Sample Class Prediction for the Determination of Off-Flavors in Cranberries by GC/MS

摘要

Headspace SPME GCMS with DRS and MPP statistical analysis was used to develop a model to perform rapid, accurate quality control for cranberries. A working model for identifying good from bad cranberries have been developed: (1) Sensory evaluations is difficult to do when processing millions of berries; (2) Distinguishing between good and below average berries is difficult- much easier to distinguish between good and bad; (3) This model can be improved further to distinguish between good and exceptional berries.