The test of the association between dietary intake of specific carotenoids and disease incidence requires the availability of accurate and current food composition data for individual carotenoids. To generate a carotenoid database, an artificial intelligence system was developed to evaluate data for carotenoid content of food in five general categories, namely, number of samples, analytic method, sample handling, sampling plan, and analytic quality control. Within these categories, criteria have been created to rate analytic data for beta-carotene, alpha-carotene, lutein, lycopene, and beta-cryptoxanthin in fruits and vegetables. These carotenoids are also found in human blood. Following the evaluation of data, acceptable values for each carotenoid in the foods were combined to generate a database of 120 foods. The database includes the food description; median, minimum, and maximum values for the specific carotenoids in each food; the number of acceptable values and their references; and a confidence code, which is an indicator of the reliability of a specific carotenoid value for a food. The carotenoid database can be used to estimate the intake of specific carotenoids in order to examine the association between dietary carotenoids and disease incidence.