Effect of drying method on post-processing stability and quality of 3D printed rose-yam paste
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The addition of rose pollen to the yam paste for 3D printing could not only meet consumers' needs for nutrition and health, but also provide a new way to achieve personalized customization of healthy food. In this work, the rose-yam paste was selected as material, by comparing the post-treatment shape and color stability, bioactive substance content and hardness to explore the effect of hot air drying (HD), microwave vacuum drying (MVD) and freeze drying (FD) on the stability and quality of printed products. FD products illustrated the best post-processing stability, while HD products were the worst. FD products had a higher anthocyanin retention rate of 72.45% and a higher total phenol content of 31.33 mg/100g. However, FD products showed the lowest hardness. Although MVD products showed lower sensory score in appearance and color than FD products, their flavor score was higher than FD products, and the total sensory score of MVD products was equivalent to FD products. Moreover, MVD illustrated the highest drying efficiency, and a reduction of 84% drying time was obtained when compared with FD. Therefore, the combination of MVD and 3D printing could obtain the best quality products. This study would provide useful information on the development of post-processed high value-added 3D printed products, especially for the bio-active substances.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it