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Results for “Menu Planning”

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At least 19 recordsLinked to original sources
PubMed2005

A novel artificial intelligence method for weekly dietary menu planning.

OBJECTIVES: Menu planning is an important part of personalized lifestyle counseling. The paper describes the results of an automated menu generator (MenuGene) of the web-based lifestyle counseling system Cordelia that provides personalized advice to prevent cardiovascular diseases. METHODS: The menu generator uses genetic algorithms to prepare weekly menus for web users. The objectives are derived from personal medical data collected via forms in Cordelia, combined with general nutritional guidelines. The weekly menu is modeled as a multilevel structure. RESULTS: Results show that the genetic algorithm-based method succeeds in planning dietary menus that satisfy strict numerical constraints on every nutritional level (meal, daily basis, weekly basis). The rule-based assessment proved capable of manipulating the mean occurrence of the nutritional components thus providing a method for adjusting the variety and harmony of the menu plans. CONCLUSIONS: By splitting the problem into well determined sub-problems, weekly menu plans that satisfy nutritional constraints and have well assorted components can be generated with the same method that is for daily and meal plan generation.

Algorithms↗
PubMed1976

Menu planning in the Nutrition Program for the Elderly. Modified Nutrient Standard Menu method.

A nutrient standard menu (NSM) planning method was developed for use in planning menus which provided one-third the Recommended Dietary Allowances for persons sixty years of age or older for nine indicator nutrients and calories, while restricting fat to less than 40 per cent of total calories. To eliminate manual calculations and make it easy for individuals untrained in dietetics or nutrition to use NSM planning, the nutrient composition of over a thousand commonly used menu items was listed in a menu planning manual in nutrient units which were one-tenth of the nutrient standard for the meal. Menus from third-party sources were monitored by selecting similar nutritionally analyzed menu items in the manual and adjusting the nutrient composition to conform to the portions actually served. Ten site managers of the Administration on Aging (AoA) evaluated the planning/monitoring method. The members of the group, on the average, were fifty-six years of age, had 1.6 years of education beyond high school, and had 4.6 years of foodservice experience. Approximately 83 per cent of the evaluators did not plan to monitor menus at their sites and had no formal training in dietetics or nutrition. Eighty-four per cent were able to plan menus satisfactorily after this brief introduction. The younger evaluators with more education grasped the concepts faster and were able to plan menus with greater accuracy. The data also indicated that previous experience in menu planning enhanced their ability to plan NSMs. Most felt the approach to be workable and applicable. Menu monitoring was more difficult for the evaluators. Seventy-five per cent were able to monitor menus satisfactorily, and all felt they could do so with more time. The data again showed that the younger individuals having more formal education were able to master the monitoring skills more easily.

Adult↗
PubMed1979

Menu planning competencies in administrative dietetic practice. I. The methodology.

This research was intended to develop a methodology to analyze competencies in one area of administrative dietetic practice--menu planning. Five basic competencies, with sub-competencies, in menu planning were drawn from previous research. To produce descriptive statements for each sub-competency, taped interviews were held with twenty practitioners to ascertain knowledge, attitudes, and skills required in menu planning. The original 607 responses were reduced to ninety-two by eliminating duplication and ranking them by importance. These were then expressed in appropriate behavioral terminology and validated by an educational consultant. The competency statements and sub-competencies with the ninety-two descriptors were incorporated into a questionnaire submitted to a nationwide sample of hospital administrative and generalist dietitians for further validation.

Administrative Personnel↗
PubMed1982

Kosher dietary laws and children's food preferences: guide to a camp menu plan.

Assessment of the food preferences of Jewish children and experience with the kosher dietary laws facilitated the planning of a summer camp menu. A lengthy list of foods was developed that satisfied the tastes of the campers. Recipes were modified to achieve greater value in the kosher menu. Both the children and the camp administration appreciated seeing the survey results implemented as an eight-week cycle menu. Dietitians have a responsibility to understand the cultural needs and food preferences of those whom they serve. An appreciation of ethnic and religious dietary patterns is essential in menu planning. Knowledge of the laws of kashruth and familiarity with kosher products, traditional Jewish foods, and taste preferences of Jewish children and adults are necessary to the dietitian wishing to please Jewish clientele.

Adolescent↗
PubMed1998

An artificial intelligence system for computer-assisted menu planning.

Planning nutritious and appetizing menus is a complex task that researchers have tried to computerize since the early 1960s. We have attempted to facilitate computer-assisted menu planning by modeling the reasoning an expert dietitian uses to plan menus. Two independent expert systems were built, each designed to plan a daily menu meeting the nutrition needs and personal preferences of an individual client. One system modeled rule-based, or logical, reasoning, whereas the other modeled case-based, or experiential, reasoning. The 2 systems were evaluated and their strengths and weaknesses identified. A hybrid system was built, combining the best of both systems. The hybrid system represents an important step forward because it plans daily menus in accordance with a person's needs and preferences; the Reference Daily Intakes; the Dietary Guidelines for Americans; and accepted aesthetic standards for color, texture, temperature, taste, and variety. Additional work to expand the system's scope and to enhance the user interface will be needed to make it a practical tool. Our system framework could be applied to special-purpose menu planning for patients in medical settings or adapted for institutional use. We conclude that an artificial intelligence approach has practical use for computer-assisted menu planning.

Artificial Intelligence↗
PubMed2003

Food for trans-Atlantic rowers: a menu planning model and case study.

Every 4 years, rowers from around the world compete in a 50- to 60-day trans-Atlantic rowing challenge. These ultra-distance rowers require a diet that provides adequate calories, protein, vitamins, minerals, and fluids so they can perform well day after day, minimize fatigue, and stay healthy. Yet, the rowers are confronted with menu planning challenges. The food needs to be lightweight, compact, sturdy, non-spoiling in tropical temperatures, calorie dense, easy to prepare, quick to cook, and good tasting. Financial concerns commonly add another menu planning challenge. The purpose of this case study is to summarize the rowers' food experiences and to provide guidance for sports nutrition professionals who work with ultra-endurance athletes embarking on a physical challenge with similar food requirements. The article provides food and nutrition recommendations as well as practical considerations for ultra-distance athletes. We describe an 8,000 calorie per day menu planning model that uses food exchanges based on familiar, tasty, and reasonably priced supermarket foods that provide the required nutrients and help contain financial costs.

Athletic Injuries↗
PubMed1979

Menu planning competencies in administrative dietetic practice. II. Practitioners' ratings of competence.

A nationwide sample of administrative and generalist dietitians rated five competencies with sub-competencies and ninety-two descriptors related to menu planning. Each item was rated numerically for importance and frequency of time consideration. Data were grouped according to three levels of practitioner experience. It was concluded that an effective methodology was developed for analyzing competencies for dietetic practice.

Administrative Personnel↗
PubMed1993

An accelerative enumeration algorithm for the bottle combination problem and the menu planning problem.

In the clinical practice, there are a number of instances in which the request tailored to each patient must be satisfied with a combination of ready-made medical supplies. For example, in intravenous infusion and feeding, an appropriate combination of commercially available bottles must be chosen such that fluid, electrolyte, and nutritional requirements can be satisfied for the individual patient. Menu planning also has the same feature. However, the problem of the optimal combination of medical supplies is difficult to solve exactly and quickly even with the aid of the computer, because of the combinatorial nature of this problem. We formulate the combinatorial problem of medical supplies as a nonlinear all-integer programming problem and present a fast exact algorithm to solve the problem. The proposed algorithm is proved to find an optimal combination in an acceptable calculation time for medical problems of the usual size.

Algorithms↗
PubMed1996

Patient focused menu planning: an ENB project in a hospice.

This paper discusses how a small study of the meals provided for patients in a hospice was undertaken as part of the ENB 931 Care of the Dying course, and used to change practice. The authors describe how the study provided not only useful information about the types and aspects of food both enjoyed and disliked in this setting, but also stimulated interest among nursing and kitchen staff, resulting in a programme of changes in menu planning. It is argued that while the project was undertaken as a piece of research, it actually had more in common with audit, and that audit might be a more useful activity to incorporate into ENB courses.

Clinical Nursing Research↗
PubMed1998

Sweet potato in a vegetarian menu plan for NASA's Advanced Life Support Program.

Sweet potato has been selected as one of the crops for NASA's Advanced Life Support Program. Sweet potato primarily provides carbohydrate--an important energy source, beta-carotene, and ascorbic acid to a space diet. This study focuses on menus incorporating two sets of sweet potato recipes developed at Tuskegee University. One set includes recipes for 10 vegetarian products containing fom 6% to 20% sweet potato on a dry weight basis (pancakes, waffles, tortillas, bread, pie, pound cake, pasta, vegetable patties, doughnuts, and pretzels) that have been formulated, subjected to sensory evaluation, and determined to be acceptable. These recipes and the other set of recipes, not tested organoleptically, were substituted in a 10-day vegetarian menu plan developed by the American Institute of Biological Sciences (AIBS) Kennedy Space Center Biomass Processing Technical Panel. At least one recipe containing sweet potato was included in each meal. An analysis of the nutritional quality of this menu compared to the original AIBS menu found improved beta-carotene content (p<0.05). All other nutrients, except vitamin B6, and calories were equal and in some instances greater than those listed for NASA's Controlled Ecological Life Support Systems RDA. These results suggest that sweet potato products can be used successfully in menus developed for space with the added benefit of increased nutrient value and dietary variety.

Diet, Vegetarian↗
PubMed1975

Nutrient menu planning for clinical research centers. Control by computer.

A computer program has been developed for the dietetic service of the Clinical Research Center at the University of Florida. Presently, it is used in menu planning and nutrient analysis for selective, controlled-nutrient diets and for constant diets. The program is able to compute food weights for a patient-selected daily menu which would satisfy up to twenty-three nutrient constraints and which may be optimized with respect to one or more of these. The principal benefit of the program is a saving in the dietetian's time in calculating the nutrient content of the diet and in planning diets with several constrained nutrients. It is also being used as a teaching resource for dietetic interns and dietetic trainees.

Computers↗