List Of Foods Research Articles

Assessment the Level of Awareness of Aflatoxin Contaminations in Maize-Based Meals Among Boarding School Personnel

Tanzania is a tropical country that lies few degrees south of the equator The coast area includes regions such as Dar es Salaam and Coastal region which are hot and humid with cooling breezes of the Indian Ocean. Awareness of society is a crucial aspect of ensuring the safety and quality of food. One of the risk factors in food safety is the presence of aflatoxin in various foods such as cereals, and groundnuts. The aim of this study was to assess the levels of awareness of aflatoxin B1 contamination in maize and maize flour used for meals in boarding secondary schools. A total of 90 respondents from 30 schools from 7 districts of the two regions were interviewed. Semi-structured questionnaires were used to collect information and the survey showed that 74.4% of the respondents were aware of aflatoxin contamination. 85.6% of respondents know that aflatoxin is found in food and only 14.4% were not aware. 74.4% were capable of selecting the correct list of food that can be contaminated with aflatoxin while 11.1% selected the wrong list. 14.4% of the respondents were unable to select the list of foods that can be contaminated with aflatoxin. These results indicate that most of them are aware of the issue of aflatoxin contamination in maize and its products which is good for reducing aflatoxin contamination in food products and its effect. An effective and broad awareness program for the society including boarding school personnel and students on good management of food for prevention of aflatoxins contamination and its health effects is necessary, as maize and its products are the most consumed grain in the study area.

Stable isotope ratios and current-use pesticide levels in edible insects: Implications on chemical food safety

In the past years, the European Union (EU) has added edible insects to the list of novel foods, allowing an increasing number of insect-based products into the European market. With insects gaining more popularity in the Western world, it is crucial to investigate their chemical food safety. This study aimed at investigating possible isotopic patterns in different edible insect species (n = 52) from Asia, Africa and Europe using stable isotope ratio analysis (SIRA) to provide a framework for future investigations on food authenticity and traceability. Additionally, complementary mass-spectrometric screening approaches were applied to gain a comprehensive overview of contamination levels of current-use pesticides (CUPs) in edible insects, to assess their chemical food safety. SIRA revealed significant differences between countries in δ13CVPDB- (p < 0.001) and δ15Nair- (p < 0.001) values. While it was not possible to distinguish between individual countries using principal component analysis (PCA) and linear discriminative analysis (LDA), the latter could be used to distinguish between larger geographical areas (i.e. Africa, Europe and Asia). In general, African samples had a more distinct isotopic profile compared to European and Asian samples. When comparing the isotopic compositions of samples containing pesticides with samples with no detected pesticides, differences in sulphur compositions could be observed. Additionally, LDA was able to correctly classify the presence of pesticides in a sample with 76% correct classification based on the sulphur composition. These findings show that SIRA could be a useful tool to provide a framework for future investigations on food authenticity and traceability of edible insects. A total of 26 CUPs were detected using suspect screening and an additional 30 CUPS were quantified using target analysis, out of which 9 compounds had a detection frequency higher than 30%. Most detected pesticides were below the maximum residue levels (MRLs) for meat, suggesting low contamination levels. However, dichlorvos and fipronil could be detected in the same order of magnitude as the MRLs, even in samples purchased in Europe. These findings indicate a limited chemical risk for edible insects regarding pesticide contamination. Nevertheless, the study also highlights that further and more extensive investigations are needed to give a comprehensive assessment of the chemical risk of edible insects as a novel food source in Europe. With insects recently being potentially more incorporated into daily diets, more attention should be paid to possible chemical hazards to accurately assess their risk and to ensure food safety.

Modified consistency dysphagia diet protocol for Pakistan: Development perspective

Background: Increased in life expectancy has led to the increased need for texture-modified foods for dysphagia patients, to maintain their nutrition status. At present clinical practices in Pakistan are marred with no standard diet protocols resulting in misunderstanding in recommended consistencies of both food and fluid, hence compromising patients’ safety, necessitating the work of dysphagia diet protocol. Objectives: To develop a dysphagia diet consistency protocol for Pakistan. Methods: A descriptive study recruited 16 Speech-Language Pathologists and dieticians from Rawalpindi &amp; Islamabad using convenient sampling from October 2018 to March 2019. The sample included SLPs and dieticians working for at least 1 year with dysphagia patients. To ensure the process of standardization list of food and fluids was generated by the professionals to analyze the various food textures with the help of a viscometer that contributed to labeling and defining the textures. With the help of the International Dysphagia Diet Standardization Initiative Flow Test, Fork Drip Test, Spoon tilt test, Fork Pressure Test, Spoon Pressure Test, and Finger Test, a list of food and fluid items categorized into 8 levels which help the management of dysphagia patients in clinical practice. Results: The current study developed a dysphagia diet protocol and categorized 29 foods and fluids as per the IDDSI framework. 10 items were placed in level 0 (Thin). 2 items were placed in level 1 (slightly thick). 2 items were placed in 2 (mildly thick) 1 item was placed at level 3. Level 4 included 2 items. Level 5 included 3 items. Level 6 included 4 items and Level 7 included 6 regular daily food items. Conclusion: The study successfully developed a standardized dysphagia diet consistency protocol consisting of 29 commonly readily available and popular foods consumed by Pakistanis and placed these items under 8 levels of the International Dysphagia Diet Standardization Initiative (IDDSI) recommendations. Keywords: Dysphagia; food consistency; IDDSI; swallowing disorders; texture modification.

Food pattern modeling to inform global guidance on complementary feeding of infants.

Nutrient needs are difficult to meet during infancy due to high nutrient requirements and the small quantities of food consumed. Guidelines to support food choice decisions are critical to promoting optimal infant health, growthand developmentand food pattern modeling can be used to inform guideline development. We employed the Optifood modeling system to determine if unfortified complementary foods could meet 13 nutrient targets for breastfed infants (6-11 months), and to describe food patterns that met, or came as close as possible to meeting targets. We also examined the impacts of eliminating food groups, increasing starchy staple foodsor adding sentinel unhealthy foods. We collated a global food list from dietary studies in 37 countries and used this list to develop nutrient values for a set of 35 food subgroups. We analyzed infant dietary intakes from studies in eight countries to inform maximum quantities and frequencies of consumption for these subgroups in weekly food patterns. We found that unfortified foods could meet targets for most infants for 12 nutrients, but not for iron. For the smallest and youngest infants, with the lowest energy intakes, there were additional deficits for minerals. Best-case food patterns that met targets or came as close as possible to meeting targets included ample amounts of diverse vegetables, diverse plant- and animal-source protein foods, small amounts of whole grain foods and dairyand no refined grains or added fats or sugar. There were nutrient deficits if animal-source foods or vegetables were eliminated or if unhealthy foods were included.

Assessing the performance of national sentinel food lists at subnational levels in six countries.

To assess how well national sentinel lists of the most frequently consumed foods in each food group capture data at subnational levels to measure minimum diet diversity (MDD). We analysed data from seven surveys with 24-h open dietary recalls to evaluate: (1) the percentage of reported foods that were included in each sentinel food list; (2) whether these lists captured consumption of some food groups better than others and (3) differences between estimates of dietary diversity calculated from all food items mentioned in the open 24-h recall v. only food items included in the sentinel lists. Seven subnational areas: Bangladesh (2), Benin, Colombia, Kenya, Malawi and Nepal. 8094 women 15-49 years; 4588 children 6-23 months. National sentinel food lists captured most foods reportedly consumed by women (84 %) and children (86 %). Food groups with the highest variability were 'other fruits' and 'other vegetables.' MDD calculated from the sentinel list was, on average, 6·5 (women) and 4·1 (children) percentage points lower than when calculated from open 24-h recalls, with a statistically significant difference in most subnational areas. National sentinel food lists can provide reliable data at subnational levels for most food groups, with some variability by country and sub-region. Assessing the accuracy of national sentinel food lists, especially for fruits and vegetables, before using them at the subnational level could avoid potentially underestimating dietary diversity and provide more accurate local information for programmes, policy and research.

Optimization of a Food List for Food Frequency Questionnaires Using Mixed Integer Linear Programming: A Proof of Concept Based on Data from the Second German National Nutrition Survey.

Food Frequency Questionnaires (FFQs) are important instruments to assess dietary intake in large epidemiological studies. To determine dietary intake correctly, food lists need to be adapted depending on the study aim and the target population. The present work compiles food lists for an FFQ with Mixed Integer Linear Programming (MILP) to minimize the number of foods in the food list. The optimized food lists were compared with the validated eNutri FFQ. The constraints of the MILP aimed to identify food items with a high nutrient coverage in a population and with a high interindividual variability. The optimization was based on data from the second German National Nutrition Survey. The resulting food lists were shorter than the one used in the validated eNutri FFQ.

Assessment of the dietary intake among patients with Alzheimer’s disease in Kazakhstan

AbstractBackgroundDietary intake alterations have been studied in relation to Alzheimer’s disease and have shown that a diet that is rich in fruits, vegetables, whole grains, and low‐fat dairy products may be associated with a reduced risk of cognitive decline, including Alzheimer’s disease (AD). Traditionally, the Kazakh diet is high in protein, fats, and carbohydrates, and low in fruits and vegetables. With the increasing urbanization and globalization, the diet of Kazakhs is starting to change, and more people are starting to adopt a more Westernized diet which is higher in processed foods and sugar. However, little is known about dietary patterns in AD patients from the Central Asia region. Thus, the aim of the study was to identify dietary intake among local Alzheimer’s patientsMethodWe included 106 patients with AD dementia and 100 controls and retrospectively assessed the average intake over a given time period of foods and dishes in a defined food list using the Food Frequency Questionnaire (FFQ). The FETA tool was used to analyze nutrient and food group data from the questionnaireResultOur results demonstrate that AD patients’ diets are characterized by lower fruit, vegetable, and fish consumption compared to the controls. Patients with AD dementia did significantly differ from controls in total daily energy intake (1696 (IQR 1152;2168) vs 2019 (IQR 1424;2515) kcal/day, p &gt; 0.05), in protein, total carbohydrate, and fats. The daily Vitamin C, D, E, and iodine intake was lower than recommended amounts in both groups.ConclusionAD patients in Kazakhstan have a diet with low income of fruits and vegetables which leads to certain nutrients and vitamin deficiencies. It is advised that patients follow a balanced diet that is rich in fruits, vegetables, whole grains, and lean protein sources.

Combination of Nanodelivery Systems and Constituents Derived from Novel Foods: A Comprehensive Review.

Novel Food is a new category of food, regulated by the European Union Directive No. 2015/2283. This latter norm defines a food as "Novel" if it was not used "for human consumption to a significant degree within the Union before the date of entry into force of that regulation, namely 15 May 1997". Recently, Novel Foods have received increased interest from researchers worldwide. In this sense, the key areas of interest are the discovery of new benefits for human health and the exploitation of these novel sources of materials in new fields of application. An emerging area in the pharmaceutical and medicinal fields is nanotechnology, which deals with the development of new delivery systems at a nanometric scale. In this context, this review aims to summarize the recent advances on the design and characterization of nanodelivery systems based on materials belonging to the Novel Food list, as well as on nanoceutical products formulated for delivering compounds derived from Novel Foods. Additionally, the safety hazard of using nanoparticles in food products, i.e., food supplements, has been discussed in view of the current European regulation, which considers nanomaterials as Novel Foods.

Development of a food frequency questionnaire to monitor protein intake in Flanders, Belgium

Abstract Background To improve planetary and dietary health, the Flemish government adopted the ‘Green Deal Protein Shift on our plate’ policy which aims to reverse the ratio between animal-based and plant-based protein-rich products in our diet to 40/60 by 2030. The Green Deal provides a platform for actions that unites players from across the food system. To guide the development of actions and assess their effectiveness it is crucial to closely monitor the protein consumption of the population. Methods We developed a semi-quantitative Food Frequency Questionnaire (FFQ) to be self-completed annually (2023-2030) by a representative sample of 1000 adults (18-65 years). The food list of the FFQ was developed using a stepwise approach based on the Belgian food consumption survey 2014, selecting the 90% most contributing foods to protein intake. New foods retrieved from a market research and expected innovations were added. Similar foods were combined into survey items, and portion size questions added. Protein intake was estimated using the weighted mean protein intake of the 90% most consumed foods represented in each item. A content validation study was performed to assess question comprehension, food identification and quantification. Results will allow to estimate average protein intake and evolution of protein sources over time. Results The FFQ includes 60 food items. The average completion time was 16 minutes. The content validation let to re-ordering of food items and reformulation of portion descriptions. Conclusions The newly developed FFQ will strengthen the Flemish public health surveillance system: monitoring protein intake and the ratio of animal-based versus plant-based and alternative protein will allow to guide actions and track progress towards policy objectives of the ‘Green Deal Protein Shift on our plate'. Key messages • This study highlights the role of public health surveillance systems in monitoring new policy actions and progress towards policy objectives. • This study highlights the development of rapid screening tools using a database approach and market research data.

Diagnosis, management and prevention of Pediatric Acute Hemolytic Anemia: Egyptian adapted evidence-based clinical practice guidelines

BackgroundAcute hemolytic anemia (AHA) is a common emergency in pediatric emergency departments, hence the need to adapt pre-existing high-quality practice guidelines for the diagnosis, management, and prevention of AHA to be available for national use.MethodsThe guideline panel used the adapted ADAPTE methodology. The panel prioritized the health questions and recommendations according to their importance for clinicians and patients. The procedure included searching for existing guidelines, quality appraisal, and adaptation of the recommendations to be used in low-resource countries.ResultsThe guideline provided approach to a child with AHA: laboratory diagnosis of glucose-6-phosphate dehydrogenase (G6PD) deficiency, autoimmune hemolytic anemia (AIHA), and hemolytic uremic syndrome (HUS); treatment of AHA including indications for red cell transfusion, medical treatment, plasma exchange, and indications of antibiotic in HUS; how to avoid further episodes of hemolysis; and when to refer to a hematologist. Implementation tools included a checklist for history and examination, lists of differential diagnoses, flow charts for the diagnosis of AHA, and a list of medications and food to be avoided in patients with G6PD deficiency.ConclusionThis adapted guideline will aid decision-making related to the diagnosis, management, and prevention of AHA.

Determining classes of food items for health requirements and nutrition guidelines using Gaussian mixture models.

The identification of classes of nutritionally similar food items is important for creating food exchange lists to meet health requirements and for informing nutrition guidelines and campaigns. Cluster analysis methods can assign food items into classes based on the similarity in their nutrient contents. Finite mixture models use probabilistic classification with the advantage of taking into account the uncertainty of class thresholds. This paper uses univariate Gaussian mixture models to determine the probabilistic classification of food items in the South African Food Composition Database (SAFCDB) based on nutrient content. Classifying food items by animal protein, fatty acid, available carbohydrate, total fibre, sodium, iron, vitamin A, thiamin and riboflavin contents produced data-driven classes with differing means and estimates of variability and could be clearly ranked on a low to high nutrient contents scale. Classifying food items by their sodium content resulted in five classes with the class means ranging from 1.57 to 706.27 mg per 100 g. Four classes were identified based on available carbohydrate content with the highest carbohydrate class having a mean content of 59.15 g per 100 g. Food items clustered into two classes when examining their fatty acid content. Foods with a high iron content had a mean of 1.46 mg per 100 g and was one of three classes identified for iron. Classes containing nutrient-rich food items that exhibited extreme nutrient values were also identified for several vitamins and minerals. The overlap between classes was evident and supports the use of probabilistic classification methods. Food items in each of the identified classes were comparable to allowed food lists developed for therapeutic diets. This data-driven ranking of nutritionally similar classes could be considered for diet planning for medical conditions and individuals with dietary restrictions.

Development of a Multilingual Web-Based Food Frequency Questionnaire for Adults in Switzerland.

Dietary assessment is a major challenge in epidemiological research and is associated with a high time and financial burden. Automated food frequency questionnaires (FFQs) have the potential to rapidly collect dietary intake data in large studies while reducing human error risk during data processing. We developed a semiquantitative, multilingual, electronic FFQ for real-time dietary intake assessment in the Swiss adult population, called "Swiss eFFQ". The iterative development process involved stages of content identification, construction, pretesting, translation, and adaptation of the FFQ. Using 24 h dietary recalls from 2085 participants aged 18-75 years from a nationally representative survey, we conducted a stepwise regression analysis to identify foods contributing to >90% of the variance in intakes of energy and six nutrients. All 118 foods identified in the overall cohort or in any of the Swiss linguistic regions were selected and standardized to define the comprehensive 83-item food list, covering >90% of the intake of key nutrients in the entire study population. Once validated, the Swiss eFFQ can be used to classify individuals based on their habitual diets. The methodology described in this paper enhances the transparency of the Swiss eFFQ and may help researchers to develop multilingual dietary assessment tools for other populations.

A low-carbohydrate diet in place of SGLT2i therapy in a patient with diabetic cardiomyopathy.

In patients with diabetes mellitus, the toxic milieu caused by abnormal glucose and free fatty acid handling can lead to heart failure (HF). Referred to as diabetic cardiomyopathy (DMCM), this syndrome often exists in the absence of conventional risk factors for HF such as history of myocardial infarction or hypertension. Low-carbohydrate diets (LCDs) have recently been endorsed as an efficacious therapeutic dietary approach to prevent and reverse cardiometabolic disease including type 2 diabetes mellitus (T2DM). LCDs improve systemic insulin resistance (IR), reverses cardiac remodelling in a rodent model and downregulates the expression of sodium-glucose co-transporter 2 (SGLT2) receptors in the kidney. It is therefore conceivable that a lifestyle approach such as adopting an LCD can be offered to patients with DMCM. The reported case is that of a 45-year-old man with a 15-year history of non-ischaemic cardiomyopathy, T2DM and obesity. The patient volunteered to engage in a 16-week low-carbohydrate dietary intervention trial and then self-selected to remain on this diet for 1 year. The whole-food LCD was based on simple 'traffic light' style food lists and not designed to restrict calories, protein, fat or salt. After 1 year, the patient had lost 39 kg and his cardiometabolic markers had significantly improved. LCDs present a potentially beneficial approach for patients with DMCM and could be considered as a lifestyle intervention before SGLT2i therapy is commenced. Diabetic cardiomyopathy (DMCM) is a syndrome precipitated mainly by the detrimental effects of glucose metabolism disorders such as insulin resistance and diabetes. Low-carbohydrate diets (LCD) mimic many effects of sodium-glucose co-transporter 2 inhibitors (SGLT2i). LCDs are a dietary pattern which can have significant and beneficial effects on metabolic and anthropometric markers in patients with DMCM. LCDs and SGLT2i therapy could be combined and may achieve better clinical outcomes for patients with DMCM. Combination therapy may be carried out under close supervision as the real risk for diabetic ketoacidosis remains.

RANCANG BANGUN SISTEM INFORMASI PELAYANAN RESTORAN HOTEL BERBASIS WEB DENGAN FRAMEWORK CODEIGNITER

The Batam view hotel restaurant is one of the service units in the hotel. Guests at the hotel generally enjoy eating and drinking at the restaurant. The manual system in the hotel restaurant often causes problems, such as guest orders that do not match those recorded by restaurant staff, guests often cancel orders because no one is taking orders, and Guests often have difficulty seeing the list of food and drinks available in the restaurant. Until now, this hotel restaurant does not have an online ordering system. thus resulting in several work systems being constrained. This is what prompted the author to build and design a Web- based information system for this restaurant.This website will be designed with the PHP programming language and coupled with the codeigniter framework. The research method used is Research and development (R&amp;D),This research is expected to be able to develop the restaurant into a restaurant that has an online system, so that it can increase guest satisfaction both in terms of service and providing information.

Screening of Strawberry Allergy in Egyptian Atopic Children

Background Strawberries are included in the list of allergenic foods. However, definite figures in many countries including Egypt are lacking. Children with food allergy are 2 to 4 times more likely to have asthma, eczema, and allergic rhinitis than their non-allergic peers. We therefore sought to investigate IgE-mediated strawberry sensitization among a group of atopic children and correlate it to their clinical and laboratory parameters. Patients and Methods This study comprised 256 children, 1 to 18 years old, with physician-diagnosed bronchial asthma (98 patients), allergic rhinitis (28 patients), atopic dermatitis (53 patients), food allergy (10 patients) and combined allergies (67 patients). They were enrolled consecutively from the Pediatric Allergy, Immunology and Rheumatology Unit, Children's Hospital, Ain Shams University, Cairo. Sensitization to strawberry was assessed using prick-prick test (PPT). Results Strawberry sensitization was observed in 7.8% of the studied children. Confirmed strawberry allergy was elicited in 2% of them. Strawberry sensitization was more prevalent in patients with food allergy followed by those with atopic dermatitis. Severity of allergic disease, frequency of flare ups and response to treatment did not influence the rate of strawberry sensitization in our series. Conclusion Strawberry allergy is not as common as claimed to be among Egyptian children with allergic disorders. Sensitization to strawberry did not impact the severity of allergy or response to treatment. The findings are limited by the sample size.

Machine learning accurately predicts food exchange list and the exchangeable portion.

Food Exchange Lists (FELs) are a user-friendly tool developed to help individuals aid healthy eating habits and follow a specific diet plan. Given the rapidly increasing number of new products or access to new foods, one of the biggest challenges for FELs is being outdated. Supervised machine learning algorithms could be a tool that facilitates this process and allows for updated FELs-the present study aimed to generate an algorithm to predict food classification and calculate the equivalent portion. Data mining techniques were used to generate the algorithm, which consists of processing and analyzing the information to find patterns, trends, or repetitive rules that explain the behavior of the data in a food database after performing this task. It was decided to approach the problem from a vector formulation (through 9 nutrient dimensions) that led to proposals for classifiers such as Spherical K-Means (SKM), and by developing this idea, it was possible to smooth the limits of the classifier with the help of a Multilayer Perceptron (MLP) which were compared with two other algorithms of machine learning, these being Random Forest and XGBoost. The algorithm proposed in this study could classify and calculate the equivalent portion of a single or a list of foods. The algorithm allows the categorization of more than one thousand foods with a confidence level of 97% at the first three places. Also, the algorithm indicates which foods exceed the limits established in sodium, sugar, and/or fat content and show their equivalents. Accurate and robust FELs could improve implementation and adherence to the recommended diet. Compared with manual categorization and calculation, machine learning approaches have several advantages. Machine learning reduces the time needed for manual food categorization and equivalent portion calculation of many food products. Since it is possible to access food composition databases of various populations, our algorithm could be adapted and applied in other databases, offering an even greater diversity of regional products and foods. In conclusion, machine learning is a promising method for automation in generating FELs. This study provides evidence of a large-scale, accurate real-time processing algorithm that can be useful for designing meal plans tailored to the foods consumed by the population. Our model allowed us not only to distinguish and classify foods within a group or subgroup but also to perform the calculation of an equivalent food. As a neural network, this model could be trained with other food bases and thus improve its predictive capacity. Although the performance of the SKM model was lower compared to other types of classifiers, our model allows selecting an equivalent food not from a group previously classified by machine learning but with a fully interpretable algorithm such as cosine similarity for comparing food.

Human-Behavior-Based Personalized Meal Recommendation and Menu Planning Social System

The traditional dietary recommendation systems are basically nutrition or health-aware where the human feelings on food are ignored. Human affects vary when it comes to food cravings, and not all foods are appealing in all moods. It takes a lot of effort to learn people’s food preferences and make recommendations based on their affects and nutrition. A questionnaire-based and preference-aware meal recommendation system can be a solution. However, automated recognition of social affects on different foods and planning the menu considering nutritional demand and social affect has some significant benefits over the questionnaire-based and preference-aware meal recommendations. A patient with severe illness, a person in a coma, or patients with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">locked-in syndrome</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">amyotrophic lateral sclerosis</i> (ALS) cannot express their meal preferences. Therefore, the proposed framework includes a social-affective computing module to recognize the affects of different meals where the person’s affect is detected using electroencephalography (EEG) signals. EEG allows to capture the brain signals and analyze them to anticipate affective state toward a food. In this study, we have used a 14-channel wireless Emotiv Epoc <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$+$</tex-math> </inline-formula> to measure affectivity for different food items. A hierarchical ensemble method is applied to predict affectivity upon multiple feature extraction methods and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to generate a food list based on the predicted affectivity. In addition to the meal recommendation, an automated menu planning approach is also proposed considering a person’s energy intake requirement, affectivity, and nutritional values of the different menus. The bin-packing algorithm is used for the personalized menu planning of breakfast, lunch, dinner, and snacks. The experimental findings reveal that the suggested affective computing, meal recommendation, and menu planning algorithms perform well across a variety of assessment parameters.

Halal Fermented Functional Food in Indonesia: A Review

Nowadays, people prefer to consume foods with better nutrition to enjoy life more healthily. However, Muslims must also eat halal food following the Islamic way of life; eating nutritious food alone is insufficient. Indonesia, the largest Muslim population in the world, presents a market potential for halal food manufacturers and consumers worldwide. Several varieties of regional fermented foods were listed on the halal-positive food list and free from the requirement of halal certification, as per Indonesian Halal rules. The review of Indonesian fermented foods listed in the category of positive halal foods is the main topic of this essay. The procedures used to review the chosen themes include finding the literature in online sources, screening for topic inclusion, and evaluating, extracting, and discussing the accessible data found in the publications. The potential functional local fermented food varieties are included on the positive halal list: Tape (sticky rice and cassava), Dadih, and Tempeh. These fermented foods' microbiological and chemical characteristics were discussed. Therefore, the functional value of these fermented foods is rich in phytochemicals, anti-cancer (β-glucan), antioxidant compounds (isoflavones) and probiotic components (lactic acid bacteria and yeasts).

The localization of food- and drink-related items in video games

Abstract This study examines the localization of food- and drink-related items in The Witcher 3 (2015). It analyzes the original English and Arabic versions using the corpus approach. A list of food- and drink-related lexemes was extracted from the English original game and these lexemes were traced to their context in the English and Arabic versions using the concordance function in Sketch Engine. The concordance analysis focused on the translation strategies adopted to localize food- and drink-related lexemes into Arabic and on the success of the translation in the socio-cultural and religious contexts of the target culture. The data reveals that foreign food-related terms are mostly domesticated, whereas drink-related terms are foreignized. The findings of this study suggest that foreignization strategies can be used for localization purposes to create a target video game that minimizes the cultural gaps between the source and target cultures and provides a less disruptive gaming experience.

Analysis of Factors Guests Consider for Eating and Drinking at Gloria Jean's Coffee

Tourism includes various service industries needed by tourists during their trips and temporary stays in the tourist destinations visited. Coffee shop is a type of business that is currently booming in Indonesia, especially in Bali. The purpose of this study was to find out the factors considered by guests to eat and drink at Gloria Jean's Coffee and to find out the dominant factors influencing guests' interest to eat and drink at Gloria Jean's Coffee. This research was conducted at Gloria Jeans Coffees with respondents totaling 100 respondents, the sample in this study was selected using the accidental sampling method. The data in the study were analyzed using exploratory factor analysis which was supported by the SPSS version 17.0 for windows statistical program. The results of this study are: 1) the explanation of each factor that becomes the guest's perception of eating and drinking at Gloria Jeans Coffees is the percentage considered by tourists in choosing Gloria Jeans Coffees of 78.521% can be explained by these three factors, namely factor 1 is called the advantage factor, factor 2 is called the supporting factor, factor 3 is called the image factor, and factor 4 is called the product and convenience factor. 2) Thus it can be concluded on these advantages factors that determine tourists choose Gloria Jeans Coffees are easy-to-reach locations, affordable food and beverage prices, information complexity, easy information, food and beverage lists according to standards with other Gloria outlets, complete facilities, employee ability to handle guest complaints, employee appearance, employee service and employee communication skills. 3) The supporting factors are formed by a strategic location, security, cleanliness and impressions from guests. 4) The image factor is formed by the employee's ability variable in handling guest complaints, employee friendliness variables and image variables. 5) the product and convenience factors are formed by the variable quality of food and beverages sold to consumers and the variables offered in the packages as well as the convenience variable. Keywords: Factor analysis, Perception, Coffee Shop