A new tool to guide consumers on how to mix and match foods to improve their blood glucose profiles
Sector: Raw Materials • Location: Ireland
Source: EU Funding & Tenders Portal
Low pH foods can attenuate the glycemic response to starch-rich foods. It has been demonstrated that lemon juice, due to its low pH (pH≈2.3), inhibited key digestive enzymes thereby interrupting gastric digestion of starch in vitro. This effect can significantly reduce the glycemic response in humans. In particular, adding lemon juice to a starch rich meal reduced the mean blood glucose concentrat
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Low pH foods can attenuate the glycemic response to starch-rich foods. It has been demonstrated that lemon juice, due to its low pH (pH≈2.3), inhibited key digestive enzymes thereby interrupting gastric digestion of starch in vitro. This effect can significantly reduce the glycemic response in humans. In particular, adding lemon juice to a starch rich meal reduced the mean blood glucose concentration peak by 30%. Considering the panoply of food options available, it is likely that other combinations have similar effects but no work has been conducted to develop a consolidated knowledge base to exploit this strategy. GlucoMatchMaker will go beyond the state-of-the art by addressing this knowledge gap. The main goal is to develop and test the real-life effectiveness of the first mobile app to guide individuals on how to mix and match starchy foods with other foods/beverages to attenuate glycemic responses. The research work will employ multidisciplinary knowledge and methodologies and is divided into 4 parts (1) Selection and characterization of starch-rich foods, low-pH foods/beverages and of how their combination influences starch digestion in vitro (WP1). (2) Determination of the conditions of effectiveness of these combinations (in silico models) (WP2). (3) Development of the first mobile app that will integrate this knowledge to guide the user on how to mix and match starch-rich foods with others to lower their glycemic impact (WP3). (4) Test the effectiveness of the developed strategy in a real-life context (WP4). This project addresses the United Nations and EU target to reduce premature mortality from non-communicable diseases by one third as part of the 2030 Agenda for Sustainable Development. The research plan was developed in the framework of “H2020 Work Programme - Health, demographic change and wellbeing”, specifically the aim to “translate new knowledge into innovative applications and accelerate large-scale uptake and deployment”. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
