Projects
MADOC - Collection and Meta-Analysis of Data on composition of Organic and Conventional foods
- Project Dates: From February 2010 to February 2011
- Project Leader: Prof. Chris Seal
- Staff: Team members: Dr. Kirsten Brandt, Dr. Roy Sanderson, Prof. Carlo Leifert; Research Fellow: Dominika Średnicka
- Sponsors: Sheepdrove Charitable Trust, Registered Charity No: 328369, Address: Sheepdrove Organic Farm, Lambourn, Berkshire, RG17 7UU, UK, Website: www.sheepdrove.com
Project aim The main aim of the MADOC is to collect and analyse data from published composition comparisons of organic and conventional foods using state-of-the-art meta-analysis approaches
Background to the project Demand for foods produced using organic, and to a lesser extent other ‘low input’ crop production methods has increased rapidly over the last 20 years.
Characteristics known to be associated by consumers with crop foods from ‘low input’ production systems (and in particular organic systems) include ”healthier”, “tastier”, “GM-free”, and/or “protective of the environment and biodiversity”. Perceived health benefits associated with organic foods are mainly based on the prohibition of the use of chemosynthetic pesticides, plant and animal growth regulators and many food additives (e.g. colourings; hydrogenated fats, processing aids and preservatives). However, scientific studies showing differences in the concentrations of other nutritionally desirable (e.g. antioxidants, vitamins) and undesirable compounds (mycotoxins, heavy metals) in foods from different production systems may also affect consumer perception and demand.
The MADOC project was therefore established to:
(i) provide access to the available studies measuring the effects of production systems (organic, other low input and conventional) on food composition
(ii) carry out expert consultations aimed at improving methodologies to carry out meta-analyses of available comparative food composition data
(iii) establish a data base of comparative composition data based on the available literature and to regularly up-date the data base
(iv)
carry-out meta-analyses of comparative composition data using optimised methodologies resulting from expert consultation