Patents
Literature
2 results about "Food group" patented technology
Efficacy Topic
Property
Owner
Technical Advancement
Application Domain
Technology Topic
Technology Field Word
Patent Country/Region
Patent Type
Patent Status
Application Year
Inventor
A food group is a collection of foods that share similar nutritional properties or biological classifications. Nutrition guides typically divide foods into food groups and recommend daily servings of each group for a healthy diet. In the United States for instance, USDA has described food as being in from 4 to 11 different groups.
Packaging product, packaging group comprising at least two packaging products, method for manufacturing such packaging products
The packaged product (1) includes a container (2) and packaging (10). The container (2) includes: - a container body (2.0) defining a cavity (6), - food components (4) in the cavity (6), and - a diaphragm (9) that closes the cavity (6). The packaging (10) includes: - a protective sheet (12) covering the container body (2.0), and - a closing sheet (14) covering a portion of the diaphragm (9) and the protective sheet (12) to enclose the container (2) between the protective sheet (12) and the closing sheet (14). The closing sheet (14) and the protective sheet (12) are attached along a sheet attachment section (20) extending around the diaphragm (9). A weakening line (22) extends around the diaphragm (9) to allow a cap (24) to separate from the closing sheet (14) under manual force (F) for retrieving the container (2).
Owner:SOCIETE DES PRODUITS NESTLE SA
Dietary recommendation method based on candidate menu generation and nutrition-driven multi-objective optimization
The invention relates to the field of intelligent recommendation of recipes, in particular to a diet recommendation method based on candidate menu generation and nutrition-driven multi-objective optimization. The method comprises the following steps: firstly, constructing a collaborative recommendation model HyKBC-Rec fusing hyperbolic knowledge graph embedding and a knowledge perception attention mechanism, modeling a hierarchical semantic relationship between menus in a hyperbolic space, and carrying out weighted aggregation on historical diet behaviors of a user through multi-head attention; therefore, robust user preference modeling is realized under the condition of sparse user-menu interaction data. Secondly, a nutrition-driven multi-target weekly catering optimization algorithm NDMO is provided, and on the premise that hard constraints such as energy intake, menu number and repetition times are met, targets such as Chinese healthy dietary index, low sodium, energy stability, food diversity and food group coverage are synergistically optimized; and an executable personalized weekly diet scheme is generated through a multi-objective evolutionary optimization method.
Owner:BEIJING TECH & BUSINESS UNIV