Optimization of the process of drying of corn seeds with the use of microwaves
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 heating and drying of various types of food using microwave improve the economy of time and energy. The physiological quality variation of the seeds submitted to microwave drying is known to some extent. In this context, some authors have reported excellent performance using this technique, on germination rates, after drying. The commercial use of microwave drying in seeds is irrelevant, which motivates more extensive research on the benefits and challenges of this technique that can increase its insertion in the post-harvest handling steps of agricultural products. Corn is a product of high worldwide relevance. Therefore, the use of microwaves in its drying process has excellent potential to arrive at significant savings in its production. Thus, this study is aimed to evaluate the effects on the physiological quality of the seeds submitted to different drying conditions, using the microwave radiation. To that end, corn seeds, with a water content of 20% on wet basis (w.b.), were dried at 40, 50, and 60 °C, at power ratings of 0, 0.6, and 1.2 W/g; in the vacuum condition. Drying occurred continuously, with intermittent power, until the seeds reached the 12% wet basis; in this condition, the seeds could be stored with secure. Germination tests performed shortly after drying showed that the temperature of 40 °C at a power of 0.6 W/g had a reduction in drying time of approximately 5 h when compared to conventional drying (40 °C and 0.0 W/g). The evaluation of the physiological quality of the seeds showed no significant difference in the germination, vigor, and longevity indices of the treated seeds.
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 | 0.000 | 0.000 |
| 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