Table 2.
Overview of data analysis strategy for calibration and prediction models.
| Prediction | Training sample | X-data | Y-data | Calibration model | |
|---|---|---|---|---|---|
| Storage time | set 1 | E-nose | D of Storage | C-model (storage time) | |
| Haugh units | set 1 | E-nose | Haugh unit values | C-model (HU) | |
| Odor | set 1 | E-nose | Odor scores | C-model (odor) | |
| Overall acceptability | set 1 | E-nose | Overall acceptability scores | C-model (overall acceptability) | |
| Validation | Unknown sample | X-data | via Calibration model | Y predicted | |
| Storage time | set 2 | E-nose | C-model (storage time) | D of storage | |
| Haugh units | set 2 | E-nose | C-model (HU) | Haugh unit value | |
| Odor | set 2 | E-nose | C-model (odor) | Odor score | |
| Overall acceptability | set 2 | E-nose | C-model (overall acceptability) | Overall acceptability score |