During pregnancy, mothers-to-be should adapt their diet to meet increases in nutrient requirements. Pregnant women appear to be keener to adopt healthier diets, but are not always successful. The objective of the present study was to determine whether a guided, stepwise and tailored dietary counselling programme, designed using an optimisation algorithm, could improve the nutrient adequacy of the diet of pregnant women, beyond generic guidelines. Pregnant women (n 80) who attended Notre-Dame-de-Bon-Secours Maternity Clinic were randomly allocated to the control or intervention arm. Dietary data were obtained twice from an online 3-d dietary record. The nutrient adequacy of the diet was calculated using the PANDiet score, a 100-point diet quality index adapted to the specific nutrient requirements for pregnancy. Women were supplied with generic dietary guidelines in a reference booklet. In the intervention arm, they also received nine sets of tailored dietary advice identified by an optimisation algorithm as best improving their PANDiet score. Pregnant women (n 78) completed the 12-week dietary follow-up. Initial PANDiet scores were similar in the control and intervention arms (60·4 (sd 7·3) v. 60·3 (sd 7·3), P = 0·92). The PANDiet score increased in the intervention arm (+3·6 (sd 9·3), P = 0·02) but not in the control arm (−0·3 (sd 7·3), P = 0·77), and these changes differed between arms (P = 0·04). In the intervention arm, there were improvements in the probabilities of adequacy for α-linolenic acid, thiamin, folate and cholesterol intakes (P < 0·05). Tailored dietary counselling using a computer-based algorithm is more effective than generic dietary counselling alone in improving the nutrient adequacy of the diet of French women in mid-pregnancy.

Abstract:In this paper, we present the implementation of a dedicated software, MAP-OPT, for optimising the design of Modified Atmosphere Packaging of refrigerated fresh, nonrespiring food products. The core principle of this software is to simulate the impact of gas (O 2 /CO 2 ) exchanges on the growth of gas-sensitive microorganisms in the packed food system. In its simplest way, this tool, associated with a data warehouse storing food, bacteria and packaging properties, allows the user to explore his/her system in a user-friendly manner by adjusting/changing the pack geometry, packaging material and gas composition (mixture of O 2 /CO 2 /N 2 ). Via the @Web application, the data warehouse associated with MAP-OPT is structured by an ontology, which allows data to be collected and stored in a standardized format and vocabulary in order to be easily retrieved using a standard querying methodology. In an optimisation approach, the MAP-OPT software enables to determine the packaging characteristics (e.g. gas permeabil-

International audienceEnzymatic hydrolysis of the main components of lignocellulosic biomass is one of the promising methods to further upgrading it into biofuels. Biomass pre-treatment is an essential step in order to reduce cellu- lose crystallinity, increase surface and porosity and separate the major constituents of biomass. Scientific literature in this domain is increasing fast and could be a valuable source of data. As these abundant sci- entific data are mostly in textual format and heterogeneously structured, using them to compute biomass pre-treatment efficiency is not straightforward. This paper presents the implementation of a Decision Support System (DSS) based on an original pipeline coupling knowledge engineering (KE) based on semantic web technologies, soft computing techniques and environmental factor computation. The DSS allows using data found in the literature to assess environmental sustainability of biorefinery sys- tems. The pipeline permits to: (1) structure and integrate relevant experimental data, (2) assess data source reliability, (3) compute and visualize green indicators taking into account data imprecision and source reliability. This pipeline has been made possible thanks to innovative researches in the coupling of ontologies, uncertainty management and propagation. In this first version, data acquisition is done by experts and facilitated by a termino-ontological resource. Data source reliability assessment is based on domain knowledge and done by experts. The operational prototype has been used by field experts on a realistic use case (rice straw). The obtained results have validated the usefulness of the system. Further work will address the question of a higher automation level for data acquisition and data source reliabil- ity assessment