Evaluating Vegetable Nutrition for Dental Health Maintenance Using an Orthopair Fuzzy Z-Number Decision-Making Model

Vegetables play a significant role in the human diet in that it provides vitamins and minerals vital to oral health. Nevertheless, it is a fuzzy multicriteria decision-making (MCDM) problem as the nutrient content is diverse and there are hard trade-offs to be made to determine the most appropriate types that would support dental health. To deal with this, we constructed and organized a new dataset of 115 types of vegetables against 16 types of nutritional factors based on USDA FoodData Central (2025), which we call the Dental Health Maintenance Criteria (DHMC). To assess these data, we used the Orthopair Z-Numbers (OZN), which reflect the expert judgments along with the reliability, Fuzzy Weighted Zero Inconsistency (FWZIC), which reflects the consistency of the expert-driven weighting, and a modified Ranking Alternatives with Weights of Criterion (RAWEC), which balances the beneficial and cost nutrients when computing the ranking. It was revealed that calcium and fluoride were the most influential nutrients, while grape leaves, parsley, and garlic ranked among the highest-performing vegetables, whereas iceberg lettuce and sweet onions were among the lowest. The framework was proven to be robust and reliable with six sensitivity scenarios and comparative analysis with the traditional MCDM methods. The present research offers an interpretable and replicable instrument to evaluate the dietary intake benefits of vegetables to oral health, and its possible uses in nutritional planning, preventive dentistry, and health recommendation systems by artificial intelligence.