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58 results for “food selection”
DIETxPOSOME: a FAIR database detailing food contaminants occurrence in selected foods
<p>The DIETxPOSOME FAIR database provides detailed quantification of 73 contaminants, including 4 heavy metals, 18 polycyclic aromatic hydrocarbons (PAHs), 10 pesticides, 29 mycotoxins, and 12 heterocyclic aromatic amines (HAAs), in 16 food items across various food groups (cereals, vegetables, fruits, starchy roots, dairy products, nuts, meat, eggs, fish, legumes and vegetable oils). Data was obtained through a combination of literature extraction protocols and machine learning.</p> <p>A list of pertinent research articles on food contaminants in globally significant food items was sourced from PubMed. Machine learning enabled the automatic filtering of these papers (<a href="../records/7826130">https://zenodo.org/records/7826130</a>), which were subjected to a manual evaluation. Subsequently, specific foods (wheat, maize, beef, cheese, pasta, potatoes, carrots, rice, bread, chicken eggs, peanuts, beans, cabbage, apple, olive oil, and salmon) were selected based on their comprehensive contaminant profiles. Information was extracted from 145 relevant articles of the 151 research articles pertaining to the selected food items. Following extraction, the data was confirmed and evaluated by three reviewers, adhering to stringent criteria. </p> <p>The food items in the DIETxPOSOME FAIR database can be integrated into complex dietary patterns in an experimental context, for example, aligned with the EAT-Lancet Commission Reference Diet for Healthy and Sustainable Food Systems. This framework allows the simulation of real-world dietary exposure or worst-case scenarios, facilitating comprehensive risk assessment of unavoidable food contaminants.</p> <p> </p>
Fig. 4 in Food attractants for mass trapping of fruit flies (Diptera: Tephritidae) and its selectivity for beneficial arthropods
Fig. 4. Proportion of tephritids (dark grey), beneficial arthropods (white), and other non-target insects (light grey) captured by the different treatments in the 2017 and 2018 seasons.
Fig. 3 in Food attractants for mass trapping of fruit flies (Diptera: Tephritidae) and its selectivity for beneficial arthropods
Fig. 3. Proportion of gravid (dark grey) and non-gravid (light grey) females of Ceratitis capitata lured to the different treatments on pre- and post-harvest period during the 2018 season (NS = no significant differences, * = P ≤ 0.05). (A–B) Dixieland peach; (C–D) Fuji Kiku apple; (E–F) Satsuma mandarin. Treatments with no captures are not presented.
Fig. 2 in Food attractants for mass trapping of fruit flies (Diptera: Tephritidae) and its selectivity for beneficial arthropods
Fig. 2. Proportion of gravid (dark grey) and non-gravid (light grey) females of Ceratitis capitata lured to the different treatments on pre- and post-harvest period during the 2017 season (NS = no significant differences, * = P ≤ 0.05). (A–B) Dixieland peach; (C–D) Fuji Kiku apple; (E–F) Satsuma mandarin. Treatments with no captures are not presented.
Fig. 1 in Food attractants for mass trapping of fruit flies (Diptera: Tephritidae) and its selectivity for beneficial arthropods
Fig. 1. Cumulative Ceratitis capitata captures expressed as females per trap per d index for the pre-harvest (light gray) and post-harvest (dark gray) periods are shown, for the 3 field trials and the 2 seasons of evaluation. Different letters indicate significant differences between treatments in the cumulative captures of females for the total trial period.
Fig. 2 in Trophic relationships in fish assemblages of Neotropical floodplain lakes: selectivity and feeding overlap mediated by food availability
Fig. 2. Ordination by principal coordinate analysis (PCoA) of the food resource availability for six floodplain lakes along the Upper Paraná River, Paraná-Mato Grosso do Sul. AQI = aquatic insects; OAI = other aquatic invertebrates; OTI = other terrestrial invertebrates; PLA = plants; TRI = terrestrial insects.
Fig.5 in Trophic relationships in fish assemblages of Neotropical floodplain lakes: selectivity and feeding overlap mediated by food availability
Fig.5. Relationship between the mean of the proportional overlap Index (IS) and the scores of the first PCoA axis of resource availability in isolated floodplain lakes along the upper Paraná River.Values of IS closer to 1 indicates greater diet overlap. The mean IS was calculated based on individuals of 3 (ZÉ = ZÉ Marinho), 7 (Carioca = Car), 4 (TiÃo = Tia), 5 (Genipapo = Gen), 2 (CidÃo = Cid) and 5 species (Canal = Can).AQI = aquatic insects; PLA = plants.
Fig. 1 in Trophic relationships in fish assemblages of Neotropical floodplain lakes: selectivity and feeding overlap mediated by food availability
Fig. 1. Locations of the lakes on the upper Paraná River floodplain, Brazil: 1, Canal do Meio; 2, Carioca; 3, ZÉ Marinho; 4, CidÃo; 5, Genipapo; 6, TiÃo.
Fig. 4 in Trophic relationships in fish assemblages of Neotropical floodplain lakes: selectivity and feeding overlap mediated by food availability
Fig. 4. Relationship of the mean the Schoener's Index (O) between pairs of species and the scores of the first PCoA axis of resource availability in isolated floodplain lakes along the upper Paraná River. The mean O was calculated based on 10 (ZÉ = ZÉ Marinho), 28 (Carioca = Car), 6 (TiÃo = Tia), 21 (Genipapo = Gen), 3 (CidÃo = Cid) and 10 (Canal = Can) pairs of species. AQI = aquatic insects; PLA = plants.
Fig. 3 in Trophic relationships in fish assemblages of Neotropical floodplain lakes: selectivity and feeding overlap mediated by food availability
Fig. 3. Relationships between feeding selectivity by fish and the availability of food resources for six floodplain lakes along the Upper Paraná River, ParanáMato Grosso do Sul. Shape of data distribution (envelope effect) was significant.
Food quantity and the intensity of the alarm signal combine to modulate the resource selection in a termite species
<p>Maximizing food intake while minimizing risk is an important trade-off in the foraging behavior of most animals. In general, foragers are vulnerable and the ability to trade off benefits (food quantity) against costs (risk of being killed) may provide a considerable ecological advantage. Despite the increasing number of studies, the effects of food quantity and mortality risk signals on resource selection in eusocial insect is not well understood. Here, we investigated the combination of distinct levels of food quantity and the intensity of alarm signal on resource selection of a Neotropical termite, <em>Nasutitermes</em> <em>corniger</em> (Motschulsky) (Termitidae: Nasutitermitinae). Manipulative bioassays with binary and multiple choices were conducted over time to check the recruitment of termite groups among resources containing different levels of food quantity and alarm signals. Overall, our results showed that regardless of food quantity, termites avoid a food source if there is even a small amount of alarm signal. This work contributes to a better understanding of habitat use by termite species. Furthermore, it shows for the first time the combined effects of food quantity and alarm signals on the resource selection of an important ecological and economic termite species. </p>
Online Food and Beverage Labels and Vending Machine Selections
ClinicalTrials.gov study NCT05432271. IPD Sharing: YES. Countries: 1. Publications: 1.
Food quantity and the intensity of the alarm signal combine to modulate the resource selection in a termite species
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Food composition database for nutrient intake: selected vitamins and minerals in selected European countries
<p>Following a request from the European Commission for a review of European dietary reference values (DRVs), the EFSA’s Panel on Dietetic Products, Nutrition and Allergies (NDA) has prepared a number of Scientific Opinions on DRVs for micronutrients. The DATA Unit supported this activity by estimating the nutrient intake of a number of micronutrients in nine selected European countries and different age groups. In addition, the DATA Unit also provided information on average content of food sources of the respective nutrients per country based on the composition database, as well as main food group contributors to nutrient intakes and assessed the comparability of the provided data with pertinent published intake data.</p> <p>Intake estimates have been assessed using food consumption data from the EFSA Comprehensive Food Consumption Database (EFSA, 2011a) and the EFSA Nutrient composition database. Food composition data used to populate the Nutrient composition database were provided to EFSA through the EFSA procurement project ‘<em>Updated food composition database for nutrient intake’</em> (Roe at al., 2013). Data were provided following the EFSA specification for standard sample description for food and feed and were classified according to the FoodEx2 classification system of EFSA (EFSA, 2011b).</p> <p>The food composition data used in these assessments and here published cover the following vitamins and minerals: calcium (Ca); copper (Cu); cobalamin (vitamin B12); magnesium (Mg); niacin; phosphorus (P); potassium (K); riboflavin; thiamin; iron (Fe); selenium (Se); vitamin B6; vitamin K, zinc (Zn), and vitamin E<sup>1</sup>. The food composition dataset contains data from seven<sup>2</sup> countries: Finland, France, Germany, Italy, Netherlands, Sweden, and United Kingdom. This dataset version has been checked for outliers but is prior to data completion for missing foods and nutrient values.</p> <p><sup>1</sup> Vitamin E is defined as alpha-tocopherol (AT) only, however as most food composition databases in the EU contain values as alpha-tocopherol equivalents (TE), data on TE are also provided</p> <p><sup>2</sup> For the nutrient intake estimates of Ireland and Latvia present in the opinions of the EFSA Panel on Dietetic Products, Nutrition and Allergies (NDA), food composition data from UK and Germany were respectively used</p>
Selection of summer feeding sites and food resources by female migratory caribou (Rangifer tarandus) determined using camera collars
<p>Female migratory caribou (Rangifer tarandus) depend on the availability of summer habitat resources to meet the needs associated with lactation and the accumulation of fat reserves to survive when resources are less abundant. Because of the large scales at which habitat and resource data are usually available, information on how female migratory caribou select habitat and resources at fine scales in the wild is lacking. To document selection of summer feeding sites, we equipped 52 female caribou with camera collars from 2016 to 2018. We collected a total of 65,150 10-sec videos between June 1st and September 1st for three years with contrasted spring phenology. We determined the selection at the feeding site scale (3rd scale of Johnson) and food item scale (4th scale of Johnson) using resource selection probability functions. This data base contains the data of the behaviors observed, habitat used as feeding site, habitat unused has habitat, consumed and unconsumed resources, insect presence and other variables.</p>
A selective role for receptor activity-modifying protein in sub-chronic action of the amylin selective receptor agonist NN1213 compared to salmon calcitonin on body weight and food intake in male mice
<p>Raw data prism files for the manuscript "A selective role for receptor activity-modifying protein in sub-chronic action of the amylin selective receptor agonist NN1213 compared to salmon calcitonin on body weight and food intake in male mice"</p>
Data for: Fear before food: Scale-dependence in elk habitat selection
<ol> <li>Habitat selection is a critical aspect of a species' ecology requiring complex decision-making that is both hierarchical and scale-dependent, since factors that influence selection may be nested or unequal across scales.</li> <li>Elk (<em>Cervus</em> <em>canadensis</em>) ranged widely across diverse habitats in North America prior to European settlement and subsequent eastern extirpation. Most habitat studies have occurred within their contemporary western range, even after eastern elk reintroductions began. As habitat selection can vary by geographic location, available cover, season, and diel period, it is important to understand how a non-migratory, reintroduced population in northern Wisconsin, USA is limited by the lack of variation in topography, elevation, and vegetation.</li> <li>We tested scale-dependent habitat selection on 79 adult elk from 2017–2020. We used resource selection functions across both temporal and spatial scales to understand differences in selection of topographic and environmental features.</li> <li>We found that selection varied both spatially and temporally and elk selected areas with the greatest potential to influence fitness at larger scales (i.e., landscape scale), meaning elk selected areas closer to escape cover and further from "risky" features (e.g., wolf territory centers, county roads and highways). We found stronger avoidance to wolf territory centers during spring, suggesting elk were selecting safer habitats during calving season. We found elk selected habitats with less canopy cover across both spatial scales and all seasons, suggesting that elk selected these areas for better access to forage as forest stands in early seral stages have greater nutritional value and forage biomass than closed-canopy forests and direct solar radiation to provide warmth in the cooler seasons.</li> <li>This study highlights how processes at different spatial and temporal scales influence species' decision-making. It provides insight into the complexity of making informed decisions in which an individual is responding to their immediate environment while simultaneously making decisions in the context of the larger landscape. Scale-dependent behavior is crucial to understand within specific geographic regions as these decisions scale up to influence population dynamics. </li> </ol>
Meal selection when plant-based food is presented as the default for a catered event
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Food Selectivity Protocol for Children With Autism Spectrum Disorders
ClinicalTrials.gov study NCT06179940. IPD Sharing: NO. Countries: 1. Publications: 3.
Health Impacts of Sustainable Ingredient Selection in the Food and Drink Industry - ALTERNATIVE PROTEIN STUDY
ClinicalTrials.gov study NCT01898351. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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