Fostering quality data in food composition databases: visions for the future

2004 ◽  
Vol 17 (3-4) ◽  
pp. 251-258 ◽  
Author(s):  
Barbara Burlingame
Keyword(s):  
Food Composition ◽  
Quality Data ◽  
The Future

Review of Mouthfeel Classification. A New Perspective of Food Perception

2020 ◽  
pp. 1-10
Author(s):  
Georgios Agorastos
Keyword(s):  
Food Product ◽  
Food Composition ◽  
Product Categories ◽  
Human Interface ◽  
Model Classification ◽  
Flavor Perception ◽  
Food Perception ◽  
The Future ◽  
New Perspective

Characteristics of a food product are the backbone of sensory research and it is essential to describe the food flavor with well-defined and agreed-upon concepts. This paper reviews the current bibliography related to taste/flavor perception, with a particular focus on mouthfeel. A summary of the current mouthfeel vocabularies is given and research approaches are evaluated. A general mouthfeel model is presented that overarches product categories and has shown its use in practice. The intention is to contribute to an increased understanding of taste and flavor and mouthfeel sensations. This paper reveals the ambiguity of terms that are regularly used in literature. This is influenced by different focus in research. Three classes of research related to mouthfeel are identified: (1) product oriented (molecular attributes), (2) product/human oriented (human interface: receptors, saliva, chewing, etc.) and (3) human oriented (after swallowing). For the future of research in flavor of foods and beverages, it is essential to have consensus on the definitions of relevant concepts and to have a model (classification) based on an approach that is generally accepted. A mouthfeel model is potentially a powerful tool for food producers and researchers alike since it can be used to classify food based on the differences in food composition. Generalist descriptors that can be used to describe mouthfeel in foods and beverages can improve the communication between diverse audiences and contribute to the understanding of taste, flavor and particularly mouthfeel.

The New Data Quality Task Group (DQTG): ensuring high quality data today and in the future

Metabolomics ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 539-540 ◽  
Author(s):  
Daniel W. Bearden ◽  
Richard D. Beger ◽  
David Broadhurst ◽  
Warwick Dunn ◽  
Arthur Edison ◽  
...  
Keyword(s):  
Data Quality ◽  
Task Group ◽  
Quality Data ◽  
High Quality ◽  
High Quality Data ◽  
The Future

scholarly journals Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill Mix Considerations

2021 ◽  
Vol 18 (6) ◽  
pp. 2891
Author(s):  
Madhan Balasubramanian ◽  
Aliya Hasan ◽  
Suruchi Ganbavale ◽  
Anfal Alolayah ◽  
Jennifer Gallagher
Keyword(s):  
Oral Health ◽  
Health Workforce ◽  
Workforce Planning ◽  
Data Sources ◽  
Rapid Review ◽  
Quality Data ◽  
Health Workforce Planning ◽  
Skill Mix ◽  
Planning Models ◽  
The Future

Over the last decade, there has been a renewed interest in oral health workforce planning. The purpose of this review is to examine oral health workforce planning models on supply, demand and needs, mainly in respect to their data sources, modelling technique and use of skill mix. A limited search was carried out on PubMed and Web of Science for published scientific articles on oral health workforce planning models between 2010 to 2020. No restrictions were placed on the type of modelling philosophy, and all studies including supply, demand or needs based models were included. Rapid review methods guided the review process. Twenty-three studies from 15 countries were included in the review. A majority were from high-income countries (n = 17). Dentists were the sole oral health workforce group modelled in 13 studies; only five studies included skill mix (allied dental personnel) considerations. The most common application of modelling was a workforce to population ratio or a needs-based demand weighted variant. Nearly all studies presented weaknesses in modelling process due to the limitations in data sources and/or non-availability of the necessary data to inform oral health workforce planning. Skill mix considerations in planning models were also limited to horizontal integration within oral health professionals. Planning for the future oral health workforce is heavily reliant on quality data being available for supply, demand and needs models. Integrated methodologies that expand skill mix considerations and account for uncertainty are essential for future planning exercises.

scholarly journals 2-D Numerical modelling of hydrodynamic and sediment transport in Agathis Lake

2019 ◽  
Vol 270 ◽  
pp. 04019
Author(s):  
Rian Mantasa Salve Prastica ◽  
Herr Soeryantono ◽  
Dwinanti Rika Marthanty
Keyword(s):  
Water Quality ◽  
Rainy Season ◽  
Quality Data ◽  
Sampling Location ◽  
Water Sampling ◽  
Water Quality Data ◽  
Data Prediction ◽  
The Future ◽  
Water Quality Problem ◽  
Resource Modelling

Problems about lakes are inclining every year, especially for water quality problem. Policy decisions to conserve lakes could be well achieved by data prediction. Modelling by using software could describe the future conditions of lake and give policymakers to legislate the best alternative solution. This research studies Agathis lake characteristics. The lake is situated in Universitas Indonesia, Depok, West Java, Indonesia. The research employs Resource Modelling Associates (RMA) program to simulate hydraulic and water quality data. This research will determine the most representative water sampling location and type of TSS for calibration analysis. Next, this research simulates two scenarios of lake’s conditions. The simulation is run by modelling the lake with wetland scenario and with rainy season scenario. After running several iterations, the most representative water sampling location is in the upper part of the water column and the best model of TSS is mixed TSS. Two simulated scenarios produce a reasonable result and could predict the future conditions of Agathis Lake. The research recommends that the sediment trap, that is located in the inlet of the lake, should be well-treated regularly in rainy season, and Universitas Indonesia should manage and arrange the suitable plants to be applied in the future constructed wetland.

Ascorbic acid content in exotic fruits: A contribution to produce quality data for food composition databases

2011 ◽  
Vol 44 (7) ◽  
pp. 2237-2242 ◽  
Author(s):  
Ana Valente ◽  
Tânia Gonçalves Albuquerque ◽  
Ana Sanches-Silva ◽  
Helena S. Costa
Keyword(s):  
Ascorbic Acid ◽  
Acid Content ◽  
Ascorbic Acid Content ◽  
Food Composition ◽  
Quality Data ◽  
Exotic Fruits

scholarly journals Planning the Future Oral Health Workforce: A Rapid Review of Supply, Demand and Need Models, Data Sources and Skill MIX Considerations

2021 ◽  
Author(s):  
Madhan Balasubramanian ◽  
Aliya Hasan ◽  
Suruchi Ganbavale ◽  
Anfal Alolayah ◽  
Jennifer Gallagher
Keyword(s):  
Oral Health ◽  
Health Workforce ◽  
Workforce Planning ◽  
Data Sources ◽  
Rapid Review ◽  
Quality Data ◽  
Health Workforce Planning ◽  
Skill Mix ◽  
Planning Models ◽  
The Future

Over the last decade, there has been a renewed interest in oral health workforce planning. The purpose of this review is to examine oral health workforce planning models on supply, demand and needs, mainly in respect to their data sources, modelling technique and use of skill mix. A search was carried out on PubMed, Web of Science, and Google Scholar databases for published scientific articles on oral health workforce planning models between 2010 to 2020. No restrictions were placed on the type of modelling philosophy, and all studies including supply, demand or needs based models were included. Rapid review methods guided the review process. Twenty-three studies from 15 different countries were included in the review. A majority were from high income countries (n=17). Dentists were the sole oral health workforce group modelled in 13 studies; only five studied included skill mix (allied dental personnel) considerations. The most common application of modelling was a workforce to population ratio or a needs-based demand weighted variant. Nearly all studies presented weaknesses in modelling process due to the limitations in data sources and/or non availability of necessary data to inform oral health workforce planning. Skill mix considerations in planning models were also limited to horizontal integration within oral health professionals. Planning for the future oral health workforce is heavily reliant on quality data being available for supply, demand and needs models. Integrated methodologies that expand skill mix considerations and account for uncertainty are essential for future planning exercises.

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