While metabolomics is increasingly used to investigate the food metabolome and identify new markers of food exposure, limited attention has been given to the validation of such markers. The main objectives of the present study were to (1) discover potential food exposure markers (PEMs) for a range of plant foods in a study setting with a mixed dietary background and (2) validate PEMs found in a previous meal study. Three-day weighed dietary records and 24-h urine samples were collected three times during a 6-month parallel intervention study from 107 subjects randomized to two distinct dietary patterns. An untargeted UPLC-qTOF-MS metabolomics analysis was performed on the urine samples, and all features detected underwent strict data analyses, including an iterative paired t test and sensitivity and specificity analyses for foods. A total of 22 unique PEMs were identified that covered 7 out of 40 investigated food groups (strawberry, cabbages, beetroot, walnut, citrus, green beans and chocolate). The PEMs reflected foods with a distinct composition rather than foods eaten more frequently or in larger amounts. We found that 23 % of the PEMs found in a previous meal study were also valid in the present intervention study. The study demonstrates that it is possible to discover and validate PEMs for several foods and food classes in an intervention study with a mixed dietary background, despite the large variability in such a dataset. Final validation of PEMs for intake of foods should be performed by quantitative analysis.