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Fruit Juices

Fruit juices are non-alcoholic beverages extracted from various types of fruits.
They are rich in vitamins, minerals, and natural sugars, providing health benefits such as improved hydration, immune support, and cardiovascular health.
Fruit juices can be made from a wide range of fruits, including oranges, apples, grapes, pineapples, and berries.
Thier flavor, nutrient content, and processing methods can vary.
Researching optimal fruit juice formulations and production protocols is crucial for developing high-quality, consumer-friendly products.
PubCompare.ai's AI-powered platform can help streamline this process by easily locating and comparing relevent research protocols from literature, preprints, and patents to identifiy the best solutions for your fruit juice product development needs.

Most cited protocols related to «Fruit Juices»

We created an overall plant-based diet index (PDI), a healthful plant-based diet index (hPDI), and an unhealthful plant-based diet index (uPDI). The procedure we used to create these indices is similar to the one used by Martínez-González et al. [13 (link)]; their “provegetarian food pattern” is similar in composition to our PDI. Frequencies of consumption of each food were converted into servings consumed per day. Then the number of servings of foods that belonged to each of 18 food groups were added up. The 18 food groups were created on the basis of nutrient and culinary similarities, within larger categories of animal foods and healthy and less healthy plant foods. We distinguished between healthy and less healthy plant foods using existing knowledge of associations of the foods with T2D, other outcomes (CVD, certain cancers), and intermediate conditions (obesity, hypertension, lipids, inflammation). Plant foods not clearly associated in one direction with several health outcomes, specifically alcoholic beverages, were not included in the indices. We also excluded margarine from the indices, as its fatty acid composition has changed over time from high trans fat to high unsaturated fat. We controlled for alcoholic beverages and margarine consumption in the analysis.
Healthy plant food groups included whole grains, fruits, vegetables, nuts, legumes, vegetable oils, and tea/coffee, whereas less healthy plant food groups included fruit juices, sugar-sweetened beverages, refined grains, potatoes, and sweets/desserts. Animal food groups included animal fats, dairy, eggs, fish/seafood, meat (poultry and red meat), and miscellaneous animal-based foods.
S1 Table details examples of foods constituting the food groups. The 18 food groups were divided into quintiles of consumption, and each quintile was assigned a score between 1 and 5. For PDI, participants received a score of 5 for each plant food group for which they were above the highest quintile of consumption, a score of 4 for each plant food group for which they were above the second highest quintile but below the highest quintile, and so on, with a score of 1 for consumption below the lowest quintile (positive scores). On the other hand, participants received a score of 1 for each animal food group for which they were above the highest quintile of consumption, a score of 2 for each animal food group for which they were between the highest and second highest quintiles, and so on, with a score of 5 for consumption below the lowest quintile (reverse scores). For hPDI, positive scores were given to healthy plant food groups, and reverse scores to less healthy plant food groups and animal food groups. Finally, for uPDI, positive scores were given to less healthy plant food groups, and reverse scores to healthy plant food groups and animal food groups. The 18 food group scores for an individual were summed to obtain the indices, with a theoretical range of 18 (lowest possible score) to 90 (highest possible score). The observed ranges at baseline were 24–85 (PDI), 28–86 (hPDI), and 27–90 (uPDI) across the cohorts. The indices were analyzed as deciles, with energy intake adjusted at the analysis stage.
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Publication 2016
Alcoholic Beverages Animals Cereals Coffee Diet Eggs Fabaceae Fats Fats, Unsaturated Fatty Acids Feeds, Animal Fishes Food Fowls, Domestic Fruit Fruit Juices High Blood Pressures Inflammation Lipids Malignant Neoplasms Margarine Meat Nutrients Nuts Obesity Plants Plants, Edible Red Meat Seafood Solanum tuberosum Sugar-Sweetened Beverages Vegetable Oils Vegetables Whole Grains
The ENERGY-child questionnaire was developed in order to assess EBRBs of the child as well as personal, and family and school-environmental determinants related to these EBRBs. The questionnaire was divided in eight sections, i.e. (A) Demographic characteristics; (B) Soft drinks and spending pocket money on soft drinks; (C) Fruit juices; (D) Breakfast behaviour; (E) Physical activity behaviour; (F) Screen viewing behaviour; and (G) Dieting behaviour. In the current study we assessed the test-retest reliability and construct validity of all sections (150 items), except 'demographic characteristics'.
Most concepts were measured by only one or two items due to practical constraints with regard to the length of the questionnaire. The questionnaire was developed from existing measures or such existing measures were adapted for the behaviours included in the ENERGY-child questionnaire [12 (link)-14 (link)]. More details on the development of the questionnaire, the pre-testing, and translation procedures are described elsewhere [11 (link)]. The ENERGY-child questionnaire is available via the ENERGY-website in English and all languages in which the questionnaire was administered: http://www.projectenergy.eu.
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Publication 2011
Child Fruit Juices Soft Drinks
Lifestyle habits of interest were physical activity, television watching, alcohol use, sleep duration, and diet, and cigarette smoking was a potential confounding factor (Table 1, and Tables 1 and 2 in the Supplementary Appendix, available with the full text of this article at NEJM.org). On the basis of their plausible biologic effects, the dietary factors we assessed included fruits, vegetables, whole grains, refined grains, potatoes (including boiled or mashed potatoes and french fries), potato chips, whole-fat dairy products, low-fat dairy products, sugar-sweetened beverages, sweets and desserts, processed meats, unprocessed red meats, fried foods, and trans fat (see Table 1 in the Supplementary Appendix). We also evaluated nuts, 100%-fruit juices, diet sodas, and subtypes of dairy products and potatoes. Different types of alcohol drinks were also evaluated. To assess aggregate dietary effects, changes in each dietary factor independently associated with weight gain were categorized in quintiles and assigned ascending values (1 to 5) or descending values (5 to 1) for habits inversely or positively associated with weight gain, respectively; these ordinal values were summed to generate an overall score for dietary change.
Publication 2011
Biopharmaceuticals Cereals Dairy Products Diet Dietary Modification DNA Chips Fat-Restricted Diet Food Fruit Fruit Juices Meat Nuts Potato Red Meat Sugar-Sweetened Beverages Therapy, Diet Vegetables Whole Grains
We obtained data on purchases from January 2012 through December 2014 from Nielsen Mexico’s Consumer Panel Services, which is equivalent to the data from the US Nielsen Homescan panel.28 (link) In the US, Nielsen Homescan data have been used in several studies, including some that have linked purchases to data on nutrition labels to determine the caloric content of purchases and to evaluate industry efforts.29 (link)
30 (link) However, linking purchases to nutrition data is currently not possible in Mexico owing to the lack of comprehensive data sources related to labeling. Therefore we focused on changes in the volumes of beverages purchased.
Each year the Nielsen Mexico Consumer Panel Services samples Mexican households in 53 cities (in 28 states plus Mexico City) with more than 50 000 inhabitants. Based on government statistics, this sample represents 63% of the Mexican population and 75% of food and beverage expenditures in 2014.31 The original dataset contained 205 827 household-month observations from 6286 households. We used complete case analysis; 715 observations (0.3%) were dropped because of missing information on the highest educational attainment of the heads of the households. Consequently, our analytic sample included 205 112 household months across 6253 households, of which 86% participated in all rounds. Each household is weighted based on household composition, locality, and socioeconomic measures through iterative proportional fitting to match demographic estimates from the National Institute of Statistics and Geography (Instituto Nacional de Estadística Geografía e Informática, INEGI). Enumerators visited the households every two weeks to collect diaries, product packaging from special bins provided for this study (scanned by the enumerators), and receipts, and to carry out pantry surveys. Bar code information provided all other data.
For descriptive purposes, we categorized the sample into the six regions used by INEGI: central north, central south, Mexico City, north east, north west, and south. The variables we used in the analysis included demographic information on household composition (age and sex of each household member) and socioeconomic status; information that is updated annually. Socioeconomic status groups (low, middle, and high) were based on a six category measure derived from annually updated questions on household ownership of assets (for example, number of bathrooms, number of bedrooms, number of vehicles owned) and education attainment of the head of the household. Onto the Nielsen Mexico Consumer Panel Services data we overlaid two contextual measures: the state’s quarterly unemployment rate from INEGI,32 and the two economic minimum daily salary for each year from Mexico’s National Commission of Minimum Salaries33 (after adjusting for state and quarter specific inflation from INEGI’s consumer price indices, www.inegi.org.mx/est/contenidos/proyectos/inp/inpc.aspx).
In this analysis we used the purchase of beverages by each household between 1 January 2012 and 31 December 2014. Data from the Nielsen Mexico Consumer Panel Services include the number of units purchased and the volume and price of each unit. From these we totalled the monthly volume and beverage categories each household purchased across each of the 36 months. Then we calculated the volume per capita per day for interpretability. Our beverage categories followed the 2012 National Health and Nutrition Survey (Encuesta Nacional de Salud y Nutrición) groupings for beverage intake as much as possible22 (link)
34 ; these were further grouped into larger categories or subgrouped as described in supplemental table 1. We classified products into beverage categories in 2014 based on product descriptions and sources available on the internet and in stores. In this study we focus on the top level taxed and untaxed beverages. Our two categories for taxed beverages were carbonated sodas and non-carbonated sugar sweetened beverages, and our three categories for untaxed beverages were carbonated drinks such as diet sodas; sparkling, still, or plain water; and other drinks, including unsweetened dairy beverages and fruit juices. The Consumer Panel Services did not collect information on purchases of dairy products from all of the sampled households until October 2012 (personal communication). Therefore we limited our analyses of the categories “other untaxed drinks” and “overall untaxed beverages” to October 2012 through December 2014.
Publication 2016
Beverages Dairy Products Diet Drinks Food Fruit Juices Head Head of Household Households Sugar-Sweetened Beverages
All personnel who assessed study outcomes were unaware of the group assignments. The primary outcome was the change in BMI at 2 years. To calculate BMI, trained personnel measured weight and height using calibrated scales and stadiometers, respectively. We used data from bioelectrical impedance analysis (BIA) and the equation of Sun et al.15 (link) to calculate body fat as a percentage of total body weight. In three telephone interviews conducted at each assessment (baseline, 1 year, and 2 years), participants were asked to recall their dietary intake and physical activity during the preceding 24 hours. Dietary intake data were collected with Nutrition Data System for Research (NDSR) software, versions 2006 through 2011, developed by the Nutrition Coordinating Center, University of Minnesota, Minneapolis. Final calculations were completed with NDSR, version 2011. Variables used to assess dietary quality included reported daily servings of sugar-sweetened, artificially sweetened, and unsweetened beverages; servings of 100% fruit juices; total energy and sugar intakes; and energy intake from sugar-sweetened beverages and 100% fruit juices. The interviewer also asked each participant to recall the activity performed most often during each 15-minute block throughout the previous day.16 (link),17 (link) We calculated a daily physical-activity factor, using metabolic equivalent (MET) levels for each reported activity,18 (link) and hours of television viewing.
Publication 2012
Beverages Bioelectrical Impedance Body Fat Carbohydrates Diet Fruit Juices Interviewers Mental Recall Metabolic Equivalent Sugar-Sweetened Beverages

Most recents protocols related to «Fruit Juices»

A single 24-h dietary assessment was completed at baseline for each child by one parent using the online Automated Self-Administered 24-h (ASA24) Dietary Assessment Tool 2016-Canadian version (National Cancer Institute, Bethesda, MD). The Canadian version of ASA24 calculates the nutrient profile of reported dietary intake using the Food Patterns Equivalents Database (FPED), Food and Nutrients Database for Dietary Studies (FNDDS), and Canadian Nutrient File (CNF). Energy and nutrient intakes were screened for outliers using the adjusted box plot method [18 (link)] and implausible dietary intakes.
Total sugar and added sugar intakes were calculated by ASA24. FS intake was defined as added sugar plus sugar from 100% fruit juice (includes fruit juice concentrate diluted to single strength and fruit juice that is not from concentrate) [1 , 19 ]; and determined using a standardized and semi-automated stepwise approach as described in Additional File 1.
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Publication 2023
Carbohydrates Child Diet Food Fruit Juices Nutrient Intake Nutrients Parent Self-Assessment
The SANHANES-1 questionnaire (21 ) was also used to collect information regarding the frequency of consuming street food (FF). The FF list comprised processed meat (i.e., sausages, polony, and cold cuts, such as Viennas, Frankfurters, Russians, and salami); fast food/takeaway foods, including pizzas, fried chicken, fried fish, and burgers, that were packaged to take home; fried meat and fish dishes (i.e., chips, fried chicken, and fried fish) that were consumed on site; deep-fried snacks (i.e., fries/chips, vetkoek, samoosas, and doughnuts), fresh fruits (i.e., all kinds of fruits, excluding fruit juices and dried fruits), sugar-sweetened beverages (SSBs) (i.e., gas/fizzy and reconstituted cold drinks). Consumption frequency for each food item was measured as “none”, “every day”, “1–3 times per week”, and “4–6 times per week”.
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Publication 2023
Chickens Common Cold DNA Chips Fast Foods Food Fruit Fruit Juices Hyperostosis, Diffuse Idiopathic Skeletal Meat phenylalanyl-arginyl-iodotyrosine Snacks Sugar-Sweetened Beverages
A validated, semi-quantitative 32-item Beverage Intake Assessment Questionnaire (BIAQ) [10 (link)] and a 143-item validated semi-quantitative FFQ (38) specifying usual portion sizes, were administered by trained dietitians to assess habitual fluid and dietary intakes, respectively. These two questionnaires have been validated within populations of older, Spanish individuals, which are analogous to the current study population, and both have been found to be reproducible with relative validity [10 (link), 38 (link)]. The BIAQ recorded the frequency of consumption of various beverage types during the month prior to the visit date. The average daily fluid intake from beverages was estimated from the servings of each type of beverage. The questionnaire items on beverages included: tap water, bottled water, natural fruit juices, bottled fruit juices, natural vegetable juices, bottled vegetable juices, whole milk, semi-skimmed milk, skimmed milk, drinking yogurt, milkshakes, vegetable drinks, soups, jellies and sorbets, soda, light/zero soda, espresso, coffee, tea, beer, non-alcoholic beer, wine, spirits, mixed alcoholic drinks, energy drinks, sports drinks, meal replacement shakes, and other beverages. The water and nutrient contents of the beverages were estimated mainly using the CESNID Food Composition Tables [39 ], complemented with data from the BEDCA Spanish Database of Food Composition [40 ].
The FFQ collected data on food intake based on the year prior to the visit according to nine possible frequency categories, which ranged from “never or almost never” to “> 6 portions/day” and based on the dietary guidelines for the Spanish population [41 ]. The information collected was converted into grams per day, multiplying portion sizes by consumption frequency and dividing the result by the period assessed. Ten food groups composed of vegetables, fruits, legumes, cereals, dairy beverages, meat and poultry, fats, nuts, fish/seafood, and other foods were determined to assess the contribution of foods to total water intake. Food groups and energy intake were estimated using Spanish food composition tables [42 , 43 ]. Drinking water intake, water intake from all fluids, total water intake, EFSA total fluid water intake (TFWI), and EFSA total water intake (TWI) were computed (descriptions summarized in Additional file 1: Table S1). Drinking water intake was estimated based on tap and bottled water intakes based on BIAQ responses. Water intake from all fluids was computed from tap and bottled water, plus water from other beverages based on responses to the BIAQ. Total water intake encompassed water intake from all fluids in addition to water present in food sources based on responses to the FFQ. Water intake was further categorized based on established reference values. The EFSA recommendations for total water intake (EFSA TWI) for older adults (2.5 L/day and 2.0 L/day for men and women, respectively) in conditions of moderate environmental temperature and moderate physical activity [20 ] were used as reference values. Further categorizations were determined based on total water intake from fluids alone, based on EFSA recommendations (EFSA TFWI), where recommended levels for older adults are set to at least 2.0 L/day and 1.6 L/day for men and women, respectively [20 ].
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Publication 2023
Aged Alcoholic Beverages Alcoholics Beer Beverages Cereals Coffee Dietitian Eating Energy Drinks Fabaceae Fats Fishes Food Food Additives Fowls, Domestic Fruit Fruit Juices Gels Hispanic or Latino Light Meat Milk Multiple Endocrine Neoplasia Type 2a Nutrients Nuts Seafood Tremor Vegetable Juices Vegetables Water Consumption Wine Woman Yogurt
All animal procedures complied with the NIH Guide for Care and Use of Laboratory Animals, and were approved by the institutional animal care and use committee of the Royal Netherlands Academy of Arts and Sciences. Two male macaque monkeys participated in the experiment. They were 5 (M1) and 8 (M2) y old at the start of the experiments and weighted between 7 and 8 (M1) and 8 and 9 (M2) kg over the course of the recordings. The monkeys were socially housed in pairs in a specialized primate facility with natural daylight, controlled humidity and temperature. The home cage was a large floor-to-ceiling cage that allowed natural climbing and swinging behavior. The cage had a solid floor, covered with sawdust, and was enriched with toys and foraging items. The diet consisted of monkey chow supplemented with fresh fruit. The access to fluid was controlled, according to a carefully designed regime for fluid uptake. During weekdays the animals received diluted fruit juice in the experimental set up upon correctly performed trials. We ensured that the animals drank sufficient fluid in the set up and supplemented extra fluid after the recording session if the monkeys did not drink enough. In the weekend the animals received at least 700 mL of water in the home cage supplied in a drinking bottle. The animals were regularly checked by veterinary staff and animal caretakers and their weight and general appearance were recorded in an electronic logbook daily during fluid control periods.
Publication 2023
Animals Animals, Laboratory Fruit Fruit Juices Humidity Institutional Animal Care and Use Committees Macaca Males Monkeys Primates Therapy, Diet

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Publication 2023
Beverages Diet Food Fruit Fruit Juices Plant Leaves Soft Drinks Vegetables

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More about "Fruit Juices"

Fruit-based beverages, Citrus juices, Berry juices, Tropical fruit juices, Juice concentrates, Fruit juice blends, Pasteurized juices, Cold-pressed juices, Juice extraction methods, Juice processing techniques, Nutritional profiles of juices, Vitamin and mineral content, Natural sugars, Antioxidants, Hydration benefits, Immune system support, Cardiovascular health, Juice quality assessment, Brix measurement, Titratable acidity, pH testing, Viscosity analysis, Color evaluation, Sensory analysis, Product development, Formulation optimization, Packaging considerations, Shelf-life studies, Juice safety and regulations, PAL-1 refractometer, Digital refractometer, CR-400 colorimeter, PR-101 refractometer, Handheld refractometer, Atago refractometer model PR 101, Synergy H1 microplate reader, Titroline Easy titrator, Digital caliper, HI 96801 sugar/salt analyzer.