This aversion can be influenced by various factors, including food neophobia and the sensory and visual appeal of the foods that are being presented. Hence, understanding how visual cues affect children’s willingness to eat can provide insights into effective strategies to enhance their dietary habits. This research explores the influence of visual cues on the dietary behaviors of children aged 9 to 12, their willingness to consume and request healthy foods such as vegetables, within the context of challenges such as food neophobia. This study examines how intrinsic cues (e.g., vegetable characteristics) and extrinsic cues (e.g., the plate’s color and shape) affect children’s liking and emotional responses, impacting their willingness to eat and request purchases from parents. Conducted using a sample of 420 children, this cross-sectional study reveals that attributes such as a plate’s color and shape significantly affect food-related behaviors and emotions. A validated and reliable self-administered questionnaire was employed. Independent t-tests and ANOVA were used to test the differences between gender and food neophobia, while Spearman correlations were used for correlation analysis. Visual cues served as the independent variables, liking and emotional responses as the mediating variables, and willingness behaviors as the dependent variable. Hierarchical regression analyses were conducted to explore the relationships among intrinsic cues, extrinsic cues, and the mediating effect of liking and emotional responses. Findings show that boys prefer blue and triangular plates, while girls prefer pink plates, generating more positive emotions. Children with food neophobia initially experience aversion, but this can be reduced by enhancing sensory appeal and emotional engagement. The findings underscore the importance of leveraging visual cues and fostering positive emotional experiences to encourage healthier eating habits and increase children’s acceptance and purchase of nutritious foods. Full article

The global market for potato and corn chips is rapidly expanding due to the modern fast-paced lifestyle. However, the high fat content, especially saturated fats in these deep-fried snacks, poses significant health risks such as hypertension, coronary heart disease, and diabetes. In this study, fatty acid profiles of commercially available corn and potato chips are analyzed and their impacts on consumer preferences in Turkey is examined. The findings reveal notable differences in the nutritional content between potato and corn chips, with potato chips generally having higher fat and protein content. The survey results indicate that consumer preferences are significantly influenced by age, education level, and occupation. The factor analysis identified three main components affecting purchasing decisions: nutritional value and additives, hygiene and brand quality, and price and affordability. Considering these insights, manufacturers should be encouraged to reformulate their products to meet the increasing demand for healthier options, emphasize food safety standards, and balance product quality with affordability to appeal to a broader range of consumers. Full article

This study leverages approximately 7500 reviews from Skytrax to explore the determinants of airport service quality and their influence on passenger recommendations. The dataset includes various features such as terminal cleanliness, terminal seating, terminal signs, food and beverages, airport shopping, WiFi connectivity, and airport staff. The research employs a comprehensive methodology encompassing statistical data analysis, predictive modelling, and interaction effects analysis. The descriptive analysis of time-series data highlighted trends and fluctuations in service quality and recommendations, providing insights into temporal dynamics. Multiple machine learning models, including logistic regression, Random Forest, SVM, KNN, Gradient Boosting, and Neural Networks, were developed in this study and cross-validated for airport recommendation based on Skytrax’s online reviews. Among others, Gradient Boosting emerged as the most accurate model with an 88.15% mean accuracy. Interaction effects revealed significant combined influences, such as terminal cleanliness and terminal seating, on passenger recommendations. This multifaceted approach offers robust insights into factors influencing airport recommendations and guides improvements in airport management to enhance passenger satisfaction. Future work will focus on a general-purpose machine learning framework and its toolbox development for airport service quality analysis based on online reviews from various sources. Full article

Aims: Various dietary risk factors for type 2 diabetes have been identified. A short assessment of dietary patterns related to the risk for type 2 diabetes mellitus may be relevant in clinical practice given the largely preventable nature of the disease. The aim of this study was to investigate the reproducibility of a short food frequency questionnaire based on available knowledge of diabetes-related healthy diets. In addition, we aimed to investigate whether a Diabetes Dietary Quality Index based on this questionnaire was related to metabolic risk factors, including measures of beta cell function and insulin sensitivity. Methods: A short food frequency questionnaire was composed by selecting fourteen questions (representing eight dietary factors) from existing food frequency questionnaires on the basis of their reported relationship with diabetes risk. Healthy participants (N = 176) from a Dutch family study completed the questionnaire and a subgroup (N = 123) completed the questionnaire twice. Reproducible items from the short questionnaire were combined into an index. The association between the Diabetes Dietary Quality index and metabolic risk factors was investigated using multiple linear regression analysis. Measures of beta cell function and insulin sensitivity were derived from a mixed meal test and an euglycemic–hyperinsulinemic and modified hyperglycemic clamp test. Results: Our results show that this new short food frequency questionnaire is reliable (Intraclass Correlations ranged between 0.5 and 0.9). A higher Diabetes Dietary Quality index score was associated with lower 2 h post-meal glucose (β −0.02, SE 0.006, p < 0.05), HbA1c (β −0.07, SE 0.02, p < 0.05), total cholesterol, (β −0.02, SE 0.07, p < 0.05), LDL cholesterol, (β −0.19, SE 0.07, p < 0.05), fasting (β −0.4, SE 0.16, p < 0.05) and post-load insulin, (β −3.9, SE 1.40, p < 0.05) concentrations and the incremental AUC of glucose during MMT (β −1.9, SE 0.97, p < 0.05). The scores obtained for the oral glucose insulin sensitivity-derived mixed meal test were higher in subjects who scored higher on the Diabetes Dietary Quality index (β 0.89, 0.39, p < 0.05). In contrast, we found no significant associations between the Diabetes Dietary Quality index and clamp measures of beta cell function. Conclusions: We identified a questionnaire-derived Diabetes Dietary Quality index that was reproducible and inversely associated with a number of type 2 diabetes mellitus and metabolic risk factors, like 2 h post-meal glucose, Hba1c and LDL, and total cholesterol. Once relative validity has been established, the Diabetes Dietary Quality index could be used by health care professionals to identify individuals with diets adversely related to development of type 2 diabetes. Full article

Background: The activation of the growth hormone receptor (GHR) is a major determinant of body growth. Defective GHR signaling, as seen in human Laron dwarfism, resulted in low plasma IGF-1 concentrations and limited growth, but also marked absence in the development of breast cancer and type 2 diabetes. In vitro, we identified a small molecule (C#1) that inhibits the translation of GHR mRNA to receptor protein. Methods: Before its application in humans as a potential anticancer drug, C#1 was tested in animals to evaluate whether it could be administered to achieve a plasma concentration in vivo that inhibits cell proliferation in vitro without causing unwanted toxicity. To evaluate the efficacy and toxicity of C#1, a group of six intact female Beagle dogs was treated daily each morning for 90 days with an oral solution of C#1 in Soiae oleum emulgatum at a dose of 0.1 mg/kg body weight. During treatment, dogs were closely monitored clinically, and blood samples were taken to measure plasma C#1 concentrations, complete blood counts (CBC), clinical chemistry, and endocrinology. At the end of the treatment, dogs were euthanized for gross and histopathological analysis. An additional group of six female Beagle dogs was included for statistical reasons and only evaluated for efficacy during treatment for 30 days. Results: Daily administration of C#1 resulted in a constant mean plasma concentration of approximately 50 nmol/L. In both groups, two out of six dogs developed decreased appetite and food refusal after 4–5 weeks, and occasionally diarrhea. No significant effects in CBC or routine clinical chemistry were seen. Plasma IGF-1 concentrations, used as biomarkers for defective GHR signaling, significantly decreased by 31% over time. As plasma growth hormone (GH) concentrations decreased by 51% as well, no proof of GHR dysfunction could be established. The measured 43% decrease in plasma acylated/non-acylated ghrelin ratios will also lower plasma GH concentrations by reducing activation of the GH secretagogue receptor (GHSR). C#1 did not directly inhibit the GHSR in vivo, as shown in vitro. There were no significant effects on glucose, lipid, or folate/homocysteine metabolism. Conclusions: It is concluded that with daily dosing of 0.1 mg C#1/kg body weight, the induction of toxic effects prevented further increases in dosage. Due to the concomitant decrease in both IGF-1 and GH, in vivo inhibition of GHR could not be confirmed. Since the concept of specific inhibition of GHR synthesis by small molecules remains a promising strategy, searching for compounds similar to C#1 with lower toxicity should be worthwhile. Full article

This study established novel and high-throughput strategies for the simultaneous analysis of 30 fluorinated emerging pollutants in different matrices from the shrimp aquaculture system in eastern China using UHPLC-MS/MS. The parameters of SPE for analysis of water samples and of QuEChERS methods for sediment and shrimp samples were optimized to allow the simultaneous detection and quantitation of 17 per- and polyfluoroalkyl substances (PFASs) and 13 fluoroquinolones (FQs). Under the optimal conditions, the limits of detection of 30 pollutants for water, sediment, and shrimp samples were 0.01–0.30 ng/L, 0.01–0.22 μg/kg, and 0.01–0.23 μg/kg, respectively, while the limits of quantification were 0.04–1.00 ng/L, 0.03–0.73 μg/kg, and 0.03–0.76 μg/kg, with satisfactory recoveries and intra-day precision. The developed methods were successfully applied to the analysis of multiple samples collected from aquaculture ponds in eastern China. PFASs were detected in all samples with concentration ranges of 0.18–0.77 μg/L in water, 0.13–1.41 μg/kg (dry weight) in sediment, and 0.09–0.96 μg/kg (wet weight) in shrimp, respectively. Only two FQs, ciprofloxacin and enrofloxacin, were found in the sediment and shrimp. In general, this study provides valuable insights into the prevalence of fluorinated emerging contaminants, assisting in the monitoring and control of emerging contaminants in aquatic foods. Full article